0.2.3

Fix the binary order of the result from the NMR backend

0.2.2

Changes

• Add a uniform interface QLayer for varational quantum algorithms
• Add new quantum algorithms such as QAE, quantum walk, and QSVC
• Implement interfaces to work with classical machine learning framework
• Add a new backend to run SpinQit codes on any third-party platform that supports OpenQASM

0.1.0

Version 0.1.0 is the first release of SpinQit, offering all the fundamental functions of a Quantum Software Development Kit (QSDK). Users can write quantum algorithms using SpinQit syntax, OpenQASM 2.0, or Qiskit 0.31.0, and execute them cross-platform on a basic CPU simulator, a PyTorch autograd simulator, SpinQ's nuclear magnetic quantum computer, and the Taurus Cloud platform. Version 0.1.0 supports fault-tolerant quantum algorithms such as Grover, HHL, QFT, QPE, etc. Users can directly run these algorithms or construct more complex algorithms using them. This release also supports variational quantum algorithms and quantum machine learning algorithms, and can be interfaced with classical machine learning frameworks for hybrid training. For more details on APIs and examples, please refer to the documentation in the source code.