Practical Limits of Error Correction for Quantum Metrology

Abstract

Noise is the greatest obstacle in quantum metrology that limits it achievable precision and sensitivity. There are many techniques to mitigate the effect of noise, but this can never be done completely. One commonly proposed technique is to repeatedly apply quantum error correction. Unfortunately, the required repetition frequency needed to recover the Heisenberg limit is unachievable with the existing quantum technologies. In this article we explore the discrete application of quantum error correction with current technological limitations in mind. We establish that quantum error correction can be beneficial and highlight the factors which need to be improved so one can reliably reach the Heisenberg limit level precision.

Distributing Multipartite Entanglement over Noisy Quantum Networks

“…Furthermore one could apply this same methodology to different distribution schemes [40], introducing entanglement purification rounds in the bipartite distribution scheme [25] or even different quantum repeater protocols [41], opening the way to optimally generate multipartite entanglement over noisy quantum networks. This is important to understand how the quantum internet must evolve so distributed quantum technologies, namely distributed quantum sensing becomes capable of going beyond the classical bounds of precision and realising the quantum advantage that can be attained using multipartite entanglement [42,43].…”

Advantages and Bottlenecks of Quantum Machine Learning for Remote Sensing

“…However, quantum computation is still in a fairly developmental stage. Currently, there exists limited error correction for quantum computers, like those provided by IBMs quantum experience [8]. As such, there is a restriction to the number of operations that can be performed before the information stored in the quantum computer become useless.…”

On Circuit-based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification

“…Today, there are exists a number of differing quantum devices, such as programmable superconducting processors [8], quantum annealers [9], and photonic quantum computers [10]. However, QC still presents some technological limitations, as reported in [11] with a special concern with noise and limited error correction. Specific algorithms, namely the Noisy Intermediate-Scale Quantum Computing (NISQ) algorithms, have been designed to tackle these issues [12].…”