Above a critical noise strength, operator scrambling in random circuits is suppressed leading to classical simulability; below it, simulation stays exponentially hard.
Noise-induced contraction of MPO truncation errors in noisy random circuits and Lindbladian dynamics
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
quant-ph 2years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
A differentiable tensor-network framework learns CPTP noise channels from single-circuit measurement data on IBM hardware and generalizes the model to unrelated circuits.
citing papers explorer
-
Noise-induced Simulability Transition from Operator Scrambling
Above a critical noise strength, operator scrambling in random circuits is suppressed leading to classical simulability; below it, simulation stays exponentially hard.
-
Quantum hardware noise learning via differentiable Kraus representation on tensor networks
A differentiable tensor-network framework learns CPTP noise channels from single-circuit measurement data on IBM hardware and generalizes the model to unrelated circuits.