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1. Computing for the DUNE Long-Baseline Neutrino Oscillation Experiment

   https://doi.org/10.1051/epjconf/202024511002  

   Schellman, Heidi (January 2020, EPJ Web of Conferences)

   Doglioni, C.; Kim, D.; Stewart, G.A.; Silvestris, L.; Jackson, P.; Kamleh, W. (Ed.)

   This paper is based on a talk given at Computing in High Energy Physics in Adelaide, South Australia, Australia in November 2019. It is partially intended to explain the context of DUNE Computing for computing specialists. The Deep Underground Neutrino Experiment (DUNE) collaboration consists of over 180 institutions from 33 countries. The experiment is in preparation now, with commissioning of the first 10kT fiducial volume Liquid Argon TPC expected over the period 2025-2028 and a long data taking run with 4 modules expected from 2029 and beyond. An active prototyping program is already in place with a short test-beam run with a 700T, 15,360 channel prototype of single-phase readout at the Neutrino Platform at CERN in late 2018 and tests of a similar sized dual-phase detector scheduled for mid-2019. The 2018 test-beam run was a valuable live test of our computing model. The detector produced raw data at rates of up to 2GB/s. These data were stored at full rate on tape at CERN and Fermilab and replicated at sites in the UK and Czech Republic. In total 1.2 PB of raw data from beam and cosmic triggers were produced and reconstructed during the six week testbeam run. Baseline predictions for the full DUNE detector data, starting in the late 2020’s are 30-60 PB of raw data per year. In contrast to traditional HEP computational problems, DUNE’s Liquid Argon TPC data consist of simple but very large (many GB) 2D data objects which share many characteristics with astrophysical images. This presents opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing. 

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2. The Pixel Luminosity Telescope: a detector for luminosity measurement at CMS using silicon pixel sensors

   https://doi.org/10.1140/epjc/s10052-023-11713-6  

   Ayala, E.; CarreraJarrin, E.; Ahmed, I.; Campbell, A.; Danilov, V.; EstevezBanos, L. I.; Giraldi, A.; Guthoff, M.; Hempel, M.; Henschel, H.; et al (July 2023, The European Physical Journal C)

   Abstract The Pixel Luminosity Telescope is a silicon pixel detector dedicated to luminosity measurement at the CMS experiment at the LHC. It is located approximately 1.75 m from the interaction point and arranged into 16 “telescopes”, with eight telescopes installed around the beam pipe at either end of the detector and each telescope composed of three individual silicon sensor planes. The per-bunch instantaneous luminosity is measured by counting events where all three planes in the telescope register a hit, using a special readout at the full LHC bunch-crossing rate of 40 MHz. The full pixel information is read out at a lower rate and can be used to determine calibrations, corrections, and systematic uncertainties for the online and offline measurements. This paper details the commissioning, operational history, and performance of the detector during Run 2 (2015–18) of the LHC, as well as preparations for Run 3, which will begin in 2022. 

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3. Comparative evaluation of analogue front-end designs for the CMS Inner Tracker at the High Luminosity LHC

   https://doi.org/10.1088/1748-0221/16/12/P12014  

   Adam, W.; Bergauer, T.; Blöch, D.; Dragicevic, M.; Frühwirth, R.; Hinger, V.; Steininger, H.; Beaumont, W.; Di Croce, D.; Janssen, X.; et al (December 2021, Journal of Instrumentation)

   Abstract The CMS Inner Tracker, made of silicon pixel modules, will be entirely replaced prior to the start of the High Luminosity LHC period. One of the crucial components of the new Inner Tracker system is the readout chip, being developed by the RD53 Collaboration, and in particular its analogue front-end, which receives the signal from the sensor and digitizes it. Three different analogue front-ends (Synchronous, Linear, and Differential) were designed and implemented in the RD53A demonstrator chip. A dedicated evaluation program was carried out to select the most suitable design to build a radiation tolerant pixel detector able to sustain high particle rates with high efficiency and a small fraction of spurious pixel hits. The test results showed that all three analogue front-ends presented strong points, but also limitations. The Differential front-end demonstrated very low noise, but the threshold tuning became problematic after irradiation. Moreover, a saturation in the preamplifier feedback loop affected the return of the signal to baseline and thus increased the dead time. The Synchronous front-end showed very good timing performance, but also higher noise. For the Linear front-end all of the parameters were within specification, although this design had the largest time walk. This limitation was addressed and mitigated in an improved design. The analysis of the advantages and disadvantages of the three front-ends in the context of the CMS Inner Tracker operation requirements led to the selection of the improved design Linear front-end for integration in the final CMS readout chip. 

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4. Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

   https://doi.org/10.1088/2632-2153/ad6a00  

   Yoo, Jieun; Dickinson, Jennet; Swartz, Morris; Di_Guglielmo, Giuseppe; Bean, Alice; Berry, Douglas; Blanco_Valentin, Manuel; DiPetrillo, Karri; Fahim, Farah; Gray, Lindsey; et al (August 2024, Machine Learning: Science and Technology)

   Abstract Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of $O$(40 MHz) and intelligently reduces the data within the pixelated region of the detectorat ratewill enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector’s data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300  $\mu W$with an area of less than 0.2 mm². The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area. 

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5. Development of an MKID Frequency-to-Pixel LED Mapper for SPT-3G+

   https://doi.org/10.1109/tasc.2024.3519087  

   Martsen, E S; Barry, P S; Benson, B A; Dibert, K R; Fichman, K N; Natoli, T; Rouble, M; Yu, C (August 2025, IEEE Transactions on Applied Superconductivity)

   SPT-3G+ is the next-generation camera for the South Pole Telescope (SPT). SPT is designed to measure the cosmic microwave background (CMB) and the mm/sub-mm sky. The planned focal plane consists of 34,000 microwave kinetic inductance detectors (MKIDs), divided among three observing bands centered at 220, 285, and 345 GHz. Each readout line is designed to measure 800 MKIDs over a 500 MHz bandwidth, which places stringent constraints on the accuracy of the frequency placement required to limit resonator collisions that reduce the overall detector yield. To meet this constraint, we are developing a two-step process that first optically maps the resonance to a physical pixel location, and then next trims the interdigitated capacitor (IDC) to adjust the resonator frequency. We present a cryogenic LED apparatus operable at 300 mK for the optical illumination of SPT-3G+ detector arrays. We demonstrate integration of the LED controls with the GHz readout electronics (RF-ICE) to take data on an array of prototype SPT-3G+ detectors. We show that this technique is useful for characterizing defects in the resonator frequency across the detector array and will allow for improvements in the detector yield. 

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