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Sergio Caracciolo

Publications and source records attributed to Sergio Caracciolo.

At least 19 recordsLinked to original sources

Spanning trees in the Assignment Problem: two theorems and two conjectures

The \emph{Minimum Matching Problem} consists of finding an independent edge set of minimum weight $M_{\star}(G)$ in a given edge-weighted graph $G$. When $G$ is bipartite, this reduces to the \emph{Assignment Problem}. We consider a variant of this problem defined by taking the union of optimal matchings across various slightly modified versions of the base graph: $H_{\mathcal{J}}(G)=\bigcup_{U \in \mathcal{J}} M_{\star}(G_{U})$. We establish two families of results: (1) In two distinct settings for the Assignment Problem, we prove that the resulting graphs $H_{\mathcal{J}}$, as well as certain associated graphs $\bar{H}_{\mathcal{J}}$, are spanning trees on the relevant base graphs $G$ and $\bar{G}$. (2) In these same settings, assuming the edge weights are given by the $p$-th power of Euclidean distances for point configurations in the plane, we show that for $p=1$ the tree $H_{\mathcal{J}}$ is non-crossing (i.e., its planar embedding has no crossing edges), whereas, remarkably, for $p=2$ the associated tree $\bar{H}_{\mathcal{J}}$ is non-crossing. Finally, we introduce novel conjectures in Statistical Mechanics, to be explored in future work: in the Random Euclidean Assignment Problem (where points are i.i.d.\ on a planar domain), we conjecture that for $p=2$ the trees $\bar{H}_{\mathcal{J}}$ are asymptotically distributed as Uniform Spanning Trees with free and wired boundary conditions in the two respective settings. In particular, suitable paths on the tree in the second setting, and on its planar dual in the first setting, are asymptotically distributed as $\text{SLE}_{\kappa}$ with $\kappa=2$.

math.CO

Simulated annealing, optimization, searching for ground states

The chapter starts with a historical summary of first attempts to optimize the spin glass Hamiltonian, comparing it to recent results on searching largest cliques in random graphs. Exact algorithms to find ground states in generic spin glass models are then explored in Section 1.2, while Section 1.3 is dedicated to the bidimensional case where polynomial algorithms exist and allow for the study of much larger systems. Finally Section 1.4 presents a summary of results for the assignment problem where the finite size corrections for the ground state can be studied in great detail.

cond-mat.dis-nn

Random assignment problems on ${2d}$ manifolds

We consider the assignment problem between two sets of $N$ random points on a smooth, two-dimensional manifold $Ω$ of unit area. It is known that the average cost scales as $E_Ω(N)\sim\frac{1}{2π}\ln N$ with a correction that is at most of order $\sqrt{\ln N\ln\ln N}$. In this paper, we show that, within the linearization approximation of the field-theoretical formulation of the problem, the first $Ω$-dependent correction is on the constant term, and can be exactly computed from the spectrum of the Laplace--Beltrami operator on $Ω$. We perform the explicit calculation of this constant for various families of surfaces, and compare our predictions with extensive numerics.

math-ph

Criticality and conformality in the random dimer model

In critical systems, the effect of a localized perturbation affects points that are arbitrarily far from the perturbation location. In this paper, we study the effect of localized perturbations on the solution of the random dimer problem in $2D$. By means of an accurate numerical analysis, we show that a local perturbation of the optimal covering induces an excitation whose size is extensive with finite probability. We compute the fractal dimension of the excitations and scaling exponents. In particular, excitations in random dimer problems on non-bipartite lattices have the same statistical properties of domain walls in the $2D$ spin glass. Excitations produced in bipartite lattices, instead, are compatible with a loop-erased self-avoiding random walk process. In both cases, we find evidence of conformal invariance of the excitations that is compatible with $\mathrm{SLE}_κ$ with parameter $κ$ depending on the bipartiteness of the underlying lattice only.

cond-mat.dis-nn

The number of optimal matchings for Euclidean Assignment on the line

We consider the Random Euclidean Assignment Problem in dimension $d=1$, with linear cost function. In this version of the problem, in general, there is a large degeneracy of the ground state, i.e. there are many different optimal matchings (say, $\sim \exp(S_N)$ at size $N$). We characterize all possible optimal matchings of a given instance of the problem, and we give a simple product formula for their number. Then, we study the probability distribution of $S_N$ (the zero-temperature entropy of the model), in the uniform random ensemble. We find that, for large $N$, $S_N \sim \frac{1}{2} N \log N + N s + \mathcal{O}\left( \log N \right)$, where $s$ is a random variable whose distribution $p(s)$ does not depend on $N$. We give expressions for the asymptotics of the moments of $p(s)$, both from a formulation as a Brownian process, and via singularity analysis of the generating functions associated to $S_N$. The latter approach provides a combinatorial framework that allows to compute an asymptotic expansion to arbitrary order in $1/N$ for the mean and the variance of

