- **Mathematical Definition of Polynomials:** Discover a more natural way of defining polynomial instances using the
polynomial's `from_expression` method. This method generates native SB polynomials (tensors of coefficients) from
`Sympy` expressions, making them easier to read and understand, especially for small dimensions.
🚧 Known issues
- A `MemoryError` is raised when creating an integer polynomial if the number of bits is large (~30 bits).
Unfortunately, there are no good fixes on the user side for this at the moment. The issue will be addressed in version 1.3.0.
The cause of this bug is the creation of a tensor containing all allowed values (*2^n* where *n* is the number of bits).
See this [issue](https://github.com/bqth29/simulated-bifurcation-algorithm/issues/13).
release-1.2.0
`simulated-bifurcation` version 1.2.0 Release Notes
What's New
- Optimization Enhancement: Experience a 2x speed boost in the optimizer.
- Algorithm Invocation Improvement: Enjoy a more user-friendly interaction with the Simulated Bifurcation algorithm through the new `minimize` and `maximize` static functions.
- General Polynomial API: Introducing a versatile polynomial API designed to construct and solve second-order multivariate polynomial problems using SB. This accommodates various variable types, including spin, binary, integer variables, and user-defined variable types.
- Implementation of several usual NP-hard optimization problems: the `models` module brings together interfaces for several NP-hard optimization problems (e.g., QUBO, Ising, number partitioning).
- Constants from physical theories have been transformed into optimization environment variables.
- Code Standardization: The codebase has undergone standardization using Black and isort code formatters, enhancing code consistency and readability.
pypi
The project has been added to PyPI. You can now download the Simulated Bifurcation algorithm for Python using
pip install simulated-bifurcation