Marchand_MICRE_V2.0_surface_precipitation_20160402_20170317
Surface precipitation based on combination of tipping bucket, surface disdrometer and W-band radar data
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Surface precipitation based on combination of tipping bucket, surface disdrometer and W-band radar data
Recently the PHENIX Collaboration has made available two-particle correlation Fourier coefficients for multiple detector combinations in minimum bias p+p and 0–5% central p+Au, d+Au, and 3 He+Au collisions at √ s NN = 200 GeV [Phys. Rev. C 105, 024901 (2022)]. Using these coefficients for three sets of two-particle correlations, azimuthal anisotropy coefficients v 2 and v 3 are extracted for midrapidity charged hadrons as a function of transverse momentum. In this paper, we use the available coefficients to explore various nonflow hypotheses as well as to compare the results with theoretical model calculations. The nonflow methods fail basic closure tests with ampt and pythia/angantyr, particularly when including correlations with particles in the low multiplicity light-projectile going direction. In data, the nonflow adjusted v 2 results are modestly lower in p+Au and the adjusted v 3 results are more significantly higher in p+Au and d+Au. However, the resulting higher values for the ratio v 3 /v 2 in p+Au at RHIC compared to p+Pb at the LHC is additional evidence for a significant overcorrection. Incorporating these additional checks, the conclusion that these flow coefficients are dominated by initial geometry coupled with final-state interactions (e.g., hydrodynamic expansion of quark-gluon plasma) remains true, and explanations based solely on initial-state glasma are ruled out. The detailed balance between intrinsic and fluctuation-driven geometry and the exact role of weakly versus strongly coupled prehydrodynamic evolution remains an open question for triangular flow, requiring further theoretical and experimental investigation.
Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms have been adapted to run on massively parallel coprocessors, such as graphics processing units (GPUs), to reduce processing time. Nevertheless, challenges remain in fully harnessing the computational capacity of coprocessors in a scalable and non-disruptive manner. This paper proposes an inference-as-a-service approach for particle tracking in high energy physics experiments. To evaluate the efficacy of this approach, two distinct tracking algorithms are tested: Patatrack, a rule-based algorithm, and Exa.TrkX, a machine learning-based algorithm. The as-a-service implementations show enhanced GPU utilization and can process requests from multiple CPU cores concurrently without increasing per-request latency. The impact of data transfer is minimal and insignificant compared to running on local coprocessors. This approach greatly improves the computational efficiency of charged particle tracking, providing a solution to the computing challenges anticipated in the High-Luminosity LHC era.
The Department of Energy for decades has explored the earth system and atmosphere through research and deployment of in-situ and remote sensing platforms during field campaigns. Among these datasets exists a vast supply of cloud particle images that provide visual insight into the complex microphysics in the clouds that span our globe. The millions of images collected over decades of deployments provides a unique opportunity to further our understanding of our atmosphere down to the crystal size. This work over the past 5 years has sought to organize these images into digestible datasets that can then be used by scientists to further our understanding of microphysics. A machine learning model was developed that categorizes over 1.5 million images across 11 weather events with over 90% accuracy according to particle type. The database was then extended to include dimensional characteristics of the particle as well as co-location of environmental properties, such as temperature and water content. Then, to initialize the connection between these data and our understanding of how crystals form and grow, weather research and forecasting simulations were run to generate the growth histories of the classified crystals. This research culminates with 2 databases per event: (1) a database of all classified crystals and their dimensional and environmental properties and (2) simulated growth histories of each crystal. Finally, a user interface was created to allow researchers to explore data statistics.
Sulfur Dioxide is a key precursor to the formation of new particles within the marine environment, yet commercial instrumentation lack sufficient precision or sensitivity to resolve the levels present in these environments. As such, the LIFSO2, a custom built fibre laser from the University of York, UK, was developed (based on the one developed by Rollins et al 2016). We are able to resolve down to the ppt level with this instrument. We present version 1 (v1) data for Dec 2024 to Mar 2025 for SO2 (1min time average) from the Cape-k precursors field campaign.
