Erdős' similarity conjecture states that for each infinite set $A\subset \mathbb R$ there is a set $P\subset [0,1]$ of *positive measure* such that for all $t\in \mathbb R$, $\delta\neq 0$ there is some $a\in A$ with $t+\delta a\notin P$. In particular, it is unknown if the sequence $A=\{2^{-n}:n\geq 1\}$ has the property above.


I am considering the following related proposition (not sure if this has been answered in previous literature):


If $E\subset [0,1]$ has *full measure* then there is $t\in \mathbb R$ and $\delta\neq 0$ such that $t+\delta 2^{-n}\in E$ for all $n\geq 1$.


Is this correct?



A Related Problem to Erdős' similarity conjecture
I want to take this opportunity to give an application of algorithmic randomness theory to this area. Accidentally I am working on the similarity problem recently and found some interesting applications of algorithmic randomness theory to the area.


For the notation of randomness you may refer to the book by Downey-Hirschfeldt or Nies. 



> 
> **Proof**: It is simple to see that if $\delta$ is $x$-random, then so is $\delta2^{-n}$ for any $n\geq 1$. But $E$ is conull and so there
>  must be a real $x$ so that every $x$-random belongs to $E$. Then it
>  is clear that every $x$-random real $\delta$ meets your requirement. QED
> 
> 
> 


Actually this method can be used to prove that for any countable set $A\subset (0,1)$ , there is a real $\delta$ so that $\delta y\in E$ for any $y\in A$ (The result was proved by Kolountzakis first). 


