Fault-tolerant fermionic quantum computing

TL;DR

This paper introduces a new fault-tolerant quantum computing framework for fermions that significantly reduces circuit depth in simulating fermionic systems, enabling more efficient quantum simulations in chemistry and physics.

Contribution

The paper develops a fermionic fault-tolerant quantum computing framework with native fermionic operations, including a universal fermionic gate set and interfacing with qubit codes, reducing simulation overhead.

Findings

Exponential reduction in circuit depth for fermionic simulations from O(N) to O(log N)

Implementation of fermionic fault-tolerance in neutral atom platforms

Introduction of a fermion-inspired qubit algorithm with logarithmic depth

Abstract

Simulating the dynamics of electrons and other fermionic particles in quantum chemistry, materials science, and high-energy physics is one of the most promising applications of fault-tolerant quantum computers. However, the overhead in mapping time evolution under fermionic Hamiltonians to qubit gates renders this endeavor challenging. We introduce fermionic fault-tolerant quantum computing, a framework which removes this overhead altogether. Using native fermionic operations we first construct a repetition code which corrects phase errors only. Within a fermionic color code, which corrects for both phase and loss errors, we then realize a universal fermionic gate set, including transversal fermionic Clifford gates. Interfacing with qubit color codes we introduce qubit-fermion fault-tolerant computation, which allows for qubit-controlled fermionic time evolution, a crucial subroutine in state-of-the-art quantum algorithms. As an application, we consider simulating crystalline materials, finding an exponential improvement in circuit depth for a single time step from $\mathcal{O}(N)$ to $\mathcal{O}(\log(N))$ with respect to lattice site number $N$ while retaining a site count of $\tilde{\mathcal{O}}(N)$, implying a linear-in-$N$ end-to-end gate depth for simulating materials, as opposed to quadratic in previous approaches. We also introduce a fermion-inspired qubit algorithm with $O(\mathrm{log}(N)$ depth, but a prohibitive number of additional ancilla qubits. We show how our framework can be implemented in neutral atoms, overcoming the apparent inability of neutral atoms to implement non-number-conserving gates. Our work opens the door to fermion-qubit fault-tolerant quantum computation in platforms with native fermions such as neutral atoms, quantum dots and donors in silicon, with applications in quantum chemistry, material science, and high-energy physics.