math.PR

The p-Airy distribution

In this manuscript we consider the set of Dyck paths equipped with the uniform measure, and we study the statistical properties of a deformation of the observable "area below the Dyck path" as the size $N$ of the path goes to infinity. The deformation under analysis is apparently new: while usually the area is constructed as the sum of the heights of the steps of the Dyck path, here we regard it as the sum of the lengths of the connected horizontal slices under the path, and we deform it by applying to the lengths of the slices a positive regular function $ω(\ell)$ such that $ω(\ell) \sim \ell^p$ for large argument. This shift of paradigm is motivated by applications to the Euclidean Random Assignment Problem in Random Combinatorial Optimization, and to Tree Hook Formulas in Algebraic Combinatorics. For $p \in \mathbb{R}^+ \smallsetminus \left\{ \frac{1}{2}\right\}$, we characterize the statistical properties of the deformed area as a function of the deformation function $ω(\ell)$ by computing its integer moments, finding a generalization of a well-known recursion for the moments of the area-Airy distribution, due to Takács. Most of the properties of the distribution of the deformed area are \emph{universal}, meaning that they depend on the deformation parameter $p$, but not on the microscopic details of the function $ω(\ell)$. We call \emph{$p$-Airy distribution} this family of universal distributions.

math.CO

The Dyck bound in the concave 1-dimensional random assignment model

We consider models of assignment for random $N$ blue points and $N$ red points on an interval of length $2N$, in which the cost for connecting a blue point in $x$ to a red point in $y$ is the concave function $|x-y|^p$, for $0 1$, where the optimal matching is trivially determined, here the optimization is non-trivial. The purpose of this paper is to introduce a special configuration, that we call the \emph{Dyck matching}, and to study its statistical properties. We compute exactly the average cost, in the asymptotic limit of large $N$, together with the first subleading correction. The scaling is remarkable: it is of order $N$ for $p<\frac{1}{2}$, order $N \ln N$ for $p=\frac{1}{2}$, and $N^{\frac{1}{2}+p}$ for $p>\frac{1}{2}$, and it is universal for a wide class of models. We conjecture that the average cost of the Dyck matching has the same scaling in $N$ as the cost of the optimal matching, and we produce numerical data in support of this conjecture. We hope to produce a proof of this claim in future work.

cond-mat.dis-nn

Selberg integrals in 1D random Euclidean optimization problems

We consider a set of Euclidean optimization problems in one dimension, where the cost function associated to the couple of points $x$ and $y$ is the Euclidean distance between them to an arbitrary power $p\ge1$, and the points are chosen at random with flat measure. We derive the exact average cost for the random assignment problem, for any number of points, by using Selberg's integrals. Some variants of these integrals allows to derive also the exact average cost for the bipartite travelling salesman problem.

cond-mat.dis-nn

Average optimal cost for the Euclidean TSP in one dimension

The traveling-salesman problem is one of the most studied combinatorial optimization problems, because of the simplicity in its statement and the difficulty in its solution. We study the traveling salesman problem when the positions of the cities are chosen at random in the unit interval and the cost associated to the travel between two cities is their distance elevated to an arbitrary power $p\in \mathbb{R}$. We characterize the optimal cycle and compute the average optimal cost for every number of cities when the measure used to choose the position of the cities is flat and asymptotically for large number of cities in the other cases. We also show that the optimal cost is a self-averaging quantity, and we test our analytical results with extensive simulations.

cond-mat.dis-nn

Remarks on replica diagonal collective field condensations in SYK

In the Sachdev-Ye-Kitaev model with generic order $q \ge 4$ random couplings, we compute the critical temperature relating the Majorana fermions high temperature perturbative vacuum to the vacuum where the replica diagonal collective field $G(τ, τ')$ condenses. We study, by a finite temperature diagrammatic analysis, the effective action of an auxiliary Hubbard-Stratonovich bilocal field related to $G(τ, τ')$ in the large $N$ limit. Subtelties that arise in switching from the operatorial to the functional integral representation of the SYK thermal partition function are also discussed.

hep-th

Lattice QCD$_2$ effective action with Bogoliubov transformations

In the Wilson's lattice formulation of QCD, a fermionic Fock space of states can be explicitly built at each time slice using canonical creation and annihilation operators. The partition function $Z$ is then represented as the trace of the transfer matrix, and its usual functional representation as a path integral of $\exp(- S)$ can be recovered in a standard way. However, applying a Bogoliubov transformation on the canonical operators before passing to the functional formalism, we can isolate a vacuum contribution in the resulting action which depends only on the parameters of the transformation and fixes them via a variational principle. Then, inserting in the trace defining $Z$ an operator projecting on the mesons subspace at each time slice and making the physical assumption that the true partition function is well approximate by the projected one, we can also write an effective quadratic action for mesons. We tested the method in the renowned 't Hooft model, namely QCD in two spacetime dimensions for large number of colours, in Coulomb gauge.

