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Releases: PennyLaneAI/pennylane-pq

Version 0.4.1

08 Aug 08:26
453d1bf
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Bug fixes

  • Remove opening of requirements.txt from within setup.py. This avoids a FileNotFoundError if installing via pip, as Python renames this file during packaging to requires.txt.
    (#53)

Contributors

This release contains contributions from (in alphabetical order):

Josh Izaac

v0.4.0

29 Jun 10:04
9ca9e59
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Updating the plugin to work with PL version 0.4. Changes

  • Adds support for PennyLane version 0.4. This includes:

    • Renaming expectation -> observable in various places in the documentation
    • Device.expectations -> Device.observables
    • Device.pre_expval -> Device.pre_measure
    • Device.post_expval -> Device.
  • Adds support for pennylane.var() QNode return type

  • Updates the minimum required PennyLane version to 0.4

  • Update the documentation to reflect PennyLane v0.4 support

Release 0.2.1

13 Feb 22:37
9c98bff
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Bug fix release. Allows PennyLane-ProjectQ devices to be used with all newer version of PennyLane, not just version 0.2.0.

Release 0.2

30 Jan 22:00
4a2d289
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New features since last release

  • Adds support for PennyLane v0.2
  • Increases the number of supported measurements on the IBM backend by automatically applying operations before the the final measurement (which is always in the PauliZ basis) (#38)
  • Adds support for the new PennyLane Identity expectation in all devices provided by this plugin (#36)
  • The simulator backend now supports the simulation of finite statistics expectation values if shots!=0, by sampling from the exact probability distribution (#35)

Improvements

  • Improved the documentation of specifying credentials via the configuration file (#48)
  • Improves the handling of kwargs and the corresponding documentation (#39)
  • Corrected and improved documentation of the supported operations

Contributors

This release contains contributions from:

Christian Gogolin

Release 0.1

13 Nov 09:54
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First public release of PennyLane ProjectQ plugin.

Contributors

This release contains contributions from:

Christian Gogolin, Maria Schuld, Josh Izaac, Nathan Killoran, and Ville Bergholm.