Article

Article title QUIDD-BASED QUANTUM COMPUTER MODELING METHOD
Authors O.K. Evseev, S.M. Gushanskiy, V.F. Guzik
Section SECTION V. ALGORITHMS AND MODELLING, INFORMATION SAFETY
Month, Year 01, 2013 @en
Index UDC 681.3.06:530.145.001.57
DOI
Abstract Quantum computer simulation requires processing of huge-size matrixes containing several distinct elements. The most effective method of decreasing calculation costs for simulation was developed in the University of Michigan and was called Quantum Information Decision Diagrams. In order to improve the efficiency of the base QuIDD methodic this article covers its key aspects and advises level-wise recursive methods of QuIDD graph reduction and matrix member-wise operations. Methods set out in this article can be used for developing a graph-based mathematical model of a universal quantum computer, operating at the maximal dimension of the quantum register of about 50 q-bits.

Download PDF

Keywords Quantum computation; simulation; q-bit; QuIDD graph; matrix; state vector; tensor product; level-wise operations.
References 1. Shor P.W. Scheme for reducing decoherence in quantum memory // Phys. Rev. – 1995. – Vol. A52, № 4. – P. R2493-R2496.
2. Grover L.K. A fast quantum mechanical algorithm for database search // Proc. of 28th Annual ACM Symposium on the Theory of Computing. – 1996. – P. 212-232.
3. Chris McCubbin. Модель квантового вычислителя с открытым исходным кодом на Maple / URL: http://web.archive.org/web/20060116174553/http://userpages.umbc.edu/~cmccub1/quacs/quacs.html (дата обращения: 27.03.2012).
4. Lib Quantum. Моделирование квантовой механики / URL: http://www.enyo.de /libquantum (дата обращения: 27.03.2012).
5. Black P.E., Lane A.W. Modeling Quantum Information Systems // Proc. of the Interational Society for Optical Engineering. – 2004. – № 5436. – P. 340-347.
6. Viamontes G.F., Markov I.L., Hayes J.P. Quantum circuit simulation – Quantum Information Processing, Springer. – 2009. – 194 p.
7. Bahar R.I., Frohm E.A., Gaona C.M. Algebraic decision diagrams and their applications // ICCAD '93, Santa Clara, CA, USA, November 07-11 – Los Alamitos, CA, USA: IEEE Computer Society Press. – 1993. – P. 188-191.
8. Sanner S., McAllester D. Affine algebraic decision diagrams and their Application to Structured Probabilistic Inference // Proc. of IJCAI-05, San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. 2005. – 7 p.

Comments are closed.