bio | website | |
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location | ||
age | ||
visits | member for | 5 years, 5 months |
seen | Jul 16 at 7:14 | |
stats | profile views | 935 |
1. Postdoctoral researcher in quantum informatics (concerning efficient algorithms to describe quantum mechanical systems, and/or how to use quantum mechanical systems to implement efficient algorithms).
2. Lover of toy problems and charicatures of The Big Picture alike, with a special interest in combinatorics, algebra, and phase transitions between them.
3. Lifelong enthusiast of mathematics.
2. Lover of toy problems and charicatures of The Big Picture alike, with a special interest in combinatorics, algebra, and phase transitions between them.
3. Lifelong enthusiast of mathematics.
Sep 24 |
awarded | Autobiographer |
Jul 2 |
awarded | Curious |
Apr 15 |
awarded | Popular Question |
Feb 2 |
awarded | Yearling |
Oct 17 |
accepted | Condition number of a random 0-1 matrix |
Oct 17 |
comment |
Condition number of a random 0-1 matrix
Because it's clear that this answer is still morally correct --- the 01 case is after all related to the symmetric case by a displacement by the all-1s matrix, which is very nearly orthogonal to all singular vectors but those of the largest singular value --- I'm accepting this answer. Perhaps these results also pertain exactly to the 01 case, though it's a bit frustrating that my certainty about this is undermined by a tacit but undeniable assumption of symmetry elsewhere in this work, which prevents me from being certain of the precise probabilistic lower bounds. |
Oct 15 |
comment |
Condition number of a random 0-1 matrix
Unfortunately, it is difficult to tell whether or not the results in Lecture 18 of Vershynin's notes apply. While these would be the sort of results that I want, a casual glance at the notes of Lecture 7 imply that he might be implicitly restricting to subgaussian distributions with mean 0. My Bernoulli variables have mean $\frac12$, of course, and while I can see how to translate the results for the largest singular value, I do not know how to perform this translation for the minimum singular value. Can you point me to results which explicitly accomodate distributions with non-zero mean? |
Oct 15 |
comment |
Condition number of a random 0-1 matrix
This seems like an interesting tangent, but I don't detect the relation to the Bernoulli variables which I consider. I suppose asymptotically the matrix $A^{\mathsf T} A$ will look as though it has Gaussian coefficients, but as I think you're hinting (to a deleted comment?) in a comment to the original question, these are not independent. |
Oct 14 |
asked | Condition number of a random 0-1 matrix |
Feb 2 |
awarded | Yearling |
Feb 1 |
asked | Presentation of tree decompositions (and related concepts) in terms of continuous maps? |
Nov 7 |
revised |
Matrices that are > 1 in a sense
Replaced all references with the 2-norm by Frobenius norm. |
Nov 7 |
comment |
Matrices that are > 1 in a sense
@Suvrit: good point. I'm used to dealing almost exclusively with normal operators, so the fact that they are not in fact equivalent in general had not occurred to me. I'll edit the answer. |
Oct 26 |
awarded | Enthusiast |
Oct 17 |
revised |
Matrices that are > 1 in a sense
Fixed typo |
Oct 17 |
revised |
Matrices that are > 1 in a sense
Revised to answer the question for right-multiplication, and to work more directly with singular vectors |
Oct 16 |
answered | Matrices that are > 1 in a sense |
Oct 11 |
revised |
How does the Schmidt decomposition generalize to tensor products of several finite-dimensional systems?
fixed typo, revised definitions of variables |
Oct 11 |
revised |
How does the Schmidt decomposition generalize to tensor products of several finite-dimensional systems?
added 191 characters in body |
Oct 11 |
asked | How does the Schmidt decomposition generalize to tensor products of several finite-dimensional systems? |