English

The number of optimal matchings for Euclidean Assignment on the line

Probability 2021-07-16 v1 Disordered Systems and Neural Networks Combinatorics

Abstract

We consider the Random Euclidean Assignment Problem in dimension d=1d=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, exp(SN)\sim \exp(S_N) at size NN). 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 SNS_N (the zero-temperature entropy of the model), in the uniform random ensemble. We find that, for large NN, SN12NlogN+Ns+O(logN)S_N \sim \frac{1}{2} N \log N + N s + \mathcal{O}\left( \log N \right), where ss is a random variable whose distribution p(s)p(s) does not depend on NN. We give expressions for the asymptotics of the moments of p(s)p(s), both from a formulation as a Brownian process, and via singularity analysis of the generating functions associated to SNS_N. The latter approach provides a combinatorial framework that allows to compute an asymptotic expansion to arbitrary order in 1/N1/N for the mean and the variance of

Keywords

Cite

@article{arxiv.2101.04926,
  title  = {The number of optimal matchings for Euclidean Assignment on the line},
  author = {Sergio Caracciolo and Vittorio Erba and Andrea Sportiello},
  journal= {arXiv preprint arXiv:2101.04926},
  year   = {2021}
}