Exponentially more precise quantum simulation of fermions I: Quantum chemistry in second quantization

TL;DR

This paper introduces two novel quantum algorithms for simulating molecular systems with exponential improvements in precision and efficiency over previous methods, utilizing a truncated Taylor series approach in second quantization.

Contribution

The paper presents the first application of truncated Taylor series for Hamiltonian simulation in quantum chemistry, achieving logarithmic scaling with precision and lower gate counts than prior methods.

Findings

First algorithm requires O(N^8 t) gates.

Second algorithm achieves O(N^5 t) gates with exponential precision.

Algorithms are applicable to a broad class of fermionic models.

Abstract

We introduce novel algorithms for the quantum simulation of molecular systems which are asymptotically more efficient than those based on the Trotter-Suzuki decomposition. We present the first application of a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision, an exponential improvement over all prior methods. The two algorithms developed in this work rely on a second quantized encoding of the wavefunction in which the state of an $N$ spin-orbital system is encoded in ${\cal O}(N)$ qubits. Our first algorithm requires at most $\widetilde{\cal O}(N^8 t)$ gates. Our second algorithm involves on-the-fly computation of molecular integrals, in a way that is exponentially more precise than classical sampling methods, by using the truncated Taylor series simulation technique. Our second algorithm has the lowest gate count of any approach to second quantized quantum chemistry simulation in the literature, scaling as $\widetilde{\cal O}(N^{5} t)$. The approaches presented here are readily applicable to a wide class of fermionic models, many of which are defined by simplified versions of the chemistry Hamiltonian.