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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-ph2025
Sparsity-Driven Entanglement Detection in High-Dimensional Quantum States
Stav Lotan, Hugo Defienne, Ronen Talmon +1
The characterization of high-dimensional quantum entanglement is crucial for advanced quantum computing and quantum information algorithms. Traditional methods require extensive da…