Supports advanced programming in Python and is compatible with Open QASM 2.0 and Qiskit syntax.
Quantum programs can be submitted to real quantum computers, quantum simulators, the SpinQ cloud , and any QASM-based cloud platform.
Provides foundational fault-tolerant quantum algorithms as well as variational quantum algorithms and quantum machine learning algorithms for the NISQ era.
Easily integrates with classical machine learning frameworks like PyTorch, TensorFlow, and PaddlePaddle
Offers quantum circuit optimizations including redundant gate simplification, single- and two-qubit gate fusion, and removal of control qubit along with hardware topology-based circuit transformation and qubit mapping.
Includes both CPU and GPU quantum simulators, supporting advanced features like backpropagation and noise simulation.
The intermediate representation-based compilation system allows for the flexible addition of frontend syntax and backend execution platforms.
Uses a consistent interface to flexibly configure execution platforms, measurement methods, gradient algorithms, and more for efficient computation based on the execution platform.
Supports connections to local NMR and superconducting quantum computers, multiple quantum simulators, the SPINQ cloud platform, and any third-party quantum platform that supports Open QASM.
The code has been open-sourced, providing a community for quantum computing professionals to communicate and share, facilitating the development and application of quantum computing.
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