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At least 1,261 records · Page 70

In-Pixel Readout IC with compact in-pixel ADC for Pixel detectors at HL LHC

The prototype Smart Pixel concept test chip (SP28), designed in a CMOS 28 nm bulk process, is a proof of concept readout integrated circuit (ROIC) designed for a future Phase III High Luminosity upgrade of the Large Hadron Collider. It employs a synchronous analog to digital converter (ADC) for the front-end design, with signal processing and data conversion within a single bunch crossing of 25 ns. It is therefore capable of accurately detecting hits occurring in consecutive bunch crossings, without off-time registration of events and pileup insensitivity, making it particularly suitable for the inner most layers of the vertex detector. The ROIC consists of a matrix of 32 × 16 pixels, each 25 × 25 µm 2 in size. Each pixel contains a charge sensitive preamplifer with leakage current compensation, three auto-zero comparators for a 2-bit fash-type ADC. The total power consumption is approximately 5 µW per pixel. The measured noise at the output of all the hit comparators across the ROIC is < 90 e- with threshold dispersion < 45 e-RMS, which allows an in-time threshold setting of ≈ 475 e-.

Parpillon, Benjamin↗

Variational autoencoders for at-source data reduction and anomaly detection in high energy particle detectors

Detectors in next-generation high-energy physics experiments face several daunting requirements, such as high data rates, damaging radiation exposure, and stringent constraints on power, space, and latency. To address these challenges, machine learning in readout electronics can be leveraged for smart detector designs, enabling intelligent inference and data reduction at-source. Variational autoencoders (VAEs) offer a variety of benefits for front-end readout; an on-sensor encoder can perform efficient lossy data compression while simultaneously providing a latent space representation that can be used for anomaly detection. Results are presented from low-latency and resource-efficient VAEs for front-end data processing in a futuristic silicon pixel detector. Encoder-based data compression is found to preserve good performance of off-detector analysis while significantly reducing the off-detector data rate as compared to a similarly sized data filtering approach. Furthermore, the latent space information is found to be a useful discriminator in the context of real-time sensor defect monitoring. Together, these results highlight the multifaceted utility of autoencoder-based front-end readout schemes and motivate their consideration in future detector designs.

47 OTHER INSTRUMENTATION↗

Air quality impacts from the development of unconventional oil and gas well pads: Air toxics and other volatile organic compounds

Unconventional oil and natural gas development (UOGD) has expanded rapidly across the United States in recent decades and raised concerns about associated air quality impacts. While significant effort has been made to quantify methane emissions, relatively few observations have been made of Volatile Organic Compounds (VOCs), especially during drilling and completion of new wells. Extensive air monitoring during development of several large, multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin, provides a novel opportunity to examine changes in local air toxics and other VOC concentrations during well drilling and completions and production. These operations offer an especially useful case to study as several management practices were implemented to reduce emissions (e.g., electrified, grid-powered drill rigs and closed loop fluid handling systems to reduce truck traffic and limit fluid handling on the pad). With simultaneous measurements of methane and 50 VOCs from October 2018 to December 2022 at as many as 19 sites near well pads, in adjacent neighborhoods, and at a more distant reference location, we identify impacts from each phase of well development and production. Use of weekly, time-integrated canisters, a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous photoionization detectors (PID) to trigger canister collection upon detection of VOC-rich plumes, and an instrumented vehicle, provided a powerful suite of measurements to characterize both transient plumes and longer-term changes in air quality. Prior to the start of well development, VOC gradients were small across Broomfield. Once drilling commenced, concentrations of oil and gas (O&G) related VOCs, including alkanes and aromatics, increased around active well pads. Concentration increases were clearly apparent during certain operations, including drilling, coil tubing/millout operations, and production tubing installation. Emissions of C 8 –C 10 n-alkanes during drilling operations highlighted the importance of VOC emissions from synthetic drilling mud chosen to reduce odor impacts. More than 90 samples were collected of transient plumes. Using composition measurements, meteorological data, and information about well pad activities, these plumes were connected with specific UOGD operations including drilling, flowback, and production equipment maintenance. The chemical signatures of these plumes differed by operation type (e.g., C 8 –C 10 n-alkanes constituted a larger fraction of measured VOCs in drilling-related plumes). Concentrations of individual, oil and gas-related VOCs in these plumes were often several orders of magnitude higher than in background air, with maximum ethane and benzene concentrations of 79,600 and 819 ppbv, respectively. Because these plumes typically impact a monitoring site for just several minutes, they are easily missed by slower-responding instruments. Study measurements highlight future emission mitigation opportunities during UOGD operations, including better control of emissions from shakers that separate drill cuttings from drilling mud, production separator maintenance operations, and periodic emptying of sand cans during flowback operations.

