Related papers: Extracting Low-Lying Lambda Resonances Using Corre…
With the ongoing experimental interest in exploring the excited hadron spectrum, evaluations of the matrix elements describing the formation and decay of such states via radiative processes provide us with an important connection between…
Low Gain Avalanche Detectors(LGADs) is one of the candidate sensing technologies for future 4D-tracking applications and recently have been qualified to be used in the ATLAS and CMS timing detectors for the CERN High Luminosity Large Hadron…
Laser induced breakdown spectroscopy technique is employed for quantitative analysis of aluminum samples by different classical machine learning approaches. A Q-switch Nd:YAG laser at fundamental harmonic of 1064 nm is utilized for creation…
Low-Gain Avalanche Diodes are a type of silicon Avalanche Photo-Diodes originally developed for the fast detection of minimum ionizing particles in high-energy physics experiments. Thanks to their fast timing performance, the Low-Gain…
Independent low-rank matrix analysis (ILRMA) is a fast and stable method for blind audio source separation. Conventional ILRMAs assume time-variant (super-)Gaussian source models, which can only represent signals that follow a…
We study the coupled pion-nucleon system (negative parity, isospin 1/2) based on a lattice QCD simulation for nf=2 mass degenerate light quarks. Both, standard 3-quarks baryon operators as well as meson-baryon (4+1)-quark operators are…
The state-of-the-art dimensionality reduction approaches largely rely on complicated optimization procedures. On the other hand, closed-form approaches requiring merely eigen-decomposition do not have enough sophistication and nonlinearity.…
We compute the ratio $\Lambda_L/\Lambda_{\bar{MS}}$ between the scale parameter $\Lambda_L$, associated with a lattice formulation of QCD using the overlap-Dirac operator, and $\Lambda_{\bar{MS}}$ of the $\bar{\rm MS}$ renormalization…
We consider the solution of systems of linear algebraic equations (SLAEs) with an ill-conditioned or degenerate exact matrix and an approximate right-hand side. An approach to solving such a problem is proposed and justified, which makes it…
Compressed sensing is an important problem in many fields of science and engineering. It reconstructs signals by finding sparse solutions to underdetermined linear equations. In this work we propose a deterministic and non-parametric…
We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. standard Gaussian entries, which are possibly corrupted by arbitrary outliers.…
We present a general framework for engineering two-dimensional (2D) sub-wavelength topological optical lattices using spatially dependent atomic dark states in a $\Lambda$-type configuration of the atom-light coupling. By properly designing…
We generated configurations with the approximate fixed-point Dirac operator $D_\mathrm{FP}$ on a $12^4$ lattice with $a \approx 0.13 $fm where the scale was set by $r_0$. The distributions of the low lying eigenvalues in different…
This paper addresses identification of sparse linear and noise-driven continuous-time state-space systems, i.e., the right-hand sides in the dynamical equations depend only on a subset of the states. The key assumption in this study, is…
We present a novel method for solving Canonical Correlation Analysis (CCA) in a sparse convex framework using a least squares approach. The presented method focuses on the scenario when one is interested in (or limited to) a primal…
We study the isoscalar and isovector $J=0,1$ mesons with the overlap operator within two flavour lattice QCD. After subtraction of the lowest-lying Dirac eigenmodes from the valence quark propagator all disconnected contributions vanish and…
We propose $\textsf{ScaledGD($\lambda$)}$, a preconditioned gradient descent method to tackle the low-rank matrix sensing problem when the true rank is unknown, and when the matrix is possibly ill-conditioned. Using overparametrized factor…
Negative sampling schemes enable efficient training given a large number of classes, by offering a means to approximate a computationally expensive loss function that takes all labels into account. In this paper, we present a new connection…
Integrated sensing and communication (ISAC) is a potential technology of the sixth-generation (6G) mobile communication system, which enables communication base station (BS) with sensing capability. However, the performance of single-BS…
This paper develops a systematic approach to realising linear detectors with an optimised sensitivity, allowing for the detection of extremely weak signals. First, general constraints are derived on a specific class of input-output transfer…