Note: this tutorial needs updating and has not been recently tested for basic functionality: use at own risk

In [1]:
from __future__ import print_function
In [2]:
import os
import sys
import time
import json

import pygsti

%pylab inline
Populating the interactive namespace from numpy and matplotlib
In [3]:
#Load example quantities from files
gs_target = pygsti.io.load_gateset("tutorial_files/Example_Gateset.txt")
gs_mc2gst = pygsti.io.load_gateset("tutorial_files/Example_MC2GST_Gateset.txt")

ds = pygsti.io.load_dataset("tutorial_files/Example_Dataset.txt", cache=True)

fiducials = pygsti.io.load_gatestring_list("tutorial_files/Example_FiducialList.txt")
germs = pygsti.io.load_gatestring_list("tutorial_files/Example_GermsList.txt")
maxLengths = json.load(open("tutorial_files/Example_maxLengths.json","r"))

specs = pygsti.construction.build_spam_specs(fiducials)
Loading tutorial_files/Example_Dataset.txt: 100%
Writing cache file (to speed future loads): tutorial_files/Example_Dataset.txt.cache

Parametric Bootstrapping

Here we do parametric bootstrapping, as indicated by the 'parametric' argument below. The output is eventually stored in the "mean" and "std" GateSets, which hold the mean and standard deviation values of the set of bootstrapped gatesets (after gauge optimization). It is this latter "standard deviation Gateset" which holds the collection of error bars. Note: due to print setting issues, the outputs that are printed here will not necessarily reflect the true accuracy of the estimates made.

In [4]:
#The number of simulated datasets & gatesets made for bootstrapping purposes.  
# For good statistics, should probably be greater than 10.
numGatesets=10

param_boot_gatesets = pygsti.drivers.make_bootstrap_gatesets(
                        numGatesets, ds, 'parametric', fiducials, fiducials, germs, maxLengths,
                        inputGateSet=gs_mc2gst, startSeed=0, returnData=False,
                        verbosity=2)
Creating DataSets: 
0 Generating parametric dataset.
1 Generating parametric dataset.
2 Generating parametric dataset.
3 Generating parametric dataset.
4 Generating parametric dataset.
5 Generating parametric dataset.
6 Generating parametric dataset.
7 Generating parametric dataset.
8 Generating parametric dataset.
9 Generating parametric dataset.
Creating GateSets: 
Running MLGST Iteration 0 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24430657954
  1.19541285105
  0.972320887627
  0.924565187278
  0.051646837852
  0.0235729617374
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 53.752 (92 data params - 40 model params = expected mean of 52; p-value = 0.407044)
  Completed in 0.1s
  2*Delta(log(L)) = 53.9388
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 53.752 (92 data params - 40 model params = expected mean of 52; p-value = 0.407044)
  Completed in 0.0s
  2*Delta(log(L)) = 53.9388
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 136.04 (168 data params - 40 model params = expected mean of 128; p-value = 0.296731)
  Completed in 0.1s
  2*Delta(log(L)) = 136.06
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 406.903 (441 data params - 40 model params = expected mean of 401; p-value = 0.40868)
  Completed in 0.2s
  2*Delta(log(L)) = 407.508
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 812.725 (817 data params - 40 model params = expected mean of 777; p-value = 0.181528)
  Completed in 0.3s
  2*Delta(log(L)) = 814.023
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1182.5 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.323728)
  Completed in 0.4s
  2*Delta(log(L)) = 1184.23
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1526.74 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.624697)
  Completed in 0.7s
  2*Delta(log(L)) = 1528.65
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1918.09 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.565623)
  Completed in 1.0s
  2*Delta(log(L)) = 1920.41
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2253.9 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.806931)
  Completed in 1.1s
  2*Delta(log(L)) = 2256.51
  Iteration 9 took 1.2s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2605.37 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.894892)
  Completed in 2.9s
  2*Delta(log(L)) = 2608.27
  Iteration 10 took 3.2s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1303.77 below upper bound of -4.60018e+06
      2*Delta(log(L)) = 2607.54 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.889285)
    Completed in 1.9s
  2*Delta(log(L)) = 2607.54
  Final MLGST took 1.9s
  
Iterative MLGST Total Time: 9.4s
Running MLGST Iteration 1 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24462644244
  1.16391558424
  0.954007097645
  0.92144715149
  0.0282314704911
  0.0205782809412
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 63.7117 (92 data params - 40 model params = expected mean of 52; p-value = 0.127914)
  Completed in 0.1s
  2*Delta(log(L)) = 63.7499
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 63.7117 (92 data params - 40 model params = expected mean of 52; p-value = 0.127914)
  Completed in 0.0s
  2*Delta(log(L)) = 63.7499
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 119.606 (168 data params - 40 model params = expected mean of 128; p-value = 0.689576)
  Completed in 0.1s
  2*Delta(log(L)) = 119.723
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 398.006 (441 data params - 40 model params = expected mean of 401; p-value = 0.53284)
  Completed in 0.2s
  2*Delta(log(L)) = 398.085
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 807.775 (817 data params - 40 model params = expected mean of 777; p-value = 0.215506)
  Completed in 0.3s
  2*Delta(log(L)) = 808.819
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1176.93 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.365858)
  Completed in 0.4s
  2*Delta(log(L)) = 1178.31
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1522.5 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.653494)
  Completed in 0.7s
  2*Delta(log(L)) = 1524.22
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1874.24 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.810402)
  Completed in 0.8s
  2*Delta(log(L)) = 1876.28
  Iteration 8 took 0.9s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2254.17 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.805836)
  Completed in 1.6s
  2*Delta(log(L)) = 2256.6
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2667.6 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.652713)
  Completed in 2.1s
  2*Delta(log(L)) = 2670.47
  Iteration 10 took 2.3s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1334.89 below upper bound of -4.6007e+06
      2*Delta(log(L)) = 2669.78 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.641607)
    Completed in 2.9s
  2*Delta(log(L)) = 2669.78
  Final MLGST took 2.9s
  
Iterative MLGST Total Time: 9.7s
Running MLGST Iteration 2 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24487669817
  1.15380695435
  0.9568980082
  0.911484529351
  0.0436469558895
  0.0260466370097
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 46.4266 (92 data params - 40 model params = expected mean of 52; p-value = 0.691931)
  Completed in 0.1s
  2*Delta(log(L)) = 46.4652
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 46.4266 (92 data params - 40 model params = expected mean of 52; p-value = 0.691931)
  Completed in 0.0s
  2*Delta(log(L)) = 46.4652
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 124.97 (168 data params - 40 model params = expected mean of 128; p-value = 0.559264)
  Completed in 0.1s
  2*Delta(log(L)) = 125.483
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 441.78 (441 data params - 40 model params = expected mean of 401; p-value = 0.0782058)
  Completed in 0.2s
  2*Delta(log(L)) = 443.224
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 846.689 (817 data params - 40 model params = expected mean of 777; p-value = 0.0414261)
  Completed in 0.3s
  2*Delta(log(L)) = 848.695
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1245.57 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.0420003)
  Completed in 0.4s
  2*Delta(log(L)) = 1248.66
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1625.46 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.075647)
  Completed in 0.6s
  2*Delta(log(L)) = 1628.84
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2034.48 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.046588)
  Completed in 0.9s
  2*Delta(log(L)) = 2038.23
  Iteration 8 took 1.0s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2447.25 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.0257897)
  Completed in 1.6s
  2*Delta(log(L)) = 2451.45
  Iteration 9 took 1.8s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2783.11 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.121147)
  Completed in 2.4s
  2*Delta(log(L)) = 2787.59
  Iteration 10 took 2.7s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1393.4 below upper bound of -4.60025e+06
      2*Delta(log(L)) = 2786.79 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.111542)
    Completed in 3.6s
  2*Delta(log(L)) = 2786.79
  Final MLGST took 3.6s
  
Iterative MLGST Total Time: 10.9s
Running MLGST Iteration 3 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.2448605943
  1.21338143204
  0.974133743467
  0.927811130122
  0.0349618129799
  0.00276832343227
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 66.5848 (92 data params - 40 model params = expected mean of 52; p-value = 0.0839743)
  Completed in 0.1s
  2*Delta(log(L)) = 67.1017
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 66.5848 (92 data params - 40 model params = expected mean of 52; p-value = 0.0839743)
  Completed in 0.0s
  2*Delta(log(L)) = 67.1017
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 126.098 (168 data params - 40 model params = expected mean of 128; p-value = 0.530968)
  Completed in 0.1s
  2*Delta(log(L)) = 126.62
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 377.592 (441 data params - 40 model params = expected mean of 401; p-value = 0.793768)
  Completed in 0.2s
  2*Delta(log(L)) = 378.374
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 766.929 (817 data params - 40 model params = expected mean of 777; p-value = 0.594703)
  Completed in 0.3s
  2*Delta(log(L)) = 767.893
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1108.93 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.860668)
  Completed in 0.4s
  2*Delta(log(L)) = 1110.19
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1500.64 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.786334)
  Completed in 0.7s
  2*Delta(log(L)) = 1502.41
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1911.73 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.605691)
  Completed in 1.0s
  2*Delta(log(L)) = 1913.92
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2292.57 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.614628)
  Completed in 1.2s
  2*Delta(log(L)) = 2295.13
  Iteration 9 took 1.4s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2663.2 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.674733)
  Completed in 1.9s
  2*Delta(log(L)) = 2666.11
  Iteration 10 took 2.2s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1332.69 below upper bound of -4.60053e+06
      2*Delta(log(L)) = 2665.38 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.66392)
    Completed in 3.0s
  2*Delta(log(L)) = 2665.38
  Final MLGST took 3.0s
  
Iterative MLGST Total Time: 9.5s
Running MLGST Iteration 4 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24546178062
  1.16653406048
  0.981667764959
  0.879092800621
  0.0576399380988
  0.0301734937346
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 65.4214 (92 data params - 40 model params = expected mean of 52; p-value = 0.100014)
  Completed in 0.1s
  2*Delta(log(L)) = 65.5603
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 65.4214 (92 data params - 40 model params = expected mean of 52; p-value = 0.100014)
  Completed in 0.0s
  2*Delta(log(L)) = 65.5603
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 146.928 (168 data params - 40 model params = expected mean of 128; p-value = 0.120916)
  Completed in 0.1s
  2*Delta(log(L)) = 147.258
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 422.888 (441 data params - 40 model params = expected mean of 401; p-value = 0.216898)
  Completed in 0.2s
  2*Delta(log(L)) = 424.087
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 794.254 (817 data params - 40 model params = expected mean of 777; p-value = 0.325864)
  Completed in 0.3s
  2*Delta(log(L)) = 795.972
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1204.97 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.180104)
  Completed in 0.4s
  2*Delta(log(L)) = 1207.03
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1576.6 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.282129)
  Completed in 0.7s
  2*Delta(log(L)) = 1579.07
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1928.75 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.497294)
  Completed in 0.8s
  2*Delta(log(L)) = 1931.51
  Iteration 8 took 0.9s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2300.49 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.569234)
  Completed in 1.5s
  2*Delta(log(L)) = 2303.62
  Iteration 9 took 1.6s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2720.5 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.371414)
  Completed in 2.4s
  2*Delta(log(L)) = 2724.07
  Iteration 10 took 2.7s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1361.66 below upper bound of -4.59984e+06
      2*Delta(log(L)) = 2723.31 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.357127)
    Completed in 3.7s
  2*Delta(log(L)) = 2723.31
  Final MLGST took 3.7s
  
