Quantum Simulation

13,420 papers

Quantum Simulation Research Context

This category collects papers on quantum simulation methods for chemistry, materials, many-body systems, condensed matter, and physics models.

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All sources 13420 arXiv preprints 11138 Crossref 853 OpenAlex 66 Europe PMC 342 PubMed 800 DOAJ 221
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Showing 9073-9084 of 13,420

Photoprotecting uracil by coupling with lossy nanocavities

Simone Felicetti, Jacopo Fregoni, Thomas Schnappinger, Sebastian Reiter, Regina de Vivie-Riedle, Johannes Feist

2020 arXiv arXiv preprint

Picking Efficient Portfolios from 3,171 US Common Stocks with New Quantum and Classical Solvers

Jeffrey Cohen, Clark Alexander

2020 arXiv arXiv preprint

Pinning of Andreev bound states to zero energy in two-dimensional superconductor- semiconductor Rashba heterostructures

Olesia Dmytruk, Daniel Loss, Jelena Klinovaja

2020 Crossref Physical Review B

Poincaré crystal on the one-dimensional lattice

Pei Wang

2020 arXiv arXiv preprint

Polaritonic Chemistry: Collective Strong Coupling Implies Strong Local Modification of Chemical Properties

Dominik Sidler, Christian Schäfer, Michael Ruggenthaler, Angel Rubio

2020 arXiv arXiv preprint

Polyadic Quantum Classifier

William Cappelletti, Rebecca Erbanni, Joaquín Keller

2020 arXiv arXiv preprint

Polynomial algebras from $su(3)$ and the generic model on the two sphere

Francisco Correa, Mariano A. del Olmo, Ian Marquette, Javier Negro

2020 arXiv arXiv preprint

Positive-energy spectra of atomic hydrogen in a magnetic field with an adiabatic-basis-expansion method

L. B. Zhao, K. D. Wang, K. Bartschat

2020 arXiv arXiv preprint

Possibility of coherent electron transport in a nanoscale circuit

Mark J. Hagmann

2020 arXiv arXiv preprint

Postselection-free entanglement dynamics via spacetime duality

Matteo Ippoliti, Vedika Khemani

2020 arXiv arXiv preprint

Power spectrum and form factor in random diagonal matrices and integrable billiards

Roman Riser, Eugene Kanzieper

2020 arXiv arXiv preprint

Predicting toxicity by quantum machine learning

Teppei Suzuki, Michio Katouda

2020 arXiv arXiv preprint
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