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A Structured Survey of Quantum Computing for the Financial Industry

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arxiv 2204.10026 v1 pith:KASRZPOR submitted 2022-04-21 q-fin.GN

classification q-fin.GN
keywords quantumindustryfinancialcomputingapplicationscasescomputersfinance
verification ladder T0 review T1 audit T2 compute T3 formal

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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. First quantum applications for the financial industry involving optimization, simulation, and machine learning problems have already been proposed and applied to use cases such as portfolio management, risk management, and pricing derivatives. This survey reviews platforms, algorithms, methodologies, and use cases of quantum computing for various applications in finance in a structured way. It is aimed at people working in the financial industry and serves to gain an overview of the current development and capabilities and understand the potential of quantum computing in the financial industry.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Circuit Optimization for the Fault-Tolerance Era: Do We Have to Start from Scratch?

    quant-ph 2025-09 conditional novelty 6.0 of 10

    Existing NISQ optimization passes can reduce estimated FTQC resource requirements, with rotation-gate reduction providing the largest gains.

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