[HN Gopher] Mathematicians prove Polya's conjecture for the eige...
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       Mathematicians prove Polya's conjecture for the eigenvalues of a
       disk
        
       Author : rbanffy
       Score  : 187 points
       Date   : 2024-03-02 12:27 UTC (10 hours ago)
        
 (HTM) web link (phys.org)
 (TXT) w3m dump (phys.org)
        
       | VyseofArcadia wrote:
       | arXiv link: https://arxiv.org/abs/2203.07696
        
       | snitty wrote:
       | Mathematicians prove that you can deduce the shape of disk based
       | on the frequencies it produces when you hit it with a stick.
        
         | m3kw9 wrote:
         | Useful as a magic trick, guessing the shape of your disc when
         | you hit it
        
         | kadoban wrote:
         | I can deduce the disk's shape without even hitting it. It's a
         | disk.
        
         | gus_massa wrote:
         | The first sentense is very misleading:
         | 
         | > _Is it possible to deduce the shape of a drum from the sounds
         | it makes?_
         | 
         | That's a known problem with a (very nice) negative answer
         | https://www.ams.org/publicoutreach/feature-column/fcarc-1997...
         | 
         | IIUC this article is about the problem in the other direction,
         | i.e. from the shape (a disk!) to the frecuencies of the sound
         | (eigenvalues).It's not about an exact calculation, but about an
         | aproximation of them.
         | 
         | > _The conjecture bears on the estimation of the frequencies of
         | a round drum or, in mathematical terms, the eigenvalues of a
         | disk._
         | 
         | From the research paper:
         | 
         | > _The celebrated Polya's conjecture (1954) in spectral
         | geometry states that the eigenvalue counting functions of the
         | Dirichlet and Neumann Laplacian on a bounded Euclidean domain
         | can be estimated from above and below, respectively, by the
         | leading term of Weyl's asymptotics._
         | 
         | <guessing> The Weyl's asymtotics is probably a good estimation
         | of the very high frecuencies/eigenvalues, and the conjeture is
         | probabbly that you can use the estimation as upper or lower
         | bounds instead of just an aproximation.<guessing> [Sorry, not
         | my area and I have not enough time to read the paper.]
        
       | mikhailfranco wrote:
       | The title words remind of an unrelated fact, Gershgorin Disks:
       | The eigenvalues of any N x N matrix, A,        are contained in
       | the union of N discs in the complex plane.        The center of
       | the i_th disc is the i_th diagonal element of A.        The
       | radius of the i_th disc is the absolute values        of the off-
       | diagonal elements in the i_th row.
       | 
       | https://blogs.sas.com/content/iml/2019/05/22/gershgorin-disc...
       | 
       | It's rather remarkable, unexpected, and perhaps shocking, when
       | you first hear it. There does not seem to be enough information
       | to make it true. But it is.
       | 
       | I used it in a real project to cancel noise.
        
         | frutiger wrote:
         | Sounds very cool. One thing I didn't understand though:
         | 
         | > The radius of the i_th disc is the absolute values
         | 
         | How can a radius of a single disc (i.e. a single value)
         | correspond to multiple values?
        
           | reactordev wrote:
           | I'm assuming, but could be wrong as my matrix math ended with
           | GameDev, that the radius of the disk = the absolute values of
           | the other things. +\\- depending on which side of the disk
           | they fall?
           | 
           | That line got me as well.
        
             | Sharlin wrote:
             | It's missing the word "sum". Which apparently my brain
             | auto-deduced for me because I didn't notice anything off in
             | the sentence on the first reading.
        
               | _zoltan_ wrote:
               | My brain also automatically added sum and also haven't
               | noticed anything, but I have a math degree, maybe it's
               | just assuming things :-)
        
               | frutiger wrote:
               | I have a physics degree and did not assume it, that might
               | explain the difference :)
        
           | ximeng wrote:
           | If you look at the link there's a formula showing it's the
           | sum.
        
             | abetusk wrote:
             | Specifically:                   r_i = \sum_{i \ne j} |A_{i
             | j}|
        
           | tomrod wrote:
           | Sum the absolute values of a row for all the off diagonal
           | elements
        
           | Infinity315 wrote:
           | An intuitive explaination is imagine a nearly diagonal matrix
           | where the values along the diagonal are much larger than
           | values on the off diagonal. We know the eigenvalues of a
           | diagonal matrix is simply the values on the diagonal, so for
           | nearly diagonal matrices you can be pretty sure that the true
           | eigenvalues are going to be pretty close to those diagonal
           | entries, but a natural question to ask is how far we'd
           | deviate from those diagonal entries.
           | 
           | The answer to the above question is Gerschgorin disks and
           | it's closely related cousin Brauer's Oval of Cassini.
           | 
           | For matrices with real eigenvalues it's moreso along the real
           | number line, only for cases where the eigenvalues are
           | imaginary do we imagine disks.
        
         | abetusk wrote:
         | What was the noise cancelling project? How did you use this
         | fact to cancel noise?
        
           | sdenton4 wrote:
           | Just guessing, but....
           | 
           | A common noise cancellation technique is to throw away small
           | eigenvalues, as in PCA. This result relates eigenvalues to
           | the structure of the matrix, so might be helpful for reducing
           | ev's without bothering with diagonalization?
           | 
           | [Edit] This would presumably involve just zeroing out the
           | rows with small diagonal elements and small-ish off-diagonal
           | norm... Center the eigenvalue estimate disk at zero, and then
           | zero out the rest of the row to make the estimate exact.
        
