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The physics potential of timing layers with a few tens of pico-second resolution in the calorimeters of future collider detectors is explored here. These studies show how such layers can be used for particle identification and illustrate the potential for detecting new event signatures originating from physics beyond the standard model.
The Deep Underground Neutrino Experiment (DUNE) is an international project for neutrino physics and proton-decay searches, currently in the design and planning stages. Once built, DUNE will consist of two detectors exposed to the world's most intense neutrino beam. The near detector at Fermilab will record neutrino interactions near the beginning of the beam line. The other, much larger, detector, comprising four 10-kton liquid argon time projection chambers (LArTPCs), will be installed at a depth of 1.5 km at the Sanford Underground Research Facility in South Dakota, about 1,300 km away from the neutrino source. The unique combination of the high-intensity neutrino beam, DUNE's high-resolution near detector system, and massive LArTPC far detector enables a variety of probes of Beyond-the-Standard-Model (BSM) physics, from the discovery of new particles (sterile neutrinos or dark matter), to precision tests of beyond the three-flavor mixing paradigm, non-standard neutrino interactions (NSIs), heavy neutral leptons, and the detailed study of rare processes (e.g., neutrino trident production). This article reviews these physics topics and discusses the prospects for their discovery at the DUNE experiment.
In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.
Molecular self-assembly is a powerful tool in materials design, wherein non-covalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing self-assembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physics-based simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assembly - biomineralizing peptides, hierarchical peptoids, and large protein assemblies, and will aid in the development of a new synthesis science for achieving precise molecular control in materials design
This project provided financial support for early-career participants of the 2022 Gordon Research Seminar (GRS) on Multiphoton Processes, which was held on June 11 & 12, 2022 in Smithfield, Rhode Island, in conjunction with the Gordon Research Conference (GRC) on the same topic, held on June 12-17, 2022 in the same location. The GRC on Multiphoton Processes is an established conference series in the field of Atomic, Molecular and Optical (AMO) Physics with intense lasers. It regularly attracts around one hundred fifty researchers from around the world to present and discuss their forefront research featuring light-matter interaction in a variety of systems, ranging from atoms and molecules to nanosystems. In order to increase the attendance of early-career researchers at the GRC, in particular graduate students, post-docs, and other scientists with comparable levels of experience and education, the general assembly of the GRC on Multiphoton Processes decided during their last session in 2018 to organize a Gordon Research Seminar in conjunction with the next conference and organized and attended by early-career researchers. The GRS's primary intent is to provide a forum to graduate students and post-docs working in the field of intense and ultrafast AMO physics to present and exchange new data and cutting-edge ideas and to network with their peers at other research institutions around the U.S. and the world.
Significant evidence exists for the apparent disappearance of electron-type neutrinos in radioactive source experiments. Yet, interpreted within the standard ‘3+1 sterile neutrino scenario’, precision short-baseline measurements of electron antineutrinos from nuclear reactors strongly disagree with these results. Recently, it has been demonstrated that allowing for a finite wavepacket size for the reactor neutrinos can ameliorate such a tension, however the smallness of the required wavepackets is a subject of intense debate. In this work, we demonstrate that a ‘broad’ sterile neutrino may relax this tension in much the same way. Such a phenomenological possibility can arise in plausible hidden sector scenarios, such as a clockwork-style sector, for which we provide a concrete microscopic model.
X-ray radiography systems are a key national security technology enabling non-invasive cargo screening. However, the scintillators currently used in these systems have limitations in performance that prompt research for new suitable materials. Here, in this work, crystal growth, physical properties, and optical and scintillation properties of a new halide perovskite scintillator RbSrI 3 were investigated for the first time. The melting point was determined to be 453 °C. Divalent europium and ytterbium were investigated as potential luminescent activators. Light yield and energy resolution of RbSrI 3 :Eu 5 mol% was 78,700 ph/MeV and 2.8 % at 662 keV, and that of RbSrI 3 :Yb 0.5 mol% was 24,000 ph/MeV and 4.9 % at 662 keV.
