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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.15459 |
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| _version_ | 1866912909623296000 |
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| author | Sarracino, Giuseppe Cardone, Vincenzo Fabrizio Scaramella, Roberto Riccio, Giuseppe Bulgarelli, Andrea Burigana, Carlo Cappelli, Luca Cavuoti, Stefano Farsian, Farida Graziotti, Irene Meneghetti, Massimo Murante, Giuseppe Parmiggiani, Niccolò Rizzo, Alessandro Schillirò, Francesco Testa, Vincenzo Trombetti, Tiziana |
| author_facet | Sarracino, Giuseppe Cardone, Vincenzo Fabrizio Scaramella, Roberto Riccio, Giuseppe Bulgarelli, Andrea Burigana, Carlo Cappelli, Luca Cavuoti, Stefano Farsian, Farida Graziotti, Irene Meneghetti, Massimo Murante, Giuseppe Parmiggiani, Niccolò Rizzo, Alessandro Schillirò, Francesco Testa, Vincenzo Trombetti, Tiziana |
| contents | An Amplitude-Encoded Quantum Genetic Algorithm (AEQGA) has been developed to minimize $χ^2$ functions of different cosmological probes (Supernovae Type Ia, Baryon Acoustic Oscillations, Cosmic Microwave Background Radiation), to find the best-fit value for two cosmological parameters, namely the Hubble Constant and the density matter content of the Universe today. Our main aim is to pave the way to testing the adoption of quantum optimization in the inference of the cosmological parameters that describe the universe evolution. AEQGA computes the merit function classically, and then uses a quantum circuit to entangle the population and perform crossover and mutation operations. The results show consistency with the isocontours of the objective functions. We then tested the general behavior of AEQGA as a function of its hyperparameters and compared it with a second quantum genetic algorithm found in the literature as well as with classical algorithms, finding consistent results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_15459 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Quantum Genetic Algorithm with application to Cosmological Parameters Estimation Sarracino, Giuseppe Cardone, Vincenzo Fabrizio Scaramella, Roberto Riccio, Giuseppe Bulgarelli, Andrea Burigana, Carlo Cappelli, Luca Cavuoti, Stefano Farsian, Farida Graziotti, Irene Meneghetti, Massimo Murante, Giuseppe Parmiggiani, Niccolò Rizzo, Alessandro Schillirò, Francesco Testa, Vincenzo Trombetti, Tiziana Cosmology and Nongalactic Astrophysics An Amplitude-Encoded Quantum Genetic Algorithm (AEQGA) has been developed to minimize $χ^2$ functions of different cosmological probes (Supernovae Type Ia, Baryon Acoustic Oscillations, Cosmic Microwave Background Radiation), to find the best-fit value for two cosmological parameters, namely the Hubble Constant and the density matter content of the Universe today. Our main aim is to pave the way to testing the adoption of quantum optimization in the inference of the cosmological parameters that describe the universe evolution. AEQGA computes the merit function classically, and then uses a quantum circuit to entangle the population and perform crossover and mutation operations. The results show consistency with the isocontours of the objective functions. We then tested the general behavior of AEQGA as a function of its hyperparameters and compared it with a second quantum genetic algorithm found in the literature as well as with classical algorithms, finding consistent results. |
| title | A Quantum Genetic Algorithm with application to Cosmological Parameters Estimation |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2602.15459 |