QuAIRKit 0.4.4 Release Note

Feature Rollout

• OpenQASM 2.0 import support: Circuit.from_qasm2() enables loading quantum circuits from OpenQASM 2.0 strings, supporting standard gates, measurements, and reset operations.
• Circuit feature update:
  • Negative index support: Circuit operations now support negative indices (counting from the end).
  • Batch support for encoding layers: basis_encoding, amplitude_encoding, angle_encoding, iqp_encoding now support batch operations.
  • Batch support for QASM: QASM export and related functions now support batch processing.
  • Circuit.from_operators: reconstruct a Circuit from a saved operator list.
  • Enhanced reset functionality: reset method now accepts torch.Tensor as replace_state parameter.
• Performance optimization: Operator acceleration and improved batch measurement execution with gradient support.

Stability Update

• Improved numerical stability in state collapse and measurement operations.
• Enhanced system index handling and validation in Circuit methods.
• Refactored LOCCNet and measurement logic for better performance and reliability.
• Improved probability dimension handling in state simulators and batch operations.
• Expanded unit test coverage for circuit and state-related functionals.
• Fixed tensor shape handling and cloning issues in state evolution methods.

New Tutorials

• Add a tutorial for new features
  • LOCCNet: Quantum State Discrimination

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QuAIRKit 0.4.3 Release Note

Stability Update

• Added future warnings for updated interfaces
• Added minor bug fixes on LOCCNet and CNOT computation.

New Tutorials

• Add nine tutorials for the course AIAA 5072 instructed in HKUST(GZ), including
  • Brief Introduction to Quantum Computing
  • Quantum error mitigation
  • Variational quantum eigensolver
  • Entanglement
  • Superdense coding
  • Quantum state teleportation
  • Quantum state amplitude amplification
  • Quantum phase estimation
  • Hamiltonian simulation

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QuAIRKit 0.4.1 Release Note

Feature Rollout

• Third-party cloud integration: QuAIRKit can now set backend to third-party cloud platforms, and support measurement & expectation value with gradients.
• Circuit feature update:
  • encoding layers: data encoding layer interfaces, including basis_encoding, amplitude_encoding, angle_encoding, iqp_encoding.
  • qasm & qasm2: export circuit to OpenQASM-like or OpenQASM 2.0 format.
  • quasi & param_quasi: interfaces for appending (parameterized) quasi-probability unitary operations.
  • Circuit.dagger: reverse the entire circuit with inverse operators.
• LOCC functionals: new application OneWayLOCCNet, designed for simulating and searching LOCC protocols.

Stability Update

• Improved the computation logic for Measure, Collapse and CNOT.
• Expanded unit test coverage for LOCC and circuit-related functionals.
• Functions in database that support qudit inputs do not have to specify num_systems.

New Tutorials

• Add three tutorials for new features, including
  • Drawing Quantum Circuits with QuAIRKit
  • Running QuAIRKit with third-party quantum cloud platforms
  • Quantum State Teleportation and Distribution

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QuAIRKit 0.4.0 Release Note

Feature Rollout

• Physical mapping: Circuit can now be initialized with the argument physical_idx, enabling operations such as concatenation and sorting of circuits based on their physical locations.
• Circuit interface update:
  • Added new permutation gates: Circuit.permute (permutation gate) and Circuit.control_permute (controlled permutation gate).
  • Added new Trotter decomposition layer: Circuit.trotter, which implements Hamiltonian evolution operators via Trotter decomposition.
  • Expanded oracle functionality: Circuit.oracle and Circuit.param_oracle now accept an optional argument control_idx (default: None), allowing controlled operations at different positions. The method Circuit.control_oracle will be gradually deprecated in future releases. For example, the usage

  cir.oracle(u, [[0, 1], 2], control_idx=3)

is equivalent to applying the unitary:

$$(I - \ket{10}\bra{10}) \otimes I + \ket{10}\bra{10} \otimes U$$

• LaTeX plot: Circuit visualization in QuAIRKit is now rendered via Quantikz, a LaTeX package for quantum circuits, replacing the previous Matplotlib implementation. Users with a local LaTeX installation (TeX Live 2024 or newer recommended) can now generate high-quality circuit diagrams & LaTeX codes directly from Circuit.plot, supporting academic visualizations including:
  • circuit presentation in different forms (adjusted by argument style)
  • channels, multi-controlled operations, SWAP and permutations.
  • measurements, post-selections and one-way LOCC operations.

