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Frequency-independent circuits measure amplitude of sine waves via Schmitt-trigger circuits, pair of inverters, and two flip-flop stages. Accuracy of unit is limited by Schmitt trigger threshold levels, which depend on temperature and on component variations from unit to unit.
This paper summarizes work conducted throughout a SULI internship at Fermi National Accelerator Laboratory focused on building an unsupervised machine learning model for real-time anomaly detection in ProtoDUNE Horizontal Drift. Using simulated data, we trained an autoencoder model on a pure cosmic dataset, and evaluated it on both cosmic and neutrino events---making the model an anomaly detector. The goal was to make a model which matches or exceeds the current ADC Simple Window trigger algorithm so that our model can perform at the same rate but provide sensitivity to potential beyond-the-Standard-Model (BSM) signatures. In the end, we were able to construct a model which slightly exceeds the capabilities of the ADC Simple Window while remaining completely unsupervised, achieving $31.9 \pm 0.2$\% ($26.6 \pm 0.2$\%) $\nu$ efficiency at 5 Hz (2 Hz), a 3.6 (3.2) percentage point increase. Additionally, $17.5 \pm 0.3$\% ($18.3 \pm 0.3$\%) of the events that passed the autoencoder at 5 Hz (2 Hz) were missed by the current trigger algorithm. Future work will investigate alternative normalization methods, including quantile transformation, and evaluate the model on ProtoDUNE-HD detector-glitch data if that data becomes available.
This paper summarizes work conducted throughout a SULI internship at Fermi National Accelerator Laboratory focused on building an unsupervised machine learning model for real-time anomaly detection in ProtoDUNE Horizontal Drift. Using simulated data, we trained an autoencoder model on a pure cosmic dataset, and evaluated it on both cosmic and neutrino events---making the model an anomaly detector. The goal was to make a model which matches or exceeds the current ADC Simple Window trigger algorithm so that our model can perform at the same rate but provide sensitivity to potential beyond-the-Standard-Model (BSM) signatures. In the end, we were able to construct a model which slightly exceeds the capabilities of the ADC Simple Window while remaining completely unsupervised, achieving $31.9 \pm 0.2$\% ($26.6 \pm 0.2$\%) $\nu$ efficiency at 5 Hz (2 Hz), a 3.6 (3.2) percentage point increase. Additionally, $17.5 \pm 0.3$\% ($18.3 \pm 0.3$\%) of the events that passed the autoencoder at 5 Hz (2 Hz) were missed by the current trigger algorithm. Future work will investigate alternative normalization methods, including quantile transformation, and evaluate the model on ProtoDUNE-HD detector-glitch data if that data becomes available.
This paper summarizes work conducted throughout a SULI internship at Fermi National Accelerator Laboratory focused on building an unsupervised machine learning model for real-time anomaly detection in ProtoDUNE Horizontal Drift. Using simulated data, we trained an autoencoder model on a pure cosmic dataset, and evaluated it on both cosmic and neutrino events—making the model an anomaly detector. The goal was to make a model which matches or exceeds the current ADC Simple Window trigger algorithm so that our model can perform at the same rate but provide sensitivity to potential beyond-the-Standard-Model (BSM) signatures. In the end, we were able to construct a model which slightly exceeds the capabilities of the ADC Simple Window while remaining completely unsupervised, achieving 31.9 ± 0.2% (26.6 ± 0.2%) ν efficiency at 5 Hz (2 Hz), a 3.6 (3.2) percentage point increase. Additionally, 17.5 ± 0.3% (18.3 ± 0.3%) of the events that passed the autoencoder at 5 Hz (2 Hz) were missed by the current trigger algorithm. Future work will investigate alternative normalization methods, including quantile transformation, and evaluate the model on ProtoDUNE-HD detector-glitch data if that data becomes available.
