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Register a new userBounds on determinants of perturbed diagonal matrices
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We give upper and lower bounds on the determinant of a perturbation of the identity matrix or, more generally, a perturbation of a nonsingular diagonal matrix. The matrices considered are, in general, diagonally dominant. The lower bounds are best possible, and in several cases they are stronger than well-known bounds due to Ostrowski and other authors. If $A = I-E$ is an $n times n$ matrix and the elements of $E$ are bounded in absolute value by $varepsilon le 1/n$, then a lower bound of Ostrowski (1938) is $det(A) ge 1-nvarepsilon$. We show that if, in addition, the diagonal elements of $E$ are zero, then a best-possible lower bound is [det(A) ge (1-(n-1)varepsilon),(1+varepsilon)^{n-1}.] Corresponding upper bounds are respectively [det(A) le (1 + 2varepsilon + nvarepsilon^2)^{n/2}] and [det(A) le (1 + (n-1)varepsilon^2)^{n/2}.] The first upper bound is stronger than Ostrowskis bound (for $varepsilon < 1/n$) $det(A) le (1 - nvarepsilon)^{-1}$. The second upper bound generalises Hadamards inequality, which is the case $varepsilon = 1$. A necessary and sufficient condition for our upper bounds to be best possible for matrices of order $n$ and all positive $varepsilon$ is the existence of a skew-Hadamard matrix of order $n$.
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Let ${mathcal D}(n)$ be the maximal determinant for $n times n$ ${pm 1}$-matrices, and $mathcal R(n) = {mathcal D}(n)/n^{n/2}$ be the ratio of ${mathcal D}(n)$ to the Hadamard upper bound. Using the probabilistic method, we prove new lower bounds on ${mathcal D}(n)$ and $mathcal R(n)$ in terms of $d = n-h$, where $h$ is the order of a Hadamard matrix and $h$ is maximal subject to $h le n$. For example, $mathcal R(n) > (pi e/2)^{-d/2}$ if $1 le d le 3$, and $mathcal R(n) > (pi e/2)^{-d/2}(1 - d^2(pi/(2h))^{1/2})$ if $d > 3$. By a recent result of Livinskyi, $d^2/h^{1/2} to 0$ as $n to infty$, so the second bound is close to $(pi e/2)^{-d/2}$ for large $n$. Previous lower bounds tended to zero as $n to infty$ with $d$ fixed, except in the cases $d in {0,1}$. For $d ge 2$, our bounds are better for all sufficiently large $n$. If the Hadamard conjecture is true, then $d le 3$, so the first bound above shows that $mathcal R(n)$ is bounded below by a positive constant $(pi e/2)^{-3/2} > 0.1133$.
Let $D(n)$ be the maximal determinant for $n times n$ ${pm 1}$-matrices, and ${mathcal R}(n) = D(n)/n^{n/2}$ be the ratio of $D(n)$ to the Hadamard upper bound. We give several new lower bounds on ${mathcal R}(n)$ in terms of $d$, where $n = h+d$, $h$ is the order of a Hadamard matrix, and $h$ is maximal subject to $h le n$. A relatively simple bound is [{mathcal R}(n) ge left(frac{2}{pi e}right)^{d/2} left(1 - d^2left(frac{pi}{2h}right)^{1/2}right) ;text{ for all }; n ge 1.] An asymptotically sharper bound is [{mathcal R}(n) ge left(frac{2}{pi e}right)^{d/2} expleft(dleft(frac{pi}{2h}right)^{1/2} + ; Oleft(frac{d^{5/3}}{h^{2/3}}right)right).] We also show that [{mathcal R}(n) ge left(frac{2}{pi e}right)^{d/2}] if $n ge n_0$ and $n_0$ is sufficiently large, the threshold $n_0$ being independent of $d$, or for all $nge 1$ if $0 le d le 3$ (which would follow from the Hadamard conjecture). The proofs depend on the probabilistic method, and generalise previous results that were restricted to the cases $d=0$ and $d=1$.
Due to their importance in both data analysis and numerical algorithms, low rank approximations have recently been widely studied. They enable the handling of very large matrices. Tight error bounds for the computationally efficient Gaussian elimination based methods (skeleton approximations) are available. In practice, these bounds are useful for matrices with singular values which decrease quickly. Using the Chebyshev norm, this paper provides improved bounds for the errors of the matrix elements. These bounds are substantially better in the practically relevant cases where the eigenvalues decrease polynomially. Results are proven for general real rectangular matrices. Even stronger bounds are obtained for symmetric positive definite matrices. A simple example is given, comparing these new bounds to earlier ones.
Let ngeq3 and J_{n}:=circ(J_{1},J_{2},...,J_{n}) and j_{n}:=circ(j_{0},j_{1},...,j_{n-1}) be the ntimesn circulant matrices, associated with the nth Jacobsthal number J_{n} and the nth Jacobsthal-Lucas number j_{n}, respectively. The determinants of J_{n} and j_{n} are obtained in terms of the Jacobsthal and Jacobsthal-Lucas numbers. These imply that J_{n} and j_{n} are invertible. We also derive the inverses of J_{n} and j_{n}.
This note contains two remarks. The first remark concerns the extension of the well-known Cayley representation of rotation matrices by skew symmetric matrices to rotation matrices admitting -1 as an eigenvalue and then to all orthogonal matrices. We review a method due to Hermann Weyl and another method involving multiplication by a diagonal matrix whose entries are +1 or -1. The second remark has to do with ways of flipping the signs of the entries of a diagonal matrix, C, with nonzero diagonal entries, obtaining a new matrix, E, so that E + A is invertible, where A is any given matrix (invertible or not).
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