Algorithms for quantum simulation at finite energies
Sirui Lu, Mari Carmen Ba\~nuls, J. Ignacio Cirac

TL;DR
This paper presents two quantum algorithms for efficiently exploring energy-specific properties of many-body systems, enabling calculations of microcanonical and canonical ensemble averages without long quantum evolutions.
Contribution
The paper introduces novel hybrid quantum algorithms that perform energy filtering and Monte Carlo sampling, overcoming classical limitations like the sign problem.
Findings
Polynomial scaling of computational time with qubits and inverse error
Efficient expectation value computation without long quantum evolutions
Circumvention of the sign problem in quantum Monte Carlo simulations
Abstract
We introduce two kinds of quantum algorithms to explore microcanonical and canonical properties of many-body systems. The first one is a hybrid quantum algorithm that, given an efficiently preparable state, computes expectation values in a finite energy interval around its mean energy. This algorithm is based on a filtering operator, similar to quantum phase estimation, which projects out energies outside the desired energy interval. However, instead of performing this operation on a physical state, it recovers the physical values by performing interferometric measurements without the need to prepare the filtered state. We show that the computational time scales polynomially with the number of qubits, the inverse of the prescribed variance, and the inverse error. In practice, the algorithm does not require the evolution for long times, but instead a significant number of measurements in…
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