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 Apr 28 awarded Popular Question Jul 2 awarded Curious Mar 16 accepted Diagonalization of $M=ab^t+ba^t$ Mar 5 awarded Yearling Jan 13 comment Diagonalization of $M=ab^t+ba^t$ @yoirgos: thanks ! Can you conclude and give the values of $\lambda_1$ and $\lambda_2$ and the formula for the associated eigenvectors ? Jan 13 asked Diagonalization of $M=ab^t+ba^t$ Jan 16 revised What is the definition of front propagation? added 57 characters in body Jan 16 asked What is the definition of front propagation? Oct 25 comment Approximation of stochastic differential equations @TheBridge : thanks. Of course studying z_t and applying Gronwall Lemma is the classical strategy. But here the problem is that you cannot bound the Lipschitz coefficient because it is only assumed locally lipschitz... Oct 24 asked Approximation of stochastic differential equations Aug 14 awarded Tumbleweed Jul 8 accepted spectral norm of random matrix Jul 6 awarded Nice Question May 2 awarded Commentator May 2 accepted Linear inhomogeneous PDE May 2 comment Linear inhomogeneous PDE Thnak you! I give you the answer. May 1 comment Linear inhomogeneous PDE Thank you very much. I think your value of $\lambda^*$ slightly overestimates the real one. This is maybe because $\bar{u}-u$ is not completely negligible as you mentioned. How could we improve your estimate ? May 1 asked Linear inhomogeneous PDE May 1 comment Eigenvalues of the 1D laplacian with mixed boundary conditions @GiuseppeNegro Thank you! It confirms my first intuition then. So I guess we cannot solve $u=\Delta u$ with such B.C. using the usual separation of variable method... Because when doing so, we decompose the solution along the eigenvectors, and here without a discrete spectrum I do not know how to do it. Apr 30 comment Eigenvalues of the 1D laplacian with mixed boundary conditions @GiuseppeNegro Hi, thanks for the hint; I tried this already. I find a zero eigenvalue (ok) but then I cannot exclude positive eigenvalues, and I do not get a discrete spectrum. So I believe I may be wrong.