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Paddle Quantum 2.2.2
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@Quleaf Quleaf released this 07 Dec 08:29
· 7 commits to master since this release
v2.2.2
2ac9f37

Release Note

New Features

  • paddle_quantum.ansatz.Circuit:
    • New member function plot: now we can plot the circuit using matplotlib.
  • paddle_quantum.gate:
    • New Gate Sdg: dagger of the S gate
    • New Gate Tdg: dagger of the T gate
  • New Gate member gate_info: contains the necessary information for the Gate class. You can revise this member to adjust the appearance of a particular gate class in Circuit.plot.
  • paddle_quantum.channel:
    • New Channel MixedUnitaryChannel: a random mixed unitary channel.
    • Kraus operator of the Depolarizing channel is revised for consistency with the representation in QCQI.
    • New Channel ChoiRepr: a general quantum channel under the Choi representation.
  • New Channel StringspringRepr: a general quantum channel under the Choi representation.
  • paddle_quantum.state:
    • paddle_quantum.state.State:
      • New member function normalize: provide the ability to be self-normalized.
      • New member function evolve: provide the ability of self-evolution for a given Hamiltonian and time.
      • New member function kron: Kronecker product for State class.
    • New function is_state_vector: verify whether the input data is a legal state vector.
    • New function is_density_matrix: verify whether the input data is a legal density matrix.
  • New operation @: matrix multiplication for State class (under density_matrix backend).
  • paddle_quantum.qpp: new module, providing a systematic set of tools for quantum phase processing. See the corresponding tutorial for more details.
  • paddle_quantum.qml: new module that includes models in the domain of QML. Currently it contains the VSQL (Variational Shadow Quantum Learning) model and related functionals.

Improvements

  • paddle_quantum.linalg: inputs of functions are now compatible with paddle_quantum.state.State, paddle.Tensorand numpy.ndarray.
  • paddle_quantum.qinfo:
    • Inputs of functions are now compatible with paddle_quantum.state.State, paddle.Tensorand numpy.ndarray.
  • Rewrite the logic of partial_trace, partial_trace_discontiguous and partial_transpose using tensor contraction, significantly improving the performance of these three functions.

New Tutorials

Introduction

  • Add the introduction part for the resolution of version conflict happened when using QuLeaf to connect the quantum computer.

Machine Learning

  • Add the tutorial Variational quantum amplitude estimation which implements single-qubit variational quantum amplitude estimation (VQAE).

Quantum Simulation

  • Add the tutorial Hamiltonian Simulation with qDRIFT which introduces a random method named quantum stochastic drift protocol (qDRIFT) which is based on product formula.
  • Add the tutorial Quantum Phase Processing which provides access to the eigenphases of the target unitary, allowing phase transformation or extraction to be done in an efficient and precise manner.
  • Add the tutorial Variational Quantum Metrology which introduces a variational method to search an optimal Ramsey interferometer for estimating the unknown parameters.

Bug Fixes

  • Fix the bug in the paddle_quantum.ansatz.vans module caused by the implementation of the parameter gate.
  • Fix some typo and mistakes in the tutorials and the API docs.

Dependencies

  • cvxpy: newly added.
  • rich: newly added.
  • scipy: remove the version restrictions.
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