mindquantum 发行版

v0.11.0

2025-08-07 01:18

0.11.0

## MindQuantum 0.11.0 Release Notes

### 主要特性和增强

#### Simulator

- [STABLE] [`mqchem`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.mqchem.MQChemSimulator.html): 新增 `mqchem` 模拟器后端。该模拟器基于配置相互作用（CI）方法，通过在固定电子数的子空间中进行计算，为量子化学问题提供了内存和计算效率更高的解决方案。其核心组件包括 ([`!2717`](https://gitee.com/mindspore/mindquantum/pulls/2717))：
    - [`MQChemSimulator`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.mqchem.MQChemSimulator.html): CI空间模拟器，默认初始化为Hartree-Fock态。
    - [`UCCExcitationGate`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.mqchem.UCCExcitationGate.html): 用于构建UCC拟设线路的专用激发门。
    - [`CIHamiltonian`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.mqchem.CIHamiltonian.html): 用于在CI空间中高效计算期望值的哈密顿量包装器。
    - [`prepare_uccsd_vqe`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.mqchem.prepare_uccsd_vqe.html): 自动化UCCSD-VQE实验准备流程的高级函数。
- [STABLE] [`mqvector_cq`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html): 新增 `mqvector_cq` 模拟器后端，利用 NVIDIA cuQuantum SDK 进一步加速在 NVIDIA GPU 上的量子线路模拟 ([`!2724`](https://gitee.com/mindspore/mindquantum/pulls/2724))。该后端依赖于cuquantum，因此需要在环境中正确安装cuqauntum后方可使用，详情请参考cuquantum官网上的安装指南。

#### Algorithm

- [STABLE] **QAIA 算法后端扩展**: 为量子退火启发式算法（QAIA）家族（包括 [`ASB`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.ASB.html), [`BSB`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.BSB.html), [`DSB`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.DSB.html), [`LQA`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.LQA.html), [`CAC`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.CAC.html), [`CFC`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.CFC.html), [`SFC`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.SFC.html), [`NMFA`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.NMFA.html), [`SimCIM`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.SimCIM.html)）新增了基于 PyTorch 的 GPU 和 NPU 后端支持，显著提升了在相应硬件上的计算性能。用户现在可以通过 `backend` 参数选择 `'gpu-float32'` 或 `'npu-float32'` ([`!2669`](https://gitee.com/mindspore/mindquantum/pulls/2669), [`!2678`](https://gitee.com/mindspore/mindquantum/pulls/2678))。

### 问题修复

- [`PR2727`](https://gitee.com/mindspore/mindquantum/pulls/2727): 修复了线路图的 SVG 导出功能在处理多控 CNOT 门时只显示一个控制比特的问题。
- [`PR2717`](https://gitee.com/mindspore/mindquantum/pulls/2717): 修复了 `uccsd_singlet_get_packed_amplitudes` 中双激发振幅索引错误的问题，确保了从CCSD计算中提取的振幅的正确性。
- [`PR2716`](https://gitee.com/mindspore/mindquantum/pulls/2716): 修复了 SABRE 和 MQSABRE 映射算法在处理非连续物理比特ID（例如，`[12, 13, 15]`）时会崩溃的问题。
- [`PR2713`](https://gitee.com/mindspore/mindquantum/pulls/2713): 修复了 `TimeEvolution` 在处理含常数项（单位算符）的哈密顿量时的问题，现在会正确地将其转换为全局相位门。
- [`PR2679`](https://gitee.com/mindspore/mindquantum/pulls/2679): 修复了 NMFA 算法在包含外场 `h` 时 `J_norm` 计算不正确的问题。
- [`PR2714`](https://gitee.com/mindspore/mindquantum/pulls/2714): 修复了在 Windows CI 环境下，当 Python 安装在带空格的路径中时可能出现的链接器错误。
- [`PR2650`](https://gitee.com/mindspore/mindquantum/pulls/2650): 修复了 `Rn` 门在某些情况下可能出现的除零错误。
- [`PR2648`](https://gitee.com/mindspore/mindquantum/pulls/2648): 修复了 `sabre` 映射算法中 `barrier` 门处理不当的问题。

### 其他更新

- **QAIA 算法**:
    - 增强了对输入参数的检查，确保耦合矩阵 `J` 是对称且对角线为零，为用户提供更明确的指引 ([`!2710`](https://gitee.com/mindspore/mindquantum/pulls/2710))。
    - 优化了 [`LQA`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.LQA.html) 算法，通过缓存中间计算结果减少了冗余计算 ([`!2656`](https://gitee.com/mindspore/mindquantum/pulls/2656))。
    - 改进了部分算法中数值不稳定时的错误提示信息，使其更具指导性 ([`!2710`](https://gitee.com/mindspore/mindquantum/pulls/2710))。
- **依赖项**: 更新了依赖项，现在要求 `scipy>=1.13.1`。
- 为 `ParameterResolver` 中出现复数以及 `SB` 模拟器使用 `int8` 精度时增加了警告提示 ([`!2651`](https://gitee.com/mindspore/mindquantum/pulls/2651))。

### 贡献者

感谢以下开发者做出的贡献：

beastsenior, dsdsdshe, GhostArtyom, liushiwei2024, lyq, MangroveCoder, YangleiSHAO, zengqg, ZhuangJP, 葛宇非, 满成, 肖阳, 左博伟.

欢迎以任何形式对项目提供贡献！

最后提交信息为： !2730 feat(build): Enable Position Independent Executables (PIE)

v0.10.0

1e951a1

2025-02-13 19:29

0.10.0

# MindQuantum Release Notes

## MindQuantum 0.10.0 Release Notes

### 主要特性和增强

#### Algorithm

- [BETA] [`virtual_distillation`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/error_mitigation/mindquantum.algorithm.error_mitigation.virtual_distillation.html): 新增基于虚拟蒸馏的误差缓解算法，通过创建量子态的虚拟副本并在纠缠系统上进行测量来减少量子噪声。
- [BETA] [`QuantumNeuron`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.QuantumNeuron.html): 新增基于重复直到成功（RUS）策略的量子神经元实现，通过量子电路模拟经典神经元行为，应用非线性函数旋转。
- [STABLE] [`SGAnsatz`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.SGAnsatz.html): 新增序列生成变分量子线路，可高效生成具有固定键维度的矩阵乘积态。该ansatz通过在相邻量子比特上应用参数化量子线路块，自然适应一维量子多体问题。
- [STABLE] [`SGAnsatz2D`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.SGAnsatz2D.html): 新增二维序列生成变分量子线路，可生成字符串键态。支持通过指定二维网格尺寸自动生成遍历路径，或通过自定义线路集合构建特定类型的string-bond态。
- [STABLE] [`qjpeg`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.qjpeg.html): 新增基于量子傅里叶变换的量子图像压缩算法，可以通过减少量子比特数量来压缩量子图像，同时保留频域中的关键信息。
- [STABLE] [`cnry_decompose`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/compiler/mindquantum.algorithm.compiler.cnry_decompose.html): 新增对CnRY门的分解。
- [STABLE] [`cnrz_decompose`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/compiler/mindquantum.algorithm.compiler.cnrz_decompose.html): 新增对CnRZ门的分解。
- [STABLE] [`BSB`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.BSB.html): 为弹道模拟分叉算法添加GPU加速支持，支持`'cpu-float32'`, `'gpu-float16'`, `'gpu-int8'`三种精度选项。
- [STABLE] [`DSB`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/qaia/mindquantum.algorithm.qaia.DSB.html): 为离散模拟分叉算法添加GPU加速支持，支持`'cpu-float32'`, `'gpu-float16'`, `'gpu-int8'`三种精度选项。
- [STABLE] [`qudit_symmetric_encoding`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.qudit_symmetric_encoding.html): 新增qudit编码功能，将d级量子态映射到量子比特态，通过对称编码实现，在标准量子比特量子计算机上高效模拟高维量子系统。
- [STABLE] [`qudit_symmetric_decoding`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.qudit_symmetric_decoding.html): 新增解码功能，将量子比特对称态或矩阵解码为qudit态或矩阵，增强对多能级量子系统的支持。解码过程涉及将对称量子比特态转换为相应的qudit态，便于在标准量子比特量子计算机上高效模拟高维量子系统。
- [STABLE] [`qutrit_symmetric_ansatz`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.qutrit_symmetric_ansatz.html): 引入qutrit对称ansatz，构建保持任意qutrit门编码对称性的量子比特ansatz。该功能通过利用对称性保持变换，允许在标准量子比特量子计算机上高效模拟高维量子系统。ansatz支持分解为`"zyz"`或`"u3"`基，并可选择性地包含全局相位。

