tensorflow/quantum

StochasticCost as a feature of layers

Open

#411 geöffnet am 12. Okt. 2020

Auf GitHub ansehen
 (2 Kommentare) (0 Reaktionen) (0 zugewiesene Personen)Python (653 Forks)github user discovery
area/performancehelp wantedkind/feature-requestskill-level/expertstatus/needs-design

Repository-Metriken

Stars
 (2.145 Stars)
PR-Merge-Metriken
 (PR-Metriken ausstehend)

Beschreibung

In the past, subsampling of PauliTerms from input PauliSums was taken care of by an option in the SGDifferentiator module. However, there were a few issues with its implementation there:

  1. Instead of subsampling PauliTerms from PauliSums, it actually changed the shape of the measurement tensor by subsampling PauliSums.
  2. Had a python implementation instead of a C++ op backend.
  3. Does not fit the new differentiator interface being implemented in #409 .

Fortunately, in discussions on the design doc for the new differentiators, it looks like this could be a feature we still want to keep, and pull up to the level of tfq.layers. Since, this subsampling of PauliTerms can speed up the estimation of expectation values in any context, not just when seeking gradients. See also #230 for the possible interaction of such a feature with Engine. Thinking to take this on in the near future. Thoughts on this @MichaelBroughton @jaeyoo ?

Contributor Guide