Following tremendous success of the graphene-derived fundamental and applied research, the magnetic van der Waals materials that can be cleaved into monolayer two-dimensional atomic crystals have emerged as a new platform in the studies of low-dimensional physics and in the design of artificial heterostructures with novel properties. Because of that, the family of dihalides and trihalides of the 3d transition group receive a strong renewed interest. Together with our experimental collaborators, we have investigated the novel dynamical properties of one of such promising material CoI 2 , and demonstrated that spin excitations in it are prone to substantial breakdown and complex level repulsion, the important quantum effects whose theoretical understanding has been significantly advanced by our group in the last two decades. Both phenomena are dramatically revealed by experiments and verified by the theory in our joint study, published in Nature Physics. Altogether, our results pave the way toward a new research direction for the magnetic van der Waals materials.
A key goal of condensed matter physics research is to identify new phases of matter, and to understand the universal features of the phase transitions between them. In the past decade, physicists have uncovered a wealth of new phases with interesting surface properties, exemplified by the theoretical prediction and subsequent experimental discovery of topological insulators and superconductors. Traditional condensed matter systems are usually in a thermal equilibrium state and typically at very low temperature. Very recently, experimental advances have sparked interest in the non-equilibrium setting. Non-equilibrium systems can host new phases and phenomena with no equilibrium counterpart, and could also enable robust ways to build quantum memory devices to store and manipulate quantum information in a coherent manner. These phases and phenomena are inherently “dynamical”: they are described not by changes in the arrangement or structure of the constituent particles, but instead marked by sharp distinctions in how the particles move and exchange energy or quantum information. The discovery of robust non-equilibrium phases raises many fundamental questions: Can we develop a systematic theory of states of matter and of dynamical transitions between such states? How can such states be realized and probed experimentally? The main goal of this project was to explore the emergence of topological phases and quantum criticality (two cornerstones of modern condensed matter physics in equilibrium) in such non-equilibrium quantum systems. Specific goals included (1) using tensor networks to efficiently represent non-equilibrium states of matter and their phase transitions; (2) studying and designing new probes for periodically driven systems; and (3) developing analytic and numerical tools to analyze non-equilibrium topological phase transitions. Advances in these directions were achieved using novel techniques appropriate to study the non-equilibrium dynamics in many-body quantum systems combining strong interactions and randomness. Taken together, these results provide a new conceptual framework for understanding the emergence of quantum critical and topological properties in quantum systems far from thermal equilibrium.
Abstract Measures of inconsistency and tension between datasets have become an essential part of cosmological analyses. It is important to accurately evaluate the significance of such tensions when present. We propose here a Bayesian interpretation of inconsistency measures that can extract information about physical inconsistencies in the presence of data scatter. This new framework is based on the conditional probability distribution of the level of physical inconsistency given the obtained value of the measure. We use the index of inconsistency as a case study to illustrate the new interpretation framework, but this can be generalized to other metrics. Importantly, there are two aspects in the quantification of inconsistency that behave differently as the number of model parameters increases. The first is the probability for the level of physical inconsistency to reach a threshold which drops with the increase of the number of parameters under consideration. The second is the actual level of physical inconsistency which remains rather insensitive to such an increase in parameters. The difference between these two aspects is often overlooked, which leads to a long-standing ambiguity: when a given inconsistency is found between two constraints, its “significance” seems to be lower when considered in a higher-dimensional parameter space. This ambiguity is resolved by the Bayesian interpretation we introduce in this work because the conditional probability distribution includes all the statistical information of the level of physical inconsistency. Finally, we apply the Bayesian interpretation to examine the (in)consistency between Planck versus the Cepheid-based local measurement, the Dark Energy Survey (DES), the Atacama Cosmology Telescope (ACT) and WMAP. We confirm and revisit the degrees of previous physical inconsistencies and show the stability of the new interpretation with respect to the number of cosmological parameters compared to the commonly used n-σ interpretation when applied to cosmological tensions in multi-parameter spaces.
