Qmech

Qmech is a software framework for quantum mechanics simulations and educational visualization. It provides a collection of algorithms and utilities to model quantum systems described by the Schrödinger equation, including single-particle and many-body problems. The project emphasizes modularity, extensibility, and interoperability with established numerical libraries.

Implemented primarily in Python with performance-critical components in C++ and CUDA, Qmech offers solvers for static and dynamic problems. These include exact diagonalization, iterative eigenvalue methods such as Lanczos and Arnoldi, time evolution using Trotter–Suzuki and Krylov approaches, and tensor-network techniques for low-dimensional systems. It also supports basis-set representations common in quantum chemistry, lattice models, and continuum problems, and provides a flexible API, built-in visualization, and hooks to external libraries like NumPy, SciPy, and PETSc/SLEPc.

Architecturally, Qmech follows a modular design with a plugin system for algebra backends, model builders, solvers, and data I/O. It ships with example models, including a particle in a potential well, simple spin chains, and Hubbard-type lattices, to help users prototype and compare methods.

History and development: the project emerged from a collaboration of researchers across several institutions and released its first public version in open source. Major revisions added improved scalability, extended chemistry workflows, and better documentation. The project is maintained by a community of developers and academic contributors with governance guidelines for contributions.

Use and reception: Qmech is used in teaching laboratories, research groups, and prototype workflows for quantum simulation and materials modeling. It is praised for its approachable API and reproducible workflows, though its performance is sensitive to problem size and hardware, and some users note that GPU support and documentation could be expanded.