NSF Award
2320630
This project is focused on developing modules that provide precise timing and space information for the construction of a high-granularity timing-layer to be integrated into the LHCb Upgrade II calorimeter at the CERN laboratory in Switzerland and future high-luminosity colliders. The development of this instrument will be an essential element of an ambitious physics program rich in discovery potential that will advance our understanding of elementary particles and their interactions. High spatial resolution combined with a precise time stamp has broad applications to future colliders and industrial instruments, for example medical devices. The group will develop full-size modules comprising a sensor and its processing electronics, integrated into an optimized package with electrical and mechanical properties suitable for scalability into large planes. Its components comprise novel ultrafast sensors with fine space segmentation and complex electronics that combine sophisticated signal manipulation and data processing. This R&D project is synergistic with the semiconductor industry in the United States and the many efforts of applying artificial intelligence techniques to advanced technology. <br/><br/>The goal of the effort is to integrate this detector in the LHCb Upgrade II at the CERN LHC collider following the high-luminosity upgrade (HL-LHC). The HL-LHC era offers the possibility of unprecedented reach in many landmark measurements. The high luminosity, combined with increased efficiency for photons, pions, electrons, and positrons, will be a formidable combination that, thanks to the flexible software trigger, will allow the group to optimize the data taking to specific interesting decays. In addition, this instrument is aligned with basic research needs in calorimetry for future collider applications. It can also be adapted to construct hadron identification devices for future e+e- colliders. The stringent specifications involve sensor and microelectronics features that are at the edge of current technologies. Challenging requirements on the speed and radiation resistance on the sensors, speed and low noise performance of the analog processing, complexity of the digital section, and encompassing algorithms possibly optimized with machine-learning techniques have far-reaching implications for advancement in microelectronics.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
