Tqix.pis: A toolbox for quantum dynamics simulation of spin ensembles in Dicke basis

Abstract

We introduce tqix.pis, a library of tqix, for quantum dynamics simulation of spin ensembles. The library emulates a dynamic process by a quantum circuit, including initializing a quantum state, executing quantum operators, and measuring the final state. It utilizes collective processes in spin ensembles to reduce the dimension from exponentially to quadratically with the number of particles, i.e., the quantum state spans in Dicke basis. It also facilitates the simulation time with multi-core processors and Graphics Processing Units. The library is thus applicable for the simulation of ensembles of large number of particles that have collective properties. Various phenomena, such as spin squeezing, variational quantum squeezing, quantum phase transition, and many-body quantum dynamics, can be simulated using the library. Program summaryProgram Title:▪: A toolbox for quantum dynamics simulation of spin ensembles in Dicke basis.CPC Library link to program files:https://doi.org/10.17632/wxvncw5jkv.2Licensing provisions: GPLv3Programming language: Python (≥3.6)External routines: NumPy, SciPy, SymPy, Matplotlib, Sklearn, pyTorch (for GPUs users).Nature of problem:▪ is a library in ▪, an open-source program providing some convenient tools for quantum measurement, quantum tomography, quantum metrology, and others. The library allows executing quantum circuits of spin ensembles in Dicke basis assisting from multi-core processors and Graphics Processing Units (GPUs).Solution method: Execute quantum circuits with a large number of particles. It generates a collective quantum register (collective state) by an ensemble of spin-1/2 particles under the collective process, evolves the state under applied quantum gates (collective operators), and provides measurement results on the Dicke basis.Additional comments including restrictions and unusual features:•Note for Installation:Download the source code and run: ▪Or install directly from PyPI, run: ▪(Note: conda may be used to install the external pyTorch library.)•Official website: https://vqisinfo.wixsite.com/tqix•API website: https://tqix-developers.readthedocs.io/en/latest/index.html•PyPI: https://pypi.org/project/tqix/