This is a significant release, bringing the plugin up to date with the latest
PennyLane and Qiskit features.
New features since last release
* The plugin and the tests have been completely re-written from scratch, to ensure
high quality and remove technical debt.
[44](https://github.com/XanaduAI/pennylane-qiskit/pull/44)
[43](https://github.com/XanaduAI/pennylane-qiskit/pull/43)
* Samples and variance support have been added to all devices.
[46](https://github.com/XanaduAI/pennylane-qiskit/pull/46)
* Multi-qubit hermitian observables are now supported, due to
support being added in Qiskit version 0.12.
* Support has been added for IBM Q Experience 2.0.
[44](https://github.com/XanaduAI/pennylane-qiskit/pull/44)
Improvements
* Hardware and software devices are now treated identically, with expectations,
variance, and samples computed via the _probability_, not the amplitudes.
This has several consequences:
- It makes the code cleaner and simpler, as there is now one defined
way of computing statistics.
- It is faster in most cases, as this does not require computing
large matrix-vector products, or Kronecker products. Instead,
eigenvalues of single- and multi-qubit observables are computed using
dyanamic programming.
- It reduces the number of tests required.
* Test suite now includes tests against the IBM Q Experience, in addition
to the local simulators.
Bug fixes
* Due to the move to IBM Q 2.0 credentials, users remaining with IBM Q v1.0
now must pass an additional URL argument to the service. The plugin
has been modified to allow the user to pass this argument if required.
[44](https://github.com/XanaduAI/pennylane-qiskit/pull/44)
Contributors
This release contains contributions from:
Shahnawaz Ahmed, Josh Izaac
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