54 ENVIRONMENTAL SCIENCES↗

Characterization of stilbene-d 12 for neutron spectroscopy without time of flight

In this work, we have experimentally characterized the light-output response of a deuterated trans-stilbene (stilbene-d 12 ) crystal to quasi-monoenergetic neutrons in the 0.8 to 4.4 MeV energy range. These data allowed us to perform neutron spectroscopy measurements of a DT 14.1 MeV source and a 239 PuBe source by unfolding the impinging neutron spectrum from the measured light-output response. The stilbene-d 12 outperforms a 1 H-stilbene of similar size when comparing the shape of the unfolded spectra and the reference ones. These results confirm the viability of non-hygroscopic stilbene-d 12 crystal for direct neutron spectroscopy without need for time-of-flight measurements. This capability makes stilbene-d 12 a well suited detector for fast-neutron spectroscopy in many applications including nuclear reaction studies, radiation protection, nuclear non-proliferation, and space travel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of the absolute single-photon detection efficiency of HRPPD

Pixelated High Rate Picosecond Photon Detectors (HRPPDs) by Incom Inc. are promising photosensors for use in Ring Imaging CHerenkov (RICH) detectors, where a high gain, sub-mm position resolution and sub-100ps timing resolution are required in a single photon mode. Quantum Efficiency (QE) has been measured for the first batch of EIC HRPPDs both by Incom and EIC research groups at Jefferson Lab and Brookhaven Lab, with peak values at ∼365 nm typically exceeding 30%. Furthermore, in this study, we present a first direct measurement of Photon Detection Efficiency being equal to (17.1 ± 0.1 [stat] ± 0.3 [sys])% at 398.6 nm, for a pixel near the center of HRPPD, in a photoelectron pulse counting mode using a picosecond diode laser. HRPPD QE at the same spot and at the same wavelength was evaluated to be (24.4 ± 0.1 [stat] ± 0.3 [sys])%, leading to a Collection Efficiency estimate of (70.3 ± 1.6)%, which is consistent with the expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Total neutron cross-section measurement on CH with a novel 3D-projection scintillator detector

In order to extract neutrino oscillation parameters, long-baseline neutrino oscillation experiments rely on detailed models of neutrino interactions with nuclei. These models constitute an important source of systematic uncertainty, partially because detectors to date have been blind to final state neutrons. Three-dimensional projection scintillator trackers comprise components of the near detectors of the next generation long-baseline neutrino experiments. Due to the good timing resolution and fine granularity, this technology is capable of measuring neutron kinetic energy in neutrino interactions on an event-by-event basis and will provide valuable data for refining neutrino interaction models and ways to reconstruct neutrino energy. Two prototypes have been exposed to the neutron beamline at Los Alamos National Laboratory (LANL) in both 2019 and 2020, with neutron energies between 0 and 800 MeV. In order to demonstrate the capability of neutron detection, the total neutron-scintillator cross section as a function of neutron energy is measured and compared to external measurements. The measured total neutron cross section in scintillator between 98 and 688 MeV is 0.36 ± 0.05 barn.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experiments with neutron induced neutron emission from U-235, Pu-239, and graphite

A neutron induced neutron emission experiment was conducted as the Los Alamos Neutron Science Center (LANSCE) facility at Los Alamos National Laboratory (LANL). In this experiment, a sample was placed in a well collimated neutron beam and was surrounded by an array of 28 fast neutron detectors (EJ-309). The experiment was performed with a neutron flight path of 21.5 m from the source to the sample, and 1 m from the sample to the detectors. The neutron emission from the sample was measured as a function of neutron time of flight covering an incident energy range from 0.7- 20 MeV. The samples included U-235, Pu-239, carbon (graphite), and blanks that matched the encapsulation of the sample. The measured samples were constantly cycled in and out of the neutron beam. This type of experiment measures neutron emission from all reactions occurring in the sample such as fission and elastic and inelastic scattering. Similar to the methodology previously developed at RPI, the measurements were compared with detailed simulations of the experiment using different cross section evaluations for the sample. The observed differences can be attributed to the evaluated neutron cross section and angular distributions. The carbon sample was used as a reference to validate both the experiment and simulation methodology and showed good agreement between experiments and simulations. A review of the experimental setup, analysis methods, and some of the results will be presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Spectral characterization of an SPDC source with a fast broadband spectrometer

