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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Phase-2 Upgrade of the CMS Data Acquisition

The High Luminosity LHC (HL-LHC) will start operating in 2027 after the third Long Shutdown (LS3), and is designed to provide an ultimate instantaneous luminosity of 7:5 × 10$^{34}$ cm$^{-2}$ s$^{-1}$, at the price of extreme pileup of up to 200 interactions per crossing. The number of overlapping interactions in HL-LHC collisions, their density, and the resulting intense radiation environment, warrant an almost complete upgrade of the CMS detector. The upgraded CMS detector will be read out by approximately fifty thousand highspeed front-end optical links at an unprecedented data rate of up to 80 Tb/s, for an average expected total event size of approximately 8 - 10 MB. Following the present established design, the CMS trigger and data acquisition system will continue to feature two trigger levels, with only one synchronous hardware-based Level-1 Trigger (L1), consisting of custom electronic boards and operating on dedicated data streams, and a second level, the High Level Trigger (HLT), using software algorithms running asynchronously on standard processors and making use of the full detector data to select events for offline storage and analysis. The upgraded CMS data acquisition system will collect data fragments for Level-1 accepted events from the detector back-end modules at a rate up to 750 kHz, aggregate fragments corresponding to individual Level- 1 accepts into events, and distribute them to the HLT processors where they will be filtered further. Events accepted by the HLT will be stored permanently at a rate of up to 7.5 kHz. This paper describes the baseline design of the DAQ and HLT systems for the Phase-2 of CMS.

Badaro, Gilbert↗
DOE OSTI2023

Hardware design and testing of the generic rear transition module for the global trigger subsystem of ATLAS Phase-II Upgrade

Abstract In the framework of the ATLAS experiment’s Phase-II Upgrade at the High-Luminosity Large Hadron Collider (HL-LHC), new and improved trigger hardware and algorithms will be implemented onto a single-level, 10 μs-latency architecture. The Global Trigger is a new subsystem which will bring event-filter capabilities by performing offline-like algorithms on full-granularity calorimeter data. The implementation of the functionality is firmware-focused and composed of several processing nodes, which are hosted on identical hardware, made up of an Advanced Telecommunications Computing Architecture (ATCA) front board, called Global Common Module (GCM), and a rear transition module (RTM), called Generic RTM (GRM). The GRM, which was developed to mitigate the risks deriving from the complex design and power management of the GCM, features an advanced Xilinx Versal Prime system-on-chip and can handle communication with the GCM and Front-End Link eXchange (FELIX) subsystem and trigger processors through 124 25.8 Gb/s transceiver links, for readout and control. Additionally, the GRM mounts a Low-Power GigaBit Transceiver (lpGBT) chip which enables emulation of the detector front-ends for integration tests. This paper presents the GRM hardware design and its testing.

Instruments & Instrumentation↗
DOE OSTI2024

Machine Learning for DUNE Supernova Trigger

One of the major scientific goals of the Deep Underground Neutrino Experiment (DUNE) is to detect and measure the neutrino flux originating from galactic core-collapse supernovae. These neutrinos provide an opportunity to study the end of life evolution of massive stars, and reveal information about the structure of core-collapse that is not visible in observations of the electromagnetic spectrum. Because of the rarity of these events, it is crucial that DUNE is able to detect supernova neutrino interactions when they occur. However, this will require sifting through a large quantity of data, motivating the development of a trigger algorithm to identify significant events and discard irrelevant data. Machine learning provides a potential approach to building this trigger. This project generates ADC and ground truth images of simulated neutrino interactions in a LArTPC detector to be used for machine learning, and uses them to train a sparse Convolutional Neural Network (C NN). The performance of this model when applied to the task of pixel classification based on interaction type is examined. This project found that the sparse CNN approach has the potential to have high accuracy in pixel classification, meaning it may be highly relevant to the development of a supernova neutrino trigger for the DUNE far detector.