Iterative MLGST Total Time: 10.8s
Running MLGST Iteration 5 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24437399366
  1.15913106375
  0.96471164286
  0.925272228881
  0.0417459810904
  0.0115152340233
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 47.5845 (92 data params - 40 model params = expected mean of 52; p-value = 0.648018)
  Completed in 0.1s
  2*Delta(log(L)) = 47.8345
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 47.5845 (92 data params - 40 model params = expected mean of 52; p-value = 0.648018)
  Completed in 0.0s
  2*Delta(log(L)) = 47.8345
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 121.065 (168 data params - 40 model params = expected mean of 128; p-value = 0.655296)
  Completed in 0.1s
  2*Delta(log(L)) = 121.199
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 425.539 (441 data params - 40 model params = expected mean of 401; p-value = 0.191372)
  Completed in 0.2s
  2*Delta(log(L)) = 425.903
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 801.086 (817 data params - 40 model params = expected mean of 777; p-value = 0.267078)
  Completed in 0.3s
  2*Delta(log(L)) = 801.362
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1184.72 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.307605)
  Completed in 0.4s
  2*Delta(log(L)) = 1185.66
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1554.89 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.42487)
  Completed in 0.6s
  2*Delta(log(L)) = 1556.09
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1969.1 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.257212)
  Completed in 0.8s
  2*Delta(log(L)) = 1970.77
  Iteration 8 took 0.9s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2316.13 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.477754)
  Completed in 0.8s
  2*Delta(log(L)) = 2318.09
  Iteration 9 took 1.0s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2725.19 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.347671)
  Completed in 2.4s
  2*Delta(log(L)) = 2727.63
  Iteration 10 took 2.7s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1363.45 below upper bound of -4.60109e+06
      2*Delta(log(L)) = 2726.9 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.339209)
    Completed in 5.1s
  2*Delta(log(L)) = 2726.9
  Final MLGST took 5.1s
  
Iterative MLGST Total Time: 11.4s
Running MLGST Iteration 6 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24373571951
  1.16655847582
  0.951729162665
  0.921746887733
  0.0477682961697
  0.012527219858
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 84.9713 (92 data params - 40 model params = expected mean of 52; p-value = 0.0026406)
  Completed in 0.1s
  2*Delta(log(L)) = 85.2475
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 84.9713 (92 data params - 40 model params = expected mean of 52; p-value = 0.0026406)
  Completed in 0.0s
  2*Delta(log(L)) = 85.2475
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 156.521 (168 data params - 40 model params = expected mean of 128; p-value = 0.0439993)
  Completed in 0.1s
  2*Delta(log(L)) = 156.738
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 428.934 (441 data params - 40 model params = expected mean of 401; p-value = 0.161632)
  Completed in 0.2s
  2*Delta(log(L)) = 429.111
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 826.048 (817 data params - 40 model params = expected mean of 777; p-value = 0.10827)
  Completed in 0.3s
  2*Delta(log(L)) = 827.05
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1203.35 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.188813)
  Completed in 0.4s
  2*Delta(log(L)) = 1204.73
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1570.13 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.322161)
  Completed in 0.7s
  2*Delta(log(L)) = 1571.83
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1993.53 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.149558)
  Completed in 1.0s
  2*Delta(log(L)) = 1995.71
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2435.44 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.0376067)
  Completed in 1.5s
  2*Delta(log(L)) = 2438.12
  Iteration 9 took 1.6s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2801.01 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.0796543)
  Completed in 2.7s
  2*Delta(log(L)) = 2804.01
  Iteration 10 took 3.0s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1401.61 below upper bound of -4.60012e+06
      2*Delta(log(L)) = 2803.23 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.0753764)
    Completed in 3.0s
  2*Delta(log(L)) = 2803.23
  Final MLGST took 3.0s
  
