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Patricia Conde-Muíño

Publications and source records attributed to Patricia Conde-Muíño.

2 recordsLinked to original sources

Marionette: Data Structure Description and Management for Heterogeneous Computing

Adapting large, object-oriented C++ codebases for hardware acceleration might be extremely challenging, particularly when targeting heterogeneous platforms such as GPUs. Marionette is a C++17 library designed to address this by enabling flexible, efficient, and portable data structure definitions. It decouples data layout from the description of the interface, supports multiple memory management strategies, and provides efficient data transfers and conversions across devices, all of this with minimal runtime overhead due to the compile-time nature of its abstractions. By allowing interfaces to be augmented with arbitrary functions, Marionette maintains compatibility with existing code and offers a streamlined interface that supports both straightforward and advanced use cases. This paper outlines its design, usage, and performance, including a CUDA-based case study demonstrating its efficiency and flexibility.

cs.DC↗

Simulation-based inference in the search for CP violation in leptonic WH production

Sources of CP violation beyond the Standard Model (BSM) are required to explain the baryonic asymmetry of the Universe. In this work, we study BSM CP-violating components in the HWW interaction in WH production, parametrized by an effective dimension-6 CP-odd operator. We explore a machine learning simulation-based inference method that estimates a detector-level optimal observable - SALLY - comparing it with energy-dependent and angular observables, exploring different binnings for their distributions. We show that in regions of phase space where the interference between SM and the effective operator dominates, a SALLY observable leads to optimal limits. In regions where effects of the quadratic term of the effective operator start becoming dominant, such an observable still leads to optimal limits. This work aims to test current multivariate techniques and inform analysis strategies for LHC Run 3 and beyond.

hep-ph↗