A Resource Allocating Compiler for Lattice Surgery

TL;DR

This paper introduces a compiler that transforms quantum circuits into lattice surgery operations, optimizing resource estimation for large-scale fault-tolerant quantum computing.

Contribution

It presents a novel compiler that automates the translation of quantum circuits into lattice surgery, managing resources and enabling scalable quantum circuit compilation.

Findings

Compiler manages memory as surface code patches

Estimates space-time volume and cycle counts

Supports recursive reuse of lattice surgery objects

Abstract

The emerging field of quantum resource estimation is aimed at providing estimates of the hardware requirements (`quantum resources') needed to execute a useful, fault-tolerant quantum computation. Given that quantum computers are intended to compete with supercomputers, useful quantum computations are likely to involve the use of millions of qubits and error correction clock cycles. The compilation and benchmarking of these circuits depends on placement and routing algorithms, which are infeasible to construct at scale by hand. We offer a compiler that transforms a quantum circuit into a sequence of lattice surgery operations. The compiler manages memory in terms of surface code patches and costs the space-time volume and cycle counts of the input circuits. These compiled lattice surgery objects are then recursively repurposed as gates for larger scale compilations. Our code is available on GitHub under a permissive software license and we welcome community contributions.