Sachdev-Ye-Kitaev model: Non-self-averaging properties of the energy
spectrum
- URL: http://arxiv.org/abs/2208.11008v1
- Date: Tue, 23 Aug 2022 14:42:44 GMT
- Title: Sachdev-Ye-Kitaev model: Non-self-averaging properties of the energy
spectrum
- Abstract summary: The short time (large energy) behavior of the Sachdev-Ye-Kitaev model (SYK) is one of the main motivation to the growing interest garnered by this model.
True chaotic behaviour sets in at the Thouless time, which can be extracted from the energy spectrum.
It is shown that the SYK model in non-self-averaging even in the thermodynamic limit which must be taken into account.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The short time (large energy) behavior of the Sachdev-Ye-Kitaev model (SYK)
is one of the main motivation to the growing interest garnered by this model.
True chaotic behaviour sets in at the Thouless time, which can be extracted
from the energy spectrum. In order to do so, it is necessary to unfold the
spectrum, i.e., to filter out global tendencies. Using a simple ensemble
average for unfolding results in a parametically low estimation of the Thouless
energy. By examining the behavior of the spectrum as the distribution of the
matrix elements is changed into a log-normal distribution it is shown that the
sample to sample level spacing variance determines this estimation of the
Thouless energy. Using the singular value decomposition method, SVD, which
filters out these sample to sample fluctuations, the Thouless energy becomes
parametrically much larger, essentially of order of the band width. It is shown
that the SYK model in non-self-averaging even in the thermodynamic limit which
must be taken into account in considering its short time properties.
Related papers
- FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions [0.11122493020689471]
Free energy Offering Generative Sampler (FrOGS) is a hybrid discrete neural sampler that couples an autoregressive model to a continuous-time Markov chain.<n>We train a single model across a wide range of chemical conditions to produce estimates on a common absolute free-energy scale.
arXiv Detail & Related papers (2026-09-01T21:38:36Z) - Hierarchical Exponential-Gaussian Mixtures for Watch-Time Distribution Prediction [74.05279072166697]
Exponential-Gaussian Mixture Network (EGMN) models the full conditional WT distribution.<n>EGMN is vulnerable to variance collapse, component redundancy, and inactive components.<n>We propose a Hierarchical Exponential-Gaussian Mixture (HEGM) model that addresses these failure modes.
arXiv Detail & Related papers (2026-08-24T15:06:18Z) - Probing Chaos and Criticality with Observational Entropy and Finite-Resolution Measurements [0.0]
observational entropy (OE) provides a framework for quantifying chaos and probing criticality.<n>Our results establish OE as a compact information-theoretic bridge between classical instability, quantum criticality, and realistic finite-resolution measurements.
arXiv Detail & Related papers (2026-05-22T12:57:03Z) - SYK thermal expectations are classically easy at any temperature [49.788604174558564]
We give a simple classical algorithm that approximates thermal expectations.<n>We show it has quasi-polynomial cost $nO(log n/)$ for all temperatures above a phase transition in the free energy.
arXiv Detail & Related papers (2026-02-26T04:48:32Z) - Principle of Minimal Heating for Collapse and Hybrid Gravitational Models [0.0]
Energy nonconservation is a prominent, testable prediction of collapse and hybrid classical-quantum gravitational models.<n>We resolve this arbitrariness by a simple principle: for a fixed $r_C$, select the distribution that minimizes the heating rate.<n>We apply this approach to the most investigated collapse models: GRW, CSL, and DP.
arXiv Detail & Related papers (2025-11-01T17:47:28Z) - Eigenstate Thermalization Hypothesis correlations via non-linear Hydrodynamics [0.0]
We provide a prediction for the late-time behavior of time-ordered free cumulants in the thermodynamic limit.<n>Good agreement is observed in both infinite and finite-temperature regimes.
arXiv Detail & Related papers (2025-05-11T06:35:16Z) - Scalable Equilibrium Sampling with Sequential Boltzmann Generators [60.00515282300297]
We extend the Boltzmann generator framework and introduce Sequential Boltzmann generators with two key improvements.
The first is a highly efficient non-equivariant Transformer-based normalizing flow operating directly on all-atom Cartesian coordinates.
We demonstrate the first equilibrium sampling in Cartesian coordinates of tri, tetra, and hexapeptides that were so far intractable for prior Boltzmann generators.
arXiv Detail & Related papers (2025-02-25T18:59:13Z) - Unusual energy spectra of matrix product states [0.0]
We consider the energy spectra of approximate matrix product state ground states.
We find that contributions to the spectra are roughly constant out to surprisingly high energy.
The unusual spectra, which appear to be a general feature of compressed wavefunctions, have a strong effect on sampling-based methods.
arXiv Detail & Related papers (2024-08-24T16:08:21Z) - Quantum thermodynamics of the Caldeira-Leggett model with non-equilibrium Gaussian reservoirs [0.0]
We introduce a non-equilibrium version of the Caldeira-Leggett model in which a quantum particle is strongly coupled to a set of engineered reservoirs.
Strongly displaced/squeezed reservoirs can be used to generate an effective time dependence in the system Hamiltonian.
We show the quantum-classical correspondence between the heat statistics in the non-equilibrium Caldeira-Leggett model and the statistics of a classical Langevin particle under the action of squeezed and displaced colored noises.
arXiv Detail & Related papers (2024-04-30T21:41:34Z) - Iterated Denoising Energy Matching for Sampling from Boltzmann Densities [109.23137009609519]
Iterated Denoising Energy Matching (iDEM)
iDEM alternates between (I) sampling regions of high model density from a diffusion-based sampler and (II) using these samples in our matching objective.
We show that the proposed approach achieves state-of-the-art performance on all metrics and trains $2-5times$ faster.
arXiv Detail & Related papers (2024-02-09T01:11:23Z) - Randomly Pruning the Sachdev-Ye-Kitaev model [0.0]
The Sachdev-Ye-Kitaev model (SYK) is renowned for its short-time chaotic behavior.
The Thouless energy, representing the energy scale at which the universal chaotic behavior in the energy spectrum ceases, can be determined from the spectrum itself.
arXiv Detail & Related papers (2024-01-14T16:20:16Z) - Adaptive Annealed Importance Sampling with Constant Rate Progress [68.8204255655161]
Annealed Importance Sampling (AIS) synthesizes weighted samples from an intractable distribution.
We propose the Constant Rate AIS algorithm and its efficient implementation for $alpha$-divergences.
arXiv Detail & Related papers (2023-06-27T08:15:28Z) - The open Haldane-Shastry chain: thermodynamics and criticality [0.0]
We study the thermodynamics and criticality of the su($m|n$) Haldane-Shastry chain of $BC_N$ type.
We identify the critical intervals in chemical potential space and compute their corresponding Fermi velocities.
arXiv Detail & Related papers (2022-06-06T14:41:06Z) - An Energy-Based Prior for Generative Saliency [62.79775297611203]
We propose a novel generative saliency prediction framework that adopts an informative energy-based model as a prior distribution.
With the generative saliency model, we can obtain a pixel-wise uncertainty map from an image, indicating model confidence in the saliency prediction.
Experimental results show that our generative saliency model with an energy-based prior can achieve not only accurate saliency predictions but also reliable uncertainty maps consistent with human perception.
arXiv Detail & Related papers (2022-04-19T10:51:00Z) - Sub-diffusive Thouless time scaling in the Anderson model on random
regular graphs [0.0]
We study the scaling of the Thouless time in the Anderson model on random regular graphs with on-site disorder.
We find that the scaling of the Thouless time is consistent with the existence of a sub-diffusive regime anticipating the localized phase.
arXiv Detail & Related papers (2022-01-12T19:56:56Z) - Particle Dynamics for Learning EBMs [83.59335980576637]
Energy-based modeling is a promising approach to unsupervised learning, which yields many downstream applications from a single model.
The main difficulty in learning energy-based models with the "contrastive approaches" is the generation of samples from the current energy function at each iteration.
This paper proposes an alternative approach to getting these samples and avoiding crude MCMC sampling from the current model.
arXiv Detail & Related papers (2021-11-26T23:41:07Z) - Deterministic Gibbs Sampling via Ordinary Differential Equations [77.42706423573573]
This paper presents a general construction of deterministic measure-preserving dynamics using autonomous ODEs and tools from differential geometry.
We show how Hybrid Monte Carlo and other deterministic samplers follow as special cases of our theory.
arXiv Detail & Related papers (2021-06-18T15:36:09Z) - Distribution of Kinks in an Ising Ferromagnet After Annealing and the
Generalized Kibble-Zurek Mechanism [0.8258451067861933]
We consider a one-dimensional Isingmagnet induced by a temperature quench in finite time.
The universal power-law scaling of cumulants is corroborated by numerical simulations based on Glauber dynamics.
We consider linear, nonlinear, and exponential cooling schedules, among which the latter provides the most efficient shortcuts to cooling in a given time.
arXiv Detail & Related papers (2021-05-19T13:58:33Z) - Out-of-time-order correlations and the fine structure of eigenstate
thermalisation [58.720142291102135]
Out-of-time-orderors (OTOCs) have become established as a tool to characterise quantum information dynamics and thermalisation.
We show explicitly that the OTOC is indeed a precise tool to explore the fine details of the Eigenstate Thermalisation Hypothesis (ETH)
We provide an estimation of the finite-size scaling of $omega_textrmGOE$ for the general class of observables composed of sums of local operators in the infinite-temperature regime.
arXiv Detail & Related papers (2021-03-01T17:51:46Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.