Related papers: HEP Software Foundation Community White Paper Work…
This note introduces CutLang, a domain specific language that aims to provide a clear, human readable way to define analyses in high energy particle physics (HEP) along with an interpretation framework of that language. A proof of principle…
Realistic environments for prototyping, studying and improving analysis workflows are a crucial element on the way towards user-friendly physics analysis at HL-LHC scale. The IRIS-HEP Analysis Grand Challenge (AGC) provides such an…
Data-intensive science is increasingly reliant on real-time processing capabilities and machine learning workflows, in order to filter and analyze the extreme volumes of data being collected. This is especially true at the energy and…
This paper presents an architecture for the analysis management in high energy physics experiments. Some new concepts on data analysis are introduced. A protocol for organizing and operating an analysis is raised. A toolkit following this…
We present an application, EasyScan_HEP, for connecting programs to scan the parameter space of High Energy Physics (HEP) models using various sampling algorithms. We develop EasyScan_HEP according to the principle of flexibility and…
Every year the PHENIX collaboration deals with increasing volume of data (now about 1/4 PB/year). Apparently the more data the more questions how to process all the data in most efficient way. In recent past many developments in HEP…
Compelling arguments suggest the presence of new physics at energy scales that will be probed by frontier energy colliders over the next decade. Arguments for each of the many flavors of new physics that have been proposed seem much less…
Careful preservation of experimental data, simulations, analysis products, and theoretical work maximizes their long-term scientific return on investment by enabling new analyses and reinterpretation of the results in the future. Key…
Large High Energy Physics (HEP) experiments adopted a distributed computing model more than a decade ago. WLCG, the global computing infrastructure for LHC, in partnership with the US Open Science Grid, has achieved data management at the…
Modern searches for physics beyond the Standard Model produce rapidly expanding literature containing heterogeneous information, including textual analyses, numerical datasets, and graphical exclusion limits. Integrating these distributed…
The HL-LHC presents significant challenges for the HEP analysis community. The number of events in each analysis is expected to increase by an order of magnitude and new techniques are expected to be required; both challenges necessitate…
High-energy physics phenomenology often requires linking multiple computational tools to evaluate observables, likelihoods, and experimental constraints across nontrivial parameter spaces. In this work, we introduce Jarvis-HEP, a…
This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing…
In recent years, digital object management practices to support findability, accessibility, interoperability, and reusability (FAIR) have begun to be adopted across a number of data-intensive scientific disciplines. These digital objects…
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research…
Designing a reliable target is already a challenge for MW-class facilities today and has led several major accelerator facilities to operate at lower than design power due to target concerns. With present plans to increase beam power for…
Data analysis is a powerful tool in all experimental sciences. Statistical methods, such as sampling theory, computer technologies necessary for handling large amounts of data, skill in analysing information contained in different types of…
We make the case for the systematic, reliable preservation of event-wise data, derived data products, and executable analysis code. This preservation enables the analyses' long-term future reuse, in order to maximise the scientific impact…
As the climate crisis intensifies, understanding the environmental impact of professional activities is paramount, especially in sectors with historically significant resource utilisation. This includes High Energy Physics (HEP) and related…
This report summarizes the work of the Computational Frontier topical group on end user analysis for Snowmass 2021. End User Analysis refers to the extraction of physics results from reconstructed and simulated experimental data. High…