Knowing the properties of single photons produced in a Spontaneous Parametric Down-Conversion (SPDC) source can be crucial for specific applications and uses. In particular, the spectral properties are of key relevance. Here, we investigate a commercial SPDC source using our fast broadband spectrometer. Our analysis is a valid method for other SPDC sources, as well as other single-photon generation techniques, thus providing a good example of how to use this spectrometer design. We calibrate the spectrometer using known lines of the argon emission spectrum. We show that the two down-converted photons from the SPDC source have different spectral properties depending on the pump power, and under which condition we measured spectrally similar down-converted photons. Finally, we were able to reconstruct and investigate the spectral information for the pump photon.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploration of Neutron-Rich Isotopes around N = 50 via the In-Flight Fission of a 345 MeV/Nucleon 238 U Beam

A search for new neutron-rich isotopes beyond $Z=28$ and $N=50$ was performed using a 345 MeV/nucleon $^{238}$U beam at RI Beam Factory in RIKEN Nishina Center. The BigRIPS separator and state-of-the-art radiation detectors were used to efficiently separate and identify the produced nuclei. For the first time, we have observed and determined the production cross sections for eight neutron-rich isotopes $^{72}$Cr, $^{74,75}$Mn, $^{77}$Fe, $^{79,80}$Co, $^{85}$Cu, and $^{90}$Ga. This study broadens our understanding of nuclear existence and paves the way for investigating the properties of neutron-rich medium-mass nuclei.

Shimizu, Yohei [RIKEN, Saitama (Japan); et al.]↗

Measurement of the scintillation and ionization response of liquid xenon at MeV energies in the EXO-200 experiment

In this work, liquid xenon (LXe) is employed in a number of current and future detectors for rare event searches. We use the EXO-200 experimental data to measure the absolute scintillation and ionization yields generated by γ interactions from 228 Th (2615 keV), 226 Ra (1764 keV), and 60 Co (1332 keV and 1173 keV) calibration sources, over a range of electric fields. The W value that defines the recombination-independent energy scale is measured to be 11.5±0.5 (syst.) ±0.1 (stat.) eV. These data are also used to measure the recombination fluctuations in the number of electrons and photons produced by the calibration sources at the MeV scale, which deviate from extrapolations of lower-energy data. Additionally, a semiempirical model for the energy resolution of the detector is developed, which is used to constrain the recombination efficiency, i.e., the fraction of recombined electrons that result in the emission of a detectable photon. Detailed measurements of the absolute charge and light yields for MeV-scale electron recoils are important for predicting the performance of future neutrinoless double β -decay detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observation of χ c 0 → Σ + Σ ¯ − η and evidence for χ c 1 , 2 → Σ + Σ ¯ − η

Using ( 27.12 ± 0.14 ) × 10 8 ψ ( 3686 ) events collected with the BESIII detector, the decay χ c 0 → Σ + Σ ¯ − η is observed for the first time with a signal significance of 7.0 σ , and evidence for χ c 1 → Σ + Σ ¯ − η and χ c 2 → Σ + Σ ¯ − η is found with signal significances of 4.3 σ and 4.6 σ , respectively. The branching fractions are determined to be B ( χ c 0 → Σ + Σ ¯ − η ) = ( 1.26 ± 0.20 ± 0.13 ) × 10 − 4 , B ( χ c 1 → Σ + Σ ¯ − η ) = ( 5.10 ± 1.21 ± 0.67 ) × 10 − 5 , and B ( χ c 2 → Σ + Σ ¯ − η ) = ( 5.46 ± 1.18 ± 0.50 ) × 10 − 5 , where the first uncertainties are statistical, and the second ones are systematic. Published by the American Physical Society 2024

Ablikim, M.↗

Gravitational Wave Symphony from Oscillating Spectator Scalar Fields

We investigate a generic source of stochastic gravitational wave background due to the parametric resonance of oscillating scalar fields in the early Universe. By systematically analyzing benchmark models through lattice simulations and considering a wide range of parameters, we demonstrate that such a scenario can lead to detectable signals in gravitational wave detectors over a broad frequency range and potentially address the recent findings by pulsar timing array experiments. Furthermore, these models naturally yield ultralight dark matter candidates or dark radiation detectable by cosmic microwave background observatories. Published by the American Physical Society 2024

