Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Markov Chains and Hitting Times for Error Accumulation in Quantum Circuits

Long Ma, Jaron Sanders

Published Jan 1, 2021• 1 citation
Publisher
DOI
10.1007/978-3-030-92511-6_3

Related papers

A Quantum Algorithm for Estimating Hitting Times of Markov Chains

Anirban Narayan Chowdhury, Rolando D. Somma

Bulletin of the American Physical Society•Mar 15, 2016•0 citations

Mean hitting times of quantum Markov chains in terms of generalized inverses

Carlos F. Lardizabal

arXiv:1907.01313•Quantum Information Processing•Jul 8, 2019•4 citations

Stopping times for quantum Markov chains

Luigi Accardi, Dmitri Koroliouk

Journal of Theoretical Probability•Jul 1, 1992•17 citations

Markov chains for error accumulation in quantum circuits

Long Ma, Jaron Sanders

We study a model for the accumulation of errors in multi-qubit quantum computations, as well as a model describing continuous errors accumulating in a single qubit. By modeling the error process in a quantum computation using two coupled Markov chains, we are able to capture a weak form of time-dependency between errors in the past and future. By subsequently using techniques from the field of discrete probability theory, we calculate the probability that error measures such as the fidelity and trace distance exceed a threshold analytically. The formulae cover fairly generic error distributions, cover multi-qubit scenarios, and are applicable to e.g. the randomized benchmarking protocol. To combat the numerical challenge that may occur when evaluating our expressions, we additionally provide an analytical bound on the error probabilities that is of lower numerical complexity, and we also discuss a state space reduction that occurs for stabilizer circuits. Finally, taking inspiration from the field of operations research, we illustrate how our expressions can be used to e.g. decide how many gates one can apply before too many errors accumulate with high probability, and how one can lower the rate of error accumulation in existing circuits through simulated annealing.

arXiv:1909.04432•Sep 10, 2019•0 citations

Decoherence in Quantum Markov Chains

Raqueline A. M. Santos, Renato Portugal, Marcelo Dutra Fragoso

It is known that under some assumptions the hitting time in quantum Markov chains is quadratically smaller than the hitting time in classical Markov chains. This work extends this result for decoherent quantum Markov chains. The decoherence is introduced using a percolation-like graph model, which allows us to define a decoherent quantum hitting time and to establish a decoherent-intensity range for which the decoherent quantum hitting time is quadratically smaller than the the classical hitting time. The detection problem under decoherence is also solved with quadratic speedup in this range.

arXiv:1204.6238•Apr 27, 2012•0 citations

QUANTUM MARKOV CHAINS : THE RECURRENCE PROBLEM

Luigi Accardi, Dmitri Koroliouk

QP-PQ, quantum probability and white noise analysis•Oct 1, 1991•17 citations
We study a model for the accumulation of errors in multi-qubit quantum computations, as well as a model describing continuous errors accumulating in a single qubit. By modeling the error process in a quantum computation using two coupled Markov chains, we are able to capture a weak form of time-dependency between errors in the past and future. By subsequently using techniques from the field of discrete probability theory, we calculate the probability that error measures such as the fidelity and trace distance exceed a threshold analytically. The formulae cover fairly generic error distributions, cover multi-qubit scenarios, and are applicable to e.g. the randomized benchmarking protocol. To combat the numerical challenge that may occur when evaluating our expressions, we additionally provide an analytical bound on the error probabilities that is of lower numerical complexity, and we also discuss a state space reduction that occurs for stabilizer circuits. Finally, taking inspiration from the field of operations research, we illustrate how our expressions can be used to e.g. decide how many gates one can apply before too many errors accumulate with high probability, and how one can lower the rate of error accumulation in existing circuits through simulated annealing.
It is known that under some assumptions the hitting time in quantum Markov chains is quadratically smaller than the hitting time in classical Markov chains. This work extends this result for decoherent quantum Markov chains. The decoherence is introduced using a percolation-like graph model, which allows us to define a decoherent quantum hitting time and to establish a decoherent-intensity range for which the decoherent quantum hitting time is quadratically smaller than the the classical hitting time. The detection problem under decoherence is also solved with quadratic speedup in this range.