Design of the ECCE Detector for the Electron Ion Collider

Preprint submitted to Nuclear Instruments and Methods A. The file archived on this institutional repository has not been certified by peer review.32 pages, 29 figures, 9 tablesThe EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector.Office of Science in the Department of Energy, the National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR; This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05- 00OR22725. The work of AANL group are supported by the Science Committee of RA, in the frames of the research project # 21AG-1C028. And we gratefully acknowledge that support of Brookhaven National Lab and the Thomas Jefferson National Accelerator Facility which are operated under contracts DESC0012704 and DE-AC05-06OR23177 respectivel

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

arXiv preprint [v2] Fri, 20 May 2022 03:23:44 UTC (2,296 KB) made available under a Creative Commons (CC BY) Attribution Licence, now in press, published by Elsevier: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, available online 17 November 2022 at: https://doi.org/10.1016/j.nima.2022.167748The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.Office of Nuclear Physics in the Office of Science in the Department of Energy; National Science Foundation, and the Los Alamos National Laboratory Laboratory Directed Research and Development (LDRD) 20200022DR

A new approach to the molecular analysis of docking, priming, and regulated membrane fusion

Studies using isolated sea urchin cortical vesicles have proven invaluable in dissecting mechanisms of Ca2+-triggered membrane fusion. However, only acute molecular manipulations are possible in vitro. Here, using selective pharmacological manipulations of sea urchin eggs ex vivo, we test the hypothesis that specific lipidic components of the membrane matrix selectively affect defined late stages of exocytosis, particularly the Ca2+-triggered steps of fast membrane fusion. Egg treatments with cholesterol-lowering drugs resulted in the inhibition of vesicle fusion. Exogenous cholesterol recovered fusion extent and efficiency in cholesterol-depleted membranes; α-tocopherol, a structurally dissimilar curvature analogue, selectively restored fusion extent. Inhibition of phospholipase C reduced vesicle phosphatidylethanolamine and suppressed both the extent and kinetics of fusion. Although phosphatidylinositol-3-kinase inhibition altered levels of polyphosphoinositide species and reduced all fusion parameters, sequestering polyphosphoinositides selectively inhibited fusion kinetics. Thus, cholesterol and phosphatidylethanolamine play direct roles in the fusion pathway, contributing negative curvature. Cholesterol also organizes the physiological fusion site, defining fusion efficiency. A selective influence of phosphatidylethanolamine on fusion kinetics sheds light on the local microdomain structure at the site of docking/fusion. Polyphosphoinositides have modulatory upstream roles in priming: alterations in specific polyphosphoinositides likely represent the terminal priming steps defining fully docked, release-ready vesicles. Thus, this pharmacological approach has the potential to be a robust high-throughput platform to identify molecular components of the physiological fusion machine critical to docking, priming, and triggered fusion

The energetic particle detector: energetic particle instrument suite for the Solar Orbiter mission

After decades of observations of solar energetic particles from space-based observatories, relevant questions on particle injection, transport, and acceleration remain open. To address these scientific topics, accurate measurements of the particle properties in the inner heliosphere are needed. In this paper we describe the Energetic Particle Detector (EPD), an instrument suite that is part of the scientific payload aboard the Solar Orbiter mission. Solar Orbiter will approach the Sun as close as 0.28 au and will provide extra-ecliptic measurements beyond ∼30° heliographic latitude during the later stages of the mission. The EPD will measure electrons, protons, and heavy ions with high temporal resolution over a wide energy range, from suprathermal energies up to several hundreds of megaelectronvolts/nucleons. For this purpose, EPD is composed of four units: the SupraThermal Electrons and Protons (STEP), the Electron Proton Telescope (EPT), the Suprathermal Ion Spectrograph (SIS), and the High-Energy Telescope (HET) plus the Instrument Control Unit that serves as power and data interface with the spacecraft. The low-energy population of electrons and ions will be covered by STEP and EPT, while the high-energy range will be measured by HET. Elemental and isotopic ion composition measurements will be performed by SIS and HET, allowing full particle identification from a few kiloelectronvolts up to several hundreds of megaelectronvolts/nucleons. Angular information will be provided by the separate look directions from different sensor heads, on the ecliptic plane along the Parker spiral magnetic field both forward and backwards, and out of the ecliptic plane observing both northern and southern hemispheres. The unparalleled observations of EPD will provide key insights into long-open and crucial questions about the processes that govern energetic particles in the inner heliosphere

AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider

The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the "glue" that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector