pygsti.report.direct_mc2gst_gateset

pygsti.report.direct_mc2gst_gateset(gateStringToEstimate, gateStringLabel, dataset, specs, targetGateset, svdTruncateTo=0, minProbClipForWeighting=0.0001, probClipInterval=(-1000000.0, 1000000.0), verbosity=0)

Constructs a gateset of LSGST estimates for target gates and gateStringToEstimate.

Starting with a Direct-LGST estimate for gateStringToEstimate, runs LSGST using the same strings that LGST would have used to estimate gateStringToEstimate and each of the target gates. That is, LSGST is run with strings of the form:

  1. prepStr
  2. effectStr
  3. prepStr + effectStr
  4. prepStr + singleGate + effectStr
  5. prepStr + gateStringToEstimate + effectStr

and the resulting Gateset estimate is returned.

Parameters:
  • gateStringToEstimate (GateString or tuple) – The single gate string to estimate using LSGST
  • gateStringLabel (string) – The label for the estimate of gateStringToEstimate. i.e. gate_matrix = returned_gateset[gate_label]
  • dataset (DataSet) – The data to use for LGST
  • specs (2-tuple) – A (prepSpecs,effectSpecs) tuple usually generated by calling build_spam_specs(...)
  • targetGateset (GateSet) – The target gate set used by LGST to extract gate labels and an initial gauge
  • svdTruncateTo (int, optional) – The Hilbert space dimension to truncate the gate matrices to using a SVD to keep only the largest svdToTruncateTo singular values of the I_tildle LGST matrix. Defaults to no truncation.
  • minProbClipForWeighting (float, optional) – defines the clipping interval for the statistical weight used within the chi^2 function (see chi2fn).
  • probClipInterval (2-tuple, optional) – (min,max) to clip probabilities to within GateSet probability computation routines (see GateSet.bulk_fill_probs)
  • verbosity (int, optional) – Verbosity value to send to do_lgst(...) and do_mc2gst(...) calls.
Returns:

A gateset containing LSGST estimates of gateStringToEstimate and the gates of targetGateset.

Return type:

Gateset