Software

Dynamiqs
Dynamiqs is a Python library for GPU-accelerated and differentiable quantum simulations. Solvers are available for the Schrödinger equation, the Lindblad master equation, the stochastic master equation, and others. The library is built with JAX and the main solvers are based on Diffrax. Documentation is available at dynamiqs.org; see the Python API for a list of all implemented functions.

The main features of Dynamiqs are:

• Running simulations on CPUs and GPUs with high-performance.
• Executing many simulations concurrently by batching over Hamiltonians, initial states or jump operators.
• Computing gradients of arbitrary functions with respect to arbitrary parameters of the system.
• Full compatibility with the JAX ecosystem with a QuTiP-like API.

Dynamiqs is mainly used for the simulation of large quantum systems, gradient-based parameter estimation and quantum optimal control. The library is designed for large-scale problems, but also runs efficiently on CPUs for smaller systems.

pybibmerge
A simple Python script to merge BibTeX files.

rgplot
A custom matplotlib style to generate nice-looking matplotlib figures, with just a single line plt.style.use('rgplot').