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Releases: dwavesystems/dwave-system

1.26.0

10 Sep 21:10
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Fixes

  • Use default resource class for macos builds on CircleCI. See #523.
  • Remove ambiguous xrefs to reduce build warnings. See #524.
  • Update for dwave-cloud-client~=0.13 and dwave-optimization~=0.3.0. See #533, #534.

Deprecation Notes

  • Deprecate VirtualGraphComposite. See #532.

1.25.0

14 Jun 15:53
9fe827d
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New Features

  • Add LeapHybridNLSampler. See #518.

Fixes

  • Update MockDWaveSampler for fast anneal. See #520.
  • Remove conditional aggregation from ReverseBatchStatesComposite. See #517.

1.25.0.dev0

12 Jun 22:20
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1.25.0.dev0 Pre-release
Pre-release

New Features

  • Add LeapHybridNLSampler

1.24.0

17 Apr 17:18
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New Features

  • Conversion from flux_biases (units of Phi0) to h (unitless) and vice-versa. See #513.

Fixes

  • Adapt MockLeapHybridSolver to work with cloud-client 0.11.3+. See #515.

1.23.0

16 Jan 15:58
13809d9
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New Features

  • NetworkX is no longer a direct dependency. See #504.

Deprecation Notes

  • Deprecate common_working_graph(). It will be removed in dwave-system 2.0. Use networkx.intersection() instead.

1.22.0

30 Nov 19:38
a1bac31
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New Features

  • Add support for Python 3.12.
  • Update the properties of the MockDWaveSampler to be more realistic. See #503.

1.21.0

05 Oct 17:23
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New Features

  • Add support for dwave-cloud-client~=0.11.0. See #500.

  • Improve performance of BQM embedding. See #498.

Fixes

  • Fix networkx missing from requirements. See #494.

  • Add time unit missing in docs. See #497.

Upgrade Notes

  • Drop support for Python 3.7. See #499.

1.20.0

26 Jul 18:07
b371200
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New Features

  • Support Python 3.11

Upgrade Notes

  • Require dimod>=0.12.7

1.19.0

29 May 20:40
d37ff69
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New Features

  • Improved documentation. See #491.

Fixes

  • Add missing dwave.embedding.zephyr namespace. See #490.

1.18.0

14 Dec 00:38
3e15d25
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Fixes

  • Fix the default time_limit calculation in LeapHybridCQMSampler. See #482.

Upgrade Notes

  • Use SciPy>=1.7.3
  • Use dwave-samplers rather than dwave-greedy
  • Use NumPy>=1.20.0
  • Use dwave-preprocessing>=0.5.0
  • Use dimod>=0.12.0