Learning transitions exist in the 2D Ising model when inferring local energies via Bayesian methods, intersecting the thermal transition at a new tricritical point and implying robustness of quantum memory in deformed toric codes under weak measurements.
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Pith papers citing it
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Introduces subdimensional entanglement entropy (SEE) as a probe of geometric-topological responses in quantum phases and establishes a bulk-to-mixed-state holographic correspondence via strong and weak symmetries on subdimensional subsystems.
Decohered non-Abelian Kitaev quantum double states exhibit strong-to-weak spontaneous symmetry breaking of non-invertible higher-form symmetries and form an information convex set whose dimension equals the pure-state ground-state degeneracy.
citing papers explorer
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Learning transitions in classical Ising models and deformed toric codes
Learning transitions exist in the 2D Ising model when inferring local energies via Bayesian methods, intersecting the thermal transition at a new tricritical point and implying robustness of quantum memory in deformed toric codes under weak measurements.
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Subdimensional Entanglement Entropy: From Geometric-Topological Response to Mixed-State Holography
Introduces subdimensional entanglement entropy (SEE) as a probe of geometric-topological responses in quantum phases and establishes a bulk-to-mixed-state holographic correspondence via strong and weak symmetries on subdimensional subsystems.
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Strong-to-weak spontaneous symmetry breaking of higher-form non-invertible symmetries in Kitaev's quantum double model
Decohered non-Abelian Kitaev quantum double states exhibit strong-to-weak spontaneous symmetry breaking of non-invertible higher-form symmetries and form an information convex set whose dimension equals the pure-state ground-state degeneracy.