from __future__ import print_function
import os
import sys
import time
import json
import pygsti
%pylab inline
Populating the interactive namespace from numpy and matplotlib
#Load example quantities from files
gs_target = pygsti.io.load_gateset("tutorial_files/Example_Gateset.txt")
gs_mc2gst = pygsti.io.load_gateset("tutorial_files/Example_MC2GST_Gateset.txt")
ds = pygsti.io.load_dataset("tutorial_files/Example_Dataset.txt", cache=True)
fiducials = pygsti.io.load_gatestring_list("tutorial_files/Example_FiducialList.txt")
germs = pygsti.io.load_gatestring_list("tutorial_files/Example_GermsList.txt")
maxLengths = json.load(open("tutorial_files/Example_maxLengths.json","r"))
specs = pygsti.construction.build_spam_specs(fiducials)
Loading tutorial_files/Example_Dataset.txt: 100% Writing cache file (to speed future loads): tutorial_files/Example_Dataset.txt.cache
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.
#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
gauge_opt_pboot_gatesets = pygsti.drivers.gauge_optimize_gs_list(param_boot_gatesets, gs_mc2gst,
plot=True)
Spam weight 0 Spam weight 1 Spam weight 2 Spam weight 3 Spam weight 4 Spam weight 5 Spam weight 6 Spam weight 7 Spam weight 8 Spam weight 9 Spam weight 10 Spam weight 11 Spam weight 12 Best SPAM weight is 0.0001
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
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.)
#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
gauge_opt_npboot_gatesets = pygsti.drivers.gauge_optimize_gs_list(nonparam_boot_gatesets, gs_mc2gst,
plot=True)
Spam weight 0 Spam weight 1 Spam weight 2 Spam weight 3 Spam weight 4 Spam weight 5 Spam weight 6 Spam weight 7 Spam weight 8 Spam weight 9 Spam weight 10 Spam weight 11 Spam weight 12 Best SPAM weight is 0.0001
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
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.')
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