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Open source · MindSpore ecosystem

Quantum circuits, differentiated end‑to‑end

Python framework for parameterized quantum circuits. CPU, GPU, and Ascend backends. Auto-differentiation via MindSpore.

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MindSpore Quantum V0.12 released

MindSpore Quantum is the open-source quantum framework from the MindSpore ecosystem. Write parameterized quantum circuits in Python, differentiate them through MindSpore's autograd, and run on CPU, GPU, or Ascend. Ships with VQE, QAOA, Grover, and quantum phase estimation, plus full-amplitude and density-matrix simulators.

Documentation
Architecture
  1. 01
    Algorithm Library
    Universal

    Grover / Shor / HHL

    Variational

    VQE / QAOA / QNN

    Quantum-inspired

    SB / LQA / SimCIM

  2. 02

    Quantum Neural Network

    Encoder

    Ansatz

    QRam

  3. 03

    Compiler

    Quantum Circuit Compilation

    Qubit Mapping

  4. 04

    Domain Specific Language

    Quantum Gate

    Quantum Circuit

    Quantum Operator

  5. 05

    Simulator

    Full Amplitude Simulator

    Density Matrix Simulator

    Quantum Chemistry Simulator

Core capabilities

User-friendly, high-performance, AI-compatible

MindSpore Quantum is built around the NISQ era. Four pillars take a quantum program from a Python expression to a real chip: a typed circuit DSL, differentiable circuits through MindSpore, three first-class simulator backends, and a batteries-included algorithm library.

  1. 01

    A Pythonic circuit DSL

    Quantum gates, circuits, parameter resolvers, and Hamiltonians as typed Python primitives. Arbitrary control on any gate, chain-rule circuit composition, and OpenQASM export.

    • Quantum Gate
    • Quantum Circuit
    • Parameter Resolver
    • Observable
  2. 02

    Differentiable end to end

    Parameterized circuits differentiate through MindSpore's autograd via the adjoint method. VQE, QAOA, and QNN models compose with any MindSpore optimizer, an order of magnitude faster on QAOA than competing frameworks.

    • VQE
    • QAOA
    • QNN
    • Adjoint gradient
    • Ansatz library
  3. 03

    Three backends, one model

    State-vector and density-matrix simulators tuned per architecture: SIMD with OpenMP on x86, CUDA on NVIDIA, NEON on Ascend. Switch single- and double-precision per run, no recompile.

    • x86 (AVX)
    • GPU (CUDA)
    • Ascend (NEON)
    • Noise channels
  4. 04

    Algorithms, batteries included

    VQE, QAOA, Grover, Shor, HHL, and Quantum Phase Estimation as one-line APIs. A dedicated VQE quantum-chemistry simulator is open-sourced in-tree, ready for LiH, H₂O, and beyond.

    • Grover
    • Shor
    • HHL
    • QPE
    • VQE chemistry simulator
Research

100+ peer-reviewed papers from 30+ institutions — including Peking University, Tsinghua, and Shanghai Jiao Tong.

Start Learning

  1. 01

    Quantum foundations

    Zero-foundation introduction to quantum information and computing — the math, the postulates, and the vocabulary you need before writing any circuit.

  2. 02

    Install and set up

    Install MindSpore Quantum on Linux, macOS, Windows, or Ascend, and stand up a local compile + debug environment.

  3. 03

    Algorithm case studies

    Runnable walkthroughs of VQE, QAOA, Grover, and quantum phase estimation — the jumping-off point for research work.

  4. 04

    Video courses

    Chinese only

    Recorded lectures covering the introduction to quantum computing, MindSpore Quantum programming, case analysis, and applications.

Start building quantum programs with MindSpore Quantum

Install Documentation