Efficient Qubit Simulation of Hybrid Oscillator-Qubit Quantum Computation

TL;DR

This paper presents an efficient qubit-based simulation framework for hybrid oscillator-qubit quantum processors, enabling Gaussian operations with exponentially reduced resources compared to traditional Fock basis methods.

Contribution

It introduces a position encoding method for simulating continuous-variable quantum operations on qubit systems with polylogarithmic complexity per gate, surpassing previous exponential resource approaches.

Findings

Efficient simulation of Gaussian operations with $O( ext{log}^2( ext{parameters}))$ qubit gates.

Exponential resource savings over Fock basis encoding.

Numerical characterization of quantum Fourier transform errors for resource estimation.

Abstract

We introduce a framework for simulating hybrid oscillator-qubit quantum processors on qubit-only systems through position encoding. By encoding continuous-variable position and momentum wave functions into qubit amplitudes, our method efficiently simulates all Gaussian and conditional Gaussian operations -- encompassing the phase-space instruction set (beam splitter, single-qubit rotation, conditional displacement) and extending to squeezing, conditional squeezing, conditional rotation, and conditional beam splitter -- using $O\!\left(\log^2\!\left(\Gamma + \log(1/\epsilon)\right)\right)$ qubit gates per hybrid gate, where $\Gamma$ is the Fock-level bound and $\epsilon$ is the target precision. This polylogarithmic per-gate complexity represents an exponential improvement over Fock basis encoding approaches, which require exponential quantum or classical resources in the number of qubits per mode. We provide rigorous numerical characterization of quantum Fourier transform errors for Fock-bounded states, enabling precise resource estimation for practical implementations. This work establishes that hybrid oscillator-qubit algorithms can be implemented on qubit processors with polynomial overhead, providing new insights into the computational power trade-offs between discrete-variable and hybrid continuous-discrete-variable quantum computing.