Evaluating thermal expectation values by almost ideal sampling with Trotter gates

Abstract

We investigate the sampling efficiency for the simulations of quantum many-body systems at finite temperatures when initial sampling states are generated by applying Trotter gates to random phase product states (RPPSs). We restrict the number of applications of Trotter gates to be proportional to the system size, and thus the preparation would be easily accomplished in fault-tolerant quantum computers. When the Trotter gates are made from a nonintegrable Hamiltonian, we observe that the sampling efficiency increases with system size. This trend means that almost ideal sampling of initial states can be achieved in sufficiently large systems. We also find that the sampling efficiency is almost equal to that obtained by a typical pure quantum (TPQ) state method utilizing Haar random sampling in some cases. These findings suggest that chaotic Hamiltonian dynamics can transform RPPSs into an alternative to TPQ states for evaluating thermal expectation values.

7 pages, 9 figures, accepted version

References in corpus (5)

• Strong and weak thermalization of infinite non-integrable quantum systems
• Minimally Entangled Typical Thermal State Algorithms
• Random phase vector for calculating the trace of a large matrix
• Predicting Gibbs-State Expectation Values with Pure Thermal Shadows
• Energy-filtered random-phase states as microcanonical thermal pure quantum states

Cited by in corpus (3)

• Calculating the many-body density of states on a digital quantum computer
• Simulating Floquet scrambling circuits on trapped-ion quantum computers
• Sample complexity of matrix product states at finite temperature