Reconstructing the internal three-dimensional quark and gluon structures of hadrons through generalized parton distributions (GPDs) from hard exclusive scattering processes is one of the most challenging tasks in nuclear and particle physics. In this paper, we introduce a new optimized reference frame that, for the first time, enables a unified view of all the reactions sensitive to GPDs and facilitates the interpretation of a variety of phase-space patterns that were previously hardly accessible and interpretable. Similarly to how the heliocentric description advanced our understanding of the solar system and gravitation, our new frame centers around a quasireal state, allows for a consistent separation of physical scales, and reveals a novel quantum interference mechanism. Published by the American Physical Society 2025
The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework leverages existing Community Coordinated Modeling Center services: Run on Request post processing tools that generate model time series outputs and the new Community Coordinated Modeling Center Metadata Registry that describes simulation runs using Space Physics Archive Search and Extract metadata. The new CAMEL visualization tool compares the modeled time series with observational data and computes a suite of skill scores such as Prediction Efficiency, Root Mean Square Error, and Symmetric Signed Percentage Bias. Model data pairs used for skill calculations are obtained considering a user selected maximum difference between the time of observation and the nearest model output. The system renders available data for all locations and time periods selected using interactive visualizations that allow the user to zoom, pan, and pick data values along traces. Skill scores are reported for each selected event or aggregated over all events for all participating model runs. Separately, scores are reported for all locations (satellites or stations) and for each location individually. We are building on past experiences with model data comparisons of magnetosphere and ionosphere model outputs from GEM2008, GEMCEDAR Electrodynamics Thermosphere Ionosphere, and the SWPC Operational Space Weather Model challenges. The CAMEL visualization tool is demonstrated using three validation studies: (a) Wang Sheeley Arge heliosphere simulations compared against OMNI solar wind data, (b) ground magnetic perturbations from several magnetosphere and ionosphere electrodynamics models as observed by magnetometers, and (c) electron fluxes from several ring current simulations compared to Radiation Belt Storm Probes Helium Oxygen Proton Electron instrument measurements, integrated over different energy ranges.
Virtual fit tests using 3D body scans have provided a cost-effective means to predictively assess spacesuit fit for the current and future astronaut population. However, fit is a complex issue influenced by physical interferences, subjective preference, and many other factors. Fit can substantially differ between the type of hardware, environmental conditions, and tasks being performed. Namely, fit changes across different contexts, such as 3D printed mockup evaluations, pressurized one-g suited test events, neutral buoyancy and other training events, and flight extravehicular activities (EVA). These challenges make it difficult to validate virtual fit frameworks to physical suit sizing. This study proposes a new method of validation using the wealth of historically archived suit fit data. Physically Assessed Fit (PAF) data was assessed from astronauts and test volunteers who wore the legacy Extravehicular Mobility Unit (EMU). The data was collected during the past decades at NASA and considered to be most reliable and dependable. Each participant was 3D scanned for body shape and spacesuit-critical dimensions were measured per NASA guidelines. The participants’ size preference for hard upper torso (HUT) assembly was retrieved from their pressurized suit fit check records. Fit assessments were also updated after one-g EVA training, neutral buoyancy training, and EVA flights. Virtually Assessed Fit (VAF) was done by overlaying the CAD model of a HUT with the 3D body scans of the PAF participants. Each body scan was iteratively adjusted for the position inside the HUT to minimize the suit-to-body contact interference while satisfying a set of prescribed requirements. Then the residual contact area, depth, and volume were quantified as VAF metrics. This process was repeated for the different HUT sizes, including medium, large, and extra-large. Statistical modeling is currently in progress and will be presented at the conference. A statistical classifier will be developed to predict a fit probability for different HUT sizes as a function of the corresponding person’s VAF metrics. The HUT size with the highest fit probability will constitute the most likely size selection for the person, and the prediction will be compared against the corresponding PAF data. The participant data will be randomly pre-grouped into either a model development or validation subset. While the model development subset will be used to build the probability model, the validation subset will be used to assess the model accuracy. Also, the locations and magnitudes of suit-body-contacts will be estimated from VAF. This information can identify the critical suit geometry and body shape features that influence suit fit. The variations found in PAF size selections by subjects with similar VAF metrics will allow for investigations into subjective preferences, for example, tight versus loose fit. Overall, this study is expected to provide a structured validation of a virtual suit fit framework, which has not been possible in the past. The outcome can also provide useful insights and potential limitations for interpreting virtual fit tests for future spacesuit designs and population accommodation.
