Geodesic
Thermalization in Kitaev’s quantum double models via tensor network techniques
Forum of Mathematics, Sigma, Tome 11 (2023)

Voir la notice de l'article provenant de la source Cambridge University Press

We show that every ergodic Davies generator associated to any 2D Kitaev’s quantum double model has a nonvanishing spectral gap in the thermodynamic limit. This validates rigorously the extended belief that those models are useless as self-correcting quantum memories, even in the non-abelian case. The proof uses recent ideas and results regarding the characterization of the spectral gap for parent Hamiltonians associated to Projected Entangled Pair States in terms of a bulk-boundary correspondence. 
@article{10_1017_fms_2023_98,
     author = {Angelo Lucia and David P\'erez-Garc{\'\i}a and Antonio P\'erez-Hern\'andez},
     title = {Thermalization in {Kitaev{\textquoteright}s} quantum double models via tensor network techniques},
     journal = {Forum of Mathematics, Sigma},
     publisher = {mathdoc},
     volume = {11},
     year = {2023},
     doi = {10.1017/fms.2023.98},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1017/fms.2023.98/}
}
TY  - JOUR
AU  - Angelo Lucia
AU  - David Pérez-García
AU  - Antonio Pérez-Hernández
TI  - Thermalization in Kitaev’s quantum double models via tensor network techniques
JO  - Forum of Mathematics, Sigma
PY  - 2023
VL  - 11
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/articles/10.1017/fms.2023.98/
DO  - 10.1017/fms.2023.98
LA  - en
ID  - 10_1017_fms_2023_98
ER  - 
%0 Journal Article
%A Angelo Lucia
%A David Pérez-García
%A Antonio Pérez-Hernández
%T Thermalization in Kitaev’s quantum double models via tensor network techniques
%J Forum of Mathematics, Sigma
%D 2023
%V 11
%I mathdoc
%U http://geodesic.mathdoc.fr/articles/10.1017/fms.2023.98/
%R 10.1017/fms.2023.98
%G en
%F 10_1017_fms_2023_98
Angelo Lucia; David Pérez-García; Antonio Pérez-Hernández. Thermalization in Kitaev’s quantum double models via tensor network techniques. Forum of Mathematics, Sigma, Tome 11 (2023). doi: 10.1017/fms.2023.98

Cité par Sources :