# Scalable characterization of localizable entanglement in noisy topological quantum codes

## TL;DR

This paper introduces scalable methods to quantify localizable entanglement in noisy topological quantum codes, combining experimental and computational approaches to assess entanglement in large, noisy quantum systems.

## Contribution

It presents two novel prescriptions for characterizing entanglement in noisy stabilizer states, including scalable algorithms and open-source tools for practical implementation.

## Key findings

- Lower bounds of localizable entanglement vary with qubit distance.
- Methodology successfully applied to noisy topological color codes.
- Provides scalable geometric and algebraic techniques for stabilizer states.

## Abstract

Topological quantum error correcting codes have emerged as leading candidates towards the goal of achieving large-scale fault-tolerant quantum computers. However, quantifying entanglement in these systems of large size in the presence of noise is a challenging task. In this paper, we provide two different prescriptions to characterize noisy stabilizer states, including the surface and the color codes, in terms of localizable entanglement over a subset of qubits. In one approach, we exploit appropriately constructed entanglement witness operators to estimate a witness-based lower bound of localizable entanglement, which is directly accessible in experiments. In the other recipe, we use graph states that are local unitary equivalent to the stabilizer state to determine a computable measurement-based lower bound of localizable entanglement. If used experimentally, this translates to a lower bound of localizable entanglement obtained from single-qubit measurements in specific bases to be performed on the qubits outside the subsystem of interest. Towards computing these lower bounds, we discuss in detail the methodology of obtaining a local unitary equivalent graph state from a stabilizer state, which includes a new and scalable geometric recipe as well as an algebraic method that applies to general stabilizer states of arbitrary size. Moreover, as a crucial step of the latter recipe, we develop a scalable graph-transformation algorithm that creates a link between two specific nodes in a graph using a sequence of local complementation operations. We develop open-source Python packages for these transformations, and illustrate the methodology by applying it to a noisy topological color code, and study how the witness and measurement-based lower bounds of localizable entanglement varies with the distance between the chosen qubits.