Quantum Markov semigroups on d-dimensional systems have infinite-time capacities determined by peripheral space structure, with convergence after time t ≳ d² ln(d), and explicit bounds showing n-qubit memories fail after t ≳ n 2^{2n} (global correction) or t ≳ ln(n) (local).
Decomposition of Quantum Markov Chains and Its Applications
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Markov chains have been widely employed as a fundamental model in the studies of probabilistic and stochastic communicating and concurrent systems. It is well-understood that decomposition techniques play a key role in reachability analysis and model-checking of Markov chains. (Discrete-time) quantum Markov chains have been introduced as a model of quantum communicating systems [1] and also a semantic model of quantum programs [2]. The BSCC (Bottom Strongly Connected Component) and stationary coherence decompositions of quantum Markov chains were introduced in [3, 4, 5]. This paper presents a new decomposition technique, namely periodic decomposition, for quantum Markov chains. We further establish a limit theorem for them. As an application, an algorithm to find a maximum dimensional noiseless subsystem of a quantum communicating system is given using decomposition techniques of quantum Markov chains.
fields
quant-ph 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Information storage and transmission under Markovian noise
Quantum Markov semigroups on d-dimensional systems have infinite-time capacities determined by peripheral space structure, with convergence after time t ≳ d² ln(d), and explicit bounds showing n-qubit memories fail after t ≳ n 2^{2n} (global correction) or t ≳ ln(n) (local).