Iterative MLGST Total Time: 10.5s
Running MLGST Iteration 7 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.2446716307
  1.16332597655
  0.924480987796
  0.901584474949
  0.0412758255531
  0.0231098191713
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 53.1539 (92 data params - 40 model params = expected mean of 52; p-value = 0.429505)
  Completed in 0.1s
  2*Delta(log(L)) = 53.1606
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 53.1539 (92 data params - 40 model params = expected mean of 52; p-value = 0.429505)
  Completed in 0.0s
  2*Delta(log(L)) = 53.1606
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 130.176 (168 data params - 40 model params = expected mean of 128; p-value = 0.429799)
  Completed in 0.1s
  2*Delta(log(L)) = 130.011
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 392.006 (441 data params - 40 model params = expected mean of 401; p-value = 0.616538)
  Completed in 0.2s
  2*Delta(log(L)) = 392.599
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 782.758 (817 data params - 40 model params = expected mean of 777; p-value = 0.435418)
  Completed in 0.3s
  2*Delta(log(L)) = 783.828
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1126.75 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.75928)
  Completed in 0.4s
  2*Delta(log(L)) = 1128.21
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1487.9 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.848059)
  Completed in 0.6s
  2*Delta(log(L)) = 1489.67
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1863.05 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.856196)
  Completed in 1.0s
  2*Delta(log(L)) = 1865.13
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2222.55 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.909508)
  Completed in 1.5s
  2*Delta(log(L)) = 2224.93
  Iteration 9 took 1.6s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2638.71 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.785336)
  Completed in 2.6s
  2*Delta(log(L)) = 2641.57
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1320.43 below upper bound of -4.60018e+06
      2*Delta(log(L)) = 2640.87 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.776542)
    Completed in 3.6s
  2*Delta(log(L)) = 2640.87
  Final MLGST took 3.6s
  
Iterative MLGST Total Time: 10.9s
Running MLGST Iteration 8 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24432387856
  1.14904678757
  0.957002356215
  0.902434260566
  0.0467116103808
  0.0121332141202
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 48.3534 (92 data params - 40 model params = expected mean of 52; p-value = 0.618095)
  Completed in 0.1s
  2*Delta(log(L)) = 48.3879
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 48.3534 (92 data params - 40 model params = expected mean of 52; p-value = 0.618095)
  Completed in 0.0s
  2*Delta(log(L)) = 48.3879
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 107.182 (168 data params - 40 model params = expected mean of 128; p-value = 0.909384)
  Completed in 0.1s
  2*Delta(log(L)) = 107.339
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 380.231 (441 data params - 40 model params = expected mean of 401; p-value = 0.765092)
  Completed in 0.2s
  2*Delta(log(L)) = 380.855
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 751.167 (817 data params - 40 model params = expected mean of 777; p-value = 0.740782)
  Completed in 0.3s
  2*Delta(log(L)) = 752.742
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1123.92 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.777541)
  Completed in 0.4s
  2*Delta(log(L)) = 1126.07
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1503.69 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.769699)
  Completed in 0.7s
  2*Delta(log(L)) = 1506.18
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1895.57 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.702138)
  Completed in 1.0s
  2*Delta(log(L)) = 1898.45
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2245.01 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.8413)
  Completed in 1.2s
  2*Delta(log(L)) = 2248.19
  Iteration 9 took 1.4s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2615.57 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.866724)
  Completed in 2.5s
  2*Delta(log(L)) = 2619.08
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1309.19 below upper bound of -4.60057e+06
      2*Delta(log(L)) = 2618.38 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.858136)
    Completed in 3.2s
  2*Delta(log(L)) = 2618.38
  Final MLGST took 3.2s
  
Iterative MLGST Total Time: 10.3s
Running MLGST Iteration 9 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.2446590126
  1.17232819284
  0.955349676809
  0.94638204726
  0.0308787960176
  0.0111799222352
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 43.4461 (92 data params - 40 model params = expected mean of 52; p-value = 0.794856)
  Completed in 0.1s
  2*Delta(log(L)) = 43.5368
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 43.4461 (92 data params - 40 model params = expected mean of 52; p-value = 0.794856)
  Completed in 0.0s
  2*Delta(log(L)) = 43.5368
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 123.869 (168 data params - 40 model params = expected mean of 128; p-value = 0.586763)
  Completed in 0.1s
  2*Delta(log(L)) = 123.693
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 403.458 (441 data params - 40 model params = expected mean of 401; p-value = 0.456145)
  Completed in 0.2s
  2*Delta(log(L)) = 403.939
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 798.056 (817 data params - 40 model params = expected mean of 777; p-value = 0.29244)
  Completed in 0.3s
  2*Delta(log(L)) = 799.142
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1127.66 (1201 data params - 40 model params = expected mean of 1161; p-value = 0.753259)
  Completed in 0.4s
  2*Delta(log(L)) = 1128.96
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1494.28 (1585 data params - 40 model params = expected mean of 1545; p-value = 0.818719)
  Completed in 0.6s
  2*Delta(log(L)) = 1495.97
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1896.96 (1969 data params - 40 model params = expected mean of 1929; p-value = 0.69425)
  Completed in 1.0s
  2*Delta(log(L)) = 1899.08
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2310.74 (2353 data params - 40 model params = expected mean of 2313; p-value = 0.509377)
  Completed in 1.3s
  2*Delta(log(L)) = 2313.29
  Iteration 9 took 1.5s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2716.23 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.393496)
  Completed in 2.6s
  2*Delta(log(L)) = 2719.2
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 1359.25 below upper bound of -4.60053e+06
      2*Delta(log(L)) = 2718.5 (2737 data params - 40 model params = expected mean of 2697; p-value = 0.381706)
    Completed in 2.8s
  2*Delta(log(L)) = 2718.5
  Final MLGST took 2.8s
  