Damish, S.↗
DOE OSTI2026

Two-Stage Wildlife Event Classification for Edge Deployment

Camera-based wildlife monitoring is often overwhelmed by non-target triggers and slowed by manual review or cloud-dependent inference, which can prevent timely intervention for high stakes human–wildlife conflicts. Our key contribution is a deployable, fully offline edge vision sensor that achieves near-real-time, highly accurate wildlife event classification by combining detector-based empty-image suppression with a lightweight classifier trained with a staged transfer-learning curriculum. Specifically, Stage 1 uses a pretrained You Only Look Once (YOLO)-family detector for permissive animal localization and empty-trigger suppression, and Stage 2 uses a lightweight EfficientNet-based binary classifier to confirm puma on detector crops and gate downstream actions. Our design is robust to low-quality nighttime monochrome imagery (motion blur, low contrast, illumination artifacts, and partial-body captures) and operates using commercially available components in connectivity-limited settings. In field deployments running since May 2025, end-to-end latency from camera trigger to action command is approximately 4 s. Ablation studies using a dataset of labeled wildlife images (pumas, not pumas) show that the two-stage approach substantially reduces false alarms in identifying pumas relative to a full-image classifier while maintaining high recall. On the held-out test set (N = 1434 events), the proposed two-stage cascade achieves precision 0.983, recall 0.975, F1 0.979, accuracy 0.986, and balanced accuracy 0.983, with only 8 false positives and 12 false negatives. The system can be easily adapted for other species, as demonstrated by rapid retraining of the second stage to classify ringtails. Downstream responses (e.g., notifications and optional audio/light outputs) provide flexible actuation capabilities that can be configured to support intervention.

58 GEOSCIENCES↗
DOE OSTI2022

Using Cosmic Ray Muons to Assess Geological Characteristics in the Subsurface

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a wide range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location (e.g., rock overburden and density) without having to use conventional methods such as boreholes. This work uses a low-power plastic scintillator-based muon detection system as a prototype for this non-destructive geological assay methodology. Four custom designed 102 cm x 51 cm x 5 cm plastic scintillation panels are used to realize two orthogonal detection planes. Optical photons from each scintillation panel are read using OnSemi J-Series 4x4 silicon photomultiplier (SiPM) arrays in conjunction with preamplifiers. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using the QuarkNet data acquisition system (DAQ) from Fermi National Accelerator Laboratory. A custom detector holder was designed to securely mount the detection system and rotate the panels along the zenith to collect data at variable angles. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo (MC) simulation using Geant4 is being developed. Cosmic ray flux prediction will be included in the project by adding the CORSIKA MC code to the simulation toolchain. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, muons will initially be measured at the surface, establishing the baseline flux. This is followed by recording the muon flux at variable depths and zenith angles, where the data will be used by the reconstruction algorithm to predict the overburden. The result will be benchmarked against geological surveys. The measured flux data will also be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, experimental methodology, and the benchmarking efforts are detailed in this work.

Gadey, Harish Reddy↗
DOE OSTI2023

Prototype Design of Global Common Module for ATLAS Experiment’s Phase-II Upgrade

A new Global Trigger subsystem will be installed in the Level-0 Trigger as part of HL-LHC Upgrade of ATLAS during the upcoming Long-Shutdown 3. It will feature new and improved trigger hardware and algorithms, and an increased maximum output rate of 1 MHz. The Global Trigger will run offline-like trigger algorithms on full-granularity data, gathered from several sub-detectors and trigger-processing subsystems. A single Global Common Module (GCM) hardware is implemented across the Global Trigger system to be used as Multiplexer Processor, Global Event Processor and CTP Interface (gCTPi). This common hardware platform method will minimize the complexity of the firmware and simplify the system design and long-term maintenance. The GCM prototype is an ATCA front form factor board with two Xilinx Virtex UltraScale+ FPGA VU13P and one ZYNQ UltraScale+ FPGA ZU19EG and seventeen 25.78125 Gb/s FireFly duplex optical modules on it. The total power consumption of this board must be less than 350 W, and the temperature of the optical modules should be less than 70 °C in the worst case. The VU13Ps serve as algorithms processor nodes such as MUX, GEP and gCTPi, and the ZU19EG with Peta Linux OS running on it, is used as Command/Control/Readout Unit to configure and monitor the board and communicate with the ATLAS Detector Control System (DCS). The development of an ATCA blade with three large FPGAs and about 200 optical links running at 25Gb/s is a very challenging task, and the successful test results have demonstrated this GCM prototype as an advancement of state-of-the-art electronics module design in HEP experiments. This paper presents the hardware design considerations, functionalities, and performance test results of this GCM prototype.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The ATLAS trigger system for LHC Run 3 and trigger performance in 2022

The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Conceptual Design Report for the MATHUSLA Long-Lived Particle Detector near CMS

We present the Conceptual Design Report (CDR) for the MATHUSLA (MAssive Timing Hodoscope for Ultra-Stable neutraL pArticles) long-lived particle detector at the HL-LHC, covering the design, fabrication and installation at CERN Point 5. MATHUSLA is a 40 m-scale detector with an air-filled decay volume that is instrumented with scintillator tracking detectors, to be located near CMS. Its large size, close proximity to the CMS interaction point and about 100 m of rock shielding from HL-LHC backgrounds allows it to detect LLP production rates and lifetimes that are one to two orders of magnitude beyond the ultimate sensitivity of the HL-LHC main detectors for many highly motivated LLP signals. Data taking is projected to commence with the start of HL-LHC operations. We present a new 40m design for the detector: its individual scintillator bars and wavelength-shifting fibers, their organization into tracking layers, tracking modules, tower modules and the veto detector; define a high-level design for the supporting electronics, DAQ and trigger system, including supplying a hardware trigger signal to CMS to record the LLP production event; outline computing systems, civil engineering and safety considerations; and present preliminary cost estimates and timelines for the project. We also conduct detailed simulation studies of the important cosmic ray and HL-LHC muon backgrounds, implementing full track/vertex reconstruction and background rejection, to ultimately demonstrate high signal efficiency and $\ll 1$ background event in realistic LLP searches for the main physics targets at MATHUSLA. This sensitivity is robust with respect to detector design or background simulation details. Appendices provide various supplemental information.

Aitken, Branden [Victoria U.]↗
DOE OSTI2022

Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019–2020 Australian wildfires

More than 1 Tg smoke aerosol was emitted into the atmosphere by the exceptional 2019–2020 southeastern Australian wildfires. Triggered by the extreme fire heat, several deep pyroconvective events carried the smoke directly into the stratosphere. Once there, smoke aerosol remained airborne considerably longer than in lower atmospheric layers. The thick plumes traveled eastward, thereby being distributed across the high and mid-latitudes in the Southern Hemisphere, enhancing the atmospheric opacity. Due to the increased atmospheric lifetime of the smoke plume, its radiative effect increased compared to smoke that remains in lower altitudes. Global models describing aerosol-climate impacts lack adequate descriptions of the emission height of aerosols from intense wildfires. Here, we demonstrate, by a combination of aerosol-climate modeling and lidar observations, the importance of the representation of those high-altitude fire smoke layers for estimating the atmospheric energy budget. Through observation-based input into the simulations, the Australian wildfire emissions by pyroconvection are explicitly prescribed to the lower stratosphere in different scenarios. Based on our simulations, the 2019–2020 Australian fires caused a significant top-of-atmosphere (TOA) hemispheric instantaneous direct radiative forcing signal that reached a magnitude comparable to the radiative forcing induced by anthropogenic absorbing aerosol. Up to +0.50 W m -2 instantaneous direct radiative forcing was modeled at TOA, averaged for the Southern Hemisphere (+0.25 W m -2 globally) from January to March 2020 under all-sky conditions. At the surface, on the other hand, an instantaneous solar radiative forcing of up to -0.81 W m -2 was found for clear-sky conditions, with the respective estimates depending on the model configuration and subject to the model uncertainties in the smoke optical properties. Since extreme wildfires are expected to occur more frequently in the rapidly changing climate, our findings suggest that high-altitude wildfire plumes must be adequately considered in climate projections in order to obtain reasonable estimates of atmospheric energy budget changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Search for jet quenching with dijets from high-multiplicity pPb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV

The first measurement of the dijet transverse momentum balance xj in proton-lead (pPb) collisions at a nucleon-nucleon center-of-mass energy of $\sqrt{s_{NN}}$ = 8.16 TeV is presented. The xj observable, defined as the ratio of the subleading over leading jet transverse momentum in a dijet pair, is used to search for jet quenching effects. The data, corresponding to an integrated luminosity of 174.6 nb −1 , were collected with the CMS detector in 2016. The x j distributions and their average values are studied as functions of the charged-particle multiplicity of the events and for various dijet rapidity selections. The latter enables probing hard scattering of partons carrying distinct nucleon momentum fractions x in the proton- and lead-going directions. The former, aided by the high-multiplicity triggers, allows probing for potential jet quenching effects in high-multiplicity events (with up to 400 charged particles), for which collective phenomena consistent with quark-gluon plasma (QGP) droplet formation were previously observed. The ratios of x j distributions for high- to low-multiplicity events are used to quantify the possible medium effects. These ratios are consistent with simulations of the hard-scattering process that do not include QGP production. These measurements set an upper limit on medium-induced energy loss of the subleading jet of 1.26% of its transverse momentum at the 90% confidence level in high multiplicity pPb events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs

