TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.19.6.149
TI  - Learning the non-Markovian features of subsystem dynamics
PY  - 2025/12/08
UR  - https://scipost.org/SciPostPhys.19.6.149
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 19
IS  - 6
SP  - 149
A1  - Coppola, Michele
AU  - Bañuls, Mari Carmen
AU  - Lenarčič, Zala
AB  - The dynamics of local observables in a quantum many-body system can be formally described in the language of open systems. The problem is that the bath representing the complement of the local subsystem generally does not allow the common simplifications often crucial for such a framework. Leveraging tensor network calculations and optimization tools from machine learning, we extract and characterize the dynamical maps for single- and two-site subsystems embedded in an infinite quantum Ising chain after a global quench. We consider three paradigmatic regimes: integrable critical, integrable non-critical, and chaotic. For each we find the optimal time-local representation of the subsystem dynamics at different times. We explore the properties of the learned time-dependent Liouvillians and whether they can be used to forecast the long-time dynamics of local observables beyond the times accessible through direct quantum many-body numerical simulation. Our procedure naturally suggests a novel measure of non-Markovianity based on the distance between the quasi-exact dynamical map and the closest CP-divisible form and reveals that criticality leads to the closest Markovian representation at large times.
ER  -

@Article{10.21468/SciPostPhys.19.6.149,
	title={{Learning the non-Markovian features of subsystem dynamics}},
	author={Michele Coppola and Mari Carmen Bañuls and Zala Lenarčič},
	journal={SciPost Phys.},
	volume={19},
	pages={149},
	year={2025},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.19.6.149},
	url={https://scipost.org/10.21468/SciPostPhys.19.6.149},
}