相关论文: xSLHA: an Les Houches Accord reader for Python and…

Natural supersymmetry with light higgsinos is most likely to emerge from the string landscape since the volume of scan parameter space shrinks to tiny volumes for electroweak unnatural models. Rather general arguments favor a landscape…

At the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, one of the goals of colliding protons together is to search for new physics. Supersymmetry (SUSY), a popular theory of physics beyond the well-established standard model of…

Multi-Head Attention (MHA) is the core computational primitive underlying modern Large Language Models (LLMs). However, MHA suffers from a fundamental linear scaling limitation: $H$ attention heads produce exactly $H$ independent attention…

Supersymmetric grand unified theories with non-universal soft supersymmetry breaking terms are studied. By integrating out the superheavy fields at an unification scale, we compute their low-energy effective Lagrangian. We find new…

We carefully study the decay and reconstruction of long-lived particle (LLP) decays in the proposed MATHUSLA LLP detector for the HL-LHC. Our investigations are focused on three LLP benchmark models. MATHUSLA's primary physics target is…

String landscape ideas and the observation of a positive vacuum energy in the current universe suggest that there could be a future transition to an exactly supersymmetric world. Atomic and molecular binding in this susy background probably…

As the complexity of digital circuits increases, High-Level Synthesis (HLS) is becoming a valuable tool to increase productivity and design reuse by utilizing relevant Electronic Design Automation (EDA) flows, either for…

The BumpHunter algorithm is widely used in the search for new particles in High Energy Physics analysis. This algorithm offers the advantage of evaluating the local and global p-values of a localized deviation in the observed data without…

We present Multi-Scale Manifold Alignment(MSMA), an information-geometric framework that decomposes LLM representations into local, intermediate, and global manifolds and learns cross-scale mappings that preserve geometry and information.…

The recent results from the ATLAS and CMS collaborations show that the allowed range for a Standard Model Higgs boson is now restricted to a very thin region. Although those limits are presented exclusively in the framework of the SM, the…

The quadratic complexity of self attention in Transformer based LLMs renders long context inference prohibitively expensive. While Sliding Window Attention (SWA), the simplest sparse attention pattern, offers a linear complexity…

We create the first large-scale mock spectroscopic survey of gas absorption sightlines traversing the interstellar medium (ISM), circumgalactic medium (CGM), and intergalactic medium (IGM) surrounding galaxies of virtual Universes. That is,…

Cross-modal hashing is an important approach for multimodal data management and application. Existing unsupervised cross-modal hashing algorithms mainly rely on data features in pre-trained models to mine their similarity relationships.…

FlexibleSUSY is a software package for various calculations in any model of physics beyond the standard model (not just any supersymmetric model). FlexibleSUSY can solve boundary value problems and uses this to find…

In this work, we develop and analyze a Hybrid High-Order (HHO) method for steady non-linear Leray-Lions problems. The proposed method has several assets, including the support for arbitrary approximation orders and general polytopal meshes.…

We present PrismSSL, a Python library that unifies state-of-the-art self-supervised learning (SSL) methods across audio, vision, graphs, and cross-modal settings in a single, modular codebase. The goal of the demo is to show how researchers…

We present the results of a realistic global fit of the Lagrangian parameters of the Minimal Supersymmetric Standard Model assuming universality for the first and second generation and real parameters. No assumptions on the SUSY breaking…

The escalating demand for efficient decoding in large language models (LLMs) is particularly critical for reasoning-intensive architectures like OpenAI-o3 and DeepSeek-R1, which depend on extended chain-of-thought reasoning. This study…

The increasing complexity and demand for faster, energy-efficient hardware designs necessitate innovative High-Level Synthesis (HLS) methodologies. This paper explores the potential of Large Language Models (LLMs) to streamline or replace…

SPARKX is an open-source Python package developed to analyze simulation data from heavy-ion collision experiments. By offering a comprehensive suite of tools, SPARKX simplifies data analysis workflows, supports multiple formats such as…