Comparing asymptotic running time of two algorithms $\sqrt n$ and $2^{\sqrt{\log _{2}n}}$ Given two algorithms with their time-complexity $t_a(n)=\sqrt{n}$   and $t_b(n) = 2^{\sqrt{\log _{2}n}}$ and i have to show $t_b(n) = O(t_a(n)) $.

I´ve made a program to check this statement and it seems that for any given $c&gt;0,\forall n\geq16$  it holds, however i don´t know how to formally proof this ,because i can´t find any simplification for $t_b$. 

I know that i must prove $ \exists c   
 : \forall n \geq N:t_b(n) \leq c *t_a(n)$ using big-O-Notation. 

A hint/solution-idea would be really great.
In order to compare two quantities/expression, it is often easier if they are in the same form. Here try expressing $t_a(n)$ as $2^{s_a(n)}$ and compare $s_a(n)$ with $\sqrt{\log_2 n}$.

Additionally, beware of using a program to check asymptotic comparisons: e.g. $f(n)=n^{10^6}$ and $g(n)=(1,0000000000000001)^n$