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At least 577 records · Page 32

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

Short GRB Prompt and Afterglow Correlations

The Swift data set on short GRBs has now grown large enough to study correlations of key parameters. The goal is to compare long and short bursts to better understand similarities and differences in the burst origins. In this study we consider the both prompt and afterglow fluxes. It is found that the optical, X-ray and gamma-ray emissions are linearly correlated - stronger bursts tend to have brighter afterglows, and bursts with brighter X-ray afterglow tend to have brighter optical afterglow. Both the prompt and afterglow fluxes are, on average, lower for short bursts than for long. Although there are short GRBs with undetected optical emission, there is no evidence for "dark" short bursts with anomalously low opt/X ratios. The weakest short bursts have a low X-ray/gamma-ray ratio.

Gehrels, Neil↗

Maps Characterizing the Lunar Regolith Maturity

There are several parameters characterizing maturity of the lunar regolith. Most reliable of them are the ratio Is/FeO, characterizing relative concentration of nano-phase reduced iron, and the agglutinate content. The ratio Is/FeO is often called the degree of maturity of the lunar regolith. Studies of lunar samples show that the agglutinate content correlates with the maturity degree. Besides, the abundance of crystalline component, independently of its composition, anti-correlates with the maturity degree. In present paper we examine these correlations, mapping the parameter Is/FeO, the abundance of agglutinates in the lunar regolith, and the abundance of the crystalline component presented with pyroxene, plagioclase, olivine, and ilmenite. We use measurements of lunar samples made by Lunar Soil Characterization Consortium (LSCC) and multispectral lunar data of high spatial resolution available after the Clementine mission to the Moon.

V. Kaydash↗

Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems

Here we present the PI-CKL-NN method for parameter estimation in differential equation (DE) models given sparse measurements of the parameters and states. In the proposed approach, the space- or time-dependent parameters are approximated by Karhunen-Loeve (KL) expansions that are conditioned on the parameters’ measurements, and the states are approximated by deep neural networks (DNNs). The unknown weights in the KL expansions and DNNs are found my minimizing the cost function that enforces the measurements of the states the DE constraint. Regularization is achieved by adding the l2 norm of the conditional KL coefficients into the loss function. Our approach assumes that the parameter fields are correlated in space or time and enforces the statistical knowledge (the mean and the covariance function) in addition to the DE constraints and measurements as opposed to the physics-informed neural network (PINN) and other similar physics-informed machine learning methods where only DE constraints and data are used for parameter estimation. We use the PI-CKL-NN method for parameter estimation in an ordinary differential equation with an unknown time-dependent parameter and the one- and two-dimensional partial differential diffusion equations with unknown space-dependent diffusion coefficients. We also demonstrate that PI-CKL-NN is more accurate than the PINN method, especially when the observations of the parameters are very sparse

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Automated TEM Reveals Intercrystalline Correlations of Conjugated Polymers

Transmission electron microscopy (TEM) continues to transform polymer science by revealing key aspects of chain packing, phase separation and nanoscale structure. The development of instrumentation and data analyses tools is driving the field forward and enabling new experiments. Here, we use automated high-resolution TEM (HRTEM) and image processing to identify the structure of a conjugated polymer used in organic electronics. Analysis of more than 600 HRTEM images reveals lattice parameters and orientation correlations between crystals, including the preferred alignment of neighboring crystals along the same crystallographic direction that is likely the result of liquid crystalline order.

Fair, Ryan A. [Pennsylvania State University, Univ↗

Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: new models and constraints from the eBOSS measurement

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-α forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with 40963 hydrodynamical cells in a 120 Mpc (∼ 81 Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-α forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters A Lyα and n Lyα . While the best-fit Planck ΛCDM model has A Lyα = 8.79 and n Lyα = -2.363, from DR14 eBOSS data we find that A Lyα < 7.6 (95% CI) and n Lyα = -2.369 ± 0.008. The low value of A Lyα , in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman-α forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find A Lyα = 9.8 ± 1.1 in accordance with Planck.

