sqrt

It turns out you only need O(sqrt(2^n)) queries (rotations), so it's a substantial improvement over the classical case.

And when you think about sample size, the accuracy with respect to the population follows 1/sqrt(n).

So if D is large then collisions will be a problem when n approaches sqrt(D).

The birthday problem dictates that you start getting collisions after ~sqrt(D) random entries.

You should almost always be using d3.scale.sqrt() as you're comparing area, also zero in the domain should usually map to zero on the range.

Right, but the escape velocity is ~ radius * sqrt(density) anyway, and if you look at the equation for the Earth Similarity Index[0], each term has an associated weighting.

Imagine if this was called someObj.sqrt(x).

(I didn't localize the math.sqrt but I know LuaJIT wouldn't care.) * Oops, I had cheated and used a for loop instead of while.

If a group has a tendency to enter a powerful role with probability p, and there are N members of this group, then the shifts in power distribution will have standard deviation (in percentage terms) of 1/sqrt(Np(1-p)).

However, after swapping out the Float only capable square root from Swift Foundation for the C sqrt function, leaving the rest of the code identical, the execution time on the Swift code went down to 35 seconds, basically identical.

Unfortunately, you don't have the luxury of picking the vector that has a coordinate of 1/sqrt(2^n) in each direction, and observing what the black box does to that after a single application, since when you observe your quantum register you always observe a classical state.

For example to solve x=x^2 if you iterate x_(n+1)=x_n^2 then you obtain the solution 0 (in case your initial x is between -1 and 1), then you thing about looking for x = sqrt(x) and discover that it converges to 1 if you choose x1 > 1.

The Pythonic way to calculate the magnitude is something like: math.sqrt(sum((i**2 for i in numbers))) Using "with" to calculate a magnitude would be tortuous at best and it certainly wouldn't result in idiomatic code.

So "sum under square" really is doing "sqrt(sum(square(vector)))", and more generally "(a under b) x" does "b^-1(a(b(x)))".

"miniature 4-function calculators": make that 5, where the fifth function is a really fast special function unit that can do very fast sin, cos, sqrt, 1/sqrt, and many other functions.

To achieve conservation of mass, we consider the "inertial mass" of an object instead of the classical mass, where the intertial mass is given by: m'=ym y=1/sqrt(1-(v/c)^2) As you can see, y>1 and y approaches infinity as you speed approaches the speed of light.