Mosco convergence

In mathematical analysis, Mosco convergence, is a notion of convergence for functionals that is used in nonlinear analysis and set-valued analysis. It is a particular case of Γ-convergence. Mosco convergence is sometimes phrased as “weak Γ-liminf and strong Γ-limsup” convergence since it uses both the weak and strong topologies on a topological vector space X.

Mosco convergence is named after Italian mathematician Umberto Mosco, a current Harold J. Gay professor of mathematics at Worcester Polytechnic Institute.

Definition

Let X be a topological vector space and let X^∗ denote the dual space of continuous linear functionals on X. Let F_n : X → [0, +∞] be functionals on X for each n = 1, 2, ... The sequence (or, more generally, net) (F_n) is said to Mosco converge to another functional F : X → [0, +∞] if the following two conditions hold:

• lower bound inequality: for each sequence of elements x_n ∈ X converging weakly to x ∈ X,

$\liminf _{n\to \infty }F_{n}(x_{n})\geq F(x);$

• upper bound inequality: for every x ∈ X there exists an approximating sequence of elements x_n ∈ X, converging strongly to x, such that

$\limsup _{n\to \infty }F_{n}(x_{n})\leq F(x).$

Since lower and upper bound inequalities of this type are used in the definition of Γ-convergence, Mosco convergence is sometimes phrased as “weak Γ-liminf and strong Γ-limsup” convergence. Mosco convergence is sometimes abbreviated to M-convergence and denoted by

$\mathop {\text{M-lim}} _{n\to \infty }F_{n}=F{\text{ or }}F_{n}{\xrightarrow[{n\to \infty }]{\mathrm {M} }}F.$

References

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