Question about absolutely continuous measures

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The discussion revolves around constructing a measure λ such that a sequence of sigma-finite measures v1, v2, v3,... is absolutely continuous with respect to λ. The initial approach involved creating an infinite weighted measure, but the constraints of sigma-finiteness complicate this method. A theorem is referenced, stating that for any sigma-finite measure μ, a corresponding probability measure λ can be constructed where μ(A)=0 if and only if λ(A)=0. The user seeks clarification on how the original measures relate to this constructed measure μ and aims to demonstrate the absolute continuity of all initial measures with respect to μ. The thread emphasizes the need for a deeper understanding of the relationship between these measures.
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Homework Statement



Suppose we're given some sigma-finite measures v1, v2, v3,...

I want to construct \lambda such that vn is absolutely continuous w.r.t. \lambda for all n.

2. The attempt at a solution

So far, I've tried thinking of making an infinite weighted (weighted by 2^(-n)). The problem is that sigma-finiteness requires that I can't divide vn(E) by the measure of the entire space. So, I need to find a more clever way of doing this.
 
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There's a handy theorem:
Given \sigma-finite measure \mu, there exists a probability measure \lambda such that
\mu(A)=0 \mbox{ iff } \lambda(A)=0
Proof:
Let {A_n} be a sequence of measurable sets such that \Bigcup A_n=X and \mu(A)<\infty. Set
f=\sum_{k=1}^\infty 2^{-k}\frac{\chi_{A_k}}{1+\mu(A_k)}
From this we can obtain finite measure \mu_f. I leave to you showing it satisfies the hypothesis.
Good luck!
 
I don't quite understand this solution. How are all of the original measures v1, v2, ... related to this mu?

I need to show that all of those initial measures are absolutely continuous w.r.t. to mu.
 
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