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Quantum k-SAT (the problem of determining whether a k-local Hamiltonian is frustration-free) is known to be QMA_1-complete for k >= 3, and hence likely hard for quantum computers to solve. Building on a classical result of Alon and Shapira,…

Quantum Physics · Physics 2025-09-03 Ashley Montanaro , Changpeng Shao , Dominic Verdon

We study the connection between the order of phase transitions in combinatorial problems and the complexity of decision algorithms for such problems. We rigorously show that, for a class of random constraint satisfaction problems, a limited…

Computational Complexity · Computer Science 2007-05-23 Gabriel Istrate , Stefan Boettcher , Allon G. Percus

In this paper we initiate the study of the heterogeneous capacitated $k$-center problem: given a metric space $X = (F \cup C, d)$, and a collection of capacities. The goal is to open each capacity at a unique facility location in $F$, and…

Data Structures and Algorithms · Computer Science 2016-11-23 Deeparnab Chakrabarty , Ravishankar Krishnaswamy , Amit Kumar

We study several problems related to properties of non-negative matrices that arise at the boundary between quantum and classical probabilistic computation. Our results are twofold. First, we identify a large class of quantum Hamiltonians…

Quantum Physics · Physics 2010-01-22 Sergey Bravyi , Barbara Terhal

We introduce the problem of finding a satisfying assignment to a CNF formula that must further belong to a prescribed input subspace. Equivalent formulations of the problem include finding a point outside a union of subspaces (the…

Data Structures and Algorithms · Computer Science 2021-08-16 Vikraman Arvind , Venkatesan Guruswami

A local search algorithm solving an NP-complete optimisation problem can be viewed as a stochastic process moving in an 'energy landscape' towards eventually finding an optimal solution. For the random 3-satisfiability problem, the…

Statistical Mechanics · Physics 2009-11-11 Sakari Seitz , Mikko Alava , Pekka Orponen

Random constraint satisfaction problems undergo several phase transitions as the ratio between the number of constraints and the number of variables is varied. When this ratio exceeds the satisfiability threshold no more solutions exist;…

Disordered Systems and Neural Networks · Physics 2017-06-22 Alfredo Braunstein , Luca Dall'Asta , Guilhem Semerjian , Lenka Zdeborova

The problem of P vs. NP is very serious, and solutions to the problem can help save lives. This article is an attempt at solving the problem using a computer algorithm. It is presented in a fashion that will hopefully allow for easy…

Data Structures and Algorithms · Computer Science 2015-03-19 Matt Groff

An instance of a random constraint satisfaction problem defines a random subset S (the set of solutions) of a large product space (the set of assignments). We consider two prototypical problem ensembles (random k-satisfiability and…

We define and study a statistical mechanics ensemble that characterizes connected solutions in constraint satisfaction problems (CSPs). Built around a well-known local entropy bias, it allows us to better identify hardness transitions in…

Disordered Systems and Neural Networks · Physics 2026-04-17 Damien Barbier

We report a cluster of results on k-QSAT, the problem of quantum satisfiability for k-qubit projectors which generalizes classical satisfiability with k-bit clauses to the quantum setting. First we define the NP-complete problem of product…

Quantum Physics · Physics 2010-07-02 C. R. Laumann , A. M. Läuchli , R. Moessner , A. Scardicchio , S. L. Sondhi

The solution space of many classical optimization problems breaks up into clusters which are extensively distant from one another in the Hamming metric. Here, we show that an analogous quantum clustering phenomenon takes place in the ground…

Quantum Physics · Physics 2017-10-25 S. C. Morampudi , B. Hsu , S. L. Sondhi , R. Moessner , C. R. Laumann

In this work, we study diversity-aware clustering problems where the data points are associated with multiple attributes resulting in intersecting groups. A clustering solution needs to ensure that the number of chosen cluster centers from…

Data Structures and Algorithms · Computer Science 2025-05-21 Suhas Thejaswi , Ameet Gadekar , Bruno Ordozgoiti , Aristides Gionis

We study the satisfiability threshold and solution-space geometry of random constraint satisfaction problems defined over uniquely extendable (UE) constraints. Motivated by a conjecture of Connamacher and Molloy, we consider random $k$-ary…

Combinatorics · Mathematics 2026-01-27 Pu Gao , Theodore Morrison

We introduce and benchmark a stochastic local search heuristic for the NP-complete satisfiability problem 3-SAT that drastically outperforms existing solvers in the notoriously difficult realm of critically hard instances. Our construction…

Artificial Intelligence · Computer Science 2025-06-23 J. Schwardt , J. C. Budich

A satisfiability (SAT-UNSAT) transition takes place for many optimization problems when the number of constraints, graphically represented by links between variables nodes, is brought above some threshold. If the network of constraints is…

Disordered Systems and Neural Networks · Physics 2009-11-11 Olivier Rivoire , Julien Barré

Boolean Satisfiability (SAT) problems are critical in fields such as artificial intelligence and cryptography, where efficient solutions are essential. Conventional probabilistic solvers often encounter scalability issues due to complex…

Facilitated spin models on random graphs provide an ideal microscopic realization of the mode-coupling theory of supercooled liquids: they undergo a purely dynamic glass transition with no thermodynamic singularity. In this paper we study…

Statistical Mechanics · Physics 2015-06-11 Silvio Franz , Mauro Sellitto

Quantum systems that violate the eigenstate thermalisation hypothesis thereby falling outside the paradigm of conventional statistical mechanics are of both intellectual and practical interest. We show that such a breaking of ergodicity may…

Disordered Systems and Neural Networks · Physics 2020-05-20 Sthitadhi Roy , Achilleas Lazarides

In data summarization we want to choose $k$ prototypes in order to summarize a data set. We study a setting where the data set comprises several demographic groups and we are restricted to choose $k_i$ prototypes belonging to group $i$. A…

Machine Learning · Statistics 2019-05-14 Matthäus Kleindessner , Pranjal Awasthi , Jamie Morgenstern
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