LIMINAL fits nested Lindblad models to tomographic data and uses likelihood-ratio tests to identify minimal dynamics for a five-qubit superconducting processor, supporting three-local Hamiltonian terms and two-local dissipation but not three-local dissipation.
Akaike, A new look at the statistical model identifica- tion, IEEE Transactions on Automatic Control19, 716 (1974)
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Timescale coalescence in AR(1) hidden drivers creates a spectrally dark regime where persistent forcing is invisible to one-pole models, with the local spectral distance scaling as C lambda^4 due to manifold geometry.
A disorder-free spin ladder model exhibits a reversed quantum disentangled liquid at strong rung coupling, where light spins thermalize and heavy spins localize, establishing a microscopic origin for quasi-MBL.
citing papers explorer
-
Learning Lindblad Dynamics of a Superconducting Quantum Processor
LIMINAL fits nested Lindblad models to tomographic data and uses likelihood-ratio tests to identify minimal dynamics for a five-qubit superconducting processor, supporting three-local Hamiltonian terms and two-local dissipation but not three-local dissipation.
-
Timescale Coalescence Makes Hidden Persistent Forcing Spectrally Dark
Timescale coalescence in AR(1) hidden drivers creates a spectrally dark regime where persistent forcing is invisible to one-pole models, with the local spectral distance scaling as C lambda^4 due to manifold geometry.
-
Crossover from Quantum Chaos to a Reversed Quantum Disentangled Liquid in a Disorder-Free Spin Ladder
A disorder-free spin ladder model exhibits a reversed quantum disentangled liquid at strong rung coupling, where light spins thermalize and heavy spins localize, establishing a microscopic origin for quasi-MBL.