Iterative MLGST Total Time: 10.0s
In [5]:
gauge_opt_pboot_gatesets = pygsti.drivers.gauge_optimize_gs_list(param_boot_gatesets, gs_mc2gst,
                                                                 plot=True)
Spam weight 0
Spam weight 1
Spam weight 2
Spam weight 3
Spam weight 4
Spam weight 5
Spam weight 6
Spam weight 7
Spam weight 8
Spam weight 9
Spam weight 10
Spam weight 11
Spam weight 12
Best SPAM weight is 0.0001
In [6]:
pboot_mean = pygsti.drivers.to_mean_gateset(gauge_opt_pboot_gatesets, gs_mc2gst)
pboot_std  = pygsti.drivers.to_std_gateset(gauge_opt_pboot_gatesets, gs_mc2gst)

#Summary of the error bars
print("Parametric bootstrapped error bars, with", numGatesets, "resamples\n")
print("Error in rho vec:") 
print(pboot_std['rho0'], end='\n\n')
print("Error in E vec:")
print(pboot_std['E0'], end='\n\n')
print("Error in Gi:")
print(pboot_std['Gi'], end='\n\n')
print("Error in Gx:")
print(pboot_std['Gx'], end='\n\n')
print("Error in Gy:")
print(pboot_std['Gy'])
Parametric bootstrapped error bars, with 10 resamples

Error in rho vec:
Fully Parameterized spam vector with length 4
   0
   0
 0.01
   0


Error in E vec:
Fully Parameterized spam vector with length 4
   0
   0
   0
   0


Error in Gi:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
   0   0   0   0
   0   0   0   0
   0   0   0   0


Error in Gx:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
   0   0 0.01 0.02
 0.02 0.02   0   0
 0.01 0.02   0   0


Error in Gy:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
 0.01 0.01 0.02 0.02
   0 0.02   0 0.02
   0 0.02 0.02 0.01

Non-parametric Bootstrapping

Here we do non-parametric bootstrapping, as indicated by the 'nonparametric' argument below. The output is again eventually stored in the "mean" and "std" GateSets, which hold the mean and standard deviation values of the set of bootstrapped gatesets (after gauge optimization). It is this latter "standard deviation Gateset" which holds the collection of error bars. Note: due to print setting issues, the outputs that are printed here will not necessarily reflect the true accuracy of the estimates made.

(Technical note: ddof = 1 is by default used when computing the standard deviation -- see numpy.std -- meaning that we are computing a standard deviation of the sample, not of the population.)

In [7]:
#The number of simulated datasets & gatesets made for bootstrapping purposes.  
# For good statistics, should probably be greater than 10.
numGatesets=10

nonparam_boot_gatesets = pygsti.drivers.make_bootstrap_gatesets(
                          numGatesets, ds, 'nonparametric', fiducials, fiducials, germs, maxLengths,
                          targetGateSet=gs_mc2gst, startSeed=0, returnData=False, verbosity=2)
Creating DataSets: 
0 Generating non-parametric dataset.
1 Generating non-parametric dataset.
2 Generating non-parametric dataset.
3 Generating non-parametric dataset.
4 Generating non-parametric dataset.
5 Generating non-parametric dataset.
6 Generating non-parametric dataset.
7 Generating non-parametric dataset.
8 Generating non-parametric dataset.
9 Generating non-parametric dataset.
Creating GateSets: 
Running MLGST Iteration 0 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24550397209
  1.20335083144
  0.975668667345
  0.917454523185
  0.0670503056945
  0.019102495855
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 98.6739 (92 data params - 40 model params = expected mean of 52; p-value = 0.000100717)
  Completed in 0.1s
  2*Delta(log(L)) = 99.1174
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 98.6739 (92 data params - 40 model params = expected mean of 52; p-value = 0.000100717)
  Completed in 0.0s
  2*Delta(log(L)) = 99.1174
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 296.362 (168 data params - 40 model params = expected mean of 128; p-value = 2.22045e-15)
  Completed in 0.1s
  2*Delta(log(L)) = 298.374
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 898.783 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.1s
  2*Delta(log(L)) = 903.33
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1704.29 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1712.24
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2458.62 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2468.5
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3270.34 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3281.93
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4037.88 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.1s
  2*Delta(log(L)) = 4051.09
  Iteration 8 took 1.2s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4745.54 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.5s
  2*Delta(log(L)) = 4760.02
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5442.75 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.4s
  2*Delta(log(L)) = 5458.42
  Iteration 10 took 2.7s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2727.7 below upper bound of -4.59866e+06
      2*Delta(log(L)) = 5455.39 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 1.9s
  2*Delta(log(L)) = 5455.39
  Final MLGST took 1.9s
  
Iterative MLGST Total Time: 9.2s
Running MLGST Iteration 1 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24583719101
  1.17077453673
  0.957852209477
  0.916561097732
  0.0669317955101
  0.0231638779774
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 91.4608 (92 data params - 40 model params = expected mean of 52; p-value = 0.000598068)
  Completed in 0.1s
  2*Delta(log(L)) = 91.5623
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 91.4608 (92 data params - 40 model params = expected mean of 52; p-value = 0.000598068)
  Completed in 0.0s
  2*Delta(log(L)) = 91.5623
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 248.357 (168 data params - 40 model params = expected mean of 128; p-value = 9.96094e-10)
  Completed in 0.1s
  2*Delta(log(L)) = 248.944
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 812.875 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.1s
  2*Delta(log(L)) = 814.97
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1544.53 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1548.06
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2219.02 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2223.87
  Iteration 6 took 0.4s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3037.52 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.7s
  2*Delta(log(L)) = 3043.97
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3821.3 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 0.9s
  2*Delta(log(L)) = 3829.33
  Iteration 8 took 1.0s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4510.98 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.4s
  2*Delta(log(L)) = 4520.25
  Iteration 9 took 1.5s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5255.37 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.5s
  2*Delta(log(L)) = 5266.14
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2631.68 below upper bound of -4.59916e+06
      2*Delta(log(L)) = 5263.37 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 3.9s
  2*Delta(log(L)) = 5263.37
  Final MLGST took 3.9s
  
