Functional Matrices on Quantum Computing Simulation

Hernán Indíbil de la Cruz Calvo (), Fernando Cuartero Gómez, José Javier Paulet González, Mauro Mezzini and Fernando López Pelayo ()
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Hernán Indíbil de la Cruz Calvo: Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Spain
Fernando Cuartero Gómez: Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Spain
José Javier Paulet González: Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Spain
Mauro Mezzini: Educational Sciences Department, Roma Tre University, Via Ostiense, 00154 Rome, Italy
Fernando López Pelayo: Departmento de Sistemas Informáticos, Universidad de Castilla-La Mancha, Campus Universitario, 02071 Albacete, Spain

Mathematics, 2023, vol. 11, issue 17, 1-20

Abstract: In simulating Quantum Computing by using the circuit model the size of the matrices to deal with, together with the number of products and additions required to apply every quantum gate becomes a really hard computational restriction. This paper presents a data structure, called Functional Matrices, which is the most representative feature of QSimov quantum computing simulator which is also provided and tested. A comparative study of the performance of Functional Matrices with respect to the other two most commonly used matrix data structures, dense and sparse ones, is also performed and summarized within this work.

Keywords: quantum simulator; circuit model; functional matrices; computational efficiency (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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