SSIP: automated surgery with quantum LDPC codes

TL;DR

This paper introduces SSIP, an open-source Python package that automates quantum code surgery, enabling efficient logical measurements on qLDPC codes with significantly reduced qubit overhead for fault-tolerant quantum computing.

Contribution

It presents SSIP, a novel tool for automating quantum code surgery using linear algebra over finite fields, applicable to non-topological qLDPC codes.

Findings

Enables logical measurements with minimal additional qubits

Reduces qubit overhead by two orders of magnitude compared to previous estimates

Demonstrates flexibility in performing both external and internal surgery

Abstract

We present Safe Surgery by Identifying Pushouts (SSIP), an open-source lightweight Python package for automating surgery between qubit CSS codes. SSIP is flexible: it is capable of performing both external surgery, that is surgery between two codeblocks, and internal surgery, that is surgery within the same codeblock. Under the hood, it performs linear algebra over $\mathbb{F}_2$ governed by universal constructions in the category of chain complexes. We demonstrate on quantum Low-Density Parity Check (qLDPC) codes, which are not topological codes in general, and are of interest for near-term fault-tolerant quantum computing. Such qLDPC codes include lift-connected surface codes, generalised bicycle codes and bivariate bicycle codes. We show that various logical measurements can be performed cheaply by surgery without sacrificing the high code distance. For example, half of the single-qubit logical measurements in the $Z$ or $X$ basis on the $[[ 144 ,12, 12 ]]$ gross code require only 30 total additional qubits each, assuming the upper bound on distance given by QDistRnd is tight. This is two orders of magnitude lower than the additional qubit count of 1380 initially predicted by Bravyi et al.