QuGIT: A numerical toolbox for Gaussian quantum states

Abstract

Simulating quantum states on a classical computer is hard, typically requiring prohibitive resources in terms of memory and computational power. Efficient simulation, however, can be achieved for certain classes of quantum states, in particular the so-called Gaussian quantum states of continuous variable systems. In this work we introduce QuGIT - a python numerical toolbox based on symplectic methods specialized in efficiently simulating multimode Gaussian states and operations. QuGIT is exact, requiring no truncation of Hilbert space, and provides a wide range of Gaussian operations on arbitrary Gaussian states, including unitaries, partial traces, tensor products, general-dyne measurements, conditional and unconditional dynamics. To illustrate the toolbox, several examples of usage relevant to quantum optics and optomechanics are described. Program summaryProgram Title: QuGIT: Quantum Gaussian Information ToolboxCPC Library link to program files:https://doi.org/10.17632/tp4s84yc5d.1Developer's repository link:https://github.com/IgorBrandao42/Quantum-Gaussian-Information-ToolboxLicensing provisions: CC By 4.0Programming language: PythonExternal routines/libraries: NumPy, SciPyNature of problem: Conditional and unconditional dynamics of Gaussian quantum systems.Solution method: Numerical simulation of symplectic representation of Gaussian states.Additional comments including restrictions and unusual features: Problems must deal with Gaussian states following Gaussian preserving dynamics.