Related papers: Publication patterns in HEP computing
We discuss recent advances in applying Quantum Information Science to problems in high-energy nuclear physics. After outlining key developments, open challenges, and emerging connections between these disciplines, we highlight recent…
These lecture notes discuss methods, recent results and future prospects in proton-proton physics at the Large Hadron Collider.
I compare and discuss critically several measures of statistical significance in common use in astrophysics and in high energy physics. I also exhibit some relationships among them.
This whitepaper summarizes the status, plans, and challenges in the area of integrated circuit design in the United States for future High Energy Physics (HEP) experiments. It has been submitted to CPAD (Coordinating Panel for Advanced…
Advantages of quantum effects in several technologies, such as computation and communication, have already been well appreciated, and some devices, such as quantum computers and communication links, exhibiting superiority to their classical…
A R&D project has been recently launched to investigate Geant4 architectural design in view of addressing new experimental issues in HEP and other related physics disciplines. In the context of this project the use of generic programming…
With the vast majority of scientific papers now available online, this paper describes how the Web is allowing physicists and information providers to measure more accurately the impact of these papers and their authors. Provides a…
Searches for new physics in high-energy physics (HEP) experiments commonly rely on interactions with materials. A burgeoning direction is the accurate calculation and design of materials for HEP applications. In this Snowmass contribution,…
Research in high energy physics (HEP) requires huge amounts of computing and storage, putting strong constraints on the code speed and resource usage. To meet these requirements, a compiled high-performance language is typically used; while…
Our predictions for particle physics processes are realized in a chain of complex simulators. They allow us to generate high-fidelity simulated data, but they are not well-suited for inference on the theory parameters with observed data. We…
The popularity and rapid development of Cloud Computing in recent years has led to a vast number of publications capturing the accumulated knowledge in this field. Due to the interdisciplinary nature and significant relevance of cloud…
The increase in authorship of nuclear physics publications has been investigated using the large statistical samples. This has been accomplished with nuclear data mining of nuclear science references (NSR) and experimental nuclear reaction…
Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. Given the fast pace of this research, we have created a living review with the goal of providing a…
A number of scientific competitions have been organised in the last few years with the objective of discovering innovative techniques to perform typical High Energy Physics tasks, like event reconstruction, classification and new physics…
An overview of nuclei and anti-nuclei production with results from different experiments are discussed. The comparison of data with the thermal and coalescence models is also discussed to understand their production mechanisms in high…
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements.…
We review the history of jets in high energy physics, and describe in more detail the developments of the past ten years, discussing new algorithms for jet finding and their main characteristics, and summarising the status of perturbative…
This paper examines how the role of cited papers evolves over time by analyzing nearly 900 highly cited papers (HCPs) published between 2000 and 2016 and the full text of over 220,000 papers citing them. We investigate multiple citation…
The high energy physics community is discussing where investment is needed to prepare software for the HL-LHC and its unprecedented challenges. The ROOT project is one of the central software players in high energy physics since decades.…
Beginning from a basic neural-network architecture, we test the potential benefits offered by a range of advanced techniques for machine learning, in particular deep learning, in the context of a typical classification problem encountered…