Efficient learning algorithms for energy estimation imply that stable quantum algorithms cannot prepare low-energy states in systems exhibiting the quantum overlap gap property, as proven for a sparsified quantum p-spin model.
Bottlenecks in quantum channels and finite temperature phases of matter,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
quant-ph 3roles
background 1polarities
background 1representative citing papers
The unitary contribution from weak system-bath coupling in collision-model thermal state preparation tightens the fixed-point error bound, scaling rigorously as J² where J is the coupling strength.
Detectability lemma enables Gibbs sampling without Lindbladian simulation, yielding O(M) cost reduction for M-term local Lindbladians and quadratic speedup in spectral gap for frustration-free and commuting cases.
citing papers explorer
-
Quantum Glassiness From Efficient Learning
Efficient learning algorithms for energy estimation imply that stable quantum algorithms cannot prepare low-energy states in systems exhibiting the quantum overlap gap property, as proven for a sparsified quantum p-spin model.
-
Rigorous error bounds for dissipative thermal state preparation from weak system-bath coupling
The unitary contribution from weak system-bath coupling in collision-model thermal state preparation tightens the fixed-point error bound, scaling rigorously as J² where J is the coupling strength.
-
Quantum Gibbs sampling through the detectability lemma
Detectability lemma enables Gibbs sampling without Lindbladian simulation, yielding O(M) cost reduction for M-term local Lindbladians and quadratic speedup in spectral gap for frustration-free and commuting cases.