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Apr
14
comment How do we identify twin primes .
"Square root of the square root"- so basically the square root of the possible prime? How then is that better than trial division?
Apr
14
reviewed Reject How to evaluate the length of the perimeter of a low eccentricity ellipse?
Apr
13
comment Solving for the trace of a matrix
I think you are correct on both accounts, except I believe $\operatorname{vec}(D^{-1})$ should be $\operatorname{vec}(D^{-\top})$ in your last comment.
Mar
22
comment Function (algorithm) for obtaining random number(s) from dice
search term for you, arithmetic encoding.
Mar
22
reviewed Approve Is there any formula for number of divisors of $a \times b$?
Mar
13
comment Eigenvalue of anti triangular block matrix (skew matrix?)
@AlexHirzel Actually it isn't the square roots that would be helpful. I was thinking of the matrix form of the quadratic equation. Sounds to me that is the determinant of it that you want. I am not sure of any constraints that would be useful.
Mar
11
comment Eigenvalue of anti triangular block matrix (skew matrix?)
@AlexHirzel The quadratic formula does not work for matrices, short reason is square roots. Here is a question (with more links) discussing it.
Feb
7
comment Determinant of the symmetric part of a matrix.
There is pythagorean like relationship so for instance a triangle inequality can be used for the magnitude of the determinants.
Jan
28
comment How can I evaluate $\sum_{n=0}^\infty (n+1)x^n$
your link is broken.
Dec
9
awarded  Caucus
Nov
22
comment How to determine the smallest interpolation degree required?
Use progressive interpolation. When the degree is reached, the new points to interpolate will already be interpolated.
Oct
18
revised How to build a orthogonal basis from a vector?
some sign errors
Oct
15
comment Orthogonal Vectors in a 2D Lattice with minimum area
Minimizing a determinant interestingly enough is the same as lattice reduction, at least for two by two. I believe that is the case anyway from my memories of past musings... Think in terms of orthogonalizing the two vectors (so basically swap two elements of one vector, determinant becomes dot product of the two vectors)
Oct
15
comment Orthogonal Vectors in a 2D Lattice with minimum area
Now I see though that $i$ or $k$ zero is the same thing which you did note.
Oct
15
comment Orthogonal Vectors in a 2D Lattice with minimum area
My thought is that only $A$ and $B$ need be linearly dependent (or $B$ and $C$) in order to find orthogonal vectors.
Oct
15
comment Orthogonal Vectors in a 2D Lattice with minimum area
For this problem, one need not look only at the Gram matrix since the orthogonal vectors need not be in the same basis, only in the same lattice. I would guess that you have such a habit of using the Gram matrix from looking at binary quadratic forms.
Oct
14
comment Non square inversion
a pseudoinverse would work. In this case where there is an exact solution, you could also look at each column separately. Column 1 gives two equations,$0=0$ and $0.5 k_{x1} = -1$
Oct
12
answered Mathematical expression to form a vector from diagonal elements
Sep
30
awarded  Yearling
Sep
30
awarded  Explainer