Stat-mech models with symmetries capture how proliferation of two non-Abelian anyons in D4 topological order parasitically condenses a shared Abelian anyon, destroying topological order while the trivial phase remembers which anyons condensed.
Fault-tolerant quantum computation by anyons
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
method 1
citation-polarity summary
representative citing papers
A geometric phase transition produces crystalline hippocampal coding in food-caching birds that yields over 100-fold higher location memory capacity than the mist-like coding in non-caching birds.
A photonic cavity creates a chirality-controlled rotating pinning potential that performs branch-conditioned braiding of non-Abelian anyons and maps the result onto measurable cavity coherence.
Convolutional neural network decoders achieve good performance on surface code error correction and adapt across noise models, with explainable AI used to inspect their decisions.
citing papers explorer
-
Statistical Mechanics and Symmetries of Non-Abelian Anyon Proliferation: From Deformation to Decoherence
Stat-mech models with symmetries capture how proliferation of two non-Abelian anyons in D4 topological order parasitically condenses a shared Abelian anyon, destroying topological order while the trivial phase remembers which anyons condensed.
-
Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity
A geometric phase transition produces crystalline hippocampal coding in food-caching birds that yields over 100-fold higher location memory capacity than the mist-like coding in non-caching birds.
-
Photonic Chirality for Braiding and Readout of Non-Abelian Anyons
A photonic cavity creates a chirality-controlled rotating pinning potential that performs branch-conditioned braiding of non-Abelian anyons and maps the result onto measurable cavity coherence.
-
Convolutional neural network based decoders for surface codes
Convolutional neural network decoders achieve good performance on surface code error correction and adapt across noise models, with explainable AI used to inspect their decisions.
- Exact Toda Black Holes of Rank-2 Lie Groups