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On non-negative solutions to large systems of random linear equations

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  • Landmann, Stefan
  • Engel, Andreas

Abstract

Systems of random linear equations may or may not have solutions with all components being non-negative. The question is, e.g., of relevance when the unknowns are concentrations or population sizes. In the present paper we show that if such systems are large the transition between these two possibilities occurs at a sharp value of the ratio between the number of unknowns and the number of equations. We analytically determine this threshold as a function of the statistical properties of the random parameters and show its agreement with numerical simulations. We also make contact with two special cases that have been studied before: the storage problem of a perceptron and the resource competition model of MacArthur.

Suggested Citation

  • Landmann, Stefan & Engel, Andreas, 2020. "On non-negative solutions to large systems of random linear equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 552(C).
    • Handle: RePEc:eee:phsmap:v:552:y:2020:i:c:s0378437119314554
    DOI: 10.1016/j.physa.2019.122544
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    References listed on IDEAS

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    1. Imre Kondor & G'abor Papp & Fabio Caccioli, 2016. "Analytic solution to variance optimization with no short-selling," Papers 1612.07067, arXiv.org, revised Jan 2017.
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    Cited by:

    1. Axel Pruser & Imre Kondor & Andreas Engel, 2021. "Aspects of a phase transition in high-dimensional random geometry," Papers 2105.04395, arXiv.org, revised Jun 2021.
    2. Jean-Philippe Bouchaud & Matteo Marsili & Jean-Pierre Nadal, 2023. "Application of spin glass ideas in social sciences, economics and finance," Papers 2306.16165, arXiv.org.

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