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At least 577 records · Page 32

Two-component flux explanation for the high energy neutrino events at IceCube

In understanding the spectral and flavor composition of the astrophysical neutrino flux responsible for the recently observed ultrahigh-energy events at IceCube we see how important both astrophysics and particle physics are. Here, we perform a statistical likelihood analysis to the three-year IceCube data and derive the allowed range of the spectral index and flux normalization for various well-motivated physical flavor compositions at the source. While most of the existing analyses so far assume the flavor composition of the neutrinos at an astrophysical source to be (1:2:0), it seems rather unnatural to assume only one type of source, once we recognize the possibility of at least two physical sources. Bearing this in mind, we entertain the possibility of a two-component source for the analysis of IceCube data. It appears that our two-component hypothesis explains some key features of the data better than a single-component scenario; i.e. it addresses the apparent energy gap between 400 TeV and about 1 PeV and easily accommodates the observed track-to-shower ratio. Given the extreme importance of the flavor composition for the correct interpretation of the underlying astrophysical processes as well as for the ramification for particle physics, this two-component flux should be tested as more data is accumulated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Markov Chain Monte Carlo Predictions of Neutron-rich Lanthanide Properties as a Probe of r -process Dynamics

Lanthanide element signatures are key to understanding many astrophysical observables, from merger kilonova light curves to stellar and solar abundances. To learn about the lanthanide element synthesis that enriched our solar system, we apply the statistical method of Markov Chain Monte Carlo to examine the nuclear masses capable of forming the r-process rare-earth abundance peak. We describe the physical constraints we implement with this statistical approach and demonstrate the use of the parallel chains method to explore the multidimensional parameter space. We apply our procedure to three moderately neutron-rich astrophysical outflows with distinct types of r-process dynamics. We show that the mass solutions found are dependent on outflow conditions and are related to the r-process path. We describe in detail the mechanism behind peak formation in each case. We then compare our mass predictions for neutron-rich neodymium and samarium isotopes to the latest experimental data from the CPT at CARIBU. Here, we find our mass predictions given outflows that undergo an extended (n,γ)⇌(γ,n) equilibrium to be those most compatible with both observational solar abundances and neutron-rich mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Satellite freeze forecast system: Executive summary

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Martsolf, J. D.↗

Why it is Unfortunate that Linear Machine Learning “Works” so well in Electromechanical Switching of Ferroelectric Thin Films

Machine learning (ML) is relied on for materials spectroscopy. It is challenging to make ML models fail because statistical correlations can mimic the physics without causality. Here, using a benchmark band-excitation piezoresponse force microscopy polarization spectroscopy (BEPS) dataset the pitfalls of the so-called “better”, “faster”, and “less-biased” ML of electromechanical switching are demonstrated and overcome. Using a toy and real experimental dataset, it is demonstrated how linear nontemporal ML methods result in physically reasonable embedding (eigenvalues) while producing nonsensical eigenvectors and generated spectra, promoting misleading interpretations. A new method of unsupervised multimodal hyperspectral analysis of BEPS is demonstrated using long-short-term memory (LSTM) β-variational autoencoders (β-VAEs) . By including LSTM neurons, the ordinal nature of ferroelectric switching is considered. Further, to improve the interpretability of the latent space, a variational Kullback–Leibler-divergency regularization is imposed . Finally, regularization scheduling of β as a disentanglement metric is leveraged to reduce user bias. Combining these experiment-inspired modifications enables the automated detection of ferroelectric switching mechanisms, including a complex two-step, three-state one. Ultimately, this work provides a robust ML method for the rapid discovery of electromechanical switching mechanisms in ferroelectrics and is applicable to other multimodal hyperspectral materials spectroscopies.