hep-lat

Effective mesonic theory for the 't Hooft model on the lattice

We apply to a lattice version of the 't~Hooft model, QCD in two space-time dimensions for large number of colours, a method recently proposed to obtain an effective mesonic action starting from the fundamental, fermionic one. The idea is to pass from a canonical, operatorial representation, where the low-energy states have a direct physical interpretation in terms of a Bogoliubov vacuum and its corresponding quasiparticle excitations, to a functional, path integral representation, via the formalism of the transfer matrix. In this way we obtain a lattice effective theory for mesons in a self-consistent setting. We also verify that well-known results from other different approaches are reproduced in the continuum limit.

hep-lat

Exact value for the average optimal cost of bipartite traveling-salesman and 2-factor problems in two dimensions

We show that the average cost for the traveling-salesman problem in two dimensions, which is the archetypal problem in combinatorial optimization, in the bipartite case, is simply related to the average cost of the assignment problem with the same Euclidean, increasing, convex weights. In this way we extend a result already known in one dimension where exact solutions are avalaible. The recently determined average cost for the assignment when the cost function is the square of the distance between the points provides therefore an exact prediction $$\overline{E_N} = \frac{1}π\, \log N$$ for large number of points $2N$. As a byproduct of our analysis also the loop covering problem has the same optimal average cost. We also explain why this result cannot be extended at higher dimensions. We numerically check the exact predictions.

cond-mat.dis-nn

Plastic number and possible optimal solutions for an Euclidean 2-matching in one dimension

In this work we consider the problem of finding the minimum-weight loop cover of an undirected graph. This combinatorial optimization problem is called 2-matching and can be seen as a relaxation of the traveling salesman problem since one does not have the unique loop condition. We consider this problem both on the complete bipartite and complete graph embedded in a one dimensional interval, the weights being chosen as a convex function of the Euclidean distance between each couple of points. Randomness is introduced throwing independently and uniformly the points in space. We derive the average optimal cost in the limit of large number of points. We prove that the possible solutions are characterized by the presence of "shoelace" loops containing 2 or 3 points of each type in the complete bipartite case, and 3, 4 or 5 points in the complete one. This gives rise to an exponential number of possible solutions scaling as p^N , where p is the plastic constant. This is at variance to what happens in the previously studied one-dimensional models such as the matching and the traveling salesman problem, where for every instance of the disorder there is only one possible solution.

cond-mat.dis-nn

Solution for a bipartite Euclidean traveling-salesman problem in one dimension

The traveling salesman problem is one of the most studied combinatorial optimization problems, because of the simplicity in its statement and the difficulty in its solution. We characterize the optimal cycle for every convex and increasing cost function when the points are thrown independently and with an identical probability distribution in a compact interval. We compute the average optimal cost for every number of points when the distance function is the square of the Euclidean distance. We also show that the average optimal cost is not a self-averaging quantity by explicitly computing the variance of its distribution in the thermodynamic limit. Moreover, we prove that the cost of the optimal cycle is not smaller than twice the cost of the optimal assignment of the same set of points. Interestingly, this bound is saturated in the thermodynamic limit.

cond-mat.dis-nn

Anomalous scaling of the optimal cost in the one-dimensional random assignment problem

We consider the random Euclidean assignment problem on the line between two sets of $N$ random points, independently generated with the same probability density function $\varrho$. The cost of the matching is supposed to be dependent on a power $p>1$ of the Euclidean distance of the matched pairs. We discuss an integral expression for the average optimal cost for $N\gg 1$ that generalizes a previous result obtained for $p=2$. We also study the possible divergence of the given expression due to the vanishing of the probability density function. The provided regularization recipe allows us to recover the proper scaling law for the cost in the divergent cases, and possibly some of the involved coefficients. The possibility that the support of $\varrho$ is a disconnected interval is also analysed. We exemplify the proposed procedure and we compare our predictions with the results of numerical simulations.

cond-mat.dis-nn

Random Euclidean matching problems in one dimension

We discuss the optimal matching solution for both the assignment problem and the matching problem in one dimension for a large class of convex cost functions. We consider the problem in a compact set with the topology both of the interval and of the circumference. Afterwards, we assume the points' positions to be random variables identically and independently distributed on the considered domain. We analytically obtain the average optimal cost in the asymptotic regime of very large number of points $N$ and some correlation functions for a power-law type cost function in the form $c(z)=z^p$, both in the $p>1$ case and in the $p<0$ case. The scaling of the optimal mean cost with the number of points is $N^{-\frac{p}{2}}$ for the assignment and $N^{-p}$ for the matching when $p>1$, whereas in both cases it is a constant when $p<0$. Finally, our predictions are compared with the results of numerical simulations.

cond-mat.dis-nn

On the universal Gaussian behavior of Driven Lattice Gases at short-times

The dynamic and static critical behaviors of driven and equilibrium lattice gas models are studied in two spatial dimensions. We show that in the short-time regime immediately following a critical quench, the dynamics of the transverse order parameters, auto-correlations, and Binder cumulant are consistent with the prediction of a Gaussian, $i.e.,$ non-interacting, effective theory, both for the equilibrium lattice gas and its nonequilibrium counterparts. Such a "super-universal" behavior is observed only at short times after a critical quench, while the various models display their distinct behaviors in the stationary states, described by the corresponding, known universality classes.

cond-mat.stat-mech