Greetings Mathematics Community. I believe that I am thinking too hard about the following problem and would like some guidance in solving it.
Let X have finite measure and let fn:X→C and f:X→C be measurable functions. Show that if fn converges to f in L∞norm, then fn also converges to f in L1norm.
The definitions that I am working with are as follows:
We say that fn converges to f uniformly almost everywhere, essentially uniformly, or in L∞norm if, for every ϵ>0, there exists N such that for every n≥N,|fn(x)−f(x)|≤ϵ for μ−almost every x∈X. The L∞norm ||f||L∞(μ) of a measurable function f:X→C is defined to be the infimum of all the quantities M∈[0,+∞] that are essential upper bounds for f in the sense that |f(x)|≤M for almost every x. Then fn converges to f in L∞ norm if and only if ||fn−f||L∞(μ)→0 as n→∞.
We say that fn converges to f in L1norm if the quantity ||fn−f||L1(μ)=∫X|fn(x)−f(x)|dμ converges to 0 as n→∞.
Here is my attempt at solving this problem:
Since fn converges to f in L∞ norm, then we have
||fn(x)−f(x)||∞→0 as n→∞ and by definition, ||fn(x)−f(x)||∞=inf. Then ||f_n(x)-f(x)||_1 = \int |f_n(x)-f(x)|dx.
Here is where I am stuck: Could I create another function g such that ||g(x)||_1 \leq ||g(x)||_{\infty} and somehow include Markov's Inequality to show that the L^1 norm converges?
Alternatively, could I simply say that \int|f_n(x)-f(x)|dx \leq ||f_n(x)-f(x)||_{\infty} and since we are given that f_n converges to f in L^{\infty}norm, then \int|f_n(x)-f(x)|dx \leq 0?
I would be grateful for any advice or guidance. Thanks in advance.
Answer
\|f_n-f\|_1=\int_X|f_n-f|d\mu\le\|f_n-f\|_{\infty}\mu(X).
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