Abstract

Simulation of quantum systems is expected to be one of the most important applications of quantum computing, with much of the theoretical work so far having focused on fermionic and spin-frac{1}{2} systems. Here, we instead consider encodings of d-level (i.e., qudit) quantum operators into multi-qubit operators, studying resource requirements for approximating operator exponentials by Trotterization. We primarily focus on spin-s and truncated bosonic operators in second quantization, observing desirable properties for approaches based on the Gray code, which to our knowledge has not been used in this context previously. After outlining a methodology for implementing an arbitrary encoding, we investigate the interplay between Hamming distances, sparsity patterns, bosonic truncation, and other properties of local operators. Finally, we obtain resource counts for five common Hamiltonian classes used in physics and chemistry, while modeling the possibility of converting between encodings within a Trotter step. The most efficient encoding choice is heavily dependent on the application and highly sensitive to d, although clear trends are present. These operation count reductions are relevant for running algorithms on near-term quantum hardware because the savings effectively decrease the required circuit depth. Results and procedures outlined in this work may be useful for simulating a broad class of Hamiltonians on qubit-based digital quantum computers.

Highlights

  • Simulating quantum physics will likely be one of the first practical applications of quantum computers

  • We use the term binary encoding to refer operations. This highlights the need for considering multiple encodings, as an encoding that is best for one type of hardware is not necessarily universally superior

  • The mappings may be used for Hamiltonians built from subsystems of bosons, spin-s particles, molecular electronic energy levels, molecular vibrational modes, or other dlevel subsystems

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Summary

Introduction

Simulating quantum physics will likely be one of the first practical applications of quantum computers. Degrees of freedom, e.g., spin-12 systems[1,2] The latter case is relevant for simulations or of fermionic chemical electronic structure[5,6], nuclear structure[7], and condensed matter physics[8] This focus on binary degrees of freedom seems to be a natural development, partly because qubit-based quantum computation is the most widespread model used in theory, experiment, and the nascent quantum industry. The purpose of this work is both to provide a complete yet flexible framework for the mappings, and to analyze several encodings (both newly proposed and previously proposed) for a widely used set of operations and Hamiltonians This aids in determining which mappings are more efficient for particular operators and specific hardware, including near-term intermediate-scale quantum (NISQ) devices

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