The performance of muon tracking, identification, triggering, momentum resolution, and momentum scale has been studied with the CMS detector at the LHC using data collected at √(s$_{NN}$) = 5.02 TeV in proton-proton (pp) and lead-lead(PbPb) collisions in 2017 and 2018, respectively, and at √(s$_{NN}$) = 8.16 TeV in proton-lead (pPb) collisions in 2016. Muon efficiencies, momentum resolutions, and momentum scales are compared by focusing on how the muon reconstruction performance varies from relatively small occupancy pp collisions to the larger occupancies of pPb collisions and, finally, to the highest track multiplicity PbPb collisions. We find the efficiencies of muon tracking, identification, and triggering to be above 90% throughout most of the track multiplicity range. The momentum resolution and scale are unaffected by the detector occupancy. The excellent muon reconstruction of the CMS detector enables precision studies across all available collision systems.
The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1× 10 34 cm -2 s -1 , twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.
Experimental studies of ultra-relativistic heavy ion collisions at the Large Hadron Collider (LHC) depend crucially on Zero Degree Calorimeters (ZDCs) that measure neutrons produced at near-beam rapidity in nucleus-nucleus collisions. In hadronic nuclear collisions these neutrons are mainly spectator neutrons, those that do not scatter from opposing nucleons during the collision. As a result, the ZDCs provide a vital probe of heavy ion collision geometry. The ZDCs are also essential in the study of ultra-peripheral collisions that are initiated by photons associated with the electric fields of one or both nuclei. Coherent photon emission typically leaves the photon emitter intact, making the observation of no ZDC signal, on one or both sides, a tag of such processes. The ATLAS ZDCs, built prior to Run 1, were substantially upgraded for LHC Run 3. The primary upgrades included replacement of the quartz Cherenkov radiator with H_2-doped fused silica rods; installation of fast air-core signal cables between the ZDC and the ATLAS USA15 cavern; a new LED-based calibration system; and new electronics implemented for readout and fully-digital triggering. The ZDCs were also augmented with new “Reaction Plane Detectors” (RPDs) designed to measure the transverse centroid of multi-neutron showers to allow event-by-event reconstruction of the directed-flow plane in nuclear collisions. The Run 3 ZDC detectors, including the RPDs, are described in detail with emphasis on aspects that are new for Run 3.
The ATLAS tile calorimeter (TileCal) is the hadronic sampling calorimeter covering the central region of the ATLAS detector at the Large Hadron Collider (LHC). This paper gives an overview of the calorimeter’s operation and performance during the years 2015–2018 (Run 2). In this period, ATLAS collected proton–proton collision data at a centre-of-mass energy of 13 TeV and the TileCal was 99.65% efficient for data-taking. The signal reconstruction, the calibration procedures, and the detector operational status are presented. The performance of two ATLAS trigger systems making use of TileCal information, the minimum-bias trigger scintillators and the tile muon trigger, is discussed. Studies of radiation effects allow the degradation of the output signals at the end of the LHC and HL-LHC operations to be estimated. Finally, the TileCal response to isolated muons, hadrons and jets from proton–proton collisions is presented. The energy and time calibration methods performed excellently, resulting in good stability and uniformity of the calorimeter response during Run 2. The setting of the energy scale was performed with an uncertainty of 2%. The results demonstrate that the performance is in accordance with specifications defined in the Technical Design Report.
Large-scale particle physics experiments produce tens of terabytes of data every second. Innovative methods to manage the data rate at the HL-LHC, which expects to operate at 10x the luminosity of what the LHC was initially designed for, are needed. AI-on the chip provides a way to intelligently filter out low momentum clusters in the pixel detector. This will open up an opportunity to use the pixel detector for the first time in the CMS Level-1 trigger, and lead to increased sensitivity to new physics measurements and searches. We have taped out our first chip, which incorporates a $p_T$ filtering algorithm on an ASIC chip. Our initial $p_T$ filtering algorithm considers clusters that are tracked by CMS. We will report on ongoing studies seeking to enhance the performance of our filter by utilizing unsupervised learning on untracked clusters, thus increasing background rejection.
