Related papers: Required experimental accuracy to select between s…
The momentum transfer dependence of the LSP-nucleus elastic scattering cross sections is studied. New imput SUSY parameters obtained in a phenomenologically allowed parameter space are used to calculate the coherent rate for various nuclear…
To explaine the matter-antimatter asymmetry, a supersymmetric extention of the standard model is proposed where baryon and lepton numbers are local gauged(BLMSSM), and exotic superfields are introduced when gauge group is enlarged to…
I summarise the activities of the different members of the SUSY working group. There have been two major areas of activity: 1) precision measurement of the SUSY particle masses/couplings and hence those of the SUSY model parameters, 2)…
A new systematic method is developed to study to what extent the symmetry requirements alone, above all the invariance under 16 supersymmetries (SUSY), determine the completely off-shell effective action $\Gamma$ of a D-particle, i.e.…
We carry out a detailed analysis of sparticle mass spectrum in supersymmetric grand unified theories. We consider the spectroscopy of the squarks and sleptons in SU(5) and SO(10) grand unified theories, and show how the underlying…
We analyze the potential of the first LHC physics run, assuming 1/fb at sqrt[s] = 7 TeV, to discover Supersymmetry (SUSY). The results are based on SUSY parameter fits following a frequentist approach. They include the experimental…
The analysis and modelling of a range of plasmas (for example: astrophysical, laser-produced and fusion), require atomic data for a number of parameters, such as energy levels, radiative rates and electron impact excitation rates, or…
Motivated by the widely used geometric median-of-means estimator in machine learning, this paper studies statistical inference for ultrahigh dimensionality location parameter based on the sample spatial median under a general multivariate…
The prediction for the Higgs mass in the dark matter selected high-scale SUSY is explored. We show the bounds on SUSY-breaking scale in models of SM $+\tilde{w}$ and SM $+\tilde{h}/\tilde{s}$ due to the observed Higgs mass at the LHC. We…
MALDI mass spectrometry imaging (MALDI MSI) is a spatially resolved analytical tool for biological tissue analysis by measuring mass-to-charge ratios of ionized molecules. With increasing spatial and mass resolution of MALDI MSI data,…
Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent…
There are many atomistic simulation methods with very different costs, accuracies, transferabilities, and numbers of empirical parameters. I show how statistical model selection can compare these methods fairly, even when they are very…
We consider the problem of subspace estimation in situations where the number of available snapshots and the observation dimension are comparable in magnitude. In this context, traditional subspace methods tend to fail because the…
This article attempts to summarize the effort by the particle physics community in addressing the tedious work of determining the parameter spaces of beyond-the-standard-model (BSM) scenarios, allowed by data. These spaces, typically…
Comparing mathematical models offers a means to evaluate competing scientific theories. However, exact methods of model calibration are not applicable to many probabilistic models which simulate high-dimensional spatio-temporal data.…
The structure of proteins is essential for its function. The determination of protein structures is possible by experimental or predicted by computational methods, but also a combination of both approaches is possible. Here, first an…
In many high-impact applications, it is important to ensure the quality of output of a machine learning algorithm as well as its reliability in comparison with the complexity of the algorithm used. In this paper, we have initiated a…
Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for…
Searches for beyond-Standard Model physics scenarios, such as supersymmetry (SUSY), at the Large Hadron Collider (LHC) are frequently optimised on simplified models. After assuming particular particle production and decay processes,…
Data based materials science is the new promise to accelerate materials design. Especially in computational materials science, data generation can easily be automatized. Usually, the focus is on processing and evaluating the data to derive…