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quant-ph2025
Unsupervised Machine Learning for Experimental Detection of Quantum-Many-Body Phase Transitions
Ron Ziv, David Wei, Antonio Rubio-Abadal +7
Quantum many-body (QMB) systems are generally computationally hard: the computing resources necessary to simulate them exactly can often exceed the existing computation resources b…
quant-ph2022
Propagation of errors and quantitative quantum simulation with quantum advantage
S. Flannigan, N. Pearson, G. H. Low +5
The rapid development in hardware for quantum computing and simulation has led to much interest in problems where these devices can exceed the capabilities of existing classical co…