Stability Update

• Remove setup.py to fit PEP 660.
• Simplified the computation logic of controlled gates.
• Expanded unit test coverage to include features introduced in v0.3.0.
• All parameterized matrix functions in database.matrix now support batch processing of parameter inputs.
• Added detailed code examples in docstrings for functions in modules qinfo, database, loss and attributes within Circuit.
• Add several bug fixs & improvements, including:
  • Fixed an issue preventing Circuit from containing multiple probabilistic operations.
  • Fixed incorrect handling of logarithm bases other than 2 in qinfo.von_neumann_entropy.
  • Improved numerical stability by re-implementing qinfo.sqrtm purely in PyTorch, removing dependency on SciPy..

New Tutorials

• Add four tutorials, for user to learn to use QuAIRKit to study research problems in quantum computing, inlcuding
  • Analyze Barren Plateau in quantum neural networks
  • Hamiltonian simulation via Trotter decomposition
  • Rediscovering Simon's algorithm with PQC
  • Training quantum process transformation with PQC

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QuAIRKit 0.3.0 Release Note

Feature Rollout

• Probabilistic computation: internally supported parallel (pure & mixed state) computations for probabilistic outcomes generated by measurements or quasi-sampling:
  • Circuit.collapse: renamed as Circuit.measure. When desired_result is None, calling this attribute would store all mid-circuit measurement outcomes and the corresponding probability distribution.
  • Measure: same as above.
  • Circuit.locc: add one-way LOCC (unitary) protocol to the circuit. Detailed tutorials will be released in the next version.
  • State.index_select: replaced by State.prob_select, which can be called to select the particular outcome.
• Controlled operation: QuAIRKit now support multi-control unitaries:
  • Circuit.control_oracle: can inputs multi-control indices and customized projections.
    For example, cir.control_oracle(u, [[0, 1], 2], P) is equivalent to inserting the unitary

$$(I - P) \otimes I + P \otimes U$$

• Quantum information functions: Advanced the quairkit.qinfo module with the following changes:
  • mutual_information: compute the mutual information of a bipartite state
  • general_state_fidelity: compute the fidelity of two subnormalized states.
  • Nkron: now supports trivial inputs, and has an alias name nkron

Stability Update

• All matrix and channel representation functions are compatible with NumPy inputs and outputs.
• Add code examples in docstrings of functions in database.
• Improve the efficiency and interfaces of PQCombNet, which is now imported by quairkit.application.
• Add bug fixes.

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QuAIRKit 0.2.0 Release Note

Feature Rollout

• Qudit computation: QuAIRKit now support qudit systems in state evolution, circuit measurement, database generation and training. These covered functionals accept num_systems and system_dim as inputs.
  • argument num_systems is aliased with num_qubits
  • argument system_dim accepts both interger or a list of integers, representing the dimensions of all systems. Defaults to 2, i.e., all systems are qubits.
• Quantum information functions: Advanced the quairkit.qinfo module with the following changes:
  • partial_trace & partial_transpose: The interfaces of these two functions are aligned with PartialTrace and PartialTranspose in QETLAB. Moreover, these functions support qudit computations.
    • transpose_2 is now removed from quairkit.
    • partial_trace_discontiguous remains unchanged, but only supports qubit systems.
  • is_povm & is_pvm: Check whether the input set of matrices form a POVM or PVM.
  • mana_state & mana_channel: Compute the mana of input state/channel.
  • stab_nullity & stab_renyi: Compute the stabilizer nullity/Renyi entropy of input state
  • Almost all functions in quairkit.qinfo support batched array inputs.
• Training: Add training net PQCombNet for quantum circuit architectural search, can be imported by quairkit.ansatz.comb.
• State features: Add the following properties & methods for flexible usage
  • system_dim: User now can change the system dimensions of a State instance.
  • trace, transpose & permute: same as partial_trace, transpose & permute_systems, except there is no need to input data or specify system dimensions.
  • sqrt & log: same as sqrtm & logm

Stability Update

• Import regulation: Add __init__ to all top-level modules, so that the following commands

from quairkit.database import *
from quairkit.loss import *
from quairkit.qinfo import *

would not import some unexpected variables.

