Quantum minimal surfaces from quantum error. I will describe various scenarios in which tensor-network based decoders can achieve substantially improved logical error rates over other decoders. Kadanoff Seminar: Quantum minimal surfaces from quantum error correction - Geoff Pennington, IAS/Berkley.
#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. Decoding of topological quantum codes, 2022 Spring Workshop on. One is for simulation: to understand how the surface code performs under different types of realistic noise. Quantum error-correcting codes and fault-tolerant quantum computation, 2020 Summer. I will describe two ways in which tensor networks may be applied to surface-code error correction. This past year, we’ve seen implementations of distance 2 3 and distance 3 4 codes at IBM, an implementation of a distance 3 code 5 from researchers at ETH-Zurich, and even the implementation of a distance 5 code 6 from researchers at Google. I will focus on surface-code error correction, which, due to its simplicity, may be implementable in near-term devices. Encoding into the 3-qubits repetition code (left) leads to a logical heavy square lattice (right). 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. Special theory group seminar, Herbert-Walther Lecture Hall G0.25Ī universal quantum computer will require error correction to protect logical qubits from noise. The Mathematical Sciences Research Institute (MSRI), founded in 1982, is an independent nonprofit mathematical research institution whose funding sources include the National Science Foundation, foundations, corporations, and more than 90 universities and institutions.
0 kommentar(er)
