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Paulo Manrique-Mirón

Publications and source records attributed to Paulo Manrique-Mirón.

3 recordsLinked to original sources

Angle between two random segments

The study of \textit{random segments} is a classical problem in geometrical probability whose answer depends on the mechanism used to generate the segments. We consider four independent random points uniformly distributed in the unit disk and form the two labeled segments $S_{AB}$ and $S_{CD}$. The random variable of interest is the usual angle in $[0,π]$ between the vectors $B-A$ and $D-C$, conditional on the event that the two segments intersect. By introducing normal and tangential coordinates for each supporting line, we obtain an integral expression for the conditional density. The signed tangential coordinate of the intersection point is retained throughout the argument, which prevents the reflected-root overcounting that arises when only its squared norm is used. The same change of variables also recovers known distributions for the distance of a random chord from the center and for the length of a random segment. The resulting intersection probability is $\frac{1}{3}\left(1-\frac{35}{12π^2}\right)$.

math.PR↗

Condition Number of Random Tridiagonal Toeplitz Matrix

In this manuscript it is considered the eigenvalues $λ_j$ of a random tridiagonal Toeplitz matrix $T$. We study the asymptotic behavior of the joint distribution of $({|λ|_{\min} ,|λ|_{\max}})$. From this, we obtain the asymptotic distribution of the condition number when $T$ is symmetric. In the non-symmetric case, we understand well the singularity of the matrix and can give some good estimation of its condition number. It is remarkable that in both these cases, it is only necessary to consider two or three random variables, but this simplicity is apparent since the structure of the tridiagonal Toeplitz matrix provides non-trivial relation between them, which also induce the asymptotic behavior is completely determined by these input random variables. Also, we want to remark that our results are satisfied under mild conditions on the random variables.

math.PR↗

The asymptotic distribution of the condition number for random circulant matrices

In this manuscript, we study the limiting distribution for the joint law of the largest and the smallest singular values for random circulant matrices with generating sequence given by independent and identically distributed random elements satisfying the so-called Lyapunov condition. Under an appropriated normalization, the joint law of the extremal singular values converges in distribution, as the matrix dimension tends to infinity, to an independent product of Rayleigh and Gumbel laws. The latter implies that a normalized condition number converges in distribution to a Fréchet law as the dimension of the matrix increases.

math.PR↗