Jacob Biamonte
3 papers in the PaperMetrix corpus
Papers by this author
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Machine learning phase transitions with a quantum processor
2020 · Physical Review A
Machine learning has emerged as a promising approach to unveil properties of many-body systems. Recently proposed as a tool to classify phases of matter, the approach relies on classical simulation methods---such as Monte Carlo---which are …
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Self-learning eigenstates with a quantum processor.
2020 · arXiv (Cornell University)
Solutions to many-body problem instances often involve an intractable number of degrees of freedom and admit no known approximations in general form. In practice, representing quantum-mechanical states of a given Hamiltonian using available numerical methods, …
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On the mathematical structure of quantum models of computation based on Hamiltonian minimisation
2020 · arXiv (Cornell University)
Determining properties of ground states of spin Hamiltonians remains a topic of central relevance connecting disciplines of mathematical, theoretical and applied physics. In the last few decades, ground state properties of physical systems have been …