Young measure

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In mathematical analysis, a Young measure is a parameterized measure that is associated with certain subsequences of a given bounded sequence of measurable functions. Young measures have applications in the calculus of variations and the study of nonlinear partial differential equations. They are named after Laurence Chisholm Young.


We let \{ f_k \}_{k=1}^\infty be a bounded sequence in L^\infty (U,\mathbb{R}^m), where U denotes an open bounded subset of \mathbb{R}^n. Then there exists a subsequence \{ f_{k_j} \}_{j=1}^\infty \subset \{ f_k \}_{k=1}^\infty and for almost every x \in U a Borel probability measure \nu_x on \mathbb{R}^m such that for each F \in C(\mathbb{R}^m) we have F(f_{k_j}) \overset{\ast}{\rightharpoonup} \int_{\mathbb{R}^m} F(y)d\nu_\cdot(y) in L^\infty (U). The measures \nu_x are called the Young measures generated by the sequence \{ f_k \}_{k=1}^\infty.


Every minimizing sequence of I(u) = \int_0^1 (u_x^2-1)^2 + u^2dx subject to u(0)=u(1)=0 generates the Young measures \nu_x= \frac{1}{2} \delta_{-1} + \frac{1}{2}\delta_1.

This captures the essential features of all minimizing sequences to this problem, namely developing finer and finer slopes of \pm 1.


  • J.M. Ball (1989). "A version of the fundamental theorem for Young measures". In: PDEs and Continuum Models of Phase Transition. (Eds. M.Rascle, D.Serre, M.Slemrod.) Lecture Notes in Physics 344, (Berlin: Springer). pp. 207–215. 
  • L.C. Evans (1990). Weak convergence methods for nonlinear partial differential equations. Regional conference series in mathematics. American Mathematical Society. 
  • T. Roubíček (1997). Relaxation in Optimization Theory and Variational Calculus. Berlin: Walter de Gruyter. ISBN 3-11-014542-1.  (Chap.3)
  • L.C. Young (1937). "Generalized curves and the existence of an attained absolute minimum in the calculus of variations". Comptes Rendus de la Societe des Sciences et des Lettres de Varsovie, Classe III 30. pp. 212–234. 

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