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Author  |
Pyretzidis, K.; Martinez de Lejarza, J.J.; Rodrigo, G. |
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Title |
Unlocking multidimensional integration with quantum adaptive importance sampling |
Type |
Journal Article |
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Year |
2026 |
Publication |
Communications Physics |
Abbreviated Journal |
Commun. Phys. |
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Volume |
9 |
Issue |
1 |
Pages |
269 - 17pp |
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Abstract |
Multidimensional numerical integration is a central ingredient of theoretical predictions in high-energy physics, where multiloop Feynman diagrams and phase-space integrals are computationally demanding due to divergences and complex mathematical structures. Established Adaptive Importance Sampling methods for numerical integration, such as VEGAS, iteratively refine a grid in a separable way, dimension by dimension. This keeps the algorithm scalable but reduces performance when strong inter-variable correlations are present. In this work, we introduce a hybrid quantum-classical algorithm that performs Quantum Adaptive Importance Sampling (QAIS) for multidimensional Monte Carlo integration. Our approach uses a Parametrized Quantum Circuit to encode a non-separable Probability Density Function on a multidimensional grid and allocate samples efficiently in the integration domain. We apply the method to a sharply peaked loop Feynman integral and to multi-modal benchmark integrals. Our results show that QAIS provides an efficient route for high-precision evaluation of multidimensional integrals. |
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Address |
[Pyretzidis, Konstantinos; Martinez de Lejarza, Jorge J.; Rodrigo, German] Univ Valencia, Consejo Super Invest Cient, Inst Fis Corpuscular, Paterna, Spain, Email: k.pyretzidis@csic.es |
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Publisher |
Nature Portfolio |
Place of Publication |
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Language |
English |
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Original Title |
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Series Title |
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Series Volume |
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Edition |
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ISSN |
2399-3650 |
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Notes |
WOS:001849339500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
7398 |
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