Iterative MLGST Total Time: 11.1s
Running MLGST Iteration 2 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24587928058
  1.1653069138
  0.954081292751
  0.914239273392
  0.0316175274274
  0.0180748763317
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 93.2764 (92 data params - 40 model params = expected mean of 52; p-value = 0.000386683)
  Completed in 0.1s
  2*Delta(log(L)) = 93.5569
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 93.2764 (92 data params - 40 model params = expected mean of 52; p-value = 0.000386683)
  Completed in 0.0s
  2*Delta(log(L)) = 93.5569
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 264.548 (168 data params - 40 model params = expected mean of 128; p-value = 1.53207e-11)
  Completed in 0.1s
  2*Delta(log(L)) = 265.35
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 852.824 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 855.449
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1597.59 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1602.3
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2393.22 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2400.04
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3153.62 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3161.98
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4004.14 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 4014.42
  Iteration 8 took 0.7s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4804.24 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.3s
  2*Delta(log(L)) = 4816.31
  Iteration 9 took 1.5s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5494.64 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.6s
  2*Delta(log(L)) = 5507.87
  Iteration 10 took 2.9s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2752.41 below upper bound of -4.59897e+06
      2*Delta(log(L)) = 5504.81 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 2.0s
  2*Delta(log(L)) = 5504.81
  Final MLGST took 2.0s
  
Iterative MLGST Total Time: 8.9s
Running MLGST Iteration 3 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24572611089
  1.21940117097
  0.976875017673
  0.930877541327
  0.0513818811616
  0.0316019098629
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 111.101 (92 data params - 40 model params = expected mean of 52; p-value = 3.55272e-06)
  Completed in 0.1s
  2*Delta(log(L)) = 112.248
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 111.101 (92 data params - 40 model params = expected mean of 52; p-value = 3.55272e-06)
  Completed in 0.0s
  2*Delta(log(L)) = 112.248
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 262.519 (168 data params - 40 model params = expected mean of 128; p-value = 2.61924e-11)
  Completed in 0.1s
  2*Delta(log(L)) = 264.725
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 831.582 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 834.727
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1533.73 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1539.41
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2240.67 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2247.65
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3087.76 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.7s
  2*Delta(log(L)) = 3096.53
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3910.6 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 3921.18
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4629.46 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.1s
  2*Delta(log(L)) = 4641.38
  Iteration 9 took 1.2s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5300.1 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.6s
  2*Delta(log(L)) = 5313.11
  Iteration 10 took 2.9s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2655.12 below upper bound of -4.59909e+06
      2*Delta(log(L)) = 5310.23 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 4.9s
  2*Delta(log(L)) = 5310.23
  Final MLGST took 4.9s
  
Iterative MLGST Total Time: 12.1s
Running MLGST Iteration 4 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24587972369
  1.17514363414
  0.982174972059
  0.879560441108
  0.0645746514061
  0.0323833315662
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 134.098 (92 data params - 40 model params = expected mean of 52; p-value = 3.52406e-09)
  Completed in 0.1s
  2*Delta(log(L)) = 134.856
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 134.098 (92 data params - 40 model params = expected mean of 52; p-value = 3.52406e-09)
  Completed in 0.0s
  2*Delta(log(L)) = 134.856
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 279.637 (168 data params - 40 model params = expected mean of 128; p-value = 2.55018e-13)
  Completed in 0.1s
  2*Delta(log(L)) = 280.865
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 811.836 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 814.022
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1464.25 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1468.44
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2326.65 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2333.11
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3246.52 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3255.2
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3999.89 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 4009.93
  Iteration 8 took 1.0s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4823.55 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.6s
  2*Delta(log(L)) = 4835.4
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5592.79 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.2s
  2*Delta(log(L)) = 5606.12
  Iteration 10 took 2.5s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2801.54 below upper bound of -4.59866e+06
      2*Delta(log(L)) = 5603.09 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 4.3s
  2*Delta(log(L)) = 5603.09
  Final MLGST took 4.3s
  
Iterative MLGST Total Time: 11.3s
Running MLGST Iteration 5 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24471574745
  1.1691929877
  0.960719984385
  0.924282540953
  0.0658750484814
  0.0395139838088
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 113.27 (92 data params - 40 model params = expected mean of 52; p-value = 1.92039e-06)
  Completed in 0.1s
  2*Delta(log(L)) = 114.272
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 113.27 (92 data params - 40 model params = expected mean of 52; p-value = 1.92039e-06)
  Completed in 0.0s
  2*Delta(log(L)) = 114.272
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 250.232 (168 data params - 40 model params = expected mean of 128; p-value = 6.21891e-10)
  Completed in 0.1s
  2*Delta(log(L)) = 251.777
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 856.142 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 860.296
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1555.05 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1562.33
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2267.44 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2276.69
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3107.74 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3118.96
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3994.81 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 0.9s
  2*Delta(log(L)) = 4008.18
  Iteration 8 took 1.0s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4781.84 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.6s
  2*Delta(log(L)) = 4796.74
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5598.09 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.5s
  2*Delta(log(L)) = 5614.95
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2805.9 below upper bound of -4.59901e+06
      2*Delta(log(L)) = 5611.8 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 2.3s
  2*Delta(log(L)) = 5611.8
  Final MLGST took 2.3s
  
