Quantum Computational Insurance and Actuarial Science
- URL: http://arxiv.org/abs/2410.20841v2
- Date: Tue, 23 Sep 2025 06:43:34 GMT
- Title: Quantum Computational Insurance and Actuarial Science
- Authors: Huan-Yu Liu, Xi-Ning Zhuang, Chao Wang, Qing-Song Li, Meng-Han Dou, Zhao-Yun Chen, Cheng Xue, Yu-Chun Wu, Guo-Ping Guo, Guang-Can Guo,
- Abstract summary: We discuss quantum algorithms that can address insurance problems based on their mathematical nature.<n>We explore the timeline for quantum insurance, the development of quantum-enhanced insurance products, and the challenges posed by quantum computational advancements.
- Score: 7.264252557743368
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: In recent years, quantum computation has been rapidly advancing, driving a technological revolution with significant potential across various sectors, particularly in finance. Despite this, the insurance industry, an essential tool for mitigating unforeseen risks and losses, has received limited attention. This paper provides an initial exploration into the realm of quantum computational insurance and actuarial science. After introducing key insurance models and challenges, we discuss quantum algorithms that can address insurance problems based on their mathematical nature. Our study includes experimental and numerical demonstrations of quantum applications in non-life insurance, life insurance, and reinsurance. Additionally, we explore the timeline for quantum insurance, the development of quantum-enhanced insurance products, and the challenges posed by quantum computational advancements. This work systematically constructs the connection between quantum computation and the insurance industry, enhancing the development of insurance while promoting the application of quantum computation to more realistic problems.
Related papers
- Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers [51.56484100374058]
This thesis is centered around simulating quantum dynamics on quantum devices.<n>We present an overview of the most relevant quantum algorithms for quantum dynamics.<n>We identify relevant problems within quantum dynamics that could benefit from quantum simulation in the near future.
arXiv Detail & Related papers (2025-08-29T10:37:19Z) - Quantum Software Security Challenges within Shared Quantum Computing Environments [2.4742581572364126]
The number of qubits in quantum computers keeps growing, but most quantum programs remain relatively small because of the noisy nature of the underlying quantum hardware.<n>This article explores and reports the key challenges identified in quantum software security within shared quantum computing environments.
arXiv Detail & Related papers (2025-07-23T17:23:34Z) - Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications [59.0413662882849]
Quantum computing is poised to redefine the algorithmic foundations of communication systems.<n>This article outlines the fundamentals of quantum computing in a style familiar to the communications society.<n>We highlight a mathematical harmony between quantum and wireless systems, which makes the topic more enticing to wireless researchers.
arXiv Detail & Related papers (2025-06-25T22:25:47Z) - Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise [49.97673761305336]
Noise remains a major obstacle to achieving reliable quantum algorithms.<n>We present a provably noise-resilient training theory and algorithm to enhance the robustness of parameterized quantum circuit classifiers.
arXiv Detail & Related papers (2025-05-24T02:51:34Z) - Evaluating the Potential of Quantum Machine Learning in Cybersecurity: A Case-Study on PCA-based Intrusion Detection Systems [42.184783937646806]
We investigate the potential impact of quantum computing and machine learning (QML) on cybersecurity applications of traditional ML.
First, we explore the potential advantages of quantum computing in machine learning problems specifically related to cybersecurity.
Then, we describe a methodology to quantify the future impact of fault-tolerant QML algorithms on real-world problems.
arXiv Detail & Related papers (2025-02-16T15:49:25Z) - The curse of random quantum data [62.24825255497622]
We quantify the performances of quantum machine learning in the landscape of quantum data.
We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits.
Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
arXiv Detail & Related papers (2024-08-19T12:18:07Z) - On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Program Scheduling [48.142860424323395]
We introduce the Quantum Program Scheduling Problem (QPSP) to improve the utility efficiency of quantum resources.
Specifically, a quantum program scheduling method concerning the circuit width, number of measurement shots, and submission time of quantum programs is proposed to reduce the execution latency.
arXiv Detail & Related papers (2024-04-11T16:12:01Z) - Quantum Computing: Vision and Challenges [16.50566018023275]
We discuss cutting-edge developments in quantum computer hardware advancement and subsequent advances in quantum cryptography, quantum software, and high-scalability quantum computers.
Many potential challenges and exciting new trends for quantum technology research and development are highlighted in this paper for a broader debate.
arXiv Detail & Related papers (2024-03-04T17:33:18Z) - Near-Term Quantum Computing Techniques: Variational Quantum Algorithms,
Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation [5.381727213688375]
We are still a long way from reaching the maturity of a full-fledged quantum computer.
An outstanding challenge is to come up with an application that can reliably carry out a nontrivial task.
Several near-term quantum computing techniques have been proposed to characterize and mitigate errors.
arXiv Detail & Related papers (2022-11-16T07:53:15Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - Quantum computational intelligence for traveltime seismic inversion [0.0]
We implement an approach for traveltime seismic inversion through a near-term quantum algorithm based on gradient-free quantum circuit learning.
We demonstrate that a quantum computer with thousands of qubits, even if noisy, can solve geophysical problems.
arXiv Detail & Related papers (2022-08-11T12:36:58Z) - A perspective on the current state-of-the-art of quantum computing for
drug discovery applications [43.55994393060723]
Quantum computing promises to shift the computational capabilities in many areas of chemical research by bringing into reach currently impossible calculations.
We briefly summarize and compare the scaling properties of state-of-the-art quantum algorithms.
We provide novel estimates of the quantum computational cost of simulating progressively larger embedding regions of a pharmaceutically relevant covalent protein-drug complex.
arXiv Detail & Related papers (2022-06-01T15:05:04Z) - Quantum computers as an amplifier for existential risk [0.0]
We discuss the potential consequences on existential risk for humanity.
Even with the timeline for large-scale fault-tolerant quantum computing still unclear, it is highly likely that quantum computers will eventually realize an exponential speedup for certain practical applications.
arXiv Detail & Related papers (2022-04-10T00:19:29Z) - Formal Verification of Quantum Programs: Theory, Tools and Challenges [0.0]
Survey aims to be a short introduction into the area of formal verification of quantum programs.
This survey examines some of the challenges that the field may face in the future, namely the development of complex quantum algorithms.
arXiv Detail & Related papers (2021-10-04T11:00:48Z) - Imaginary Time Propagation on a Quantum Chip [50.591267188664666]
Evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems.
We propose an algorithm to implement imaginary time propagation on a quantum computer.
arXiv Detail & Related papers (2021-02-24T12:48:00Z) - An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem.
The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
arXiv Detail & Related papers (2020-05-06T14:18:44Z) - Boundaries of quantum supremacy via random circuit sampling [69.16452769334367]
Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling.
We examine the constraints of the observed quantum runtime advantage in a larger number of qubits and gates.
arXiv Detail & Related papers (2020-05-05T20:11:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.