QuGIT: A numerical toolbox for Gaussian quantum states

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. (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

Simulating quantum states on classical computers is difficult, but efficient simulation can be achieved for Gaussian quantum states. In this work, a Python toolbox called QuGIT is introduced, which is based on symplectic methods and specializes in efficient simulation of multimode Gaussian states and operations. QuGIT is exact, does not require truncation of Hilbert space, and provides a wide range of Gaussian operations.