Related papers: Wolfenstein Parametrization at Higher Order: Seemi…
Based on the relation between CP-violation phase and the other three mixing angles in Cabibbo-Kobayashi-Maskawa matrix postulated by us before, a new constraint on the parameters of Wolfenstein's parametrization is given. The result is…
The Wolfenstein parametrization of the $3\times 3$ Kobayashi-Maskawa (KM) matrix $V$ is modified by keeping its unitarity up to the accuracy of $O(\lambda^{6})$. This modification can self-consistently lead to the off-diagonal asymmetry of…
An analysis of Wolfenstein parametrization for the Kobayashi-Maskawa matrix shows that it has a serious flaw: it depends on {\em three} independent parameters instead of {\em four} as it should be. Because this approximation is currently…
Recent works show that the original Kobayashi-Maskawa (KM) form of fermion mixing matrix exhibits some advantages, especially when discussing problems such as unitarity boomerangs and maximal CP violation hypothesis. Therefore, the KM form…
The CKM matrix is not generic. The Wolfenstein parametrization encodes structure by having one small parameter, $\lambda \approx 0.22$. We pose the question: is there substructure in the CKM matrix that goes beyond the single small…
The higher order matching problem is the problem of determining whether a term is an instance of another in the simply typed $\lambda$-calculus, i.e. to solve the equation a = b where a and b are simply typed $\lambda$-terms and b is…
Some fine differences between the twin $b$-flavored unitarity triangles are calculated by means of a generalized Wolfenstein parametrization of the CKM matrix, and a possibility of experimentally establishing the second triangle is briefly…
Vecchia's approximate likelihood for Gaussian process parameters depends on how the observations are ordered, which can be viewed as a deficiency because the exact likelihood is permutation-invariant. This article takes the alternative…
Higher-order processes with parameterization are capable of abstraction and application (migrated from the lambda-calculus), and thus are computationally more expressive. For the minimal higher-order concurrency, it is well-known that the…
Based on a geometric postulation on the weak CP phase in Cabibbo-Kobayashi-Maskawa (CKM) matrix, a positive rho is asserted. Besides, 0.18<eta<0.54 and 0.048<rho<0.140 are permitted by the present data. The corresponding geometric…
The problem of approximating a matrix by a low-rank one has been extensively studied. This problem assumes, however, that the whole matrix has a low-rank structure. This assumption is often false for real-world matrices. We consider the…
We provide a framework and algorithm for tuning the hyperparameters of the Graphical Lasso via a bilevel optimization problem solved with a first-order method. In particular, we derive the Jacobian of the Graphical Lasso solution with…
The task of reconstructing a matrix given a sample of observedentries is known as the matrix completion problem. It arises ina wide range of problems, including recommender systems, collaborativefiltering, dimensionality reduction, image…
We introduce a generalized framework for studying higher-order versions of the multiscale method known as Localized Orthogonal Decomposition. Through a suitable reformulation, we are able to accommodate both conforming and nonconforming…
Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Either the set of matrices with a given rank can be explicitly…
The solvability in Sobolev spaces is proved for divergence form complex-valued higher order parabolic systems in the whole space, on a half space, and on a Reifenberg flat domain. The leading coefficients are assumed to be merely measurable…
We propose a multiscale approach for an elliptic multiscale setting with general unstructured diffusion coefficients that is able to achieve high-order convergence rates with respect to the mesh parameter and the polynomial degree. The…
The Newton, Gauss--Newton and Levenberg--Marquardt methods all use the first derivative of a vector function (the Jacobian) to minimise its sum of squares. When the Jacobian matrix is ill-conditioned, the function varies much faster in some…
We propose a new parametrisation of the Cabibbo-Kobayashi-Maskawa Matrix in which the approximations of the standard parametrisation, $|V_{cb}|\approx s_{23}$, $|V_{us}|\approx s_{12}$, are promoted to exact results.
We consider the task of aligning two sets of points in high dimension, which has many applications in natural language processing and computer vision. As an example, it was recently shown that it is possible to infer a bilingual lexicon,…