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At least 19 records

Multi‐Sensor Trajectory Reconstruction of the 24 April 2025 Alaska Fireball and Implications for Planetary Defense

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. Here, the unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals, with fragmentation source locations further guiding the identification of Doppler weather radar signatures of a meteorite fall. Incorporation of a radar-derived terminal point yielded a final trajectory solution, which agreed closely with an independent optical trajectory solution from video analysis. The reconstructed entry parameters from seismoacoustic analysis indicate a velocity of 25.3 km/s, an entry angle of 19°, and an energy release of ∼38 t TNT equivalent. Assuming a chondritic composition, the pre-entry object diameter was ∼0.7 m. Using orbital parameters from the optical solution, we estimate meteoroid composition as most likely an L-type ordinary chondrite. The event occurred in the sub-Arctic, where space-based optical systems face challenges in detection, demonstrating the critical role of dense ground-based seismoacoustic networks in characterizing high-latitude atmospheric entries. This uniquely well-recorded event demonstrates the capability of dense seismoacoustic networks to constrain bolide trajectories, energetics, and fragmentation, with radar and optical data providing critical confirmation and complementary perspectives. These results bridge the methodological gap between planetary-defense monitoring of natural impactors and space-traffic analyses of artificial reentries, illustrating how multi-sensor integration can deliver calibration-grade trajectories even for unpredicted events.

Fireball↗

FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm

The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High-Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20–40 Tb/s; processing a new batch of input data every 25 ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles (“stubs”); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within 4 µs. Here, this paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance.

47 OTHER INSTRUMENTATION↗

Shock wave formation in the thermosphere by an earthgrazing fireball: Empirical evidence for volatile-enhanced hydrodynamic shielding

Hydrodynamic shielding is a theoretically well-established but observationally elusive and experimentally difficult-to-replicate phenomenon with implications that extend far beyond meteor physics. Rare earthgrazing meteoroids with infrasound signatures that penetrate to the ground can be used to probe hydrodynamic shielding that leads to strong shock formation at high altitude. Here, we report the first coordinated optical and multi-station infrasound observations of a centimeter-scale earthgrazing fireball that generated sustained cylindrical line shock at thermospheric altitudes near 92 km. The event was recorded by numerous optical stations and three infrasound arrays, allowing trajectory reconstruction, ablation behavior, acoustic source localization, and shock characteristics. Optical observations indicate early mechanical erosion and ablation/evaporation at exceptionally low dynamic pressure, consistent with a cometary or a porous, volatile-bearing CM chondritic object. Independent infrasound detections localize shock generation to multiple points along a 164 km trajectory segment near perigee. Weak-shock modeling yields a consistent blast radius of ∼30 m, implying an acoustic-equivalent source size far exceeding the physical dimensions of the ∼45 g nucleus. We demonstrate that classical gas dynamics and ablation-driven hydrodynamic shielding alone cannot account for these observations under ambient thermospheric conditions. We show that volatile release provides the additional flow-field density enhancement required to amplify hydrodynamic shielding, reduce the effective local Knudsen number, and sustain a shock envelope capable of radiating detectable infrasound. Furthermore, these results demonstrate that small, volatile-rich meteoroids can transiently establish continuum-like flow in rarefied environments.

Astrometry↗

Search for heavy, long-lived, charged particles with large ionisation energy loss in $pp$ collisions at $ \sqrt{s} $ = 13 TeV using the ATLAS experiment and the full Run 2 dataset

This paper presents a search for hypothetical massive, charged, long-lived particles with the ATLAS detector at the LHC using an integrated luminosity of 139 fb –1 of proton–proton collisions at √s =13 TeV. These particles are expected to move significantly slower than the speed of light and should be identifiable by their high transverse momenta and anomalously large specific ionisation losses, dE/dx. Trajectories reconstructed solely by the inner tracking system and a dE/dx measurement in the pixel detector layers provide sensitivity to particles with lifetimes down to O(1) ns with a mass, measured using the Bethe–Bloch relation, ranging from 100 GeV to 3 TeV. Interpretations for pair-production of R-hadrons, charginos and staus in scenarios of supersymmetry compatible with these particles being long-lived are presented, with mass limits extending considerably beyond those from previous searches in broad ranges of lifetime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Performance of the Particle-Identification Silicon-Telescope Array coupled with the VAMOS++ magnetic spectrometer

