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Quantum Technology for Economists

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  • Isaiah Hull
  • Or Sattath
  • Eleni Diamanti
  • Goran Wendin

Abstract

Research on quantum technology spans multiple disciplines: physics, computer science, engineering, and mathematics. The objective of this manuscript is to provide an accessible introduction to this emerging field for economists that is centered around quantum computing and quantum money. We proceed in three steps. First, we discuss basic concepts in quantum computing and quantum communication, assuming knowledge of linear algebra and statistics, but not of computer science or physics. This covers fundamental topics, such as qubits, superposition, entanglement, quantum circuits, oracles, and the no-cloning theorem. Second, we provide an overview of quantum money, an early invention of the quantum communication literature that has recently been partially implemented in an experimental setting. One form of quantum money offers the privacy and anonymity of physical cash, the option to transact without the involvement of a third party, and the efficiency and convenience of a debit card payment. Such features cannot be achieved in combination with any other form of money. Finally, we review all existing quantum speedups that have been identified for algorithms used to solve and estimate economic models. This includes function approximation, linear systems analysis, Monte Carlo simulation, matrix inversion, principal component analysis, linear regression, interpolation, numerical differentiation, and true random number generation. We also discuss the difficulty of achieving quantum speedups and comment on common misconceptions about what is achievable with quantum computing.

Suggested Citation

  • Isaiah Hull & Or Sattath & Eleni Diamanti & Goran Wendin, 2020. "Quantum Technology for Economists," Papers 2012.04473, arXiv.org, revised Oct 2021.
  • Handle: RePEc:arx:papers:2012.04473
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    Cited by:

    1. Jesús Fernández-Villaverde & Isaiah J. Hull, 2023. "Dynamic Programming on a Quantum Annealer: Solving the RBC Model," NBER Working Papers 31326, National Bureau of Economic Research, Inc.
    2. Christopher McMahon & Donald McGillivray & Ajit Desai & Francisco Rivadeneyra & Jean-Paul Lam & Thomas Lo & Danica Marsden & Vladimir Skavysh, 2022. "Improving the Efficiency of Payments Systems Using Quantum Computing," Staff Working Papers 22-53, Bank of Canada.
    3. Martin Vesel'y, 2022. "Application of Quantum Computers in Foreign Exchange Reserves Management," Papers 2203.15716, arXiv.org.
    4. Hull, Isaiah & Sattath, Or, 2021. "Revisiting the Properties of Money," Working Paper Series 406, Sveriges Riksbank (Central Bank of Sweden).
    5. 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).

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    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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