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PReconditioned Iterative MultiMethod Eigensolver for solving symmetric/Hermitian eigenvalue problems and singular value problems
Krylov methods for linear problems, eigenvalues, singular values and matrix functions
Add-on package to ITensors.jl for chemistry.
The Python code provided implements the matrix-valued version of the Minimal Pole Method (MPM)
Intel MKL linear algebra backend for Julia
Computational tools for light-matter interaction including a whole zoo of nonlinear spectroscopic signals; nonadiabatic molecular dynamics, periodically driven quantum systems, quantum dynamics of …
Implementation in Julia of unitary core transformations approach to finding eigenvalues of companion matrices
Fast complex polynomial root finder, with support for arbitrary precision calculations
Some nonnegative least squares solvers in Julia
Solving linear, nonlinear equations, ordinary differential equations, ... using numerical methods in fortran
Barycentric rational approximation and interpolation in one dimension.
Fast low-rank matrix approximation in Julia
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
Packmol - Initial configurations for molecular dynamics simulations
OpenMM tutorial for the MSBS course
OpenMM is a toolkit for molecular simulation using high performance GPU code.
This is a toolbox containing the time stepping routines for a series of papers on temporal integration of low rank tensor ODEs. See the README for pdf links.
Python/C implementation of MUltiple SIgnal Classification as described by Schmidt.
Julia package for approximation by rational functions
Finite temperature tensor network algorithms including METTS and the ancilla/purification method
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
CSMC is a Python library for performing column subset selection in matrix completion tasks. It provides an implementation of the CSSMC method, which aims to complete missing entries in a matrix usi…
The purpose of this function is to provide a flexible and robust fit to one-dimensional data using free-knot splines. The knots are free and able to cope with rapid change in the underlying model. …
Tensor network simulations for finite temperature, open quantum system dynamics