The Particle-Identification Silicon-Telescope Array (PISTA) is a new detection system designed for high-resolution studies of fission process induced by multi-nucleon transfer in inverse kinematics. It is specifically optimized for experiments with the VAMOS++ magnetic spectrometer at GANIL (Grand Accélérateur National d’Ions Lourds). The array comprises eight trapezoidal ΔE-E silicon telescopes arranged in a lamp shade configuration. Each telescope integrates two single-sided stripped silicon detectors, enabling target-like recoil identification, energy loss measurements, and trajectory reconstruction. Positioned in close proximity to the target, PISTA’s compact geometry achieves high-efficiency tracking of target-like recoils produced in multi-nucleon transfer reactions at Coulomb barrier energies. The spatial segmentation of the array allows precise determination of the mass and charge of the target-like nucleus, and excitation energy of fissioning systems. This work presents the particle identification and excitation energy reconstruction performances for the interactions of 238 U beam with 12 C target. An excitation energy resolution of 800 keV (FWHM) was determined together with mass resolution of 1.1% (FWHM). The combination of PISTA and VAMOS++ magnetic spectrometer enables unprecedented investigations of the fission process as a function of the excitation energy of the fissioning nucleus, particularly for exotic systems produced in transfer-induced reactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation

A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3' RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of timeseries transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNcseq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.

59 BASIC BIOLOGICAL SCIENCES↗

Expected tracking performance of the ATLAS Inner Tracker at the High-Luminosity LHC

The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will create a very challenging environment in which to perform charged particle trajectory reconstruction, a task crucial for the success of the ATLAS physics program, and will exceed the capabilities of the current ATLAS Inner Detector (ID). A new all-silicon Inner Tracker (ITk) will replace the current ID in time for the start of the HL-LHC. To ensure successful use of the ITk capabilities in Run 4 and beyond, the ATLAS tracking software has been successfully adapted to achieve state-of-the-art track reconstruction in challenging high-luminosity conditions with the ITk detector. This paper presents the expected tracking performance of the ATLAS ITk based on the latest available developments since the ITk technical design reports.

47 OTHER INSTRUMENTATION↗

A Curated Dataset of Regional Meteor Events with Simultaneous Optical and Infrasound Observations (2006–2011)

We present a curated, openly accessible dataset of 71 regional meteor events simultaneously recorded by optical and infrasound instrumentation between 2006 and 2011. These events were captured during an observational campaign using the all-sky cameras of the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. Each entry provides optical trajectory measurements, infrasound waveforms, and atmospheric specification profiles. The integration of optical and acoustic data enables robust linkage between observed acoustic signals and specific points along meteor trajectories, offering new opportunities to examine shock wave generation, propagation, and energy deposition processes. This release fills a critical observational gap by providing the first validated, openly accessible archive of simultaneous optical–infrasound meteor observations that supports trajectory reconstruction, acoustic propagation modeling, and energy deposition analyses. By making these data openly available in a structured format, this work establishes a durable reference resource that advances reproducibility, fosters cross-disciplinary research, and underpins future developments in meteor physics, atmospheric acoustics, and planetary defense.

astrometry↗

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗

Street context of various demographic groups in their daily mobility

Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

Salgado, Ariel (ORCID:0000000177015372)↗

A Common Tracking Software Project

Abstract The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

97 MATHEMATICS AND COMPUTING↗

The CLAS12 drift chamber system

The CEBAF Large Acceptance Spectrometer at 12~GeV (CLAS12) is located in Hall~B, one of the experimental halls at Jefferson Lab. The forward part of CLAS12 is built around a superconducting toroidal magnet. The six coils of the toroid divide the detector azimuthally into six sectors. Each sector contains three multi-layer drift chambers for reconstructing the trajectories of charged particles originating from a fixed target. Each of the 18 planar chambers has two ``superlayers'' of six layers each, with the wires in the two adjacent superlayers oriented at ± 6° stereo angles. Each layer has 112 hexagonal cells spanning a range from about 5° to 40° in polar angle. The six-layer structure provides redundancy in track segment finding and good tracking efficiency even in the presence of some individual wire inefficiency. The design, construction, operation, and calibration methods are described, and estimates of the efficiency and resolution are presented from in-beam measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fermilab Italian Student Program (Final Report)

