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We demonstrate how quantum field theory problems can be embedded on quantum annealers. The general method we use is a discretisation of the field theory problem into a general Ising model, with the continuous field values being encoded into…

High Energy Physics - Phenomenology · Physics 2021-01-20 Steven Abel , Nicholas Chancellor , Michael Spannowsky

We present and analyze a quantum algorithm to estimate credit risk more efficiently than Monte Carlo simulations can do on classical computers. More precisely, we estimate the economic capital requirement, i.e. the difference between the…

Quantum Physics · Physics 2019-07-09 Daniel J. Egger , Ricardo Gacía Gutiérrez , Jordi Cahué Mestre , Stefan Woerner

A quantum financial approach to finite games of strategy is addressed, with an extension of Nash's theorem to the quantum financial setting, allowing for an entanglement of games of strategy with two-period financial allocation problems…

General Finance · Quantitative Finance 2012-02-10 Carlos Pedro Gonçalves

Quantum computers can solve specific problems that are not feasible on "classical" hardware. Harvesting the speed-up provided by quantum computers therefore has the potential to change any industry which uses computation, including finance.…

Quantum annealing offers a novel approach to finding the optimal solutions for a variety of computational problems, where the quantum annealing controls influence the observed performance and error mechanisms by tuning the underlying…

Quantum Physics · Physics 2021-01-13 Erica Grant , Travis Humble , Benjamin Stump

Currency arbitrage leverages price discrepancies in currency exchange rates across different currency pairs to gain risk-free profits. It involves multiple trading, where short-lived price discrepancies require real-time, high-speed…

Quantum Physics · Physics 2025-11-03 Suman Kumar Roy , Rahul Rana , M Girish Chandra , Nishant Kumar , Manoj Nambiar

Critical decision-making issues in science, engineering, and industry are based on combinatorial optimization; however, its application is inherently limited by the NP-hard nature of the problem. A specialized paradigm of analogue quantum…

Quantum Physics · Physics 2026-02-04 Rudraksh Sharma , Ravi Katukam , Arjun Nagulapally

The recent crash demonstrated (once again) that the description of the financial market by present financial mathematics cannot be considered as totally satisfactory. We remind that nowadays financial mathematics is heavily based on the use…

General Physics · Physics 2009-02-12 Andrei Khrennikov

Quantum algorithms have gained increasing attention for addressing complex combinatorial problems in finance, notably portfolio optimization. This study systematically benchmarks two prominent variational quantum approaches, Variational…

Quantum Physics · Physics 2025-12-05 Nouhaila Innan , Ayesha Saleem , Alberto Marchisio , Muhammad Shafique

With the increasing popularity of quantum computing and in particular quantum annealing, there has been growing research to evaluate the meta-heuristic for various problems in linear algebra: from linear least squares to matrix and tensor…

Quantum Physics · Physics 2024-10-28 Ajinkya Borle , Samuel J. Lomonaco

Quantum computing is developing fast. Real world applications are within reach in the coming years. One of the most promising areas is combinatorial optimisation, where the Quadratic Unconstrained Binary Optimisation (QUBO) problem…

Quantum Physics · Physics 2020-07-06 Frank Phillipson , Irina Chiscop

Accurate financial volatility forecasting is crucial but challenged by the non-linear, highly correlated nature of market data. Recently, quantum computing has emerged as a promising paradigm for solving complex high-dimensional sampling…

Machine Learning · Computer Science 2026-05-07 Yixiong Chen

Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes. Quantum annealers (QA) are physical devices that aim at this class of problems by exploiting quantum…

Econophysics has developed as a research field that applies the formalism of Statistical Mechanics and Quantum Mechanics to address Economics and Finance problems. The branch of Econophysics that applies of Quantum Theory to Economics and…

Computational Finance · Quantitative Finance 2015-08-27 Carlos Pedro Gonçalves

In a recent study (Ref. [1]), quantum annealing was reported to exhibit a scaling advantage for approximately solving Quadratic Unconstrained Binary Optimization (QUBO). However, this claim critically depends on the choice of classical…

Quantum Physics · Physics 2025-05-29 J. Pawlowski , P. Tarasiuk , J. Tuziemski , L. Pawela , B. Gardas

Quantum computers are not yet up to the task of providing computational advantages for practical stochastic diffusion models commonly used by financial analysts. In this paper we introduce a class of stochastic processes that are both…

Quantum Physics · Physics 2023-11-03 Eric Ghysels , Jack Morgan , Hamed Mohammadbagherpoor

Quantum annealing is a powerful tool for solving and approximating combinatorial optimization problems such as graph partitioning, community detection, centrality, routing problems, and more. In this paper we explore the use of quantum…

Quantum Physics · Physics 2025-07-17 Joel E. Pion , Susan M. Mniszewski

Quantum computers are expected to have substantial impact on the finance industry, as they will be able to solve certain problems considerably faster than the best known classical algorithms. In this article we describe such potential…

Computational Finance · Quantitative Finance 2020-11-13 Adam Bouland , Wim van Dam , Hamed Joorati , Iordanis Kerenidis , Anupam Prakash

Currency arbitrage capitalizes on price discrepancies in currency exchange rates between markets to produce profits with minimal risk. By employing a combinatorial optimization problem, one can ascertain optimal paths within directed…

Computational Finance · Quantitative Finance 2025-02-25 Sangram Deshpande , Elin Ranjan Das , Frank Mueller

In this note, we describe an experiment on portfolio optimization using the Quadratic Unconstrained Binary Optimization (QUBO) formulation. The dataset we use is taken from a real-world problem for which a classical solution is currently…