### 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

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
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Spam weight 5
Spam weight 6
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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)

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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 [ ]: