Related papers: Sustainability Assessment of Future Accelerators
We have built particle accelerators to understand the forces that make up our physical world. But we still don't understand the principles underlying our strongly connected, techno-socio-economic systems. To fill the knowledge gaps and keep…
Computer modeling is essential to research on Advanced Accelerator Concepts (AAC), as well as to their design and operation. This paper summarizes the current status and future needs of AAC systems and reports on several key aspects of (i)…
Particle colliders for high energy physics have been in the forefront of scientific discoveries for more than half a century. The accelerator technology of the collider has progressed immensely, while the beam energy, luminosity, facility…
This text is a full transcription of a lecture was given in the Joint Universities Accelerator School (JUAS) in 2023. A much shorter version is to be published in the JUAS book in 2024, along with all other lectures from the JUAS school.…
In 2015, the United Nations put forward 17 Sustainable Development Goals (SDGs) to be achieved by 2030, where data has been promoted as a focus to innovating sustainable development and as a means to measuring progress towards achieving the…
Fixed-field alternating gradient accelerators are promising candidates for next-generation 10 MW-class high power proton drivers. Recent advances in lattice design of non-scaling FFAGs have progressed toward both isochronicity and chromatic…
The Disk Loaded Waveguide (DLW) is the mostly used high frequency structure for acceleration of lightweight particles - electrons in the high energy range. In some physical experiments acceleration of more heavy particles - muons to medium…
The reliability of deep learning accelerators (DLAs) used in autonomous driving systems has significant impact on the system safety. However, the DLA reliability is usually evaluated with low-level metrics like mean square errors of the…
After recalling briefly the main physics issues beyond the Standard Model, the main physics objectives of experiments at CERN in the coming decade(s) are reviewed. These include the conclusion of the LEP programme during the year 2000, a…
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event…
The anticipated physics program at an high energy e+e- linear collider places special emphasis on the accuracy in extrapolating charged particle tracks to their production vertex to tag heavy quarks and leptons. This paper reviews physics…
Semiconductor innovation drives improvements to technologies that are critical to modern society. The country that successfully accelerates semiconductor innovation is positioned to lead future semiconductor-driven industries and benefit…
Sustainability aspects of transportation infrastructure systems primarily focus on system performance based on environmental, social, and economic impacts. In contrast, resilience aspects demonstrate the ability to withstand external shocks…
Research activities on laser plasma accelerators are paved by many significant breakthroughs. This review article provides an opportunity to show the incredible evolution of this field of research which has, in record time, allowed…
Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible. The purpose of this workshop was to consider tuning and…
The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest.…
The study group on data preservation in high energy physics, DPHEP, is moving to a new collaboration structure, which will focus on the implementation of preservation projects, such as those described in the group's large scale report…
The rapid growth of Machine Learning (ML) has increased demand for DNN hardware accelerators, but their embodied carbon footprint poses significant environmental challenges. This paper leverages approximate computing to design sustainable…
This paper provides an overview of experiments and facilities for accelerator-based dark matter searches as part of the US Community Study on the Future of Particle Physics (Snowmass 2021). Companion white papers to this paper present the…
A high-energy $e^+e^-$ Linear Collider has been considered since a long time as an important complement to the LHC. Unprecedented precision measurements as well as the exploration of so far untouched phase space for direct production of new…