I will describe various scenarios in which tensor-network based decoders can achieve substantially improved logical error rates over other decoders.
#Quantum error correction seminar how to
Another is as part of the classical control software of the error-correcting code, namely the decoder, which determines how to correct errors based on information provided by measurements. One is for simulation: to understand how the surface code performs under different types of realistic noise. He has co-developed Quantum Homodyne Tomographic Code for. Prior to that he had worked in Quantum Optics research group in Australian Defence Force Academy as Post graduate researcher. I will describe two ways in which tensor networks may be applied to surface-code error correction. He was previously Research Assistant at Centre for Quantum Technologies, National University of Singapore, where he worked in the Quantum Satellite project. I will focus on surface-code error correction, which, due to its simplicity, may be implementable in near-term devices. I will discuss how some of these challenge may be met using tensor-network methods. However, practical implementation of quantum error correcting codes remains a challenge due to the large amount of physical resources (qubits, operations) required. Quantum minimal surfaces from quantum error. Many new codes and new bounds are presented, as well as a table of upper and lower bounds on such codes of length up to 30 qubits. Kadanoff Seminar: Quantum minimal surfaces from quantum error correction - Geoff Pennington, IAS/Berkley. Special theory group seminar, Herbert-Walther Lecture Hall G0.25Ī universal quantum computer will require error correction to protect logical qubits from noise. In the present paper the problem of finding quantum-error-correcting codes is transformed into one of finding additive codes over the field GF (4) which are self-orthogonal with respect to a certain trace inner product.
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