Paper: arXiv 2507.19206

Authors: Davide Veronelli, Francesca Cibrario, Emanuele Dri, Valeria Zaffaroni, Giacomo Ranieri, Davide Corbelletto, Bartolomeo Montrucchio

Abstract

The analysis of credit risk is crucial for the efficient operation of financial institutions. Quantum Amplitude Estimation (QAE) offers the potential for a quadratic speed-up over classical methods used to estimate metrics such as Value at Risk (VaR) and Conditional Value at Risk (CVaR). However, numerous limitations remain in efficiently scaling the implementation of quantum circuits that solve these estimation problems. One of the main challenges is the use of costly and restrictive arithmetic that must be implemented within the quantum circuit. In this paper, we propose using Quantum Singular Value Transformation (QSVT) to significantly reduce the cost of implementing the state preparation operator, which underlies QAE for credit risk analysis. We also present an end-to-end code implementation and the results of a simulation study to validate the proposed approach and demonstrate its benefits.

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 4.5/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper introduces a mathematically sophisticated method using Quantum Singular Value Transformation (QSVT) to optimize state preparation for credit risk analysis (VaR/CVaR) without heavy arithmetic gates. While the theoretical formulation is strong and backed by quantum circuit simulation studies, empirical testing remains limited to synthetic NISQ simulations rather than extensive real-world market backtests.

Research Flowchart

  flowchart TD
    A[Goal: Reduce Quantum Circuit Cost for Credit Risk VaR/CVaR] --> B[Inputs: Credit Portfolio Data & Loss Distributions]
    B --> C[Method: Integrate QSVT into Quantum Amplitude Estimation]
    C --> D[Compute: Polynomial Approximation for State Preparation]
    D --> E[Simulation: End-to-End Code Execution]
    E --> F[Outcome: Reduced Arithmetic Gates & Maintained Quadratic Speed-up]

Cited References (40)

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and 32 more
  1. On the Synthesis of Quantum Circuits for Diagonal Operators in Quantum Computation (2015) — link
  2. Long-time simulations for fixed input states on quantum hardware (2022) — link
  3. Towards practical Quantum Credit Risk Analysis (2022) — link
  4. A More General Quantum Credit Risk Analysis Framework (2023) — link
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  8. Quantum Algorithms for Portfolio Optimization (2019) — link
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0 of 40 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.