classical spin
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Quantum ◽  
2022 ◽  
Vol 6 ◽  
pp. 618
Author(s):  
Davide Vodola ◽  
Manuel Rispler ◽  
Seyong Kim ◽  
Markus Müller

Mapping the decoding of quantum error correcting (QEC) codes to classical disordered statistical mechanics models allows one to determine critical error thresholds of QEC codes under phenomenological noise models. Here, we extend this mapping to admit realistic, multi-parameter noise models of faulty QEC circuits, derive the associated strongly correlated classical spin models, and illustrate this approach for a quantum repetition code with faulty stabilizer readout circuits. We use Monte-Carlo simulations to study the resulting phase diagram and benchmark our results against a minimum-weight perfect matching decoder. The presented method provides an avenue to assess fundamental thresholds of QEC circuits, independent of specific decoding strategies, and can thereby help guiding the development of near-term QEC hardware.


2021 ◽  
Vol 127 (15) ◽  
Author(s):  
E. Kermarrec ◽  
R. Kumar ◽  
G. Bernard ◽  
R. Hénaff ◽  
P. Mendels ◽  
...  

2021 ◽  
Vol 104 (10) ◽  
Author(s):  
Hao Zhang ◽  
Cristian D. Batista

Author(s):  
Serafim Teknowijoyo ◽  
Kyuil Cho ◽  
Erik I. Timmons ◽  
Makariy A. Tanatar ◽  
Jason W Krizan ◽  
...  

2021 ◽  
Vol 126 (10) ◽  
Author(s):  
Sofie Janas ◽  
Jakob Lass ◽  
Ana-Elena Ţuţueanu ◽  
Morten L. Haubro ◽  
Christof Niedermayer ◽  
...  

2021 ◽  
Vol 103 (5) ◽  
Author(s):  
Wang Yang ◽  
Alberto Nocera ◽  
Erik S. Sørensen ◽  
Hae-Young Kee ◽  
Ian Affleck

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 395
Author(s):  
Elizabeth Crosson ◽  
Aram W. Harrow

Path integral quantum Monte Carlo (PIMC) is a method for estimating thermal equilibrium properties of stoquastic quantum spin systems by sampling from a classical Gibbs distribution using Markov chain Monte Carlo. The PIMC method has been widely used to study the physics of materials and for simulated quantum annealing, but these successful applications are rarely accompanied by formal proofs that the Markov chains underlying PIMC rapidly converge to the desired equilibrium distribution. In this work we analyze the mixing time of PIMC for 1D stoquastic Hamiltonians, including disordered transverse Ising models (TIM) with long-range algebraically decaying interactions as well as disordered XY spin chains with nearest-neighbor interactions. By bounding the convergence time to the equilibrium distribution we rigorously justify the use of PIMC to approximate partition functions and expectations of observables for these models at inverse temperatures that scale at most logarithmically with the number of qubits. The mixing time analysis is based on the canonical paths method applied to the single-site Metropolis Markov chain for the Gibbs distribution of 2D classical spin models with couplings related to the interactions in the quantum Hamiltonian. Since the system has strongly nonisotropic couplings that grow with system size, it does not fall into the known cases where 2D classical spin models are known to mix rapidly.


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