36 MATERIALS SCIENCE↗

Review of Onsite Temperature and Solar Forecasting Models to Enable Better Building Design and Operations

Advanced building controls and energy optimization for new constructions and retrofits rely on accurate weather data. Traditionally, most studies utilize airport weather information as the decision inputs. However, most buildings are in environments that are quite different than those at the airport miles away. Tree cover, adjacent buildings, and micro-climate effects caused by the larger surrounding area can all yield deviations in air temperature, humidity, solar irradiance, and wind that are large enough to influence design and operation decisions. In order to overcome this challenge, there are many prior studies on developing weather forecasting algorithms from micro-to meso-scales. Additionally, this paper reviews and complies knowledge on common weather data resources, data processing methodologies and forecasting techniques of weather information. Commonly used statistical, machine learning and physical-based models are discussed and presented as two major categories: deterministic forecasting and probabilistic forecasting. Finally, evaluation metrics for forecasting errors are listed and discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

TOUGH2-seed: A coupled fluid flow and mechanical-stochastic approach to model injection-induced seismicity

Understanding the injection-induced triggering mechanism is a fundamental step towards controlling the seismicity generated by deep underground exploitation. Here we propose a modeling approach based on coupling the TOUGH2 simulator with a geomechanical-stochastic model. Additionally, the hydro-mechanical-stochastic model provides a good representation of different mechanisms influencing each other during and after the injection phase. Each mechanism affects the induced seismicity in a different way and at different times during the reservoir stimulation, confirming that a complex interaction is in place, and that more sophisticated and physics-based approaches coupled with statistical model are required to explain such a complex interaction. In addition to previous statistical and hybrid models, our approach accounts for a full 3D formulation of both stresses and fluid flow, further including all the TOUGH2 capabilities. Furthermore, it includes interactions between triggered seismic events through calculation of static stress transfer. Here, in this work, we present the main capabilities of TOUGH2-SEED and apply the model to the Basel EGS case, successfully reproducing the injection pressure as well as the evolution of the seismicity.

58 GEOSCIENCES↗

Experimental and computational kinetics study of the liquid-phase hydrogenation of C=C and C=O bonds

Solvent effects on adsorption equilibrium and reaction kinetics are evaluated for hydrogenation reactions catalyzed by Pd/alumina in a series of different solvents. Three reactants – cyclohexene, benzene and benzaldehyde – and three solvents – n-heptane (HEP), methylcyclohexane (MCHA), decalin (DL) – have been investigated. Kinetic analysis of hydrogenation of cyclohexene reveals that hydrogen adsorbs on different sites from those where cyclohexene and the solvents adsorb; however, the presence of hydrogen on these separate sites affects the heats of adsorption of the hydrocarbons. When the solvent is a weakly interacting linear alkane (HEP), the rate determining step of the reaction is the first hydrogenation of adsorbed cyclohexene. Furthermore, this conclusion is supported by DFT calculations that show a higher enthalpy barrier for the first hydrogenation than for the second, while statistical thermodynamics analysis validates the physical significance of the entropy of adsorption parameters derived from the kinetic fitting of experimental data. By contrast, with solvents such as MCHA and DL, which interact more strongly with the metal surface and compete for active sites with the reactant and the surface intermediate, the rate limiting step seems to shift to the second hydrogenation step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heat pumps for all? Distributions of the costs and benefits of residential air-source heat pumps in the United States

Electrification of fossil-fuel combustion in buildings is a key component of achieving global greenhouse gas emissions targets. We use physics simulations of 550,000 statistically representative households to analyze distributions of the costs and benefits of three air-to-air heat pump performance levels, with and without insulation upgrades, across the diversity of the US housing stock. We find positive greenhouse gas reductions in every US state for all performance levels across five 2022-2038 electric grid scenarios, with full adoption reducing national emissions by 5%-9%. We find that air-to-air heat pumps could be cost effective without subsidies in 59% of households (65 million). However, efficiency is key: whereas minimum-efficiency equipment could increase energy bills in 39% of households, this fraction is only 19% when also upgrading insulation or 5% when using higher-efficiency equipment, though both strategies have higher upfront costs. Such affordability challenges could be addressed through supportive incentives, policy, and innovation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Information-theoretic astrophysical uncertainties in the effective theory of dark matter direct detection