To continue growing as a discipline, we need to establish a new vision of where we are going that is consistent with today s physics, NASA s strategic plan, and the new OBPR direction. 1998 Roadmap focused exclusively on Physics, and did not worry about boundaries between OBPR and OSS. Updated Roadmap: Must incorporate some strategic research activities to be fully responsive to the current OBPR direction. Must capture the imagination of OBPR leadership, OMB, and Congress. Must delineate OBPR from the "beyond Einstein" program in OSS. Must address relevancy to Society explicitly. Status of the Roadmap development will be discussed after lunch today. Seeking community inputs and endorsement. Draft update targeted for June, final in August.
Discrete ordinate (S N ) and filtered spherical harmonics (FP N ) based schemes have been proven to be robust and accurate in solving the Boltzmann transport equation but they have their own strengths and weaknesses in different physical scenarios. We present a new method based on a finite element approach in angle that combines the strengths of both methods and mitigates their disadvantages. The angular variables are specified on a spherical geodesic grid with functions on the sphere being represented using a finite element basis. A positivity-preserving limiting strategy is employed to prevent non-physical values from appearing in the solutions. Here, the resulting method is then compared with both S N and FP N schemes using four test problems and is found to perform well when one of the other methods fail.
The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a Gadolinium-loaded water Cherenkov detector located in the Booster Neutrino Beam at Fermilab. One of its primary physics goals is to measure the final state neutron multiplicity of neutrino-nucleus interactions. This measurement of the neutron yield as a function of the outgoing lepton kinematics will be useful to constrain systematic uncertainties and reduce biases in future long-baseline oscillation and cross-section experiments. ANNIE is also a testbed for innovative new detection technologies. It will make use of pioneering photodetectors called Large Area Picosecond Photodetectors (LAPPDs) with better than 100 picosecond time resolution, which will enhance its reconstruction capabilities and demonstrate the feasibility of this technology as a new tool in high energy physics. The status of the experiment is reported here in terms of the overall progress, the deployment of the first LAPPD and an overview of recently taken beam and calibration data. Additional future R\&D efforts and analysis opportunities involving the use of the novel detection medium of Water-based Liquid Scintillators (WbLS) are also briefly highlighted.
Turbulent gas flows laden with small, dense particles are encountered in a wide number of important applications in both industrial settings and aerodynamics applications. Particle interactions with the underlying turbulent flow are exceedingly complex and, consequently, difficult to accurately model. The difficulty arises primarily due to the fact that response of a particle to the local environment is dictated by turbulence properties in the reference frame moving with the particle (particle-Lagrangian). The particle-Lagrangian reference frame is in turn dependent upon the particle relaxation time (time constant) as well as gravitational drift. The combination of inertial and gravitational effects in this frame complicates our ability to accurately predict particle-laden flows since measurements in the particle-Lagrangian reference frame are difficult to obtain. Therefore, in this work we will examine separately the effects of inertia and gravitational drift on particle dispersion through a combination of physical and numerical experiments. In this study, particle-Lagrangian measurements will be obtained in physical experiments using stereo image velocimetry. Gravitational drift will be varied in the variable-g environments of the NASA DC-9 and in the zero-g environment at the drop tower at NASA-Lewis. Direct numerical simulations will be used to corroborate the measurements from the variable-g experiments. We expect that this work will generate new insight into the underlying physics of particle dispersion and will, in turn, lead to more accurate models of particle transport in turbulent flows.
Recently the kagome compounds have inspired enormous interest and made some great progress such as in the field of superconductivity and topology. Here we predict a different kagome magnesium triboride (MgB 3 ) superconductor with a calculated T c ~ 12.2K and T c ~ 15.4 K by external stress, the potentially highest among the reported diverse kagome-type superconductors. We reveal its various exotic physical properties including the van Hove singularity, flat-band, multiple Dirac points, and nontrivial topology. The system can be described by a two-band model with highly anisotropic superconducting gaps on Fermi surfaces. Its topological and nodal superconducting nature is unveiled by a recently developed symmetry indicators method. In conclusion, our results suggest that MgB 3 can be a new platform to study exotic physics in the kagome structure, and pave a way to seek for more superconductors and topological materials with XY 3 -type kagome lattice.