Physics↗

Observation of the ϒ ( 3 S ) Meson and Suppression of ϒ States in Pb-Pb Collisions at s N N = 5.02 TeV

The production of ϒ ( 2 S ) and ϒ ( 3 S ) mesons in lead-lead (Pb-Pb) and proton-proton ( p p ) collisions is studied in their dimuon decay channel using the CMS detector at the LHC. The ϒ ( 3 S ) meson is observed for the first time in Pb-Pb collisions, with a significance above 5 standard deviations. The ratios of yields measured in Pb-Pb and p p collisions are reported for both the ϒ ( 2 S ) and ϒ ( 3 S ) mesons, as functions of transverse momentum and Pb-Pb collision centrality. These ratios, when appropriately scaled, are significantly less than unity, indicating a suppression of ϒ yields in Pb-Pb collisions. This suppression increases from peripheral to central Pb-Pb collisions. Furthermore, the suppression is stronger for ϒ ( 3 S ) mesons compared to ϒ ( 2 S ) mesons, extending the pattern of sequential suppression of quarkonium states in nuclear collisions previously seen for the J / ψ , ψ ( 2 S ) , ϒ ( 1 S ) , and ϒ ( 2 S ) mesons. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Opportunities and challenges to study solar neutrinos with a Q-Pix pixel readout

The study of solar neutrinos presents significant opportunities in astrophysics, nuclear physics, and particle physics. However, the low-energy nature of these neutrinos introduces considerable challenges to isolate them from background events, requiring detectors with low-energy threshold, high spatial and energy resolutions, and low data rate. We present the study of solar neutrinos with a kiloton-scale liquid argon detector located underground, instrumented with a pixel readout using the Q-Pix technology. We explore the potential of using volume fiducialization, directional topological information, light signal coincidence, and pulse-shape discrimination to enhance solar neutrino sensitivity. We find that discriminating neutrino signals below 5 MeV is very difficult. However, we show that these methods are useful for the detection of solar neutrinos when external backgrounds are sufficiently understood and when the detector is built using low-background techniques. When building a workable background model for this study, we identify 𝛾 background from the cavern walls and from capture of 𝛼 particles in radon decay chains as both critical to solar neutrino sensitivity and significantly underconstrained by existing measurements. Finally, we highlight that the main advantage of the use of Q-Pix for solar neutrino studies lies in its ability to enable the continuous readout of all low-energy events with minimal data rates and manageable storage for further off-line analyses.

multi-purpose particle detectors↗

A 32-Channel Cryo-CMOS ASIC for SNSPD Biasing and Readout with Picosecond

Superconducting nanowire single-photon detectors (SNSPD) are a promising technology for particle detection. Although SNSPDs have demonstrated picosecond timing accuracy, scaling up large arrays has proved challenging. In this work, we introduce a 32-channel cryo-CMOS application-specific integrated circuit (ASIC) that can be tightly integrated with SNSPD arrays. The ASIC is designed to operate at a temperature of 4K and can perform up to 32 simultaneous timing measurements with a root-mean-square (RMS) accuracy of 8.0ps. The ASIC includes on-chip circuitry for externally biasing superconducting devices, low-noise amplifiers for reading superconducting devices, high-resolution time-to-digital converters (TDC) for time-tagging events, and serializers for transmitting data to room-temperature electronics. The ASIC is manufactured in a 22nm FDSOI process and occupies an area of 4.0mm x 1.0mm. The performance of the ASIC was verified using custom cryogenic device models internally developed for the 22nm SOI process. Measurement results will be presented at the conference.

Fredenburg, Jeff↗

A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring

Seismology is one of the main sciences used to monitor volcanic activity worldwide. Fast, efficient, and accurate seismicity detectors are crucial to assess the activity level of a volcano in near–real time and to issue timely warnings. Traditional real–time seismic processing software uses phase onset pickers followed by a phase association algorithm to declare an event and estimate its location. The pickers typically do not identify whether the detected phase is a P or S arrival, which can have a negative impact on hypocentral location quality and complicates phase association. We implemented the deep–neural–network–based method PhaseNet to identify in real time P and S seismic waves on data from one– and three–component seismometers. We tuned the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity in Mayotte and the Lesser Antilles region. Our algorithm, which we refer to as PhaseWorm, showed promising results in both contexts and clearly outperformed the previous automatic method implemented in Mayotte. As a result, this innovative real–time processing system is now operational for seismicity monitoring in Mayotte and Martinique.

58 GEOSCIENCES↗

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