Results 41 to 50 of about 8,042,432 (193)
Digital Quantum Simulation and Circuit Learning for the Generation of Coherent States [PDF]
, 2022 Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning, and quantum optics.
Eneko Osaba +11 more
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Extending the reach of quantum computing for materials science with machine learning potentials
AIP Advances, 2022 Solving electronic structure problems represents a promising field of applications for quantum computers. Currently, much effort is spent in devising and optimizing quantum algorithms for near-term quantum processors, with the aim of outperforming ...
Julian Schuhmacher +6 more
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Challenges and opportunities in quantum machine learning
Nature Computational Science, 2022 At the intersection of machine learning and quantum computing, Quantum Machine Learning (QML) has the potential of accelerating data analysis, especially for quantum data, with applications for quantum materials, biochemistry, and high-energy physics. Nevertheless, challenges remain regarding the trainability of QML models.
Marco Cerezo +4 more
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Machine learning applied to programming quantum computers
, 2019 Click on the DOI link to access the article (may not be free).We apply machine learning to “program” quantum computers, both in simulation and in experimental hardware.
Steck, James E. +2 more
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Quantum Embedding Search for Quantum Machine Learning
IEEE Access, 2022 Quantum Embedding Search for Quantum Machine ...
Nam Nguyen 0003, Kwang-Cheng Chen
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Quantum machine learning of large datasets using randomized measurements [PDF]
, 2023 Quantum computers promise to enhance machine learning for practical applications. Quantum machine learning for real-world data has to handle extensive amounts of high-dimensional data.
M S Kim +5 more
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New trends in quantum machine learning (a) [PDF]
Europhysics Letters, 2020 Abstract Here we will give a perspective on new possible interplays between machine learning and quantum physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum technologies and algorithms to find new ways to speed up their computations by breakthroughs ...
Buffoni L., Caruso F.
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New insights into supradense matter from dissecting scaled stellar structure equations
Frontiers in Astronomy and Space SciencesThe strong-field gravity in general relativity (GR) realized in neutron stars (NSs) renders the equation of state (EOS) P(ε) of supradense neutron star matter to be essentially nonlinear and refines the upper bound for ϕ≡P/ε to be much smaller than the ...
Bao-Jun Cai, Bao-An Li
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Quantum Machine Learning—An Overview
, 2023 Quantum computing has been proven to excel in factorization issues and unordered search problems due to its capability of quantum parallelism. This unique feature allows exponential speed-up in solving certain problems.
Kyriaki A. Tychola +2 more
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Machine learning for quantum physics and quantum physics for machine learning
, 2023 Research at the intersection of machine learning (ML) and quantum physics is a recent growing field due to the enormous expectations and the success of both fields. ML is arguably one of the most promising technologies that has and will continue to disrupt many aspects of our lives.
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