3 papers
physics.comp-ph2025
Towards Symmetry-Aware Efficient Simulation of Quantum Systems and Beyond
Min Chen, Minzhao Liu, Changhun Oh +3
The efficient simulation of complex quantum systems remains a central challenge due to the exponential growth of Hilbert space with system size. Tensor network methods have long be…
quant-ph2025
Stochastic noise can be helpful for variational quantum algorithms
Junyu Liu, Frederik Wilde, Antonio Anna Mele +3
Saddle points constitute a crucial challenge for first-order gradient descent algorithms. In notions of classical machine learning, they are avoided for example by means of stochas…
quant-ph2024
Tight bounds on Pauli channel learning without entanglement
Senrui Chen, Changhun Oh, Sisi Zhou +2
Quantum entanglement is a crucial resource for learning properties from nature, but a precise characterization of its advantage can be challenging. In this work, we consider learni…