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Danny Nam

dblp:308/2515 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Computational complexity · 44% Combinatorics and discrete mathematics · 28% Mathematical optimization · 28%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Combinatorics and discrete mathematics
probabilistic combinatorics
0.512021
One-step replica symmetry breaking of random regular NAE-SAT · FOCS 2021
Computational complexity › constraint satisfaction
random constraint satisfaction
0.512021
One-step replica symmetry breaking of random regular NAE-SAT · FOCS 2021
Mathematical optimization
replica symmetry breaking
0.512021
One-step replica symmetry breaking of random regular NAE-SAT · FOCS 2021
Computational complexity
phase transition
0.112021
One-step replica symmetry breaking of random regular NAE-SAT · FOCS 2021
Computational complexity › phase transition
satisfiability threshold
0.112021
One-step replica symmetry breaking of random regular NAE-SAT · FOCS 2021

Methods — techniques the papers use, named apart from their topics

spin system · 0.5partition function analysis · 0.5moment analysis · 0.5
YearPublicationVenuePosition
2021 One-step replica symmetry breaking of random regular NAE-SAT
abstract
In a broad class of sparse random constraint satisfaction problems (CSP), deep heuristics from statistical physics predict that there is a condensation phase transition before the satisfiability threshold, governed by one-step replica symmetry breaking (1RSB). In fact, in random regular k-NAE-SAT, which is one of such random CSPS, it was verified [1] that its free energy is well-defined and the explicit value follows the 1RSB prediction. However, for any model of sparse random CSP, it has been unknown whether the solution space indeed condensates on O(1) clusters according to the 1RSB prediction. In this paper, we give an affirmative answer to this question for the random regular k-NAE-SAT model. Namely, we prove that with probability close to one, most of the solutions lie inside a bounded number of solution clusters whose sizes are comparable to the scale of the free energy. Furthermore, we establish that the overlap between two independently drawn solutions concentrates precisely at two values. This is the defining property of the one-step replica symmetry breaking class which we establish for the first time in a sparse random CSP, Our proof is based on a detailed moment analysis of a spin system, which has an infinite spin space that encodes the structure of solution clusters. We develop new techniques to study the partition function as well as enhance previous approaches which were only applicable to spin systems with finitely many spins. We believe that our method is applicable to a broad range of random CSPS in the 1RSB universality class.
Danny Nam, Allan Sly, Youngtak Sohn
FOCS1