It is anticipated that the Large Hadron Collider (LHC) will collect data from oxygen-oxygen (O+O) collisions at a center-of-mass energy of $\sqrt{s_{NN}}$ = 7 TeV to explore the effects observed in high multiplicity proton-proton (p+p) and proton-lead (p+pb) collisions that closely related to lead-lead (Pb+Pb) collisions. Furthermore, these effects include azimuthal asymmetries in particle production, as well as variations in the abundances and momentum distributions across different hadron species, which are indicative of collective particle production mechanisms induced by the interactions in the presence of a QGP. The upcoming data on O+O collisions at the LHC are expected to constrain the model parameters and refine our understanding of theoretical models. In this work, the predicted transverse momentum (p T ) spectra, rapidity density distributions (dN/dy), particle yield ratios, and p T -differential ratios of (multi)strange hadrons produced in O+O collisions at $\sqrt{s_{NN}}$ = 7 TeV using AMPT and EPOS4 models are presented. AMPT focuses on preformed hadronic interactions, while EPOS4 incorporates a QGP phase. Stronger radial flow in EPOS4 as compared to AMPT is also observed. AMPT incorporates some flow effects, but the implementation of full hydrodynamic flow in EPOS4 appears to be significantly more effective in reproducing the existing experimental data. Both models predict the final state multiplicity overlap with p+p, p+pb, and Pb+Pb collisions.
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.
A measurement of event-shape variables is presented, using a data sample produced in a special run with approximately one inelastic proton-proton collision per bunch crossing. The data were collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 64 μb −1 . A number of observables related to the overall distribution of charged particles in the collisions are corrected for detector effects and compared with simulations. Inclusive event-shape distributions, as well as differential distributions of event shapes as functions of charged-particle multiplicity, are studied. None of the models investigated are able to satisfactorily describe the data. Moreover, there are significant features common amongst all generator setups studied, particularly showing data being more isotropic than any of the simulations. Multidimensional unfolded distributions are provided, along with their correlations.
We present a novel constraint on light dark matter utilizing 1.54 metric ton/year of data acquired from the PandaX-4T dual-phase xenon time projection chamber. This constraint is derived through detecting electronic recoil signals resulting from the interaction with solar-enhanced dark matter flux. Low-mass dark matter particles, lighter than a few MeV / c 2 , can scatter with the thermal electrons in the Sun. Consequently, with higher kinetic energy, the boosted dark matter component becomes detectable via contact scattering with xenon electrons, resulting in a few keV energy deposition that exceeds the threshold of PandaX-4T. We calculate the expected recoil energy in PandaX-4T considering the Sun’s acceleration with heavy mediators and the detection capabilities of the xenon detector. The first experimental search results using the xenon detector yield the most stringent upper limits cross section of 3.51 × 10 − 39 cm 2 at 0.08 MeV / c 2 for a solar boosted dark matter mass ranging from 0.02 to 10 MeV / c 2 , achieving a 23-fold improvement compared with earlier experimental studies. Published by the American Physical Society 2025
Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.
The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV c$^{−2}$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV c$^{−2}$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP–nucleon interaction cross-sections below 1 × 10$^{−42}$ cm$^{2}$ is achievable for WIMP masses above 800 MeV c$^{−2}$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV c$^{−2}$.
An electro-optic detector is one of the diagnostic setups used in particle accelerators. It employs an electro-optic crystal to encode the longitudinal beam charge profile in the spectrum of a light pulse. The charge distribution is then reconstructed using data captured by a fast spectrometer. The measurement repetition rate should match or exceed the machine bunching frequency, which is often in the range of several MHz. A high-speed optical line detector (HOLD) is a linear camera designed for easy integration with scientific experiments. The use of modern FPGA circuits helps in the efficient collection and processing of data. The solution is based on Xilinx 7-Series FPGA circuits and implements a custom latency-optimized architecture utilizing the AXI4 family of interfaces. HOLD is one of the fastest line cameras in the world. Thanks to its hardware architecture and a powerful KALYPSO sensor from KIT, it outperforms the fastest comparable commercial devices.
Measurements from NASA’s Van Allen Probes have transformed our understanding of the dynamics of Earth’s geomagnetically-trapped, charged particle radiation. The Van Allen Probes were equipped with the Magnetic Electron Ion Spectrometers (MagEIS) that measured energetic and relativistic electrons, along with energetic ions, in the radiation belts. Accurate and routine measurement of these particles was of fundamental importance towards achieving the scientific goals of the mission. We provide a comprehensive review of the MagEIS suite’s on-orbit performance, operation, and data products, along with a summary of scientific results. The purpose of this review is to serve as a complement to the MagEIS instrument paper, which was largely completed before flight and thus focused on pre-flight design and performance characteristics. As is the case with all space-borne instrumentation, the anticipated sensor performance was found to be different once on orbit. Our intention is to provide sufficient detail on the MagEIS instruments so that future generations of researchers can understand the subtleties of the sensors, profit from these unique measurements, and continue to unlock the mysteries of the near-Earth space radiation environment.
