Tytuł artykułu
Wybrane pełne teksty z tego czasopisma
Identyfikatory
DOI
Warianty tytułu
Konferencja
Federated Conference on Computer Science and Information Systems (16 ; 02-05.09.2021 ; online)
Języki publikacji
Abstrakty
We study an optimized Adaptive Monte Carlo algorithm for the Wigner kernel- an important problem in quantum mechanics. We will compare the results with the basic adaptive approach and other stochastic approaches for computing the Wigner kernel represented by difficult multidimensional integrals in dimension d up to 12. The higher cases d > 12 will be considered for the first time. A comprehensive study and an analysis of the computational complexity of the optimized Adaptive MC algorithm under consideration has also been presented.
Rocznik
Tom
Strony
235--238
Opis fizyczny
Bibliogr. 15 poz., wz., tab., wykr.
Twórcy
autor
- Bulgarian Academy of Sciences Institute of Mathematics and Informatics ul. G. Bonchev 8, 1113 Sofia, Bulgaria
- Bulgarian Academy of Sciences Institute of Information and Communication Technologies ul. G. Bonchev 25A, 1113 Sofia, Bulgaria
autor
- Bulgarian Academy of Sciences Institute of Information and Communication Technologies ul. G. Bonchev 25A, 1113 Sofia, Bulgaria
autor
- Bulgarian Academy of Sciences Institute of Information and Communication Technologies ul. G. Bonchev 25A, 1113 Sofia, Bulgaria
autor
- Bulgarian Academy of Sciences Institute of Mathematics and Informatics ul. G. Bonchev 8, 1113 Sofia, Bulgaria
Bibliografia
- 1. Berntsen J., Espelid T.O., Genz A. (1991) An adaptive algorithm for the approximate calculation of multiple integrals, ACM Trans. Math. Softw. 17: 437–451.
- 2. Dimov I. (2008) Monte Carlo Methods for Applied Scientists, New Jersey, London, Singapore, World Scientific, 291 p., ISBN-10 981-02-2329-3.
- 3. Dimov I., Karaivanova A., Georgieva R., Ivanovska S. (2003) Parallel Importance Separation and Adaptive Monte Carlo Algorithms for Multiple Integrals, Springer Lecture Notes in Computer Science, 2542, 99–107.
- 4. Dimov I., Georgieva R. (2010) Monte Carlo Algorithms for Evaluating Sobol’ Sensitivity Indices. Math. Comput. Simul. 81(3): 506–514.
- 5. Ermakov S.M. (1985) Monte Carlo Methods and Mixed Problems, Nauka, Moscow.
- 6. Feynman R.P. (1948) Space-time approach to non-relativistic quantum mechanics, Rev. Mod. Phys. 20.
- 7. Sellier J.M. (2015) A signed particle formulation of non-relativistic quantum mechanics, Journal of Computational Physics 297: 254—265.
- 8. Sellier J.M., Dimov I. (2016) On a full Monte Carlo approach to quantum mechanics, Physica A: Statistical Mechanics and its Applications Volume 463: 45–62.
- 9. Sellier J.M., Dimov I. (2014) The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations, J. Comput. Phys. 273: 589–597.
- 10. Sellier J.M., Nedjalkov M., Dimov I. (2015) An introduction to applied quantum mechanics in the Wigner Monte Carlo formalism, Physics Reports Volume 577: 1–34.
- 11. Shao S., Lu T., Cai W. (2011) Adaptive conservative cell average spectral element methods for transient Wigner equation in quantum transport. Commun. Comput. Phys., 9: 711–739.
- 12. Shao S. and Sellier J.M. (2015) Comparison of deterministic and stochastic methods for time-dependent Wigner simulations. J. Comput. Phys., 300: 167–185.
- 13. Todorov, V., Dimov, I., Georgieva, R., & Dimitrov, S. (2019). Adaptive Monte Carlo algorithm for Wigner kernel evaluation. Neural Computing and Applications, 1-12.
- 14. Xiong Y., Chen Z., Shao S (2016) An advective-spectral-mixed method for time-dependent many-body Wigner simulations. SIAM J. Sci. Comput., to appear, [https://arxiv.org/abs/1602.08853].
- 15. Wigner E. (1932) On the quantum correction for thermodynamic equilibrium, Phys. Rev. 40: 749.
Uwagi
1. Track 1: Artificial Intelligence in Applications
2. Session: 14th International Workshop on Computational Optimization
3. Short Paper
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-15d0008b-b321-41c9-9713-f6f72daee8b3