Unsupervised machine learning phase classification for the Falicov-Kimball model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F25%3A00635853" target="_blank" >RIV/68378271:_____/25:00635853 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/25:10498244
Result on the web
<a href="https://doi.org/10.1103/PhysRevB.111.205116" target="_blank" >https://doi.org/10.1103/PhysRevB.111.205116</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1103/PhysRevB.111.205116" target="_blank" >10.1103/PhysRevB.111.205116</a>
Alternative languages
Result language
angličtina
Original language name
Unsupervised machine learning phase classification for the Falicov-Kimball model
Original language description
We apply various unsupervised machine learning methods for phase classification to investigate the finite-temperature phase diagram of the spinless Falicov-Kimball model in two dimensions. Using only particle occupation snapshots from Monte Carlo simulations as input, each technique, including a straightforward classification based on principal component analysis (PCA), successfully identifies the phase boundary between ordered and disordered phases, independent of the type of phase transition. Remarkably, these techniques also distinguish between the weakly localized and Anderson-localized regimes within the disordered phase, accurately identifying their crossover, which is a challenging task for standard methods. Among the machine learning approaches used, PCA based analysis outperforms more complex methods, such as neural network predictors and autoencoders. These results underscore the effectiveness of simple unsupervised techniques in examining phase transitions and electron localization in complex correlated systems.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10302 - Condensed matter physics (including formerly solid state physics, supercond.)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Physical Review B
ISSN
2469-9950
e-ISSN
2469-9969
Volume of the periodical
111
Issue of the periodical within the volume
20
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
205116
UT code for WoS article
001494685000001
EID of the result in the Scopus database
2-s2.0-105005146138