2025/05/14 by Ramkumar, Akshar, Cai, Yiyi, Tong, Yu +1 · 3 citations
#Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Physical sciences #Quantum Physics (quant-ph)
paper · doi:10.48550/arxiv.2505.09730
Efficient simulation of a quantum system generally relies on structural properties of the quantum state. Motivated by the recent results by Bakshi et al. on the sudden death of entanglement in high-temperature Gibbs states of quantum spin systems, we study the high-temperature Gibbs states of bounded-degree local fermionic Hamiltonians, which include the special case of geometrically local fermionic systems. We prove that at a sufficiently high temperature that is independent of the system size, the Gibbs state is a probabilistic mixture of fermionic Gaussian states. This forms the basis of an efficient classical algorithm to prepare the Gibbs state by sampling from a distribution of fermionic Gaussian states.