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 Apr 25 awarded Nice Question Nov 24 reviewed Approve Let $f:A \rightarrow B$ and C ⊂A. Define f[C]={b∈B: b=f(a) for some a∈C}. Prove or disprove each of the statement Nov 15 awarded Popular Question Oct 8 awarded Revival Sep 30 awarded Yearling 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. 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.