Finite-size corrections in the random assignment problem
classification
❄️ cond-mat.dis-nn
keywords
distributioncorrectionsassignmentnumericalproblemrandomwhenanalytically
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We analytically derive, in the context of the replica formalism, the first finite size corrections to the average optimal cost in the random assignment problem for a quite generic distribution law for the costs. We show that, when moving from a power-law distribution to a $\Gamma$ distribution, the leading correction changes both in sign and in its scaling properties. We also examine the behavior of the corrections when approaching a $\delta$-function distribution. By using a numerical solution of the saddle-point equations, we provide predictions that are confirmed by numerical simulations.
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