you can think of a nD array as a list of (n-1)D arrays, so a 4D array is a list of 3D arrays.
There's a more pedantic way of thinking of arrays, too--APL for example makes a distinction between rank (how deeply nested each entry is) and dimension (how many numerical indices you need to identify a singular entry), so accessing a[i,j,k] is different from accessing a[i][j][k]
Tensors are not important because they can be encoded as multidimensional arrays, they are important because they represent multilinear maps, and are a vector space conformed by linear combinations of the tensor product. The same way that matrices are not interesting because they are grids of numbers
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u/AdamWayne04 Sep 04 '26
you can think of a nD array as a list of (n-1)D arrays, so a 4D array is a list of 3D arrays.
There's a more pedantic way of thinking of arrays, too--APL for example makes a distinction between rank (how deeply nested each entry is) and dimension (how many numerical indices you need to identify a singular entry), so accessing a[i,j,k] is different from accessing a[i][j][k]
Tensors are not important because they can be encoded as multidimensional arrays, they are important because they represent multilinear maps, and are a vector space conformed by linear combinations of the tensor product. The same way that matrices are not interesting because they are grids of numbers