Iterative MLGST Total Time: 9.7s
Running MLGST Iteration 6 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.2454706912
  1.20039479438
  0.962462040517
  0.919961721698
  0.0489976096626
  0.0264468003084
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 92.3735 (92 data params - 40 model params = expected mean of 52; p-value = 0.000480853)
  Completed in 0.1s
  2*Delta(log(L)) = 92.6192
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 92.3735 (92 data params - 40 model params = expected mean of 52; p-value = 0.000480853)
  Completed in 0.0s
  2*Delta(log(L)) = 92.6192
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 237.363 (168 data params - 40 model params = expected mean of 128; p-value = 1.46772e-08)
  Completed in 0.1s
  2*Delta(log(L)) = 238.114
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 815.605 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 817.2
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1531.81 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1535.37
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2292 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2296.97
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3067 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3073.75
  Iteration 7 took 0.6s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3945.73 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 3954.56
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4820.88 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.4s
  2*Delta(log(L)) = 4831.68
  Iteration 9 took 1.5s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5654.88 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.4s
  2*Delta(log(L)) = 5667.44
  Iteration 10 took 2.7s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2832.11 below upper bound of -4.5984e+06
      2*Delta(log(L)) = 5664.23 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 2.8s
  2*Delta(log(L)) = 5664.23
  Final MLGST took 2.8s
  
Iterative MLGST Total Time: 9.8s
Running MLGST Iteration 7 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24510947557
  1.17112066686
  0.947794732077
  0.887769813302
  0.0520565945096
  0.0147627734961
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 97.0157 (92 data params - 40 model params = expected mean of 52; p-value = 0.000153413)
  Completed in 0.1s
  2*Delta(log(L)) = 97.2526
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 97.0157 (92 data params - 40 model params = expected mean of 52; p-value = 0.000153413)
  Completed in 0.0s
  2*Delta(log(L)) = 97.2526
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 242.701 (168 data params - 40 model params = expected mean of 128; p-value = 4.03742e-09)
  Completed in 0.1s
  2*Delta(log(L)) = 243.217
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 743.182 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 745.083
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1422.2 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1425.56
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2120.16 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2124.8
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2948.96 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 2954.97
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3788.5 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 3796.44
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4527.6 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.6s
  2*Delta(log(L)) = 4536.92
  Iteration 9 took 1.8s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5276.17 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.3s
  2*Delta(log(L)) = 5287
  Iteration 10 took 2.5s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2642.14 below upper bound of -4.59896e+06
      2*Delta(log(L)) = 5284.28 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 5.5s
  2*Delta(log(L)) = 5284.28
  Final MLGST took 5.5s
  
Iterative MLGST Total Time: 12.8s
Running MLGST Iteration 8 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24447001028
  1.16048285872
  0.943896909169
  0.912777176138
  0.0717633774961
  0.0366924472244
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 95.6424 (92 data params - 40 model params = expected mean of 52; p-value = 0.000216299)
  Completed in 0.1s
  2*Delta(log(L)) = 96.0506
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 95.6424 (92 data params - 40 model params = expected mean of 52; p-value = 0.000216299)
  Completed in 0.0s
  2*Delta(log(L)) = 96.0506
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 244.477 (168 data params - 40 model params = expected mean of 128; p-value = 2.61065e-09)
  Completed in 0.1s
  2*Delta(log(L)) = 245.07
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 710.537 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 711.619
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1369.09 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1371.56
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2147.18 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2151.29
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2962.63 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.7s
  2*Delta(log(L)) = 2968.4
  Iteration 7 took 0.8s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3783.59 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 3791.07
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4526.21 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.6s
  2*Delta(log(L)) = 4535.17
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5245.33 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.5s
  2*Delta(log(L)) = 5255.66
  Iteration 10 took 2.8s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2626.47 below upper bound of -4.59911e+06
      2*Delta(log(L)) = 5252.94 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 2.3s
  2*Delta(log(L)) = 5252.94
  Final MLGST took 2.3s
  
Iterative MLGST Total Time: 9.9s
Running MLGST Iteration 9 
--- LGST ---
  Singular values of I_tilde (truncating to first 4 of 6) = 
  4.24627607281
  1.1828960755
  0.960121416802
  0.938909418001
  0.0392610346821
  0.0300820382837
  
  Singular values of target I_tilde (truncating to first 4 of 6) = 
  4.246313691
  1.17235194083
  0.953112718624
  0.943760994228
  3.49602251407e-16
  1.72707620951e-16
  
--- Iterative MLGST: Iter 01 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 96.0807 (92 data params - 40 model params = expected mean of 52; p-value = 0.000193936)
  Completed in 0.1s
  2*Delta(log(L)) = 96.5628
  Iteration 1 took 0.1s
  
--- Iterative MLGST: Iter 02 of 10  92 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 96.0807 (92 data params - 40 model params = expected mean of 52; p-value = 0.000193936)
  Completed in 0.0s
  2*Delta(log(L)) = 96.5628
  Iteration 2 took 0.0s
  
