IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/18190.html
   My bibliography  Save this paper

Dynamic Programming on a Quantum Annealer: Solving the RBC Model

Author

Listed:
  • Fernández-Villaverde, Jesús
  • Hull, Isaiah

Abstract

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all states and generating candidate global solutions in milliseconds, irrespective of problem size. Using existing quantum hardware, we achieve an order-of-magnitude speed-up in solving the real business cycle model over benchmarks in the literature. We also provide a detailed introduction to quantum annealing and discuss its potential use for more challenging economic problems.

Suggested Citation

  • Fernández-Villaverde, Jesús & Hull, Isaiah, 2023. "Dynamic Programming on a Quantum Annealer: Solving the RBC Model," CEPR Discussion Papers 18190, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:18190
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP18190
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Frank Arute & Kunal Arya & Ryan Babbush & Dave Bacon & Joseph C. Bardin & Rami Barends & Rupak Biswas & Sergio Boixo & Fernando G. S. L. Brandao & David A. Buell & Brian Burkett & Yu Chen & Zijun Chen, 2019. "Quantum supremacy using a programmable superconducting processor," Nature, Nature, vol. 574(7779), pages 505-510, October.
    2. Hugo Benitez-Silva & John Rust & Gunter Hitsch & Giorgio Pauletto & George Hall, 2000. "A Comparison Of Discrete And Parametric Methods For Continuous-State Dynamic Programming Problems," Computing in Economics and Finance 2000 24, Society for Computational Economics.
    3. Jesús Fernández‐Villaverde & Samuel Hurtado & Galo Nuño, 2023. "Financial Frictions and the Wealth Distribution," Econometrica, Econometric Society, vol. 91(3), pages 869-901, May.
    4. Andrew Sweeting, 2013. "Dynamic Product Positioning in Differentiated Product Markets: The Effect of Fees for Musical Performance Rights on the Commercial Radio Industry," Econometrica, Econometric Society, vol. 81(5), pages 1763-1803, September.
    5. Aruoba, S. Borağan & Fernández-Villaverde, Jesús, 2015. "A comparison of programming languages in macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 265-273.
    6. Roman Orus & Samuel Mugel & Enrique Lizaso, 2018. "Forecasting financial crashes with quantum computing," Papers 1810.07690, arXiv.org, revised Jun 2019.
    7. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    8. Isaiah Hull & Or Sattath & Eleni Diamanti & Goran Wendin, 2020. "Quantum Technology for Economists," Papers 2012.04473, arXiv.org, revised Oct 2021.
    9. Sergio Boixo & Vadim N. Smelyanskiy & Alireza Shabani & Sergei V. Isakov & Mark Dykman & Vasil S. Denchev & Mohammad H. Amin & Anatoly Yu Smirnov & Masoud Mohseni & Hartmut Neven, 2016. "Computational multiqubit tunnelling in programmable quantum annealers," Nature Communications, Nature, vol. 7(1), pages 1-7, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Skavysh, Vladimir & Priazhkina, Sofia & Guala, Diego & Bromley, Thomas R., 2023. "Quantum monte carlo for economics: Stress testing and macroeconomic deep learning," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    2. Vladimir Skavysh & Sofia Priazhkina & Diego Guala & Thomas Bromley, 2022. "Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning," Staff Working Papers 22-29, Bank of Canada.
    3. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    4. Dylan Herman & Cody Googin & Xiaoyuan Liu & Alexey Galda & Ilya Safro & Yue Sun & Marco Pistoia & Yuri Alexeev, 2022. "A Survey of Quantum Computing for Finance," Papers 2201.02773, arXiv.org, revised Jun 2022.
    5. Duarte, Victor & Duarte, Diogo & Fonseca, Julia & Montecinos, Alexis, 2020. "Benchmarking machine-learning software and hardware for quantitative economics," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    6. Michael Cohen & Rui Huang, 2012. "Corporate Social Responsibility for Kids’ Sake: A Dynamic Model of Firm Participation," Working Papers 12, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    7. Ruitu Xu & Yifei Min & Tianhao Wang & Zhaoran Wang & Michael I. Jordan & Zhuoran Yang, 2023. "Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning," Papers 2303.04833, arXiv.org.
    8. Tobias Salz & Emanuel Vespa, 2020. "Estimating dynamic games of oligopolistic competition: an experimental investigation," RAND Journal of Economics, RAND Corporation, vol. 51(2), pages 447-469, June.
    9. Pizer, William A., 1999. "The optimal choice of climate change policy in the presence of uncertainty," Resource and Energy Economics, Elsevier, vol. 21(3-4), pages 255-287, August.
    10. Boppart, Timo & Krusell, Per & Mitman, Kurt, 2018. "Exploiting MIT shocks in heterogeneous-agent economies: the impulse response as a numerical derivative," Journal of Economic Dynamics and Control, Elsevier, vol. 89(C), pages 68-92.
    11. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
    12. Yannis M. Ioannides & Vassilis A. Hajivassiliou, 2007. "Unemployment and liquidity constraints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 479-510.
    13. T. Tony Ke & Jiwoong Shin & Jungju Yu, 2023. "A Model of Product Portfolio Design: Guiding Consumer Search Through Brand Positioning," Marketing Science, INFORMS, vol. 42(6), pages 1101-1124, November.
    14. Mayank Aggarwal & Anindya S. Chakrabarti & Chirantan Chatterjee, 2023. "Movies, stigma and choice: Evidence from the pharmaceutical industry," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1019-1039, May.
    15. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2019. "Dynamic Random Utility," Econometrica, Econometric Society, vol. 87(6), pages 1941-2002, November.
    16. Raphael Corbi & Fabio Miessi Sanches, 2022. "Church Competition, Religious Subsidies and the Rise of Evangelicalism: a Dynamic Structural Analysis," Working Papers, Department of Economics 2022_09, University of São Paulo (FEA-USP).
    17. Attila Ambrus & Emilio Calvano & Markus Reisinger, 2016. "Either or Both Competition: A "Two-Sided" Theory of Advertising with Overlapping Viewerships," American Economic Journal: Microeconomics, American Economic Association, vol. 8(3), pages 189-222, August.
    18. Tong Liu & Shang Liu & Hekang Li & Hao Li & Kaixuan Huang & Zhongcheng Xiang & Xiaohui Song & Kai Xu & Dongning Zheng & Heng Fan, 2023. "Observation of entanglement transition of pseudo-random mixed states," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    19. Stephen J. Terry, 2017. "Alternative Methods for Solving Heterogeneous Firm Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1081-1111, September.
    20. X. L. He & Yong Lu & D. Q. Bao & Hang Xue & W. B. Jiang & Z. Wang & A. F. Roudsari & Per Delsing & J. S. Tsai & Z. R. Lin, 2023. "Fast generation of Schrödinger cat states using a Kerr-tunable superconducting resonator," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

    More about this item

    Keywords

    Computational methods;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:18190. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.