I participated to the 2019 Fermilab Italian Student Program under the supervision of Anadi Canepa and Lorenzo Uplegger. I worked with the Fermilab research group that is involved with the R&D of the CMS Outer Tracker. The Compact Muon Solenoid (CMS) is a a general-purpose detector located at the Large Hadron Collider (LHC), the world's most powerful particle accelerator. In the next years LHC will undergo the High-Luminosity LHC upgrade, which will bring its luminosity from 1 × 10 34 cm -2 s -1 to 1.5 × 10 34 cm -2 s -1 . This increase in luminosity will require an upgrade of CMS as well, in order to comply with the augmented rate of particles which will cross the detector. The CMS tracker is a detector, composed of various modules made of silicon pixel trackers and silicon strip trackers, whose aim is to reconstruct the trajectories of the particles produced by the collisions in LHC. The tracker is ideally divided in Inner Tracker and Outer Tracker. The HL-LHC upgrade put important challenges in the designing of the tracker. It will have to withstand the irradiation of a large fluence of particles, without suffering a too severe deterioration of its performance. In addition to this, in order to comply with the increased rate of events that CMS will need to detect, the tracker will be exploited for triggering at the fully hardware Level 1 Trigger, in contrast to the current tracker, whose data are only used for the software High-Level Trigger. This feature is managed by the "stub logic", which will be explained in chapter 2. During the months of August and September at Fermilab I carried out the data analysis of three test beam runs performed in the last two years on the 2S Outer Tracker Minimules. The 2S Minimoule consists of two silicon strip trackers placed one upon the other with the strips kept parallel.

43 PARTICLE ACCELERATORS↗

Measurement of space charge effects and energy calibration in ProtoDUNE-SP

The single-phase liquid argon prototype at CERN (ProtoDUNE-SP) acts as a validation of the design for the DUNE single-phase far detector. With a total mass of 770 tons, it is the largest monolithic liquid argon single-phase time projection chamber in the world. ProtoDUNE-SP collected test-beam in autumn of 2018 and has been collecting cosmic and special calibration data since the end of 2018.The accumulation of positive ions in a LArTPC located on the surface can distort the electric field and the reconstructed particle trajectories. It is critical to understand and correct for the space charge effects in order to achieve the desired spatial and calorimetric resolutions in the LArTPC. This talk will present the measurement of space charge effects and the calorimetric measurements of the detector in ProtoDUNE-SP.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗

Dynamic mode decomposition for extrapolating nonequilibrium Green's-function dynamics

The Hartree-Fock generalized Kadanoff-Baym ansatz (HF-GKBA) offers an approximate numerical procedure for propagating the two-time nonequilibrium Green's function (NEGF). Here, using the GW self-energy, we compare the HF-GKBA to exact results for a variety of systems with long- and short-range interactions, different two-body interaction strengths, and various nonequilibrium preparations. We find excellent agreement between the HF-GKBA and exact time evolution in models when more realistic long-range exponentially decaying interactions are considered. Furthermore, this agreement persists for long times and for intermediate to strong interaction strengths. In large systems, HF-GKBA becomes prohibitively expensive for long-time evolutions. For this reason, we look at the use of dynamical mode decomposition (DMD) to reconstruct long-time NEGF trajectories from a sample of the initial trajectory. Using no more than 16% of the total time evolution, we reconstruct the total trajectory with high fidelity. Our results show the potential for DMD to be used in conjunction with HF-GKBA to calculate long-time trajectories in large-scale systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