Data-Discriminants of Likelihood Equations

Maximum likelihood estimation (MLE) is a fundamental computational problem in statistics. The problem is to maximize the likelihood function with respect to given data on a statistical model. An algebraic approach to this problem is to solve a very structured parameterized polynomial system called likelihood equations. For general choices of data, the number of complex solutions to the likelihood equations is finite and called the ML-degree of the model. The only solutions to the likelihood equations that are statistically meaningful are the real/positive solutions. However, the number of real/positive solutions is not characterized by the ML-degree. We use discriminants to classify data according to the number of real/positive solutions of the likelihood equations. We call these discriminants data-discriminants (DD). We develop a probabilistic algorithm for computing DDs. Experimental results show that, for the benchmarks we have tried, the probabilistic algorithm is more efficient than the standard elimination algorithm. Based on the computational results, we discuss the real root classification problem for the 3 by 3 symmetric matrix~model.Comment: 2 table

Cloud for Gaming

Cloud for Gaming refers to the use of cloud computing technologies to build large-scale gaming infrastructures, with the goal of improving scalability and responsiveness, improve the user's experience and enable new business models.Comment: Encyclopedia of Computer Graphics and Games. Newton Lee (Editor). Springer International Publishing, 2015, ISBN 978-3-319-08234-

Update of axion CDM energy density

We improve the estimate of the axion CDM energy density by considering the new values of current quark masses, the QCD phase transition effect and a possible anharmonic effect.Comment: 7 pages, 6 figures. References are added. A factor is correcte

Vortex fluctuations in superconducting La-Sr-Cu-O

Vortex fluctuations in the $La_{2-x}Sr_{x}CuO_{4+\delta}$ system have been studied as a function of magnetic field, temperature and carrier concentration in order to determine the dimensionality of the fluctuations. For a $x=0.10$ sample, there is a unique crossing-temperature on the magnetization vs. temperature plots for all magnetic fields up to 7 T, and the data scale very well with 2D fluctuation theory. At lower x-values where $H_{c2}$ is much smaller, there are two well defined crossing points, one at low fields (typically less than 1 T) and another at high fields (typically 3-7 T). A fit of the data to fluctuation theory shows that the low field crossing data scale as 2D fluctuations and the high field crossing data scale as 3D fluctuations. It would appear that as the magnetic field approaches $H_{c2}$, there is a 2D to 3D cross-over where the low field 2D pancake vortex structure transforms into a 3D vortex structure

Complements of hypersurfaces, variation maps and minimal models of arrangements

We prove the minimality of the CW-complex structure for complements of hyperplane arrangements in $\mathbb C^n$ by using the theory of Lefschetz pencils and results on the variation maps within a pencil of hyperplanes. This also provides a method to compute the Betti numbers of complements of arrangements via global polar invariants