| Issue |
E3S Web Conf.
Volume 307, 2021
International Interdisciplinary Scientific Conference “Digitalisation and Sustainability for Development Management: Economic, Social, and Ecological Aspects” 2021
|
|
|---|---|---|
| Article Number | 04001 | |
| Number of page(s) | 11 | |
| Section | Artificial Intelligence and Cognitive Technologies in Sustainable Development | |
| DOI | https://doi.org/10.1051/e3sconf/202130704001 | |
| Published online | 22 September 2021 | |
Hybrid classical-quantum computing: Applications to statistical mechanics of financial markets
Physical Studies Institute LLC, 7325 NE Imbrie Dr Ste 518, Hillsboro, OR 97124, USA
* Corresponding author: ingber@caa.caltech.edu
Hybrid Classical-Quantum computing is now offered by several commercial quantum computers. In this project, a model of financial options, Statistical Mechanics of Financial Markets (SMFM), uses this approach. However, only Classical (super-)computers are used to include the quantum features of these models. Since 1989, Adaptive Simulated Annealing (ASA), an optimization code using importance-sampling, has fit parameters in such models. Since 2015, PATHINT, a path-integral numerical agorithm, has been used to describe several systems in several disciplines. PATHINT has been generalized from 1 dimension to N dimensions, and from classical to quantum systems into qPATHINT. Published papers have described the use of qPATHINT to neocortical interactions and financial options. The classical space modeled by SMFM fits parameters in conditional short-time probability distributions of nonlinear nonequilibrium multivariate statistical mechanics, while the quantum space modeled by qPATHINT describes quantum money. This project demonstrates how some hybrid classical-quantum systems may be calculated using only classical (super-)computers.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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