The Deep Underground Neutrino Experiment (DUNE) is the next generation neutrino experiment currently under construction. It consists of a broadband neutrino beam at Fermilab, a high precision near detector, and the largest liquid argon time projection chamber far detector ever designed at the Sanford Underground Research Facility (SURF). The Region of Interest (ROI) filter is designed for DUNE’s online Data Acquisition (DAQ) system to address data rate constraints and enable low energy physics in the <10 MeV range. The filter employs zero suppression on the detector signal, and by tuning the readout window and threshold the data rates can be reduced by >90%. Performance of the ROI is analyzed in LArsoft on MARLEY generated low energy MC events propagated through the detector simulation. Notably, the optimized ROI filter enables a lower trigger threshold for readout at ~5-10 MeV, allowing DUNE to explore low-energy physics, specifically focusing on solar boron 8 neutrinos which are relevant in this energy range. This advancement enhances DUNE's scientific capabilities, opening avenues for detailed analyses of previously inaccessible low-energy neutrino interactions.
Experimental studies of ultra-relativistic heavy ion collisions at the Large Hadron Collider (LHC) depend crucially on Zero Degree Calorimeters (ZDCs) that measure neutrons produced at near-beam rapidity in nucleus-nucleus collisions. In hadronic nuclear collisions these neutrons are mainly spectator neutrons, those that do not scatter from opposing nucleons during the collision. As a result, the ZDCs provide a vital probe of heavy ion collision geometry. The ZDCs are also essential in the study of ultra-peripheral collisions that are initiated by photons associated with the electric fields of one or both nuclei. Coherent photon emission typically leaves the photon emitter intact, making the observation of no ZDC signal, on one or both sides, a tag of such processes. The ATLAS ZDCs, built prior to Run 1 were substantially upgraded for LHC Run 3. The primary upgrades included replacement of the quartz Cherenkov radiator with $\text{H}_2$-doped fused silica rods; installation of fast air-core signal cables between the ZDC and the ATLAS USA15 cavern; new LED-based calibration system; and new electronics implemented for readout and fully-digital triggering. The ZDCs were also augmented with new "Reaction Plane Detectors" (RPDs) designed to measure the transverse centroid of multi-neutron showers to allow event-by-event reconstruction of the directed-flow plane in nuclear collisions. The Run~3 ZDC detectors, including the RPDs, are described in detail with emphasis on aspects that are new for Run~3.
The Gamma-Ray Large Area Space Telescope (GLAST) will include a secondary instrument to augment the observatory's capabilities for GRB studies. The GLAST Burst Monitor (GBK is a collaboration between Marshall Space Flight Center, the University of Huntsville, Alabama, and the Max Plank Institute for Extraterrestrial Physics. The purpose of the GBM is to extend energy coverage below the main instrument's lower limit of about 20 MeV, and to provide an on-board burst trigger and approximate location. The instrument consists of twelve NaI detectors and two BGO detectors. This combination provides energy coverage from a few keV up to about 30 MeV.
High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).
The High-Luminosity LHC (HL-LHC) will operate at significantly increased luminosities and is expected to deliver about 3000 $fb^{-1}$ of proton-proton collision data at $\sqrt{s}=14$ TeV over a decade of operation. To maintain efficient tracking and triggering performance under high pileup and radiation conditions, the CMS experiment is upgrading its tracking detector for Phase-2 operations. The upgraded Outer Tracker (OT) will consist of Pixel-Strip (PS) and Strip-Strip (2S) silicon modules capable of providing tracking information to the Level-1 trigger at 40 MHz. Production and qualification of OT modules have been ongoing for about one year across several assembly and testing centers in the US, Europe, India, and Pakistan, requiring extensive testing to ensure stable operation in the HL-LHC environment. Fermilab is responsible for the production and testing of a significant fraction of the OT modules. The testing activities include IV characterization of silicon sensors, noise and pedestal measurements, verification of communication between module components, and burn-in studies using cold-box systems operated under controlled thermal conditions. Results from module testing and qualification studies performed during production will be presented.