• GPU speedup: Significantly improve GPU performances on batch computations.
• Add quairkit.print_info function that can print all packages and hardware information for sanity check.
• Add bug fixes and API improvements.

Tutorials

• Rewrite 4 old tutorials to improve readability.
• Add 4 new introduction tutorials, including:
  • Hamiltonian in QuAIRKit
  • Quantum gates and quantum channels
  • Quantum information tools
  • Training parameterized quantum circuits
• Add 2 new feature tutorials, including:
  • Neural network setup customization
  • Introduction to qudit quantum computing

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QuAIRKit 0.1.0 Release Note

QuAIRKit absorbs the features and semantics of Paddle Quantum v2.4.0, while making the following improvements:

Technical Improvements

• Backend Transition: transitioned the computational backend from Paddle Paddle to PyTorch, improving both stability and compatibility with existing packages.

• Modular Codebase: refactored the codebase into five discrete modules to streamline the user experience. This modular approach facilitates easier maintenance, scalability, and collaborative development.

• Batch Computation: internally supported batch computation for

  • quantum (noisy) circuit simulation;
  • expectations and measurement

Basic broadcasting rule in QuAIRKit:

Batched shape for operations	Batched shape for input states	Batched shape for output results
None	None	None
None	n	n
n	None	n
n	n	n
n	m	Error

• Pure & Mixed Auto-transition: there is no longer needed to specify the backend state_vector or density_matrix. QuAIRKit supports implicit backend transition between pure state and mixed state simulators.

Feature Rollout

• Random Seed Initialization: introduced quairkit.set_seed to initialize a random seed across all random functionals within the platform.

• Quantum computing data: Expanded the quairkit.database module with the following data:

  • phase & shift: phase and shift operators in quantum information.
  • universal_qudit: a parameterized universal qudit gate, based on parameterization with respect to Gell-Mann matrices.
  • Uf & Of: two quantum query models for Boolean functions.
  • A collection of set-based data, including:
    • std_basis & qft_basis: two quantum state bases for identity & QFT matrices, respectively.
    • bell_basis: a two-qubit Bell basis.
    • heisenberg_weyl: a set of Heisenberg-Weyl operators.
    • phase_space_point: a set of phase-space point operators in discrete phase space.
    • gell_mann: a set of Gell-Mann matrices.

• Quantum information functions: Expanded the quairkit.qinfo module with the following functions:

  • is_linear: ascertains the linearity of a given function.
  • create_matrix: constructs the matrix representation of a linear map between two vector spaces.
  • create_choi_repr: constructs the Choi representation of a linear map between two operator spaces.
  • trace_norm & p_norm: Schatten norm functions.
  • trace: Trace of input tensor along a specified axis.
  • hessian & gradient: The Hessian and general gradient of input functions.
  • decomp_1qubit & decomp_ctrl_1qubit: Decomposition of (controlled) qubit-unitary operations.

Resolved Issues

• Bug Fix: corrected various typos and inaccuracies previously present in the database.
• Controlled qubit-unitary: controlled qubit-unitary operations now require parameterization from 3 to 4 parameters.

Dependencies Update

• The minimum requirement for the Python environment has been changed to Python 3.8.
• Add pytest-xdist for unit tests.

Tutorials

Added four tutorials for feature introductions of QuAIRKit:

• circuit: quantum circuit & basic machine learning
• measure: quantum measurement
• state: quantum state
• batch: batch computation

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