--- Iterative MLGST: Iter 03 of 10  168 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 215.585 (168 data params - 40 model params = expected mean of 128; p-value = 2.0478e-06)
  Completed in 0.1s
  2*Delta(log(L)) = 216.178
  Iteration 3 took 0.1s
  
--- Iterative MLGST: Iter 04 of 10  441 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 728.515 (441 data params - 40 model params = expected mean of 401; p-value = 0)
  Completed in 0.2s
  2*Delta(log(L)) = 730.3
  Iteration 4 took 0.2s
  
--- Iterative MLGST: Iter 05 of 10  817 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 1444.66 (817 data params - 40 model params = expected mean of 777; p-value = 0)
  Completed in 0.3s
  2*Delta(log(L)) = 1449.14
  Iteration 5 took 0.3s
  
--- Iterative MLGST: Iter 06 of 10  1201 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2208.27 (1201 data params - 40 model params = expected mean of 1161; p-value = 0)
  Completed in 0.4s
  2*Delta(log(L)) = 2214.65
  Iteration 6 took 0.5s
  
--- Iterative MLGST: Iter 07 of 10  1585 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 2995.31 (1585 data params - 40 model params = expected mean of 1545; p-value = 0)
  Completed in 0.6s
  2*Delta(log(L)) = 3003.36
  Iteration 7 took 0.7s
  
--- Iterative MLGST: Iter 08 of 10  1969 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 3797.02 (1969 data params - 40 model params = expected mean of 1929; p-value = 0)
  Completed in 1.0s
  2*Delta(log(L)) = 3806.65
  Iteration 8 took 1.1s
  
--- Iterative MLGST: Iter 09 of 10  2353 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 4573.87 (2353 data params - 40 model params = expected mean of 2313; p-value = 0)
  Completed in 1.6s
  2*Delta(log(L)) = 4585.05
  Iteration 9 took 1.7s
  
--- Iterative MLGST: Iter 10 of 10  2737 gate strings ---: 
  --- Minimum Chi^2 GST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
  Sum of Chi^2 = 5334.95 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
  Completed in 2.6s
  2*Delta(log(L)) = 5347.63
  Iteration 10 took 2.9s
  
  Switching to ML objective (last iteration)
  --- MLGST ---
  Created evaluation tree with 1 subtrees.  Will divide 1 procs into 1 (subtree-processing)
   groups of ~1 procs each, to distribute over 56 params (taken as 1 param groups of ~56 params).
    Maximum log(L) = 2672.41 below upper bound of -4.59872e+06
      2*Delta(log(L)) = 5344.82 (2737 data params - 40 model params = expected mean of 2697; p-value = 0)
    Completed in 2.0s
  2*Delta(log(L)) = 5344.82
  Final MLGST took 2.0s
  
Iterative MLGST Total Time: 9.5s
In [8]:
gauge_opt_npboot_gatesets = pygsti.drivers.gauge_optimize_gs_list(nonparam_boot_gatesets, gs_mc2gst,
                                                                 plot=True)
Spam weight 0
Spam weight 1
Spam weight 2
Spam weight 3
Spam weight 4
Spam weight 5
Spam weight 6
Spam weight 7
Spam weight 8
Spam weight 9
Spam weight 10
Spam weight 11
Spam weight 12
Best SPAM weight is 0.0001
In [9]:
npboot_mean = pygsti.drivers.to_mean_gateset(gauge_opt_npboot_gatesets, gs_mc2gst)
npboot_std  = pygsti.drivers.to_std_gateset(gauge_opt_npboot_gatesets, gs_mc2gst)

#Summary of the error bars
print("Non-parametric bootstrapped error bars, with", numGatesets, "resamples\n")
print("Error in rho vec:")
print(npboot_std['rho0'], end='\n\n')
print("Error in E vec:")
print(npboot_std['E0'], end='\n\n')
print("Error in Gi:")
print(npboot_std['Gi'], end='\n\n')
print("Error in Gx:")
print(npboot_std['Gx'], end='\n\n')
print("Error in Gy:")
print(npboot_std['Gy'])
Non-parametric bootstrapped error bars, with 10 resamples

Error in rho vec:
Fully Parameterized spam vector with length 4
   0
   0
 0.01
   0


Error in E vec:
Fully Parameterized spam vector with length 4
   0
 0.01
 0.01
   0


Error in Gi:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
   0   0   0   0
   0   0   0   0
   0   0   0   0


Error in Gx:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
   0   0 0.01 0.01
 0.01 0.03   0   0
   0 0.02   0   0


Error in Gy:
Fully Parameterized gate with shape (4, 4)
   0   0   0   0
 0.01 0.01 0.03 0.01
   0 0.03   0 0.03
 0.01 0.01 0.02 0.01

In [10]:
loglog(npboot_std.to_vector(),pboot_std.to_vector(),'.')
loglog(np.logspace(-4,-2,10),np.logspace(-4,-2,10),'--')
xlabel('Non-parametric')
ylabel('Parametric')
xlim((1e-4,1e-2)); ylim((1e-4,1e-2))
title('Scatter plot comparing param vs. non-param bootstrapping error bars.')
Out[10]:
<matplotlib.text.Text at 0x10d23a320>
In [ ]:
 
In [ ]: