Generic proving of replica symmetry breaking
November 29, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Mihailo Stojnic
arXiv ID
2311.18106
Category
cond-mat.stat-mech
Cross-listed
cs.IT,
math-ph,
math.PR
Citations
1
Venue
arXiv.org
Last Checked
6 months ago
Abstract
We study the replica symmetry breaking (rsb) concepts on a generic level through the prism of recently introduced interpolating/comparison mechanisms for bilinearly indexed (bli) random processes. In particular, \cite{Stojnicnflgscompyx23} introduced a \emph{fully lifted} (fl) interpolating mechanism and \cite{Stojnicsflgscompyx23} developed its a \emph{stationarized fully lifted} (sfl) variant. Here, we present a sfl \emph{matching} mechanism that shows that the results obtained in \cite{Stojnicnflgscompyx23,Stojnicsflgscompyx23} completely correspond to the ones obtained by a statistical physics replica tool with the replica symmetry breaking (rsb) form suggested by Parisi in \cite{Par79,Parisi80,Par80}. The results are very generic as they allow to handle pretty much all bilinear models at once. Moreover, given that the results of \cite{Stojnicnflgscompyx23,Stojnicsflgscompyx23} are extendable to many other forms, the concepts presented here automatically extend to any such forms as well.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β cond-mat.stat-mech
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders
π
π
Old Age
Unsupervised Generative Modeling Using Matrix Product States
R.I.P.
π»
Ghosted
Solving Statistical Mechanics Using Variational Autoregressive Networks
R.I.P.
π»
Ghosted
Learning Thermodynamics with Boltzmann Machines
R.I.P.
π»
Ghosted
Information Flows? A Critique of Transfer Entropies
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted