We consider the Random Euclidean Assignment Problem in dimension d=1\documentclass[12pt]{minimal}
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\begin{document}$$d=1$$\end{document}, 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)\documentclass[12pt]{minimal}
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\begin{document}$$\sim \exp (S_N)$$\end{document} 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 SN\documentclass[12pt]{minimal}
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\begin{document}$$S_N$$\end{document} (the zero-temperature entropy of the model), in the uniform random ensemble. We find that, for large N, SN∼12NlogN+Ns+OlogN\documentclass[12pt]{minimal}
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\begin{document}$$S_N \sim \frac{1}{2} N \log N + N s + {\mathcal {O}}\left( \log N \right) $$\end{document}, where s is a random variable whose distribution p(s) does not depend on N. We give expressions for the moments of p(s), both from a formulation as a Brownian process, and via singularity analysis of the generating functions associated to SN\documentclass[12pt]{minimal}
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\begin{document}$$S_N$$\end{document}. 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 SN\documentclass[12pt]{minimal}
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\begin{document}$$S_N$$\end{document}.