Asymptotic Replacement for Quantum Channel Products with Applications to Inhomogeneous Matrix Product States
Lubashan Pathirana

TL;DR
This paper introduces a trace-Dobrushin theory for quantum channel products, establishing criteria for memory loss and convergence in inhomogeneous matrix product states with applications to quantum information.
Contribution
It develops a new product-level trace-Dobrushin framework for quantum channels and applies it to analyze inhomogeneous matrix product states, providing convergence and stability results.
Findings
Trace-Dobrushin coefficient decay characterizes trace-norm forgetting.
Negativity of the Lyapunov exponent is equivalent to quenched trace-norm memory loss.
Channel estimates lead to infinite-volume limits and correlation bounds in matrix product states.
Abstract
We develop a product-level trace-Dobrushin theory for finite-dimensional quantum channel products and apply it to deterministic and stationary random inhomogeneous matrix product states in left-canonical CPTP gauge. For a product of channels, the centered trace-Dobrushin coefficient quantifies the residual dependence on the input state, and its decay is the criterion for trace-norm forgetting. In the deterministic setting, this decay is equivalent to asymptotic replacement by a moving replacement channel. For two-sided products, pullback forgetting produces a unique boundary state, which determines the canonical replacement family. For stationary random CPTP cocycles, submultiplicativity of the product coefficient yields a trace-Dobrushin Lyapunov exponent. We prove that the almost sure negativity of this exponent is equivalent to quenched trace-norm memory loss and gives exponential…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