Gravitational wave (GW) events detectable by LIGO and Virgo have several possible progenitors, including black hole mergers, neutron star mergers, black hole–neutron star mergers, supernovae, and cosmic string cusps. A subset of GW events is expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO–Virgo Collaboration (LVC) sends GW candidate alerts to the astronomical community so that searches for their EM counterparts can be pursued. The DESGW group, consisting of members of the Dark Energy Survey (DES), the LVC, and other members of the astronomical community, uses the Dark Energy Camera (DECam) to perform a search and discovery program for optical signatures of LVC GW events. DESGW aims to use a sample of GW events as standard sirens for cosmology. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night’s images as quickly as possible. We discuss our search area determination, imaging pipeline, and candidate selection processes. We review results from the DESGW program during the first two LIGO–Virgo observing campaigns and introduce other science applications that our pipeline enables.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Tornadoes in Southeast South America: Mesoscale to Planetary-Scale Environments

Abstract A multiscale analysis of the environment supporting tornadoes in southeast South America (SESA) was conducted based on a self-constructed database of 74 reports. Composites of environmental and convective parameters from ERA5 were generated relative to tornado events. The distribution of the reported tornadoes maximizes over the Argentine plains, while events are rare close to the Andes and south of Sierras de Córdoba. Events are relatively common in all seasons except in winter. Proximity environment evolution shows enhanced instability, deep-layer vertical wind shear, storm-relative helicity, reduced convective inhibition, and a lowered lifting condensation level before or during the development of tornadic storms in SESA. No consistent signal in low-level wind shear is seen during tornado occurrence. However, a curved hodograph with counterclockwise rotation is present. The Significant Tornado Parameter (STP) is also maximized prior to tornadogenesis, most strongly associated with enhanced CAPE. Differences in the convective environment between tornadoes in SESA and the U.S. Great Plains are discussed. On the synoptic scale, tornado events are associated with a strong anomalous trough crossing the southern Andes that triggers lee cyclogenesis, subsequently enhancing the South American low-level jet (SALLJ) that increases moisture advection to support deep convection. This synoptic trough also enhances vertical shear that, along with enhanced instability, sustains organized convection capable of producing tornadic storms. At planetary scales, the tornadic environment is modulated by Rossby wave trains that appear to be forced by convection near northern Australia. Madden–Julian oscillation phase 3 preferentially occurs 1–2 weeks ahead of tornado occurrence. Significance Statement The main goal of this study is to describe what atmospheric conditions (from local to global scales) are present prior to and during tornadic storms impacting southeast South America (SESA). Increasing potential for deep convection, wind shear, and potential for rotating updrafts, as well as reducing convective inhibition and cloud-base height, are predominant a few hours before and during the events in connection to low-level northerly winds enhancing moisture transport to the region. Remote convective activity near northern Australia appears to influence large-scale atmospheric circulation that subsequently triggers convective storms supporting tornadogenesis 1–2 weeks later in SESA. Our findings highlight the importance of accounting for atmospheric processes occurring at different scales to understand and predict tornado occurrences.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Electromagnetic power of lightning superbolts from Earth to space

Lightning superbolts are the most powerful and rare lightning events with intense optical emission, first identified from space. Superbolt events occurred in 2010-2018 could be localized by extracting the high energy tail of the lightning stroke signals measured by the very low frequency ground stations of the World-Wide Lightning Location Network. Here, we report electromagnetic observations of superbolts from space using Van Allen Probes satellite measurements, and ground measurements, and with two events measured both from ground and space. From burst-triggered measurements, we compute electric and magnetic power spectral density for very low frequency waves driven by superbolts, both on Earth and transmitted into space, demonstrating that superbolts transmit 10-1000 times more powerful very low frequency waves into space than typical strokes and revealing that their extreme nature is observed in space. We find several properties of superbolts that notably differ from most lightning flashes; a more symmetric first ground-wave peak due to a longer rise time, larger peak current, weaker decay of electromagnetic power density in space with distance, and a power mostly confined in the very low frequency range. Their signal is absent in space during day times and is received with a long-time delay on the Van Allen Probes. These results have implications for our understanding of lightning and superbolts, for ionosphere-magnetosphere wave transmission, wave propagation in space, and remote sensing of extreme events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A New Track Trigger for Characterization of the Antiproton-Induced Background in the Mu2e Experiment