The Swift mission: scheduled for launch in early 2004: is a multiwavelength observatory for gamma-ray burst (GRB) astronomy. It is the first-of-its-kind autonomous rapid-slewing satellite for transient astronomy and pioneers the way for future rapid-reaction and multiwavelength missions. It will be far more powerful than any previous GRB mission, observing more than 100 bursts per year and performing detailed X-ray and UV/optical afterglow observations spanning timescales from 1 minute to several days after the burst. The objectives are to: 1) determine the origin of GFU3s; 2) classify GRBs and search for new types; 3) study the interaction of the ultra-relativistic outflows of GRBs with their surrounding medium; and 4) use GRBs to study the early universe out to z greater than 10. The mission is being developed by a NASA-led international collaboration. It will carry three instruments: a new-generation wide-field gamma-ray (15-150 keV) detector that will detect bursts, calculate 1-4 arcmin positions: and trigger autonomous spacecraft slews; a narrow-field X-ray telescope that will give 5 arcsec positions and perform spectroscopy in the 0.2 to 10 keV band; and a narrow-field UV/optical telescope that will operate in the 170-600 nm band and provide 0.3 arcsec positions and optical finding charts. Redshift determinations will be made for most bursts. In addition to the primary GRB science, the mission will perform a hard X-ray survey to a sensitivity of approx. 1 mCrab (approx. 2 x l0(exp -11) erg/sq cm s in the 15-150 keV band), more than an order of magnitude better than HEAO A-4. A flexible data and operations system will allow rapid follow-up observations of all types of high-energy transients. with rapid data downlink and uplink available through the NASA TDRSS system. Swift transient data will be rapidly distributed to the astronomical community and all interested observers are encouraged to participate in follow-up measurements. A Guest Investigator program for the mission will provide funding for community involvement. Innovations from the Swift program applicable to the future include: 1) a large-area gamma-ray detector us- ing the new CdZnTe detectors; 2) an autonomous rapid slewing spacecraft; 3) a multiwavelength payload combining optical, X-ray, and gamma-ray instruments; 4) an observing program coordinated with other ground-based and space-based observatories; and 5) immediate multiwavelength data flow to the community. The mission is currently funded for 2 years of operations and the spacecraft will have a lifetime to orbital decay of approx. 8 years.
The ICARUS-T600 Liquid Argon (LAr) Time Projection Chamber (TPC) is presently used as a far detector of the Short Baseline Neutrino (SBN) program at Fermilab (USA) to search for a possible LSND-like sterile neutrino signal at $\Delta m^2 \sim 1 eV^2$ with the Booster Neutrino Beam (BNB). A light detection system, based on 360 large area Photo-Multiplier Tubes (PMTs), has been realized for ICARUS-T600 to detect VUV photons produced after the passage of ionizing particles in LAr. This system is fundamental for the TPC operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the detector is exposed to a huge flux of cosmic rays due to its shallow depths operations, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the BNB spill gate. Long-term behavior of PMT gains and timing resolution, demonstrate the robustness and reliability of the ICARUS scintillation light detection system and provide valuable input for the design and operation of future large-scale liquid argon detectors.
We have developed a next-generation scanning x-ray microscope RASMI (RApid Scanning Microscopy Instrument) for high-throughput tomographic imaging. RASMI is installed at the hard x-ray nanoprobe beamline at NSLS-II and is capable of manipulating 1D multilayer Laue lenses (MLLs) and 2D optics (both zone plates and monolithically assembled 2D MLLs). The sample scanning stage utilizes line-focusing interferometry as an encoder while performing fly-scanning data acquisition. The system can be configured for both position- and time-triggering modes during fly-scanning. The microscope demonstrated a detector-limited data acquisition rate of 1.25 kHz during ptychography measurements. The initial x-ray results yielded a sample-limited resolution of ∼6 nm in 2D. RASMI can be adopted for in-vacuum applications and is a foundation for the next-generation scanning microscopy systems to be developed and commissioned at NSLS-II.
A fringe detection and measurement system was constructed for use with the CNRS Fizeau wedge laser tuner, consisting of three circuit boards. The first board is a standard Reticon RC-100 B motherboard which is used to provide the timing, video processing, and housekeeping functions required by the Reticon RL-512 G photodiode array used in the system. The sampled and held video signal from the motherboard is processed by a second, custom fabricated circuit board which contains a high speed fringe detection and locating circuit. This board includes a dc level discriminator type fringe detector, a counter circuit to determine fringe center, a pulsed laser triggering circuit, and a control circuit to operate the shutter for the He-Ne reference laser beam. The fringe center information is supplied to the third board, a commercial single board computer, which governs the data collection process and interprets the results.