Performance of topological quantum error correction in the presence of correlated noise

2018 ◽  
Vol 18 (9&10) ◽  
pp. 743-778
Author(s):  
Muhammad Ahsan ◽  
Syed Abbas Zilqurnain Naqvi

We investigate the efficacy of topological quantum error-correction in correlated noise model which permits collective coupling of all the codeword qubits to the same non-Markovian environment. In this noise model, the probability distribution over set of phase-flipped qubits, decays sub-exponentially in the size of the set and carries non-trivial likelihood of the occurring large numbers of qubits errors. We find that in the presence of noise correlation, one cannot guarantee arbitrary high computational accuracy simply by incrementing the codeword size while retaining constant noise level per qubit operation. However, if instead, per-operation qubit error probability in an n-qubits long codeword is reduced O(\sqrt{n}) times below the accuracy threshold, arbitrarily accurate quantum computation becomes feasible with acceptable scaling of the codeword size. Our results suggest that progressively reducing noise level in qubits and gates is as important as continuously integrating more qubits to realize scalable and reliable quantum computer.

2016 ◽  
Vol 14 (07) ◽  
pp. 1650040
Author(s):  
Toshiyuki Fujii ◽  
Shigemasa Matsuo ◽  
Noriyuki Hatakenaka

We propose a fluxon-controlled quantum computer incorporated with three-qubit quantum error correction using special gate operations, i.e. joint-phase and SWAP gate operations, inherent in capacitively coupled superconducting flux qubits. The proposed quantum computer acts exactly like a knitting machine at home.


2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Savvas Varsamopoulos ◽  
Koen Bertels ◽  
Carmen G. Almudever

Abstract There has been a rise in decoding quantum error correction codes with neural network–based decoders, due to the good decoding performance achieved and adaptability to any noise model. However, the main challenge is scalability to larger code distances due to an exponential increase of the error syndrome space. Note that successfully decoding the surface code under realistic noise assumptions will limit the size of the code to less than 100 qubits with current neural network–based decoders. Such a problem can be tackled by a distributed way of decoding, similar to the renormalization group (RG) decoders. In this paper, we introduce a decoding algorithm that combines the concept of RG decoding and neural network–based decoders. We tested the decoding performance under depolarizing noise with noiseless error syndrome measurements for the rotated surface code and compared against the blossom algorithm and a neural network–based decoder. We show that a similar level of decoding performance can be achieved between all tested decoders while providing a solution to the scalability issues of neural network–based decoders.


2005 ◽  
Vol 03 (01) ◽  
pp. 207-211
Author(s):  
GABRIELE DE CHIARA ◽  
ROSARIO FAZIO ◽  
CHIARA MACCHIAVELLO ◽  
G. MASSIMO PALMA

The effects of quantum error correction (QEC) on the dynamics of entanglement between logical qubits in the presence of a dephasing interaction with a correlated environment is investigated. Such a correlated reservoir introduces entanglement between physical qubits which, for short times, is interpreted as error and suppressed by the QEC routine. However for longer times, although QEC is no longer able to correct errors, it enhances the rate of entanglement production due to the interaction with the environment.


2011 ◽  
Vol 375 (37) ◽  
pp. 3255-3258 ◽  
Author(s):  
Chi-Kwong Li ◽  
Mikio Nakahara ◽  
Yiu-Tung Poon ◽  
Nung-Sing Sze ◽  
Hiroyuki Tomita

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 398
Author(s):  
Julio Carlos Magdalena de la Fuente ◽  
Nicolas Tarantino ◽  
Jens Eisert

It has long been known that long-ranged entangled topological phases can be exploited to protect quantum information against unwanted local errors. Indeed, conditions for intrinsic topological order are reminiscent of criteria for faithful quantum error correction. At the same time, the promise of using general topological orders for practical error correction remains largely unfulfilled to date. In this work, we significantly contribute to establishing such a connection by showing that Abelian twisted quantum double models can be used for quantum error correction. By exploiting the group cohomological data sitting at the heart of these lattice models, we transmute the terms of these Hamiltonians into full-rank, pairwise commuting operators, defining commuting stabilizers. The resulting codes are defined by non-Pauli commuting stabilizers, with local systems that can either be qubits or higher dimensional quantum systems. Thus, this work establishes a new connection between condensed matter physics and quantum information theory, and constructs tools to systematically devise new topological quantum error correcting codes beyond toric or surface code models.


2004 ◽  
Vol 69 (6) ◽  
Author(s):  
James P. Clemens ◽  
Shabnam Siddiqui ◽  
Julio Gea-Banacloche

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