NumPy provides a wide range of functions and tools to perform various mathematical operations on arrays and matrices efficiently. One of the most common operations is **exponentiation**, which is *the process of raising a number to a given power*. In this article, we will explore how to compute the cubic power of a large vector using two different NumPy methods.

If you want to compute the square of a vector (large or small), you can check out this article.

#### 1. Using the “** operator”:

This code generates a random vector of length `100000000`

using NumPy’s `random.rand()`

function. Then, it raises each element of the vector to the power of 3 using the `** operator`

. Finally, it displays the first five elements of the resulting vector.

#### 2. Using the “np.multiply()” function with the same array:

This code creates a NumPy array “Z” of length `1000000`

with random values between 0 and 1. It then raises each element of “Z” to the power of 3 using the `multiply()`

function, which is equivalent to using the `** operator`

. Finally, it stores the result in a new array “Z_cubed” and prints out the first five elements of this array.

- This method involves two calls to the multiply function and may be slower for very large vectors.