A modified least action principle allowing mass concentrations for the early universe reconstruction problem
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چکیده
We address the early universe reconstruction (EUR) problem (as considered by Frisch and coauthors in [24]), and the related Zeldovich approximate model [39]. By substituting the fully nonlinear Monge-Ampère equation for the linear Poisson equation to model gravitation, we introduce a modified mathematical model (”Monge-Ampère gravitation/MAG”), for which the Zeldovich approximation becomes exact. The MAG model enjoys a least action principle in which we can input mass concentration effects in a canonical way, based on the theory of gradient flows with convex potentials and somewhat related to the concept of self-dual Lagrangians developped by Ghoussoub [27]. A fully discrete algorithm is introduced for the EUR problem in one space dimension. Introduction This paper addresses the early universe reconstruction (EUR) problem discussed by Frisch and coauthors in [24, 17]. We refer to these papers for the detailed physical background of this important problem in cosmology. Here is a simplified mathematical formulation. We consider (for simplicity) a smooth closed bounded 3D domain D ⊂ R and denote the space variable by x ∈ D. We are given two times t1 > t0 > 0, two probability measures ρ0(dx), ρ1(dx) on D. We look for a time-dependent family of probability measures ρ(t, dx) on D (depending continuously on the time variable t, with respect to the weak convergence of measures), interpolating ρ0 and ρ1, at t = t0 and t = t1 respectively, and minimizing the following action
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ERC conference on Optimal Transportation and Applications
Explicit procedures are provided in the three cases above, the principal one being that the problem has an hidden structure of linear preorder with universally measurable graph. Yann Brenier (Nice). A modified least action principle allowing mass concentrations for the early universe reconstruction problem. Abstract. We discuss the reconstruction problem for the early universe, following Peeble...
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تاریخ انتشار 2017