             | sdenton4 wrote:
             | (and after one more thought about it, one would zero out
             | the row /and column/ to preserve the symmetry of the
             | matrix, if applicable, and thus keep the eigenvalues real.
             | and one would probably want to think a bit about whether
             | this kind of deletion actually makes sense for the
             | problem... doing real PCA isn't /that/ hard in most cases -
             | I think I would do something this janky only for extremely
             | large matrices or for realtime operation on a
             | microcontroller or something, and then only after thinking
             | hard about it.)
        
         | jonathan_landy wrote:
         | Matrix theory by Franklin is a great, affordable book
         | containing many interesting results such as this -- can highly
         | recommend for those interested in linear algebra.
         | 
         | https://www.amazon.com/Matrix-Theory-Dover-Books-Mathematics...
        
           | packetlost wrote:
           | If I have an atrophied high school level understanding of
           | linear algebra, will I get anything out of that book?
        
             | jonathan_landy wrote:
             | Certainly a useful reference, if you might deal with the
             | topic for some project ... but not the best refresher out
             | there for the basics.
        
           | doubloon wrote:
           | or
           | 
           | https://store.doverpublications.com/products/9780486411798
        
           | homerowilson wrote:
           | You may enjoy this:
           | 
           | https://bwlewis.github.io/cassini/
        
           | kwkelly wrote:
           | Matrix Analysis by Horn and Johnson is another great book,
           | though it is a bit pricier than a Dover book.
        
         | stabbles wrote:
         | It's not that remarkable at all? The proof requires the
         | definition and triangle inequality, that's all?
         | 
         | Given Ax=lx, take i for which |x| is largest. Look at the i'th
         | equation: sum ax = lx, move the ax term to the rhs, take
         | absolute values, divide by |x|, apply triangle inequality, and
         | you have |a - l| <= sum |a| over j[?]i. So for every eigenvalue
         | you can find such a disc.
         | 
         | That's by column, for row use A.
        
           | kmm wrote:
           | Being easy to prove doesn't make it unremarkable. Lots of
           | theorems, including this one, have straightforward proofs
           | once you are given the exact formulation. The tricky part is
           | coming up with the idea for the theorem itself. I remember
           | being (mildly) shocked when I was taught this in undergrad,
           | it just seemed too good to be true.
        
             | stabbles wrote:
             | I think that's just how textbooks present it. A fact is
             | stated but you're lacking intuition.
             | 
             | If you had played around a bit with Laplacian matrices,
             | like tri-diagonal matrices with stencil [-1, 2, -1], and
             | found that its eigenvalues are within 2 +- 2, and if you
             | also realized that A + tI has the same eigenvalues shifted
             | by t, then it's a small step to consider that the magnitude
             | of the off-diagonal may have something to do with the
             | spread of eigenvalues.
             | 
             | It's likely that Gerschgorin stumbled upon it like this.
        
             | llmzero wrote:
             | Just thinking about some intuition for the result of the
             | theorem: If the off diagonal elements are zero then the
             | diagonal element is an eigenvalue, by continuity of the
             | determinant, if the off diagonal element are small then
             | $det(A-a_{ii}\lambda)$ is almost zero, that is the new
             | eigenvalue is near aii. So it suggests that the off
             | diagonal elements measure how far is aii from being an
             | eigenvalue.
        
           | nine_k wrote:
           | The Euler's identity is also trivial to deduce, but this
           | doesn't diminish its beauty.
        
             | xanderlewis wrote:
             | The Yoneda lemma is another great example of _(once you 've
             | got the right setup) trivial but beautiful_
        
           | moralestapia wrote:
           | Huh?
           | 
           | Math 101, simple is better.
        
           | jonahx wrote:
           | removed
        
             | tsimionescu wrote:
             | They are saying that the Greshgorin theorem that the OP is
             | talking about is simple to prove, not the Polya conjecture
             | that took 70 years from the article.
        
         | bee_rider wrote:
         | It has an intuitive element to it; we're looking for the
         | eigenvalue, the vector/scalar pair where the scalar has the
         | same effect on the vector as multiplying by the matrix. And
         | we're comparing against something that looks vaguely like the
         | magnitude of the matrix (shifted by the diagonal, and of course
         | if you had a diagonal matrix, the eigenvalues would just be the
         | diagonal).
         | 
         | Not a proof or anything, of course the proof is on Wikipedia
         | and nice and elegant. Just a thought on the gut feeling.
         | 
         | I agree that it is a very nice result.
        
         | Infinity315 wrote:
         | See also Brauer's oval of Cassini which give an equivalent or
         | even better approximation of the eigenvalues of a matrix.
        
       | esafak wrote:
       | I haven't read the paper, but does it apply to arbitrarily shaped
       | drums? And if the basis can be arbitrarily large, is this an
       | exciting result? It just says that the spectral domain is
       | isomorphic?
        
         | eigenket wrote:
         | This result only applies to circular disks, spherical balls and
         | their generalisations in higher dimensions. Previously it was
         | known for shapes which tile the plane or tessellate the space
         | in higher dimensions.
        
       | perihelions wrote:
       | What do the eigenfunctions look like? I didn't know the circular
       | disk was such an exotic problem for Laplace's equation.
       | 
       | edit: Ah, I misunderstood the problem. The eigenfunctions _are_
       | exactly solved; the problem of _sorting and ordering_ their
       | eigenvalues is apparently not! From their page 4,
       | 
       | - _" Although all the eigenvalues of the Dirichlet and Neumann
       | Laplacians on the unit disk are explicitly known in terms of
       | zeros of the Bessel functions or their derivatives, see SS2
       | below, in each case the spectrum is given by a two-parametric
       | family, and rearranging it into a single monotone sequence
       | appears to be an unfeasible task."_
       | 
       | https://arxiv.org/abs/2203.07696
        
       | colesantiago wrote:
       | Nice, what are the potential use cases for this? Can I use this
       | for my business?
        
         | colesantiago wrote:
         | This is a valid question????
        
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