The impact of astrophysical uncertainties in direct detection searches can vary significantly across particle dark matter models and detector targets, due to the different velocity and momentum dependencies of the scattering cross section. We address these uncertainties for all operators of the nonrelativistic effective field theory of dark-matter/nucleon interactions, making use of the Kullback-Leibler (KL) information divergence to measure the deviation of the true dark matter velocity distribution from the Maxwell-Boltzmann form. This approach quantifies how astrophysical uncertainties affect each operator in the effective theory, without assuming any specific functional form for the velocity distribution. While for some operators the uncertainties are smaller than 1 order of magnitude for entropically motivated deviations from the Maxwell-Boltzmann form, for other operators, these uncertainties can be as large as three orders of magnitude near threshold. Furthermore, we identify the dependence of the scattering rate for various operators of the effective theory with different velocity-weighted moments of the velocity distribution, functionally analogous to the mean, variance, or skewness. This provides new analytic insight into which features of the velocity distribution are most relevant to detect a given particle dark matter model. Our technique is general and could be applied to a broader class of physics problems where a physical observable depends on the statistical moments of an uncertain theoretical distribution.

Herrera, Gonzalo [MIT, MKI; Harvard U.; Virginia T↗

Fast estimation of the look-elsewhere effect using Gaussian random fields

Abstract We discuss the use of Gaussian random fields to estimate the look-elsewhere effect correction. We show that Gaussian random fields can be used to model the null-hypothesis significance maps from a large set of statistical problems commonly encountered in physics, such as template matching and likelihood ratio tests. Some specific examples are searches for dark matter using pixel arrays, searches for astronomical transients, and searches for fast-radio bursts. Gaussian random fields can be sampled efficiently in the frequency domain, and the excursion probability can be fitted with these samples to extend any estimation of the look-elsewhere effect to lower p values. In addition, in cases where the Gaussian random field is stationary and the parameter space is Euclidean, the look-elsewhere effect correction can be computed analytically. We demonstrate these methods using two example template matching problems. Finally, we apply these methods to estimate the trial factor of a $$4^3$$ 4 3 accelerometer array for the detection of dark matter tracks in the Windchime project. When a global significance of $$3\sigma $$ 3 σ is required, the estimated trial factor for such an accelerometer array is $$10^{14}$$ 10 14 for a one-second search, and $$10^{22}$$ 10 22 for a 1-year search.

Qin, Juehang (ORCID:0000000182288949)↗

Code for the manuscript "Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning"

We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning ". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

Tian, Yifeng↗

Secondary Pion Production using the LINAC Beam on Graphite and Tungsten Targets

The Fermilab 400-MeV Linac primary proton beam can produce precision, single-species secondary beams using a production target in the MeV Test Area experimental hall; specifically, pions from 4 up to 120 MeV kinetic energy. (These low energy pions rapidly decay into a muon beam in a secondary collection and transport beamline.) Although graphite is a standard production target material given its ultra-high temperature tolerance and low impact on the post-target primary beam, secondary pion/muon total production cross sections increase approximately as Z1/3 for positive muons and N2/3 for negative muons. Higher mass targets such as tungsten can potentially increase low-energy m+ and m- rates by factors of 3 and 8, respectively. Initial production studies have confirmed higher muon yield from heavy targets (tungsten vs carbon), but also, surprisingly, show significant differences in pion production between modern hadronic models (GENIEhad) and between GEANT and MCNP, state of the art production modeling codes. This project will further investigate the production discrepancies between these two target materials and between different physics models with high-statistics runs using the GEANT-based code, G4Beamline to better quantify the results and compare with production data which will be obtained using the MTA secondary beamline.

Ahmed, Shiza↗

Radio-flaring Ultracool Dwarf Population Synthesis

Over a dozen ultracool dwarfs (UCDs), low-mass objects of spectral types ≥M7, are known to be sources of radio flares. These typically several-minutes-long radio bursts can be up to 100% circularly polarized and have high brightness temperatures, consistent with coherent emission via the electron cyclotron maser operating in approximately kilogauss magnetic fields. Recently, the statistical properties of the bulk physical parameters that describe these UCDs have become described adequately enough to permit synthesis of the population of radio-flaring objects. For the first time, I construct a Monte Carlo simulator to model the population of these radio-flaring UCDs. This simulator is powered by Intel Secure Key (ISK), a new processor technology that uses a local entropy source to improve random number generation that has heretofore been used to improve cryptography. The results from this simulator indicate that only ∼5% of radio-flaring UCDs within the local interstellar neighborhood (<25 pc away) have been discovered. I discuss a number of scenarios that may explain this radio-flaring fraction and suggest that the observed behavior is likely a result of several factors. The performance of ISK as compared to other pseudorandom number generators is also evaluated, and its potential utility for other astrophysical codes is briefly described.