#### Measure

- [STABLE] [`MeasureResult.to_json`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.MeasureResult.html#mindquantum.core.gates.MeasureResult.to_json): 支持测量结果的序列化和存储。
- [STABLE] [`MeasureResult.reverse_endian`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.MeasureResult.html#mindquantum.core.gates.MeasureResult.reverse_endian): 支持反转测量结果中比特串和测量键的字节序。

#### Operator

- [STABLE] [`mat_to_op`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.mat_to_op.html): 新增从矩阵转换为`QubitOperator`的函数，支持小端和大端量子比特排序，以便与不同的量子计算框架无缝集成。

#### Circuit

- [STABLE] 新增[`Circuit.from_qcis()`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.from_qcis)和[`Circuit.to_qcis()`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.to_qcis)函数，支持与QCIS格式互转。
- [STABLE] 新增`__eq__`和`__ne__`方法，支持电路对象比较。
- [STABLE] [`Circuit.depth()`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.depth): 新增获取量子线路深度的功能，支持考虑单比特门和栅栏门对电路深度的影响，帮助用户更好地评估和优化量子线路的复杂度。

#### Simulator

- [STABLE] [`get_reduced_density_matrix`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_reduced_density_matrix): 新增获取指定量子比特约化密度矩阵的功能，通过对其他量子比特执行部分迹运算来实现。
- [STABLE] [`get_qs_of_qubits`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_qs_of_qubits): 新增获取指定量子比特量子态的功能。如果结果态是纯态，则返回态矢量；如果是混态，则返回密度矩阵。支持以 ket 记号（狄拉克记号）格式返回量子态。
- [STABLE] 模拟器后端选择"stabilizer"时，支持使用[`reset`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.reset)重置量子态。
- [STABLE] 模拟器后端选择"stabilizer"时，支持使用[`get_expectation`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation)计算给定哈密顿量在当前量子态下的期望值。

#### Compiler

- [STABLE] [`U3Fusion`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/compiler/mindquantum.algorithm.compiler.U3Fusion.html): 新增将连续的单量子比特门融合为一个U3门的编译规则。该规则扫描电路并将作用在同一量子比特上的连续单量子比特门组合成单个U3门。对于独立的单量子比特门，也会被转换为U3形式。可选择是否跟踪和包含全局相位。
- [STABLE] [`u3_decompose`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/compiler/mindquantum.algorithm.compiler.u3_decompose.html): 新增将U3门分解为Z-X-Z-X-Z旋转序列的功能。支持标准分解（U3(θ,φ,λ) = Rz(φ)Rx(-π/2)Rz(θ)Rx(π/2)Rz(λ)）和替代分解（U3(θ,φ,λ) = Rz(φ)Rx(π/2)Rz(π-θ)Rx(π/2)Rz(λ-π)）两种方法。当任何旋转角度为常数且等于0时，相应的RZ门将被省略。
- [STABLE] [`DecomposeU3`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/compiler/mindquantum.algorithm.compiler.DecomposeU3.html): 新增U3门分解的编译规则，将U3门分解为Z-X-Z-X-Z旋转序列。支持标准和替代两种分解方法。

#### IO

- [STABLE] [`QCIS`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/io/mindquantum.io.QCIS.html): 新增量子电路与QCIS格式转换类。

#### Utilities

- [STABLE] [`random_hamiltonian`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/utils/mindquantum.utils.random_hamiltonian.html): 新增随机泡利哈密顿量生成功能。支持指定量子比特数量和泡利项数量，可设置随机种子以保证结果可重现。生成的哈密顿量可用于量子算法测试和基准测试。

### 破坏性改动

- [重要] `MeasureResult` 中的 `keys`、`samples` 的字节序被统一为小端序（little-endian）。如果您的代码使用了这两个属性，请小心检查并使用新增的 `reverse_endian` 方法进行调整。

### 问题修复

- [`PR2497`](https://gitee.com/mindspore/mindquantum/pulls/2497)：修复了 **Amplitude Encoder** 中参数名可能重复的问题。
- [`PR2410`](https://gitee.com/mindspore/mindquantum/pulls/2410)：修复了 `is_measure_end` 的错误，该错误会导致即使没有测量操作也返回 `True`。
- [`PR2410`](https://gitee.com/mindspore/mindquantum/pulls/2410)：修复了在双量子比特门中颠倒量子比特顺序后计算结果不正确的问题。
- [`PR2377`](https://gitee.com/mindspore/mindquantum/pulls/2377)：修复了 `DAGCircuit` 在处理深层线路时会出现递归错误的问题，现在支持对任意深度线路的处理。
- [`PR2345`](https://gitee.com/mindspore/mindquantum/pulls/2345)：修复了 `mqmatrix` 的 `get_expectation_with_grad` 方法在处理批量哈顿量时计算错误的问题，并添加了测试用例。
- [`PR2345`](https://gitee.com/mindspore/mindquantum/pulls/2345)：修复了未按指定顺序添加门并使用 `reverse_qubits` 时出现的错误。
- [`PR2345`](https://gitee.com/mindspore/mindquantum/pulls/2345)：修正了 `FermionOperator.hermitian()` 示例代码中的错误。
- [`PR2319`](https://gitee.com/mindspore/mindquantum/pulls/2319)：修复了 Stabilizer 模拟器的测量错误。
- [`PR2319`](https://gitee.com/mindspore/mindquantum/pulls/2319)：修复了 Stabilizer 模拟器中种子未正确应用的问题。
- [`PR2319`](https://gitee.com/mindspore/mindquantum/pulls/2319)：增加了对 Stabilizer 模拟器输出比特串正确性的检测。
- [`PR2315`](https://gitee.com/mindspore/mindquantum/pulls/2315)：使 **MQSim** 和 **Hamiltonian** 支持序列化，支持python多进程`multiprocessing`。
- [`PR2309`](https://gitee.com/mindspore/mindquantum/pulls/2309)：修复了 **QAOA** 的一些 ansatz 中缺失虚数项和系数的问题。
- [`PR2309`](https://gitee.com/mindspore/mindquantum/pulls/2309)：修复了 `QAOAAnsatz` 示例无法正常运行的问题。
- [`PR2309`](https://gitee.com/mindspore/mindquantum/pulls/2309)：修改了 ansatz 电路中的参数名称，使其与公式对应。
- [`PR2296`](https://gitee.com/mindspore/mindquantum/pulls/2296)：修复了 `kron_factor_4x4_to_2x2s()` 返回值的索引错误，确保了双比特门分解函数 `kak_decompose` 的正确性。
- [`PR2285`](https://gitee.com/mindspore/mindquantum/pulls/2285)：移除了计算梯度时不必要的输出。

### 其他更新

- 优化了量子线路第一次运行时的速度，提升了性能。
- 提高了 `params_zyz()` 函数的精度，提升了 **ZYZ** 分解的计算精度。
- 移除了未安装 `mqvector_gpu` 的警告信息，仅在使用时提示。
- 移除了未安装mindspore时的警告信息，仅在使用时提示。
- 当哈密顿量包含虚部时，增加了警告提示，提醒用户注意可能的计算结果异常。
- 提升了未安装 **MindSpore** 时警告信息的清晰度。
- 将 `pip` 源更改为清华镜像源。

### 贡献者

感谢以下开发者做出的贡献：

Arapat Ablimit, Chufan Lyu, GhostArtyom, LuoJianing, Mr1G, Waikikilick, donghufeng, dsdsdshe, xuxusheng, yuhan, zengqg, zhouyuanyang2024, 王上, 杨金元, 糖醋排骨.

欢迎以任何形式对项目提供贡献！

最后提交信息为： !2639 fix docs

v0.9.11

eb306d5

2024-01-31 17:47

v0.9.11

# MindQuantum Release Notes

## MindQuantum 0.9.11 Release Notes

### 主要特性和增强

#### Gates

- [STABLE] [`任意轴旋转门`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.Rn.html#mindquantum.core.gates.Rn): 新增绕布洛赫球上任意轴旋转的单比特门[`Rn`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.Rn.html#mindquantum.core.gates.Rn)。
- [STABLE] [`matrix`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.Rxx.html#mindquantum.core.gates.Rxx.matrix): 量子门支持通过该接口并指定参数`full=True`来获取量子门完整的矩阵形式（受作用位比特和控制位比特影响）。
- [STABLE] [`热弛豫信道`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.ThermalRelaxationChannel.html#mindquantum.core.gates.ThermalRelaxationChannel): 新增 ThermalRelaxationChannel 热弛豫信道。
- [Alpha] [`量子测量`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.Measure.html#mindquantum.core.gates.Measure): 测量门现支持比特重置功能，可将测量后的量子态重置为|0⟩态或者|1⟩态。优化测量门执行速度。
- [STABLE] [`RotPauliString`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.RotPauliString.html#mindquantum.core.gates.RotPauliString): 新增任意泡利串旋转门。
- [STABLE] [`GroupedPauli`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.GroupedPauli.html#mindquantum.core.gates.GroupedPauli): 新增泡利组合门，该门比逐个执行单个泡利门会更加快速。
- [STABLE] [`GroupedPauliChannel`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.GroupedPauliChannel.html#mindquantum.core.gates.GroupedPauliChannel): 新增泡利信道组合信道，该组合信道比逐一执行泡利信道更快。
- [STABLE] [`SX`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/gates/mindquantum.core.gates.SXGate.html): 新增根号X门。
- [STABLE] [Givens]: 新增Givens旋转门。

#### Circuit

- [STABLE] [`summary`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.summary): 通过该接口展示的量子线路汇总信息会以表格形式呈现，更加美观直接。
- [STABLE] [`svg`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.svg): 现在可以通过控制参数`scale`来对量子线路图进行缩放。
- [STABLE] [`openqasm`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit): 量子线路直接支持转化为[`openqasm`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.to_openqasm)或者从[`openqasm`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.from_openqasm)转化为mindquantum线路。

#### ParameterResolver

- [STABLE] [`PRGenerator`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/parameterresolver/mindquantum.core.parameterresolver.PRGenerator.html#mindquantum.core.parameterresolver.PRGenerator): [`new`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/parameterresolver/mindquantum.core.parameterresolver.PRGenerator.html#mindquantum.core.parameterresolver.PRGenerator.new)接口支持配置临时的前缀和后缀。

#### Ansatz

- [STABLE] [`硬件友好型量子线路`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/mindquantum.algorithm.nisq.html#ansatz): 新增多种硬件友好型量子线路，请参考论文[Physics-Constrained Hardware-Efficient Ansatz on Quantum Computers that is Universal, Systematically Improvable, and Size-consistent](https://arxiv.org/abs/2307.03563)。

#### Device

- [STABLE] [`QubitsTopology`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/device/mindquantum.device.QubitsTopology.html#mindquantum.device.QubitsTopology): 支持通过[set_edge_color](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/device/mindquantum.device.QubitsTopology.html#mindquantum.device.QubitsTopology.set_edge_color)设置不同边的颜色。支持通过`show`来直接展示拓扑结构图。

#### Simulator

- [STABLE] [`sampling`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.sampling): 加速量子模拟器在对不含噪声且测量门全部在线路末端的量子线路的采样。

#### utils

- [STABLE] [`进度条`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.utils.html#progress-bar): 新增两个基于rich构建的简单易用的进度条，分别为支持单层循环的[`SingleLoopProgress`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/utils/mindquantum.utils.SingleLoopProgress.html#mindquantum.utils.SingleLoopProgress)和支持两层循环的[`TwoLoopsProgress`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/utils/mindquantum.utils.TwoLoopsProgress.html#mindquantum.utils.TwoLoopsProgress)。
- [Alpha] [random_insert_gates]: 支持在量子线路中随机插入量子门。

#### Algorithm

- [Alpha] [`MQSABRE`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/mapping/mindquantum.algorithm.mapping.MQSABRE.html#mindquantum.algorithm.mapping.MQSABRE): 新增支持设置量子门保真度的比特映射算法。

### Bug Fix

- [`PR1971`](https://gitee.com/mindspore/mindquantum/pulls/1971): 修复[`amplitude_encoder`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/library/mindquantum.algorithm.library.amplitude_encoder.html#mindquantum.algorithm.library.amplitude_encoder)中符号错误问题。
- [`PR2094`](https://gitee.com/mindspore/mindquantum/pulls/2094): 修复[`get_expectation_with_grad`](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/simulator/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation_with_grad)在使用parameter shift规则时随机数种子单一性问题。
- [`PR2164`](https://gitee.com/mindspore/mindquantum/pulls/2164): 修复windows系统下的构建脚本传入参数问题。
- [`PR2171`](https://gitee.com/mindspore/mindquantum/pulls/2171): 修复密度矩阵模拟器在量子态复制时可能遇到的空指针问题。
- [`PR2175`](https://gitee.com/mindspore/mindquantum/pulls/2175): 修复泡利信道的概率可以为负数的问题。
- [`PR2176`](https://gitee.com/mindspore/mindquantum/pulls/2176): 修复parameter shift规则在处理含控制位量子门时的问题。
- [`PR2210`](https://gitee.com/mindspore/mindquantum/pulls/2210): 修复parameter shift规则在处理多参数门且部分参数为常数时的问题。

### 贡献者

感谢以下开发者做出的贡献：

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng, 朱祎康, dorothy20212021, dsdsdshe, buyulin, norl-corxilea, herunhong, Arapat Ablimit, NoE, panshijie, longhanlin.

欢迎以任何形式对项目提供贡献！

最后提交信息为： !2258 [PY] Fix openqasm for identity gate.

v0.9.0

ca1a612

2023-10-16 11:07

v0.9.0

# MindQuantum Release Notes

## MindQuantum 0.9.0 Release Notes

### 主要特性和增强

#### 数据精度

- [STABLE] `数据精度`: MindQuantum 现支持 `float32`、`float64`、`complex64`和`complex128`四种精度类型，可为各种算符、参数解析器和模拟器设置不同的精度类型。

#### Gates

- [STABLE] [`通用量子门`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#%E9%80%9A%E7%94%A8%E9%87%8F%E5%AD%90%E9%97%A8): 新增多个两比特泡利旋转门，包括：[`Rxx`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxx.html#mindquantum.core.gates.Rxx)，[`Rxy`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxy.html#mindquantum.core.gates.Rxy)，[`Rxz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxz.html#mindquantum.core.gates.Rxz)，[`Ryy`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Ryy.html#mindquantum.core.gates.Ryy)，[`Ryz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Ryz.html#mindquantum.core.gates.Ryz)和[`Rzz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rzz.html#mindquantum.core.gates.Rzz)。
- [STABLE] [`噪声信道`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#%E9%87%8F%E5%AD%90%E4%BF%A1%E9%81%93): 噪声信道现在支持通过 `.matrix()` 接口返回噪声信道的 kraus 算符。

#### Operator

- [STABLE] [`QubitOperator`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.QubitOperator.html#mindquantum.core.operators.QubitOperator): 新增 [`relabel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.QubitOperator.html#mindquantum.core.operators.QubitOperator.relabel) 接口，支持按照新的比特编号来重排算符。[`FermionOperator`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.FermionOperator.html#mindquantum.core.operators.FermionOperator.relabel)同样支持该功能。
- [STABLE] [`基态计算`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.ground_state_of_sum_zz.html#mindquantum.core.operators.ground_state_of_sum_zz): 新增接口支持计算只包含 pauli z 算符和 pauli z 算符的直积的哈密顿量的基态能量。

#### Ansatz

- [STABLE] [`Ansatz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#ansatz): 新增 Arixv:[`1905.10876`](https://arxiv.org/abs/1905.10876) 中提到的19个 ansatz，先均已实现。

#### Circuit

- [STABLE] [`ChannelAdder`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.circuit.html#channel-adder): 新增 `ChannelAdder` 模块，支持定制化的将各种量子噪声信道添加量子线路中，以此构成一个噪声模型，更多教案请参考：[`ChannelAdder`](https://mindspore.cn/mindquantum/docs/zh-CN/master/noise_simulator.html)。

#### Simulator

- [STABLE] [`密度矩阵模拟器`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator): 新增密度矩阵模拟器，模拟器名称为 `mqmatrix`。支持变分量子算法、噪声模拟等，与现有 `mqvector` 全振幅模拟器功能基本对齐。
- [BETA] [`parameter shift`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation_with_grad): 量子模拟器梯度算子现支持 parameter shift 算法，更贴近于实验。
- [STABLE] [`期望计算`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation): 接口与 [`get_expectation_with_grad`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation_with_grad)基本对齐，但是不会计算梯度值，节省时间。

#### Device

- [STABLE] [`QubitNode`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.QubitNode.html#mindquantum.device.QubitNode): 新增量子比特拓扑接口中的比特节点对象，支持对比特的位置和颜色以及连通性进行配置。
- [STABLE] [`QubitsTopology`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.QubitsTopology.html#mindquantum.device.QubitsTopology): 量子比特拓扑结构，支持自定义拓扑结构。同时可使用预定义结构：线性拓扑结构 [`LinearQubits`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.LinearQubits.html#mindquantum.device.LinearQubits) 和方格点拓扑结构 [`GridQubits`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.GridQubits.html#mindquantum.device.GridQubits)

#### Algorithm

- [STABLE] [`比特映射`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.mapping.SABRE.html#mindquantum.algorithm.mapping.SABRE): 新增比特映射算法 [`SABRE`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.mapping.SABRE.html#mindquantum.algorithm.mapping.SABRE)，论文请参考 Arxiv [`1809.02573`](https://arxiv.org/abs/1809.02573)。
- [BETA] [`误差缓解`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.error_mitigation.zne.html#mindquantum.algorithm.error_mitigation.zne): 新增零噪声外推算法算法来进行量子误差缓解。
- [STABLE] [`线路折叠`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.error_mitigation.fold_at_random.html#mindquantum.algorithm.error_mitigation.fold_at_random): 新增量子线路折叠功能，支持保证量子线路等价性的同时增长量子线路。
- [BETA] [`量子线路编译`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.compiler.html#module-mindquantum.algorithm.compiler): 新增量子线路编译模块，利用 [`DAG`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.compiler.DAGCircuit.html#mindquantum.algorithm.compiler.DAGCircuit) 图对量子线路进行编译，支持门替换、门融合和门分解等量子编译算法。
- [STABLE] [`ansatz_variance`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.ansatz_variance.html#mindquantum.algorithm.nisq.ansatz_variance): 新增接口计算变分量子线路中的某个参数的梯度的方差，可用于验证变分量子线路的[`贫瘠高原`](https://www.nature.com/articles/s41467-018-07090-4)现象。

#### Framework

- [STABLE] [`QRamVecLayer`](https://mindspore.cn/mindquantum/docs/zh-CN/master/layer/mindquantum.framework.QRamVecLayer.html#mindquantum.framework.QRamVecLayer): 新增 QRam 量子编码层，支持将经典数据直接编码为全振幅量子态。对应的算子为 [`QRamVecOps`](https://mindspore.cn/mindquantum/docs/zh-CN/master/operations/mindquantum.framework.QRamVecOps.html#mindquantum.framework.QRamVecOps)。

#### IO

- [STABLE] [`OpenQASM`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.io.OpenQASM.html#mindquantum.io.OpenQASM): OpenQASM 新增 [`from_string`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.io.OpenQASM.html#mindquantum.io.OpenQASM.from_string) 接口，支持将字符串格式的 OpenQASM 转化为 MindQuantum 中的量子线路。

#### Bug fix

- [`PR1757`](https://gitee.com/mindspore/mindquantum/pulls/1757): 修复[`StronglyEntangling`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.StronglyEntangling.html#mindquantum.algorithm.nisq.StronglyEntangling)在深度大于2时的bug。
- [`PR1700`](https://gitee.com/mindspore/mindquantum/pulls/1700): 修复[`CNOT`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.CNOTGate.html#mindquantum.core.gates.CNOTGate)门矩阵表达式和[`AmplitudeDampingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.AmplitudeDampingChannel.html#mindquantum.core.gates.AmplitudeDampingChannel)的逻辑错误。
- [`PR1523`](https://gitee.com/mindspore/mindquantum/pulls/1523): 修复[`PhaseDampingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.PhaseDampingChannel.html#mindquantum.core.gates.PhaseDampingChannel)的逻辑错误。

### 贡献者

感谢以下开发者做出的贡献：

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng, 朱祎康, dorothy20212021, dsdsdshe, buyulin, norl-corxilea, herunhong, Arapat Ablimit, NoE, panshijie, longhanlin.

欢迎以任何形式对项目提供贡献！

最后提交信息为： !1965 [CXX] Support I as token

预览版本

v0.9.0-rc1

d8d3fe4

2023-05-08 18:55

v0.9.0-rc1

# MindQuantum Release Notes

## MindQuantum 0.9.0 Release Notes

### 主要特性和增强

#### 数据精度

- [STABLE] `数据精度`: MindQuantum 现支持 `float32`、`float64`、`complex64`和`complex128`四种精度类型，可为各种算符、参数解析器和模拟器设置不同的精度类型。

#### Gates

- [STABLE] [`通用量子门`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#%E9%80%9A%E7%94%A8%E9%87%8F%E5%AD%90%E9%97%A8): 新增多个两比特泡利旋转门，包括：[`Rxx`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxx.html#mindquantum.core.gates.Rxx)，[`Rxy`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxy.html#mindquantum.core.gates.Rxy)，[`Rxz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rxz.html#mindquantum.core.gates.Rxz)，[`Ryy`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Ryy.html#mindquantum.core.gates.Ryy)，[`Ryz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Ryz.html#mindquantum.core.gates.Ryz)和[`Rzz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.Rzz.html#mindquantum.core.gates.Rzz)。
- [STABLE] [`噪声信道`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#%E9%87%8F%E5%AD%90%E4%BF%A1%E9%81%93): 噪声信道现在支持通过 `.matrix()` 接口返回噪声信道的 kraus 算符。

#### Operator

- [STABLE] [`QubitOperator`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.QubitOperator.html#mindquantum.core.operators.QubitOperator): 新增 [`relabel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.QubitOperator.html#mindquantum.core.operators.QubitOperator.relabel) 接口，支持按照新的比特编号来重排算符。[`FermionOperator`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.FermionOperator.html#mindquantum.core.operators.FermionOperator.relabel)同样支持该功能。
- [STABLE] [`基态计算`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.operators.ground_state_of_sum_zz.html#mindquantum.core.operators.ground_state_of_sum_zz): 新增接口支持计算只包含 pauli z 算符和 pauli z 算符的直积的哈密顿量的基态能量。

#### Ansatz

- [STABLE] [`Ansatz`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#ansatz): 新增 Arixv:[`1905.10876`](https://arxiv.org/abs/1905.10876) 中提到的19个 ansatz，先均已实现。

#### Circuit

- [STABLE] [`ChannelAdder`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.circuit.html#channel-adder): 新增 `ChannelAdder` 模块，支持定制化的将各种量子噪声信道添加量子线路中，以此构成一个噪声模型，更多教案请参考：[`ChannelAdder`](https://mindspore.cn/mindquantum/docs/zh-CN/master/noise_simulator.html)。

#### Simulator

- [STABLE] [`密度矩阵模拟器`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator): 新增密度矩阵模拟器，模拟器名称为 `mqmatrix`。支持变分量子算法、噪声模拟等，与现有 `mqvector` 全振幅模拟器功能基本对齐。
- [BETA] [`parameter shift`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation_with_grad): 量子模拟器梯度算子现支持 parameter shift 算法，更贴近于实验。
- [STABLE] [`期望计算`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation): 接口与 [`get_expectation_with_grad`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.simulator.Simulator.html#mindquantum.simulator.Simulator.get_expectation_with_grad)基本对齐，但是不会计算期望值，节省时间。

#### Device

- [STABLE] [`QubitNode`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.QubitNode.html#mindquantum.device.QubitNode): 新增量子比特拓扑接口中的比特节点对象，支持对比特的位置和颜色以及连通性进行配置。
- [STABLE] [`QubitsTopology`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.QubitsTopology.html#mindquantum.device.QubitsTopology): 量子比特拓扑结构，支持自定义拓扑结构。同时可使用预定义结构：线性拓扑结构 [`LinearQubits`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.LinearQubits.html#mindquantum.device.LinearQubits) 和方格点拓扑结构 [`GridQubits`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.device.GridQubits.html#mindquantum.device.GridQubits)

#### Algorithm

- [STABLE] [`比特映射`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.mapping.SABRE.html#mindquantum.algorithm.mapping.SABRE): 新增比特映射算法 [`SABRE`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.mapping.SABRE.html#mindquantum.algorithm.mapping.SABRE)，论文请参考 Arxiv [`1809.02573`](https://arxiv.org/abs/1809.02573)。
- [BETA] [`误差缓解`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.error_mitigation.zne.html#mindquantum.algorithm.error_mitigation.zne): 新增零噪声外推算法算法来进行量子误差缓解。
- [STABLE] [`线路折叠`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.error_mitigation.fold_at_random.html#mindquantum.algorithm.error_mitigation.fold_at_random): 新增量子线路折叠功能，支持保证量子线路等价性的同时增长量子线路。
- [BETA] [`量子线路编译`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.compiler.html#module-mindquantum.algorithm.compiler): 新增量子线路编译模块，利用 [`DAG`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.compiler.DAGCircuit.html#mindquantum.algorithm.compiler.DAGCircuit) 图对量子线路进行编译，支持门替换、门融合和门分解等量子编译算法。
- [STABLE] [`ansatz_variance`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.ansatz_variance.html#mindquantum.algorithm.nisq.ansatz_variance): 新增接口计算变分量子线路中的某个参数的梯度的方差，可用于验证变分量子线路的[`贫瘠高原`](https://www.nature.com/articles/s41467-018-07090-4)现象。

#### Framework

- [STABLE] [`QRamVecLayer`](https://mindspore.cn/mindquantum/docs/zh-CN/master/layer/mindquantum.framework.QRamVecLayer.html#mindquantum.framework.QRamVecLayer): 新增 QRam 量子编码层，支持将经典数据直接编码为全振幅量子态。对应的算子为 [`QRamVecOps`](https://mindspore.cn/mindquantum/docs/zh-CN/master/operations/mindquantum.framework.QRamVecOps.html#mindquantum.framework.QRamVecOps)。

#### IO

- [STABLE] [`OpenQASM`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.io.OpenQASM.html#mindquantum.io.OpenQASM): OpenQASM 新增 [`from_string`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.io.OpenQASM.html#mindquantum.io.OpenQASM.from_string) 接口，支持将字符串格式的 OpenQASM 转化为 MindQuantum 中的量子线路。

#### Bug fix

- [`PR1757`](https://gitee.com/mindspore/mindquantum/pulls/1757): 修复[`StronglyEntangling`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.StronglyEntangling.html#mindquantum.algorithm.nisq.StronglyEntangling)在深度大于2时的bug。
- [`PR1700`](https://gitee.com/mindspore/mindquantum/pulls/1700): 修复[`CNOT`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.CNOTGate.html#mindquantum.core.gates.CNOTGate)门矩阵表达式和[`AmplitudeDampingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.AmplitudeDampingChannel.html#mindquantum.core.gates.AmplitudeDampingChannel)的逻辑错误。
- [`PR1523`](https://gitee.com/mindspore/mindquantum/pulls/1523): 修复[`PhaseDampingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.PhaseDampingChannel.html#mindquantum.core.gates.PhaseDampingChannel)的逻辑错误。

### 贡献者

感谢以下开发者做出的贡献：

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng, 朱祎康, dorothy20212021, dsdsdshe, buyulin, norl-corxilea, herunhong, Arapat Ablimit, NoE, panshijie, longhanlin.

欢迎以任何形式对项目提供贡献！

最后提交信息为： !1512 [CXX] compress simulator memory

v0.8.0

df4825a

2023-02-13 20:16

v0.8.0

# MindQuantum Release Notes

[查看中文](https://gitee.com/mindspore/mindquantum/blob/r0.8/RELEASE_CN.md)

## MindQuantum  0.8.0 Release Notes

### Major Feature and Improvements

#### Gates

- [STABLE] [`FSim`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html?highlight=fsim#mindquantum.core.gates.FSim): Fermionic simulation gate supported, and this gate also works in variational quantum algorithm.
- [STABLE] [`U3`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html?highlight=fsim#mindquantum.core.gates.U3): The single qubit arbitrary gate U3 now will work as a single gate but not a piece of quantum circuit. U3 gate also works in variational quantum algorithm.
- [STABLE] [`Customed parameterized gate`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantum.core.gates.gene_univ_parameterized_gate). Customed parameterized gate now will compiled to machine code by jit compiler [numba](https://numba.pydata.org), and the simulator backend can call customed parameterized gate in parallel thread.
- [STABLE] [`BarrierGate`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html?highlight=fsim#mindquantum.core.gates.BarrierGate): BarrierGate now can be acted on certain qubits.
- [STABLE] [`KrausChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html?highlight=fsim#mindquantum.core.gates.KrausChannel): Design a customed kraus channel for quantum simulator.

#### Circuit

- [STABLE] [`svg`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.svg): Now you can set the `width` to split the svg circuit, so that you can copy it into your paper.

#### Simulator

- [STABLE] **New simulator supported**. `mqvector` and `mqvector_gpu` are two mindquantum simulate that prepared for cpu and gpu. And `projectq` simulator will be deprecated. The new simulator is total compatible with old one, what you only to do is to change the backend name when you initialize the simulator.

**Note**

The attachments are **GPU** version for linux platform.

最后提交信息为： !1423 update api link in release

v0.7.0

931bffa

2022-07-13 09:26

v0.7.0

# MindQuantum Release Notes

[查看中文](https://gitee.com/mindspore/mindquantum/blob/r0.7/RELEASE_CN.md)

## MindQuantum 0.7.0 Release Notes

### Major Features and Improvements

#### Circuit

- [STABLE] [`as_encoder`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.as_encoder): Method of `Circuit` to mark this circuit as an encoder circuit.
- [STABLE] [`as_ansatz`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.as_ansatz): Method of `Circuit` to mark this circuit as an ansatz circuit.
- [STABLE] [`encoder_params_name`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.encoder_params_name): Method of `Circuit` to return the encoder parameters.
- [STABLE] [`ansatz_params_name`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.ansatz_params_name): Method of `Circuit` to return the ansatz parameters.
- [STABLE] [`remove_noise`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.remove_noise): Method of `Circuit` to remove all noise channel.
- [STABLE] [`with_noise`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.Circuit.with_noise): Method of `Circuit` to add a given noise channel after every gate.
- [STABLE] [`as_encoder`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.as_encoder): A decorator to wrap a function, so that it can generate an encoder circuit.
- [STABLE] [`as_ansatz`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.as_ansatz): A decorator to wrap a function, so that it can generate an ansatz circuit.
- [STABLE] [`qfi`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.qfi): A method that can calculate the quantum fisher information of a given parameterized quantum circuit.
- [STABLE] [`partial_psi_partial_psi`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.partial_psi_partial_psi): A method that can calculate the first part of quantum fisher information.
- [STABLE] [`partial_psi_psi`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.circuit.html#mindquantum.core.circuit.partial_psi_psi): A method that can calculate the second part of quantum fisher information.

#### Gates

- [STABLE] [`AmplitudeDampingChannel`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.gates.html#mindquantum.core.gates.AmplitudeDampingChannel): Amplitude damping channel express error that qubit is affected by the energy dissipation.
- [STABLE] [`PhaseDampingChannel`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.gates.html#mindquantum.core.gates.PhaseDampingChannel): Phase damping channel express error that qubit loses quantum information without exchanging energy with environment

#### FermionOperator and QubitOperator

- [STABLE] [`split`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.operators.html#mindquantum.core.operators.FermionOperator.split): A method of FermionOperator and QubitOperator that can split the coefficient with the operator.

#### ParameterResolver

- [STABLE] [`astype`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.astype): Convert the ParameterResolver to a given type, can be float or double complex
- [STABLE] [`const`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.const): Get the constant part of this ParameterResolver.
- [STABLE] [`is_const`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.is_const): Check whether this ParameterResolver is constant.
- [STABLE] [`encoder_part`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.encoder_part): Set a part of parameter to be encoder parameter.
- [STABLE] [`ansatz_part`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.ansatz_part): Set a part of parameter to be ansatz parameter.
- [STABLE] [`as_encoder`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.as_encoder): Set all parameter to encoder parameters.
- [STABLE] [`as_ansatz`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.as_ansatz): Set all parameter to ansatz parameters.
- [STABLE] [`encoder_parameters`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.encoder_parameters): Return all encoder parameters.
- [STABLE] [`ansatz_parameters`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.ansatz_parameters): Return all ansatz parameters.
- [STABLE] [`is_hermitian`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.is_hermitian): Check whether this ParameterResolver is hermitian conjugate.
- [STABLE] [`is_anti_hermitian`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.is_anti_hermitian): Check whether this ParameterResolver is anti hermitian conjugate.
- [STABLE] [`no_grad_parameters`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.no_grad_parameters): Return all parameters that do no require gradient.
- [STABLE] [`requires_grad_parameters`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.core.parameterresolver.html#mindquantum.core.parameterresolver.ParameterResolver.requires_grad_parameters): Return all parameters that require gradient.

#### Simulator

- [STABLE] [`copy`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.simulator.html#mindquantum.simulator.Simulator.copy): The simulator can now very easy to duplicate.
- [STABLE] [`apply_gate`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.simulator.html#mindquantum.simulator.Simulator.apply_gate): In this version, you can apply a gate in differential version.
- [BETA] [`inner_product`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.simulator.html#mindquantum.simulator.inner_product): Calculate the inner product of two state in two simulator.

#### IO

- [STABLE] [`BlochScene`](https://mindspore.cn/mindquantum/docs/en/master/mindquantum.io.html): Now we support display and animate a one qubit state in bloch sphere.

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng, 朱祎康, dorothy20212021, dsdsdshe, buyulin, norl-corxilea, herunhong, Arapat Ablimit, NoE, panshijie, longhanlin.

Contributions of any kind are welcome!

最后提交信息为： !1088 Add pydocstyle to pre-commit hooks + update list of flake8 pl...

v0.6.0

6047e03

2022-04-07 17:05

v0.6.0

# MindQuantum 0.6.0

## MindQuantum 0.6.0 Release Notes

### Major Features and Improvements

#### Better iteration supported for `QubitOperator` and `FermionOperator`

> The following example will be demonstrated with `QubitOperator`

- Iter multiple terms `QubitOperator`

```python
>>> from mindquantum.core.operators import QubitOperator
>>> ops = QubitOperator('X0 Y1', 1) + QubitOperator('Z2 X3', {'a': 3})

>>> for idx, o in enumerate(ops):
>>>     print(f'Term {idx}: {o}')
```

You will get each term of this operator,

```bash
Term 0: 1 [X0 Y1]
Term 1: 3*a [Z2 X3]
```

- Iter single term `QubitOperator`

```python
>>> ops = QubitOperator('X0 Y1', 2)

>>> for idx, o in enumerate(ops.singlet()):
>>>     print(f'Word {idx}: {o}')
```

You will get each word of this operator with coefficient set to identity,

```bash
Word 0: 1 [X0]
Word 1: 1 [Y1]
```

### More built-in circuit supported

- [**general_w_state**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarygeneral-w-state): circuit that can prepare a w state.
- [**general_ghz_state**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarygeneral-ghz-state): circuit that can prepare a ghz state.
- [**bitphaseflip_operator**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarybitphaseflip-operator): circuit that can flip the sign of one or multiple calculation base.
- [**amplitude_encoder**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibraryamplitude-encoder): circuit that can encode classical number into quantum amplitude.

### Richer circuit operation supported

For origin circuit,

```python
>>> from mindquantum.core.circuit import Circuit
>>> circuit = Circuit().z(0).rx('a', 1, 0).y(1)
```

```bash
q0: ──Z──────●─────────
             │
q1: ───────RX(a)────Y──
```

- `shift` operator will shift the qubit index.

```python
from mindquantum.core.circuit import shift
>>> shift(circuit, 2)
```

```bash
q2: ──Z──────●─────────
             │
q3: ───────RX(a)────Y──
```

- Reverse circuit qubits, the circuit will be flipped upside down.

```python
>>> circuit.reverse_qubits()
```

```bash
q0: ───────RX(a)────Y──
             │
q1: ──Z──────●─────────
```

### Feature enhancement

- `MaxCutAnsatz`: [**get_partition**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#mindquantumalgorithmnisqmaxcutansatzget-partition)
- `MaxCutAnsatz`: [**get_cut_value**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#mindquantumalgorithmnisqmaxcutansatzget-cut-value)
- `Circuit`: [**is_measure_end**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.circuit.html#mindquantumcorecircuitcircuitis-measure-end)

### SVG supported

The quantum circuit build by mindquantum now can be showd by SVG in jupyter notebook, just call `svg()` of any `Circuit`.

```python
>>> from mindquantum import *

>>> circuit = (qft(range(3)) + BarrierGate(True)).measure_all()
>>> circuit.svg()
```

### Noise simulator supported

In This version, we can simulate a quantum circuit in noise simulator just by adding different noise channels. The following are supported channels:

- [`PauliChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatespaulichannel)
- [`BitFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesbitflipchannel)
- [`PhaseFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesphaseflipchannel)
- [`BitPhaseFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesbitphaseflipchannel)
- [`DepolarizingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesdepolarizingchannel)

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

最后提交信息为： !457 update to version 0.6.0

v0.6.0rc1

f61a8ef

2022-03-31 16:12

Release 0.6.0-rc1

# MindQuantum 0.6.0

## MindQuantum 0.6.0 Release Notes

### Major Features and Improvements

#### Better iteration supported for `QubitOperator` and `FermionOperator`

> The following example will be demonstrated with `QubitOperator`

- Iter multiple terms `QubitOperator`

```python
>>> from mindquantum.core.operators import QubitOperator
>>> ops = QubitOperator('X0 Y1', 1) + QubitOperator('Z2 X3', {'a': 3})

>>> for idx, o in enumerate(ops):
>>>     print(f'Term {idx}: {o}')
```

You will get each term of this operator,

```bash
Term 0: 1 [X0 Y1]
Term 1: 3*a [Z2 X3]
```

- Iter single term `QubitOperator`

```python
>>> ops = QubitOperator('X0 Y1', 2)

>>> for idx, o in enumerate(ops.singlet()):
>>>     print(f'Word {idx}: {o}')
```

You will get each word of this operator with coefficient set to identity,

```bash
Word 0: 1 [X0]
Word 1: 1 [Y1]
```

### More built-in circuit supported

- [**general_w_state**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarygeneral-w-state): circuit that can prepare a w state.
- [**general_ghz_state**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarygeneral-ghz-state): circuit that can prepare a ghz state.
- [**bitphaseflip_operator**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibrarybitphaseflip-operator): circuit that can flip the sign of one or multiple calculation base.
- [**amplitude_encoder**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.library.html#mindquantumalgorithmlibraryamplitude-encoder): circuit that can encode classical number into quantum amplitude.

