In the thermodynamic limit the quantum and classical full-counting statistics of charge coincide exactly with no finite-time corrections, while the averaged von Neumann entanglement entropy admits a fully explicit expression obtained from the Jacobi-process dynamics of correlation-matrix eigenvalues
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 2
method 1
citation-polarity summary
verdicts
UNVERDICTED 4representative citing papers
Exact results show U(1) symmetry substantially suppresses non-stabilizerness in random states, with different leading scaling from entanglement near zero charge density.
A constructed random unitary circuit hosts one scar whose perturbations thermalize via fluctuating interfaces while the scar imprints a non-local transition in entanglement dynamics.
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.
citing papers explorer
-
Domain-wall melting in all-to-all QSSEP from random-matrix theory
In the thermodynamic limit the quantum and classical full-counting statistics of charge coincide exactly with no finite-time corrections, while the averaged von Neumann entanglement entropy admits a fully explicit expression obtained from the Jacobi-process dynamics of correlation-matrix eigenvalues
-
Non-stabilizerness and U(1) symmetry in chaotic many-body quantum systems
Exact results show U(1) symmetry substantially suppresses non-stabilizerness in random states, with different leading scaling from entanglement near zero charge density.
-
Quantum many-body scars in random unitary circuits
A constructed random unitary circuit hosts one scar whose perturbations thermalize via fluctuating interfaces while the scar imprints a non-local transition in entanglement dynamics.
-
Quantum Dynamics in Krylov Space: Methods and Applications
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.