79 ASTRONOMY AND ASTROPHYSICS↗

Moving Magnetic Features Around a Pore

Spectropolarimetric observations from Sunrise/IMaX, obtained in 2013 June, are used for a statistical analysis to determine the physical properties of moving magnetic features (MMFs) observed near a pore. MMFs of the same and opposite polarity, with respect to the pore, are found to stream from its border at an average speed of 1.3 km s{sup −1} and 1.2 km s{sup −1}, respectively, with mainly same-polarity MMFs found further away from the pore. MMFs of both polarities are found to harbor rather weak, inclined magnetic fields. Opposite-polarity MMFs are blueshifted, whereas same-polarity MMFs do not show any preference for up- or downflows. Most of the MMFs are found to be of sub-arcsecond size and carry a mean flux of ∼1.2 × 10{sup 17} Mx.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling of spacecraft charging

Three types of modeling of spacecraft charging are discussed: statistical models, parametric models, and physical models. Local time dependence of circuit upset for DoD and communication satellites, and electron current to a sphere with an assumed Debye potential distribution are presented. Four regions were involved in spacecraft charging: (1) undisturbed plasma, (2) plasma sheath region, (3) spacecraft surface, and (4) spacecraft equivalent circuit.

Whipple, E. C., Jr.↗

183 GHz water line variation: An energetic outburst in orion KL

Observations of the 3(13)-2(20) transition of water vapor in the direction of Ori MC1 in 1980 February show a 50% flux increase and an apparent additional red shift of approximately 2 km/s relative to the line observed in 1977 December. From a detailed examination of the amplitude and frequency calibration, it appears unlikely that the effect is due to systematic error. The increase is attributed to the appearance of a new component at a velocity of 12 km/s with respect to the local standard of rest. The new component also has broad wings. Increased emission from a region in the high-velocity core of Ori MC1 can be due either to additional far-IR radiation to pump the 1983 GHz transition or to a change in the physical conditions in the gas. Statistical equilibrium calculations using the large-velocity-gradient formalism were carried out to develop a model for the emission. The calculations support a model in which the gas in the region of enhanced emission is hotter than the dust. The temporal coincidence between the 183 GHZ increase and the 22 GH1 water maser outburst suggests a common, impulsive cause, which has heated the gas in a part of the HV source, enhancing the emission in both transitions.

Kuiper, T. B. H.↗

Convex profiles from asteroid lightcurves

A lightcurve inversion method that yields a two-dimensional convex profile is introduced. The number of parameters that characterize the profile is limited only by the number of Fourier harmonics used to represent the parent lightcurve. The implementation of the method is outlined by a recursive quadratic programming algorithm, and its application to photoelectric lightcurves and radar measurements is discussed. Special properties of the lightcurves of geometrically scattering ellipsoids are pointed out, and those properties are used to test the inversion method and obtain a criterion for judging whether any lightcurve could actually be due to such an object. Convex profiles for several asteroids are shown, and the method's validity is discussed from a physical as well as purely statistical point of view.

Ostro, S. J.↗

183 GHz water line variation - An energetic outburst in Orion KL

Observations of the 3(13)-2(20) transition of water vapor in the direction of Ori MC1 in 1980 February show a 50 percent flux increase and an apparent additional red shift of approximately 2 km/s relative to the line observed in 1977 December. From a detailed examination of the amplitude and frequency calibration, it appears unlikely that the effect is due to systematic error. The increase is attributed to the appearance of a new component at a velocity of 12 km/s with respect to the local standard of rest. The new component also has broad wings. Increased emission from a region in the high-velocity core of Ori MC1 can be due either to additional far-IR radiation to pump the 1983 GHz transition or to a change in the physical conditions in the gas. Statistical equilibrium calculations using the large-velocity-gradient formalism were carried out to develop a model for the emission. The calculations support a model in which the gas in the region of enhanced emission is hotter than the dust. The temporal coincidence between the 183 GHz increase and the 22 GH1 water maser outburst suggests a common, impulsive cause, which has heated the gas in a part of the HV source, enhancing the emission in both transitions.

Kuiper, T. B. H.↗