Does an algorithm with complexity $\Theta(2^\sqrt{n})$ to solve any NP problem count as "good" and practical as any other polynomial algorithm? If the complexity of an arbitrary algorithm to solve any NP problem after analysis is $\Theta(2^\sqrt{n})$ then is this algorithm considered as "good" and practical algorithm?

I know that in algorithm analysis and computational complexity theory every algorithm with any polynomial complexity is considered as "good" and practical algorithm, although in mathematics and calculus $2^\sqrt{n}$ isn't polynomial by definition, but so $n\log n$, but $\Theta(n\log n)$ counts as "good" and practical algorithm to solve any NP problem.

I have already graphed the functions: $x, x\log_2x, x^2, 2^\sqrt{x}$ and $x^3$ by using some online function plotter, and for some large $x$, it appears that $ x^3&gt;2^\sqrt{x}&gt;x^2&gt;x\log_2x&gt;x$

So I think that $\Theta(2^\sqrt{n})$ is practical and "good" as $\Theta(n\log n)$ is, although both of them are not polynomial by definition.

Am I right?
Complexity is how an algorithm increases its number of steps in comparison to $n$ when we scale $n$ to a large value.

For very small $n$ , an algorithm with complexity $\Theta(2^\sqrt{n})$ can behave nearly as good as an algorithm running in polynomial time.But if we increase the $n$ , then certainly the algorithm with polynomial time will give much faster results.That's how algorithms are compared.One important thing to remember is that your $n$ is a variable related to input size and if this occurs as a power of something in time complexity then you can be sure that the algorithm is going to take a lot of time for large values of $n$.

$\Theta(2^\sqrt{n})$ is not as good as $\Theta(n\log n)$