Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3232195.3232197acmconferencesArticle/Chapter ViewAbstractPublication PagesnanoarchConference Proceedingsconference-collections
research-article

Representation of Qubit States using 3D Memristance Spaces: A first step towards a Memristive Quantum Simulator

Published: 17 July 2018 Publication History

Abstract

Development of quantum simulators is a major step towards the universal quantum computer. Quantum simulators are quantum systems that can perform specific quantum computations, or software packages that can reproduce most of the aspects of a general universal quantum computer on a general purpose classical computer. Development of quantum simulators using digital circuits, such as FPGAs is very difficult, mainly because the unit of quantum information, the qubit, has an infinite number of states, whereas the classical bit has only two. On the other hand, analog circuits comprising R, L and C elements have no internal state variables that can be used to reproduce and store qubit states. Here we take the first step towards the development of a new quantum simulator using memristors. The qubit state is mapped to a 3D space spanned by the memristances of three identical memristors. The qubit state evolution is reproduced by the input voltages applied to the memristors. We define the correspondence between the general qubit state rotation, i.e. the one-qubit quantum gates, and memristor input voltage variations and reproduce the rotations imposed by the action of quantum gates in the 3D memristance space. Our results show that, at least in principle, qubits and one-qubit quantum gates can be simulated by memristors.

References

[1]
A. Aspuru-Guzik and Ph. Walther. 2012. Photonic Quantum Simulators. Nature Physics 8 (04 2012), 285--291.
[2]
Julio T. Barreiro, Markus Müller, Philipp Schindler, Daniel Nigg, Thomas Monz, Michael Chwalla, Markus Hennrich, C. F. Roos, Peter Zoller, and R. Blatt. 2011. An open-system quantum simulator with trapped ions. Nature 470 (2011), 486--491.
[3]
Charles H. Bennett. 1982. The thermodynamics of computation---a review. International Journal of Theoretical Physics 21, 12 (01 Dec 1982), 905--940.
[4]
Z. Biolek, D. Biolek, and V. Biolková. 2009. Spice Model of Memristor With Nonlinear Dopant Drift. Radioengineering 18 (2009), 210--214.
[5]
Katherine L Brown, Suvabrata De, Vivien M Kendon, and William J Munro. 2011. Ancilla-based quantum simulation. New Journal of Physics 13, 9 (2011), 095007. http://stacks.iop.org/1367-2630/13/i=9/a=095007
[6]
L. Chua. 1971. Memristor-The missing circuit element. IEEE Transactions on Circuit Theory 18, 5 (September 1971), 507--519.
[7]
Richard P. Feynman. 1982. Simulating physics with computers. International Journal of Theoretical Physics 21, 6 (01 Jun 1982), 467--488.
[8]
Andrew A. Houck, Hakan E. Türeci, and Jens Koch. 2012. On-chip quantum simulation with superconducting circuits. Nature Physics 8, 4 (1 4 2012), 292--299.
[9]
Yogesh N Joglekar and Stephen J Wolf. 2009. The elusive memristor: properties of basic electrical circuits. European Journal of Physics 30, 4 (2009), 661. http://stacks.iop.org/0143-0807/30/i=4/a=001
[10]
Tomi H. Johnson, Stephen R. Clark, and Dieter Jaksch. 2014. What is a quantum simulator? EPJ Quantum Technology 1, 1 (23 Jul 2014), 10.
[11]
I. G. Karafyllidis. 2005. Quantum Computer Simulator Based on the Circuit Model of Quantum Computation. IEEE Transactions on Circuits and Systems I: Regular Papers 52, 8 (Aug 2005), 1590--1596.
[12]
TD Ladd, F Jelezko, R Laflamme, C Monroe, Y Nakamura, and JL O'Brien. 2010. Quantum computers. Nature 464 (3 2010), 45--53.
[13]
Michael A. Nielsen and Isaac L. Chuang. 2011. Quantum Computation and Quantum Information: 10th Anniversary Edition (10th ed.). Cambridge University Press, New York, NY, USA.
[14]
V. Ntinas, I. Vourkas, A. Abusleme, G. C. Sirakoulis, and A. Rubio. 2018. Experimental Study of Artificial Neural Networks Using a Digital Memristor Simulator. IEEE Transactions on Neural Networks and Learning Systems (2018), 1--13.
[15]
P. Pfeiffer, I. L. Egusquiza, M. Di Ventra, M. Sanz, and E. Solano. 2016. Quantum memristors. Scientific Reports 6 (2016), 29507.
[16]
T. Prodromakis, B. P. Peh, C. Papavassiliou, and C. Toumazou. 2011. A Versatile Memristor Model With Nonlinear Dopant Kinetics. IEEE Transactions on Electron Devices 58, 9 (Sept 2011), 3099--3105.
[17]
K. De Raedt, K. Michielsen, H. De Raedt, B. Trieu, G. Arnold, M. Richter, Th. Lippert, H. Watanabe, and N. Ito. 2007. Massively parallel quantum computer simulator. Computer Physics Communications 176, 2 (2007), 121--136.
[18]
P. Santini, S. Carretta, F. Troiani, and G. Amoretti. 2011. Molecular Nanomagnets as Quantum Simulators. Phys. Rev. Lett. 107 (Nov 2011), 230502. Issue 23.
[19]
Dmitri B. Strukov, Gregory S. Snider, Duncan R. Stewart, and R. Stanley Williams. 2008. The missing memristor found. Nature 453 (2008), 80.
[20]
F. L. Traversa and M. Di Ventra. 2015. Universal Memcomputing Machines. IEEE Transactions on Neural Networks and Learning Systems 26, 11 (Nov 2015), 2702--2715.
[21]
Panagiotis Vlachos and Ioannis G. Karafyllidis. 2009. Quantum game simulator, using the circuit model of quantum computation. Computer Physics Communications 180, 10 (2009), 1990--1998.
[22]
I. Vourkas and G. C. Sirakoulis. 2016. Emerging Memristor-Based Logic Circuit Design Approaches: A Review. IEEE Circuits and Systems Magazine 16, 3 (thirdquarter 2016), 15--30.

Cited By

View all
  • (2022)Nearly Quantum Computing by SimulationHigh Performance Computing10.1007/978-3-031-23821-5_15(205-219)Online publication date: 21-Dec-2022

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
NANOARCH '18: Proceedings of the 14th IEEE/ACM International Symposium on Nanoscale Architectures
July 2018
176 pages
ISBN:9781450358156
DOI:10.1145/3232195
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 July 2018

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Memristors
  2. Nanoelectronics
  3. Quantum simulators
  4. Qubits

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

NANOARCH '18
Sponsor:

Acceptance Rates

NANOARCH '18 Paper Acceptance Rate 30 of 56 submissions, 54%;
Overall Acceptance Rate 55 of 87 submissions, 63%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)5
  • Downloads (Last 6 weeks)1
Reflects downloads up to 30 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2022)Nearly Quantum Computing by SimulationHigh Performance Computing10.1007/978-3-031-23821-5_15(205-219)Online publication date: 21-Dec-2022

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media