An inclusive search for long-lived exotic particles decaying to a pair of muons is presented. The search uses data collected by the CMS experiment at the CERN LHC in proton-proton collisions at $ \sqrt{s} $ = 13 TeV in 2016 and 2018 and corresponding to an integrated luminosity of 97.6 fb$^{−1}$. The experimental signature is a pair of oppositely charged muons originating from a common secondary vertex spatially separated from the pp interaction point by distances ranging from several hundred μm to several meters. The results are interpreted in the frameworks of the hidden Abelian Higgs model, in which the Higgs boson decays to a pair of long-lived dark photons Z$_{D}$, and of a simplified model, in which long-lived particles are produced in decays of an exotic heavy neutral scalar boson. For the hidden Abelian Higgs model with m(Z$_{D}$) greater than 20 GeV and less than half the mass of the Higgs boson, they provide the best limits to date on the branching fraction of the Higgs boson to dark photons for cτ(Z$_{D}$) (varying with m(Z$_{D}$)) between 0.03 and ≈0.5 mm, and above ≈0.5 m. Our results also yield the best constraints on long-lived particles with masses larger than 10 GeV produced in decays of an exotic scalar boson heavier than the Higgs boson and decaying to a pair of muons.[graphic not available: see fulltext]
The dual-axis duo-lateral (DADL) position-sensitive silicon detector was developed to obtain precise position and energy information for detected charged particles. The Forward Array Using Silicon Technology (FAUST) is currently equipped with 68 DADL detectors backed by CsI(Tl) scintillators for the study of charged particle correlations in heavy-ion collisions where precise position and energy information is essential. When conventional signal processing electronics were used for the DADL detectors, a position dependence of the measured energy as well as distortions in the calculated particle positions were observed. In previous work, waveforms from the detector after preamplification were studied to better understand the features that give rise to these distortions; therein, a waveform analysis technique was developed to improve the energy resolution and linearity in position reconstruction. However, the reading and writing of waveforms for an entire detector array limits data collection rates and adds significant burden in data storage and analysis speed. In this work, the integrators of a Struck SIS3316 ADC were utilized to process 228 Th source data to develop and optimize a new analysis method that captures the benefits of the waveform analysis technique while circumventing the waveform writing requirement. This integrator method – capable of 59 keV (FWHM) energy resolution – was used in the collection of 35 MeV/nucleon 28 Si + 12 C collision data using FAUST to investigate exotic decays of highly excited highly deformed nuclei. In this data, a position resolution of 0.4 mm (FWHM) was obtained for 25 MeV α-particles; for α-particles near this energy that originate from 8 Be ground state decays, a 8 Be ground state width of 30 keV (FWHM) was obtained. The impact of the energy-dependent DADL position resolution emergent from electronic noise on the quality of excited state measurement was modeled and compared to the experimental data.
The n-body instability is investigated with the soft-sphere discrete element method. The divergence of nearby trajectories is quantified by the dynamical memory time. Using the inverse proportionality between the dynamical memory time and the largest Lyapunov exponent, the soft-sphere discrete element method results are compared to previous hard-sphere molecular dynamics data for the first time. Good agreement is observed at low concentrations and the degree of instability is shown to increase asymptotically with increasing spring stiffness. At particle concentrations above 30%, the soft-sphere Lyapunov exponents increase faster than the corresponding hard-sphere data. Finally, this paper concludes with a demonstration of how this case study may be used in conjunction with regression testing and code verification activities.
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The original data were collected during the field campaign of “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence) over the Atmospheric Radiation Measurement (ARM) user facility's Southern Great Plains (SGP) atmospheric observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a comprehensive collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe. For user convenience, the current data set includes several parameters commonly used in turbulent research for normalization and/or scaling: atmospheric boundary-layer height, surface conditions, convective scales for temperature, and velocity, etc.