相关论文: SFitter: Reconstructing the MSSM Lagrangian from L…

We propose a novel architecture called MLP-SRGAN, which is a single-dimension Super Resolution Generative Adversarial Network (SRGAN) that utilizes Multi-Layer Perceptron Mixers (MLP-Mixers) along with convolutional layers to upsample in…

Supersymmetric mass spectra within two variants of the seesaw mechanism, commonly known as type-II and type-III seesaw, are calculated using full 2-loop RGEs and minimal Supergravity boundary conditions. The type-II seesaw is realized using…

This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical…

After an introduction recalling the theoretical motivation for low energy (100 GeV to TeV scale) supersymmetry, this review describes the theory and experimental implications of the soft supersymmetry-breaking Lagrangian of the general…

We calculate the leading contribution to the left-right asymmetry in polarized M{\o}ller scattering from the superpartners in the Minimal Supersymmetric Standard Model (MSSM), using an effective lagrangian approach. We determine the maximum…

Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This agreement is encoded in measured Wilson coefficients and their…

Combined analyses at the Large Hadron Collider and at the International Linear Collider are important to unravel a difficult region of supersymmetry that is characterized by scalar SUSY particles with masses around 2 TeV. Precision…

Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan beta, while being constrained to…

We study the implications of LHC searches on SUSY particle spectra using flat scans of the 19-parameter pMSSM phase space. We apply constraints from flavour physics, g_mu-2, dark matter and earlier LEP and Tevatron searches. The sensitivity…

Necessary optimality conditions in Lagrangian form and the sequential minimization framework are extended to mixed-integer nonlinear optimization, without any convexity assumptions. Building upon a recently developed notion of local…

We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the CFHTLenS weak lensing survey - the first application of this method to data. In the first approach, we sample…

Despite a great deal of effort in searching for the triplet-like Higgses in the type-II seesaw model, evidence for their production is yet to be found at the LHC. As such, one might be in the balance regarding this model's relevance at the…

Matched filters are widely used to localise signal patterns due to their high efficiency and interpretability. However, their effectiveness deteriorates for low signal-to-noise ratio (SNR) signals, such as those recorded on edge devices,…

To gain a comprehensive view of what the LHC tells us about physics beyond the Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in general, search analyses are not statistically orthogonal, so…

The requirement that SUSY should solve the hierarchy problem without undue fine-tuning imposes severe constraints on the new supersymmetric states. With the MSSM spectrum and soft SUSY breaking originating from universal scalar and gaugino…

Studies of dark matter lie at the interface of collider physics, astrophysics and cosmology. Constraining models featuring dark matter candidates entails the capability to provide accurate predictions for large sets of observables and…

We consider scalar-tensor theories and reconstruct their potential U(\Phi) and coupling F(\Phi) by demanding a background LCDM cosmology. In particular we impose a background cosmic history H(z) provided by the usual flat LCDM…

Along with the desire to address more complex problems, feature selection methods have gained in importance. Feature selection methods can be classified into wrapper method, filter method, and embedded method. Being a powerful embedded…

The Linear Multistep Method Particle Filter (LMM PF) is a method for predicting the evolution in time of a evolutionary system governed by a system of differential equations. If some of the parameters of the governing equations are…

The estimation of parameters from data is a common problem in many areas of the physical sciences, and frequently used algorithms rely on sets of simulated data which are fit to data. In this article, an analytic solution for…