detector technology

How do you get the data out of particle detectors? And how do you cleverly and quickly find the data that is the most interesting to explore? In this presentation, Fermilab scientist Wes Ketchum discusses the tricks and techniques that particle physicists use to record rare subatomic interactions in real time and the challenges they encounter.

From Pesquisa, November 2020: The FAPESP scientific director shares how he encouraged behaviors that helped improve research in São Paulo. With FAPESP encouragement, researchers in Brazil have held leadership positions in international collaborations, including in a photon detection system called Arapuca. Arapuca is a technology used in Fermilab’s Short-Baseline Near Detector and a baseline technology for the international Deep Underground Neutrino Experiment, hosted by Fermilab.

Fermilab plays a key role in the Quantum Science Center, led by Oak Ridge National Laboratory. The center unites Oak Ridge’s powerhouse capabilities in supercomputing and materials science with Fermilab’s world-class high-energy physics instrumentation and measurement expertise and facilities. Drawing on their experience building and operating experiments in cosmology and particle physics and in quantum information science, the Fermilab team is engaging in QSC efforts to develop novel, advanced quantum technologies.

From NIST, Oct. 13, 2020: Researchers at NIST and their colleagues, including Fermilab scientist Gordan Krnjaic, have proposed a novel method for finding dark matter. The experiment, in which a billion millimeter-sized pendulums would act as dark matter sensors, would be the first to hunt for dark matter solely through its gravitational interaction with visible matter. A three-minute animation illustrates the new technique.

The High-Luminosity LHC will provide exciting physics opportunities but also daunting computing challenges for CMS. The amount of data will increase by a factor of 60, and the average number of pileup interactions per event is expected to increase by a factor of 5.
Researchers at Fermilab and partners are working to speed up the CMS tracking algorithm by taking advantage of modern, highly parallel CPU architectures.