Variational Benchmarks for Quantum Many-Body Problems
- URL: http://arxiv.org/abs/2302.04919v1
- Date: Thu, 9 Feb 2023 20:21:17 GMT
- Title: Variational Benchmarks for Quantum Many-Body Problems
- Authors: Dian Wu, Riccardo Rossi, Filippo Vicentini, Nikita Astrakhantsev,
Federico Becca, Xiaodong Cao, Juan Carrasquilla, Francesco Ferrari, Antoine
Georges, Mohamed Hibat-Allah, Masatoshi Imada, Andreas M. L\"auchli,
Guglielmo Mazzola, Antonio Mezzacapo, Andrew Millis, Javier Robledo Moreno,
Titus Neupert, Yusuke Nomura, Jannes Nys, Olivier Parcollet, Rico Pohle,
Imelda Romero, Michael Schmid, J. Maxwell Silvester, Sandro Sorella, Luca F.
Tocchio, Lei Wang, Steven R. White, Alexander Wietek, Qi Yang, Yiqi Yang,
Shiwei Zhang, Giuseppe Carleo
- Abstract summary: We introduce a metric of variational accuracy, the V-score, obtained from the variational energy and its variance.
We provide the most extensive curated dataset of variational calculations of many-body quantum systems to date.
- Score: 38.905177925170506
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The continued development of novel many-body approaches to ground-state
problems in physics and chemistry calls for a consistent way to assess its
overall progress. Here we introduce a metric of variational accuracy, the
V-score, obtained from the variational energy and its variance. We provide the
most extensive curated dataset of variational calculations of many-body quantum
systems to date, identifying cases where state-of-the-art numerical approaches
show limited accuracy, and novel algorithms or computational platforms, such as
quantum computing, could provide improved accuracy. The V-score can be used as
a metric to assess the progress of quantum variational methods towards quantum
advantage for ground-state problems, especially in regimes where classical
verifiability is impossible.
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