### Richer circuit operation supported

For origin circuit,

```python
>>> from mindquantum.core.circuit import Circuit
>>> circuit = Circuit().z(0).rx('a', 1, 0).y(1)
```

```bash
q0: ──Z──────●─────────
             │
q1: ───────RX(a)────Y──
```

- `shift` operator will shift the qubit index.

```python
from mindquantum.core.circuit import shift
>>> shift(circuit, 2)
```

```bash
q2: ──Z──────●─────────
             │
q3: ───────RX(a)────Y──
```

- Reverse circuit qubits, the circuit will be flipped upside down.

```python
>>> circuit.reverse_qubits()
```

```bash
q0: ───────RX(a)────Y──
             │
q1: ──Z──────●─────────
```

### Feature enhancement

- `MaxCutAnsatz`: [**get_partition**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#mindquantumalgorithmnisqmaxcutansatzget-partition)
- `MaxCutAnsatz`: [**get_cut_value**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.algorithm.nisq.html#mindquantumalgorithmnisqmaxcutansatzget-cut-value)
- `Circuit`: [**is_measure_end**](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.circuit.html#mindquantumcorecircuitcircuitis-measure-end)

### SVG supported

The quantum circuit build by mindquantum now can be showd by SVG in jupyter notebook, just call `svg()` of any `Circuit`.

```python
>>> from mindquantum import *

>>> circuit = (qft(range(3)) + BarrierGate(True)).measure_all()
>>> circuit.svg()
```

![circuit_svg](https://gitee.com/mindspore/mindquantum/raw/master/docs/circuit_svg.png)

### Noise simulator supported

In This version, we can simulate a quantum circuit in noise simulator just by adding different noise channels. The following are supported channels:

- [`PauliChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatespaulichannel)
- [`BitFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesbitflipchannel)
- [`PhaseFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesphaseflipchannel)
- [`BitPhaseFlipChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesbitphaseflipchannel)
- [`DepolarizingChannel`](https://mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.gates.html#mindquantumcoregatesdepolarizingchannel)

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

最后提交信息为： !430 update readme

v0.5.0

0b53cfe

2022-02-28 16:29

v0.5.0

## MindQuantum 0.5.0 Release Notes

### Major Features and Improvements

### API Change

#### Backwards Incompatible Change

We unified the abbreviations of some nouns in MindQuantum.

- `isparameter` property of gate changes to `parameterized`

```python
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.isparameter
True
```

</td>
<td>

```python
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.parameterized
True
```

</td>
</tr>
</table>

- `para_name` of a quantum circuit changes to `params_name`

```python
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.para_name
['a']
```

</td>
<td>

```python
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.params_name
['a']
```

</td>
</tr>
</table>

The quantum neural network API was redesigned in this version. From now on, we can easily build a hybrid quantum neural network with the help of `Simulator` in `PYNATIVE_MODE`.

The following API was removed.

1. `generate_pqc_operator`
2. `PQC`
3. `MindQuantumLayer`
4. `generate_evolution_operator`
5. `Evolution`
6. `MindQuantumAnsatzOnlyLayer`
7. `MindQuantumAnsatzOnlyOperator`

The new API was shown as below.

1. `MQOps`
2. `MQN2Ops`
3. `MQAnsatzOnlyOps`
4. `MQN2AnsatzOnlyOps`
5. `MQEncoderOnlyOps`
6. `MQN2EncoderOnlyOps`
7. `MQLayer`
8. `MQN2Layer`
9. `MQAnsatzOnlyLayer`
10. `MQN2AnsatzOnlyLayer`

The above modules are placed in `mindquantum.framework`.

#### Removed

Due to the duplication of functions, we deleted some APIs.

- `mindquantum.circuit.StateEvolution`

The following APIs have been remoted.

- `mindquantum.core.operators.Hamiltonian.mindspore_data`
- `mindquantum.core.operators.Projector.mindspore_data`
- `mindquantum.core.circuit.Circuit.mindspore_data`
- `mindquantum.core.parameterresolver.ParameterResolver.mindspore_data`

#### New feature

New gates are shown as below.

- `mindquantum.core.gates.SGate`
- `mindquantum.core.gates.TGate`

Measurement on certain qubits are now supported. The related APIs are shown as below.

- `mindquantum.core.gates.Measure`
- `mindquantum.core.gates.MeasureResult`

QASM is now supported.

- `mindquantum.io.OpenQASM`
- `mindquantum.io.random_hiqasm`
- `mindquantum.io.HiQASM`

Simulator is now separated from MindSpore backend. Now you can easily to use a simulator.

- `mindquantum.simulator.Simulator`

### Refactoring

For improving MindQuantum's package structure, we did some refactoring on MindQuantum.

`mindquantum.gate.Hamiltonian`
</td><td>

`mindquantum.core.operators.Hamiltonian`
</td></tr>
<tr><td>

`mindquantum.gate.Projector`
</td><td>

`mindquantum.core.operators.Projector`
</td></tr>
<tr><td>

`mindquantum.circuit.qft`
</td><td>

`mindquantum.algorithm.library.qft`
</td></tr>
<tr><td>

`mindquantum.circuit.generate_uccsd`
</td><td>

`mindquantum.algorithm.nisq.chem.generate_uccsd`
</td></tr>
<tr><td>

`mindquantum.circuit.TimeEvolution`
</td><td>

`mindquantum.core.operators.TimeEvolution`
</td></tr>
<tr><td>

`mindquantum.utils.count_qubits`
</td><td>

`mindquantum.core.operators.count_qubits`
</td></tr>
<tr><td>

`mindquantum.utils.commutator`
</td><td>

`mindquantum.core.operators.commutator`
</td></tr><tr><td>

`mindquantum.utils.normal_ordered`
</td><td>

`mindquantum.core.operators.normal_ordered`
</td></tr><tr><td>

`mindquantum.utils.get_fermion_operator`
</td><td>

`mindquantum.core.operators.get_fermion_operator`
</td></tr><tr><td>

`mindquantum.utils.number_operator`
</td><td>

`mindquantum.core.operators.number_operator`
</td></tr><tr><td>

`mindquantum.utils.hermitian_conjugated`
</td><td>

`mindquantum.core.operators.hermitian_conjugated`
</td></tr><tr><td>

`mindquantum.utils.up_index`
</td><td>

`mindquantum.core.operators.up_index`
</td></tr><tr><td>

`mindquantum.utils.down_index`
</td><td>

`mindquantum.core.operators.down_index`
</td></tr><tr><td>

`mindquantum.utils.sz_operator`
</td><td>

`mindquantum.core.operators.sz_operator`
</td></tr>
<tr><td>

`mindquantum.ansatz.Ansatz`</td><td>

`mindquantum.algorithm.nisq.Ansatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.MaxCutAnsatz`
</td><td>

`mindquantum.algorithm.nisq.qaoa.MaxCutAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.Max2SATAnsatz`
</td><td>

`mindquantum.algorithm.nisq.qaoa.Max2SATAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.HardwareEfficientAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.HardwareEfficientAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.QubitUCCAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.QubitUCCAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.UCCAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.UCCAnsatz`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.Transform`
</td><td>

`mindquantum.algorithm.nisq.chem.Transform`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.get_qubit_hamiltonian`
</td><td>

`mindquantum.algorithm.nisq.chem.get_qubit_hamiltonian`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd_singlet_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd_singlet_generator`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd_singlet_get_packed_amplitudes`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd_singlet_get_packed_amplitudes`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd0_singlet_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd0_singlet_generator`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.quccsd_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.quccsd_generator`
</td></tr>
<tr><td>

`mindquantum.utils.bprint`
</td><td>

`mindquantum.io.bprint`
</td></tr>
<tr><td>

`mindquantum.circuit`
</td><td>

`mindquantum.core.circuit`
</td></tr>
<tr><td>

`mindquantum.gate`
</td><td>

`mindquantum.core.gates`
</td></tr>
<tr><td>

`mindquantum.ops`
</td><td>

`mindquantum.core.operators`
</td></tr>
<tr><td>

`mindquantum.parameterresolver`
</td><td>

`mindquantum.core.parameterresolver`
</td></tr>
<tr><td></td><td></td></tr>
</table>

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

最后提交信息为： version 0.5.0

v0.5.0rc1

ab07ee3

2022-02-10 19:12

Release 0.5.0-rc1

# MindQuantum 0.5.0-rc1

## MindQuantum 0.5.0 Release Notes

### Major Features and Improvements

### API Change

#### Backwards Incompatible Change

We unified the abbreviations of some nouns in MindQuantum.

- `isparameter` property of gate changes to `parameterized`

```python
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.isparameter
True
```

</td>
<td>

```python
>>> from mindquantum import RX
>>> gate = RX('a').on(0)
>>> gate.parameterized
True
```

</td>
</tr>
</table>

- `para_name` of a quantum circuit changes to `params_name`

```python
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.para_name
['a']
```

</td>
<td>

```python
>>> from mindquantum import Circuit
>>> circ = Circuit().rx('a', 0)
>>> circ.params_name
['a']
```

</td>
</tr>
</table>

The quantum neural network API was redesigned in this version. From now on, we can easily build a hybrid quantum neural network with the help of `Simulator` in `PYNATIVE_MODE`.

