Related papers: A Flexible Parametrization of CKM matrix via Singu…

In this paper, we present a fast implementation of the Singular Value Thresholding (SVT) algorithm for matrix completion. A rank-revealing randomized singular value decomposition (R3SVD) algorithm is used to adaptively carry out partial…

Two harmonic extraction based Jacobi--Davidson (JD) type algorithms are proposed to compute a partial generalized singular value decomposition (GSVD) of a large regular matrix pair. They are called cross product-free (CPF) and inverse-free…

We present some applications of the unitarity-based Dispersion Matrix (DM) approach to the extraction of the CKM matrix element $|V_{cb}|$ from the experimental data on the exclusive $B_{(s)} \to D_{(s)}^{(*)} \ell \nu_\ell$ decays. The DM…

The current analysis of the Cabibbo-Kobayashi-Maskawa(CKM) quark mixing matrix uses the standard parametrisation by 3 mixing angles and the CP-violating KM phase. However it would be more convenient to express these mixing angle parameters…

Factorizing a large matrix into small matrices is a popular strategy for model compression. Singular value decomposition (SVD) plays a vital role in this compression strategy, approximating a learned matrix with fewer parameters. However,…

We propose a mixed precision Jacobi algorithm for computing the singular value decomposition (SVD) of a dense matrix. After appropriate preconditioning, the proposed algorithm computes the SVD in a lower precision as an initial guess, and…

The singular value decomposition (SVD) is commonly used in applications requiring a low rank matrix approximation. However, the singular vectors cannot be interpreted in terms of the original data. For applications requiring this type of…

Motivated by the recently improved results from the Fermilab Lattice and MILC Collaborations on the hadronic matrix elements entering $\Delta M_{s,d}$ in $B_{s,d}^0-\bar B_{s,d}^0$ mixing, we determine the Universal Unitarity Triangle (UUT)…

In the models with vector like quark doublets, the mass matrices of up and down type quarks are related. Precise diagonalization for the mass matrices became an obstacle in the numerical studies. In this work we propose a diagonalization…

Based upon flavor SU(3) symmetry, we perform global fits to charmless B decays into one pseudoscalar meson and one vector meson in the final states. We consider different symmetry breaking schemes and find that the one implied by na{\"i}ve…

I review currently discussed methods to determine the CKM mixing matrix element $|V_{ub}|$ from experimental data. Although the theory of inclusive decays and their spectra has entered a model-independent stage, its predictions are still…

The traditional method of computing singular value decomposition (SVD) of a data matrix is based on a least squares principle, thus, is very sensitive to the presence of outliers. Hence the resulting inferences across different applications…

We propose a mass matrix model that gives a unified description of quark and lepton with the same texture form based on a flavor 2 <-> 3 symmetry. The model is in contrast with the conventional picture that the mass matrix forms in the…

The three-flavor mixing matrix can be parameterized by the rephasing invariants Gamma_{ijk} = V_{1i} V_{2j} V_{3k}. This formulation brings out the inherent symmetry of the problem and has some appealing features. Examples illustrating the…

Most of the free parameters in the Standard Model (SM) -- a quantum field theory which has successfully elucidated the behaviors of strong, weak and electromagnetic interactions of all the known fundamental particles, come from the lepton…

In view of the observed strong hierarchy of the quark and lepton masses and of the flavor mixing angles, it is argued that the description of flavor mixing must take this into account. One particularly interesting way to describe the flavor…

Low-rank decomposition, particularly Singular Value Decomposition (SVD), is a pivotal technique for mitigating the storage and computational demands of Large Language Models (LLMs). However, prevalent SVD-based approaches overlook the…

We present a variational quantum circuit that produces the Singular Value Decomposition of a bipartite pure state. The proposed circuit, that we name Quantum Singular Value Decomposer or QSVD, is made of two unitaries respectively acting on…

Semileptonic $B_s \to K \ell \nu$ decays provide an alternative $b$-decay channel to determine the CKM matrix element $|V_{ub}|$, and to obtain a $R$-ratio to investigate lepton-flavor-universality violations. Results for the CKM matrix…

In this work, we present a mixed precision algorithm that leverages the Gram matrix and Jacobi methods to compute the singular value decomposition (SVD) of tall-and-skinny matrices. By constructing the Gram matrix in higher precision and…