International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 69 | Issue 2 | Year 2021 | Article Id. IJCTT-V69I2P109 | DOI : https://doi.org/10.14445/22312803/IJCTT-V69I2P109

Modeling The Runtime of Guassian In Quantum Computing Methods


S. Kayathri

Received Revised Accepted
29 Dec 2020 10 Feb 2021 13 Feb 2021

Citation :

S. Kayathri, "Modeling The Runtime of Guassian In Quantum Computing Methods," International Journal of Computer Trends and Technology (IJCTT), vol. 69, no. 2, pp. 61-63, 2021. Crossref, https://doi.org/10.14445/22312803/ IJCTT-V69I2P109

Abstract

In quantum computing methods, density functional theory (DFT) is the most powerful approach to calculate the electronic structure of physical systems containing a large number of atoms. Currently, a variety of computational methods that implement DFT equations in the basis set of plane waves, Gaussians, localized numerical orbital using real-space representation. There is a huge interest to make further progress in the modeling development of electronic structure calculations. In that regard, so many different and complementary research directions are currently pursued worldwide. One direction is devoted to developing methods that give accurate results in cases where standard approximations in DFT these developments include much fundamental theory.

Keywords

B3LYP, cache line, DFT, Guassian, HartreeFock, optimization.

References

[1] N. Nethercot, A. Mycroft, The Cache Behaviour of Large Lazy Functional Programs on Stock Hardware, Proceedings New York, USA, (2002).
[2] G. H. Golub and C. F. Van Loan. Matrix Computations. Johns Hopkins University Press, (1989).
[3] M. E. Wolf and M. S. Lam. A data locality algorithm. Submitted for publication., (1990) optimizing.
[4] D. Gannon and W. Jalby., The memory of hierarchy on algorithm organization.
[5] J. Dongarra, J. Du Croz, S. Hammarling, and I. Duff. Level (III) basic linear algebra programs.
[6] ACM Tanwdion.R. on Mathematical Software, (1990) 1-19. [7] In Proceedings of Annual ACM Symposium on Theory of Computing, (1981) 326-333. ACM SIGACT.
[8] The impact of hierarchical memory systems on linear algebra algorithm design.
[9] Technical Report UIUCSRD 625, University of Illinois, (1987).