The following API was removed.

1. `generate_pqc_operator`
2. `PQC`
3. `MindQuantumLayer`
4. `generate_evolution_operator`
5. `Evolution`
6. `MindQuantumAnsatzOnlyLayer`
7. `MindQuantumAnsatzOnlyOperator`

The new API was shown as below.

1. `MQOps`
2. `MQN2Ops`
3. `MQAnsatzOnlyOps`
4. `MQN2AnsatzOnlyOps`
5. `MQEncoderOnlyOps`
6. `MQN2EncoderOnlyOps`
7. `MQLayer`
8. `MQN2Layer`
9. `MQAnsatzOnlyLayer`
10. `MQN2AnsatzOnlyLayer`

The above modules are placed in `mindquantum.framework`.

#### Removed

Due to the duplication of functions, we deleted some APIs.

- `mindquantum.circuit.StateEvolution`

The following APIs have been remoted.

- `mindquantum.core.operators.Hamiltonian.mindspore_data`
- `mindquantum.core.operators.Projector.mindspore_data`
- `mindquantum.core.circuit.Circuit.mindspore_data`
- `mindquantum.core.parameterresolver.ParameterResolver.mindspore_data`

#### New feature

New gates are shown as below.

- `mindquantum.core.gates.SGate`
- `mindquantum.core.gates.TGate`

Measurement on certain qubits are now supported. The related APIs are shown as below.

- `mindquantum.core.gates.Measure`
- `mindquantum.core.gates.MeasureResult`

QASM is now supported.

- `mindquantum.io.OpenQASM`
- `mindquantum.io.random_hiqasm`
- `mindquantum.io.HiQASM`

Simulator is now separated from MindSpore backend. Now you can easily to use a simulator.

- `mindquantum.simulator.Simulator`

### Refactoring

For improving MindQuantum's package structure, we did some refactoring on MindQuantum.

`mindquantum.gate.Hamiltonian`
</td><td>

`mindquantum.core.operators.Hamiltonian`
</td></tr>
<tr><td>

`mindquantum.gate.Projector`
</td><td>

`mindquantum.core.operators.Projector`
</td></tr>
<tr><td>

`mindquantum.circuit.qft`
</td><td>

`mindquantum.algorithm.library.qft`
</td></tr>
<tr><td>

`mindquantum.circuit.generate_uccsd`
</td><td>

`mindquantum.algorithm.nisq.chem.generate_uccsd`
</td></tr>
<tr><td>

`mindquantum.circuit.TimeEvolution`
</td><td>

`mindquantum.core.operators.TimeEvolution`
</td></tr>
<tr><td>

`mindquantum.utils.count_qubits`
</td><td>

`mindquantum.core.operators.count_qubits`
</td></tr>
<tr><td>

`mindquantum.utils.commutator`
</td><td>

`mindquantum.core.operators.commutator`
</td></tr><tr><td>

`mindquantum.utils.normal_ordered`
</td><td>

`mindquantum.core.operators.normal_ordered`
</td></tr><tr><td>

`mindquantum.utils.get_fermion_operator`
</td><td>

`mindquantum.core.operators.get_fermion_operator`
</td></tr><tr><td>

`mindquantum.utils.number_operator`
</td><td>

`mindquantum.core.operators.number_operator`
</td></tr><tr><td>

`mindquantum.utils.hermitian_conjugated`
</td><td>

`mindquantum.core.operators.hermitian_conjugated`
</td></tr><tr><td>

`mindquantum.utils.up_index`
</td><td>

`mindquantum.core.operators.up_index`
</td></tr><tr><td>

`mindquantum.utils.down_index`
</td><td>

`mindquantum.core.operators.down_index`
</td></tr><tr><td>

`mindquantum.utils.sz_operator`
</td><td>

`mindquantum.core.operators.sz_operator`
</td></tr>
<tr><td>

`mindquantum.ansatz.Ansatz`</td><td>

`mindquantum.algorithm.nisq.Ansatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.MaxCutAnsatz`
</td><td>

`mindquantum.algorithm.nisq.qaoa.MaxCutAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.Max2SATAnsatz`
</td><td>

`mindquantum.algorithm.nisq.qaoa.Max2SATAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.HardwareEfficientAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.HardwareEfficientAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.QubitUCCAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.QubitUCCAnsatz`
</td></tr>
<tr><td>

`mindquantum.ansatz.UCCAnsatz`
</td><td>

`mindquantum.algorithm.nisq.chem.UCCAnsatz`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.Transform`
</td><td>

`mindquantum.algorithm.nisq.chem.Transform`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.get_qubit_hamiltonian`
</td><td>

`mindquantum.algorithm.nisq.chem.get_qubit_hamiltonian`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd_singlet_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd_singlet_generator`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd_singlet_get_packed_amplitudes`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd_singlet_get_packed_amplitudes`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.uccsd0_singlet_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.uccsd0_singlet_generator`
</td></tr>
<tr><td>

`mindquantum.hiqfermion.quccsd_generator`
</td><td>

`mindquantum.algorithm.nisq.chem.quccsd_generator`
</td></tr>
<tr><td>

`mindquantum.utils.bprint`
</td><td>

`mindquantum.io.bprint`
</td></tr>
<tr><td>

`mindquantum.circuit`
</td><td>

`mindquantum.core.circuit`
</td></tr>
<tr><td>

`mindquantum.gate`
</td><td>

`mindquantum.core.gates`
</td></tr>
<tr><td>

`mindquantum.ops`
</td><td>

`mindquantum.core.operators`
</td></tr>
<tr><td>

`mindquantum.parameterresolver`
</td><td>

`mindquantum.core.parameterresolver`
</td></tr>
<tr><td></td><td></td></tr>
</table>

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, Damien Ngyuen, zhouxu, wangzidong, yangkang, lujiale, zhangzhenghai, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

最后提交信息为： !337 0.5.0rc1

v0.3.1-rc1

e7111ce

2021-09-26 09:23

Release 0.3.1-rc1

# MindQuantum 0.3.1-rc1

## MindQuantum 0.3.1 Release Notes

### Major Features and Improvements

- Three tutorials have been rewritten to make them easier to read
- Circuit information such as qubit number, parameters will update immediately after you add gate
- The UN operator now support parameterized gate
- New ansatz that solving max 2 sat problem now are supported

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wangzidong, yangkang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

# MindQuantum 0.2.0

## MindQuantum 0.2.0 Release Notes

### Major Features and Improvements

* Parameterized FermionOperator and QubitOperator for quantum chemistry
* Different kinds of transformation between FermionOperator and QubitOperator
* UCCSD, QAOA and hardware efficient ansatz supported
* MindQuantumAnsatzOnlyLayer for simulating circuit with ansatz only circuit
* TimeEvolution with first order Trotter decomposition
* High level operations for modifying quantum circuit

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wanzidong, yankang, lujiale, fanyi, zhangwengang, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

# MindQuantum 0.1.0

## MindQuantum 0.1.0 Release Notes

Initial release of MindQuantum.

### Major Features and Improvements

* Easily build parameterized quantum circuit.
* Effectively simulate quantum circuit.
* Calculating the gradient of parameters of quantum circuit.
* PQC (parameterized quantum circuit) operator that naturally compatible with other operators in mindspore framework.
* Evolution operator that evaluate a quantum circuit and return the quantum state.
* Data parallelization for PQC operator.

### Contributors

Thanks goes to these wonderful people:

yufan, wengwenkang, xuxusheng, wanzidong, yankang, lujiale, wangkaisheng, zhoufeng, wangsiyuan, gongxiaoqing, chengxianbin, sunxiyin, wenwenkang, lvdingshun, cuijiangyu, chendiqing, zhangkai, Damien Ngyuen, Zotov Yuriy, liqin, zengjinglin, cuixiaopeng.

Contributions of any kind are welcome!

最后提交信息为： update mindquantum/version.py.