The Mu2e experiment at Fermilab will enable the search for the neutrinoless muon to electron conversion in the field of an Al nucleus, a charged lepton flavor violating process. If observed, there would be a clear indication of physics beyond the Standard Model. Mu2e aims to reach a single event sensitivity of $3 /times 10^{-17}$, improving from the previous limit by 4 orders of magnitude. This improvement relies on the development of trigger selection systems, designed to discard data from background-induced events by placing kinematic, topological cuts on a particle’s reconstructed track. One of the largest sources of background Mu2e faces is proton-antiproton annihilation. These annihilations produce a 2 GeV shower of particles, among which there could be an electron that mimics the conversion electron signal, with an expected number of 0.010 ± 0.010. The large uncertainty on this number is dominated by the systematic uncertainty associated with the theoretical production model. To better characterize this background, we have developed an antiproton trigger selection by taking advantage of the track multiplicity and topology of these events. We discuss the steps taken in this development and the first performance study of this trigger, evaluating the signal efficiency and background rate. This trigger is essential to enable a data-driven analysis targeting the reduction of the systematic uncertainty of the antiproton-induced background in the Mu2e experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗
DOE OSTI2023

Optimizing trigger-level track reconstruction for sensitivity to exotic signatures

Many compelling beyond the Standard Model scenarios predict signals that result in unconventional charged particle trajectories. Signatures for which unusual tracks are the most conspicuous feature of the event pose significant challenges for experiments at the Large Hadron Collider (LHC), particularly for the trigger. This article presents a study of track-based triggers for a representative set of long-lived and unconventional signatures at the upcoming High Luminosity LHC, as well as resulting recommendations for the target parameters of a hardware-based tracking system. Scenarios studied include large multiplicities of low-p T tracks produced in a soft-unclustered-energy-pattern model, displaced leptons and anomalous prompt tracks predicted in a Supersymmetry model with long-lived staus, and displaced hadrons predicted in a Higgs portal scenario with long-lived scalars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Multiplicity trigger detector for the S π RIT experiment

A multiplicity trigger detector (MTD) was developed for the SπRIT experiment that aims to probe the high- density symmetry energy via heavy-ion collisions (HICs). The MTD is designed to measure the charged-particle multiplicity in HICs to provide a trigger signal that can be used to select high-multiplicity events induced by central collisions. The MTD consists of two side-walls segmented into 30 plastic scintillation paddles, each equipped with a multi-pixel photon counter. A custom board with EASIROC front-end ASIC is used as readout electronics. A multiplicity logic signal is generated by an on-board FPGA that processes the discriminated signals from EASIROCs. The overall latency of the whole detector system for outputting the trigger is less than 100 ns, including 52 ns of electronics latency for processing the signals. During the measurement of 112 Sn + 124 Sn reactions at an incident energy of 270 MeV/nucleon, the minimum multiplicity threshold of the MTD was set to 4, where the overall trigger efficiency was obtained to be about 39 % for inclusive nuclear reactions. Furthermore, a simulation study with a numerical calculation of HICs found that the central collisions of impact parameters of less than 4 fm can be triggered with a high efficiency of more than 95 % by the experimental trigger condition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Light Curves and Event Rates of Axion Instability Supernovae

Abstract It was recently proposed that exotic particles can trigger a new stellar instability that is analogous to the e − e + pair instability if they are produced and reach equilibrium in the stellar plasma. In this study, we construct axion instability supernova (AISN) models caused by the new instability to predict their observational signatures. We focus on heavy axion-like particles (ALPs) with masses of ∼400 keV–2 MeV and coupling with photons of g a γ ∼ 10 −5 GeV −1 . It is found that the 56 Ni mass and the explosion energy are significantly increased by ALPs for a fixed stellar mass. As a result, the peak times of the light curves of AISNe occur earlier than those of standard pair-instability supernovae by 10–20 days when the ALP mass is equal to the electron mass. Also, the event rate of AISNe is 1.7–2.6 times higher than that of pair-instability supernovae, depending on the high mass cutoff of the initial mass function.

Mori, Kanji (ORCID:0000000325951657)↗