Walther, Michael↗

Effect of hydride vapor phase epitaxy growth conditions on the degree of atomic ordering in GaInP

We report a systematic study of CuPt-type ordering in hydride vapor phase epitaxy (HVPE)-grown Ga 0.5 In 0.5 P. Selected-area electron diffraction reveals ordering in samples grown on (001) GaAs substrates offcut toward (1$\overline{1}$1)B. The ordering is single-variant, occurring only on (1$\overline{1}$1)B planes and not on ($\overline{1}$11)B. Quantitative analysis of the order parameter by high-resolution x-ray diffraction (HRXRD) indicates that ordering increases with deposition temperature in samples grown at 600–700 °C with a constant gas-phase V/III ratio ~3. Ordering increases with V/III ratio in the range of 1.3–6.7 at a constant deposition temperature of 650°C. Photoluminescence measurements correlate the order parameter with Ga0.5In0.5P bandgap contraction, though the contraction is larger than expected based on the magnitude of order parameters measured by HRXRD. A possible reason for this discrepancy is that the photoluminescence emission occurs in the lower bandgap ordered domains, which are small and evenly dispersed throughout the material. We also show that the degree of ordering decreases with growth rate, disappearing at ~60 µm/h. The HVPE-grown material exhibits a generally weaker ordering than organometallic vapor phase epitaxy (OMVPE)-grown material, likely due to the moderate V/III ratios employed, in contrast to the V/III ratios in the 100s typical of OMVPE. However, the tendency for ordering to increase with V/III ratio suggests that the same dimer-induced stress mechanism used to explain the occurrence of ordering in OMVPE-grown material also applies to HVPE. The tendencies for ordering to increase with deposition temperature and decrease with growth rate show that kinetics limit the degree of ordering, also in agreement with OMVPE trends.

74 ATOMIC AND MOLECULAR PHYSICS↗

Solar Array in Simulated LEO Plasma Environment

Six different types of solar arrays have been tested in large vacuum chambers. The low earth orbit plasma environment was simulated in plasma vacuum chambers, where the parameters could be controlled precisely. Diagnostic equipment included spherical Langmuir probes, mass spectrometer, low-noise CCD camera with optical spectrometer, video camera, very sensitive current probe to measure arc current, and a voltage probe to register variations in a conductor potential. All data (except video) were obtained in digital form that allowed us to study the correlation between external parameters (plasma density, additional capacitance, bias voltage, etc) and arc characteristics (arc rate, arc current pulse width and amplitude, gas species partial pressures, and intensities of spectral lines). Arc inception voltages, arc rates, and current selections are measured for samples with different coverglass materials and thickness, interconnect designs, and cell sizes. It is shown that the array with wrapthrough interconnects have the highest arc threshold and the lowest current collection. Coverglass design with overhang results in decrease of current collection and increase of arc threshold. Doubling coverglass thickness cases the increase in arc inception voltage. Both arc inception voltage and current collection increase significantly with increasing a sample temperature to 80 C. Sustained discharges are initiated between adjacent cells with potential differences of 40 V for the sample with 300 micron coverglass thickness and 60 V for the sample with 150 micron coverglass thickness. Installation of cryogenic pump in large vacuum chamber provided the possibility of considerable outgassing of array surfaces which resulted in significant decrease of arc rate. Arc sites were determined by employing a video-camera, and it is shown that the most probable sites for arc inception are triple-junctions, even though some arcs were initiated in gaps between cells. It is also shown that the arc rate increases with increasing of ion collection current. The analysis of optical spectra (240-800 nm) reveals intensive narrow atomic lines (Ag, H) and wide molecular bands (OH, CH, SiH, SiN) that confirms a complicated mechanism of arc plasma generation. The results obtained seem to be important for the understanding of the arc inception mechanism, which is absolutely essential for progress toward the design of high-voltage solar array for space application.

Vayner, Boris↗

Solar Array in Simulated LEO Plasma Environment

Six different types of solar arrays have been tested in large vacuum chambers. The low Earth orbit plasma environment was simulated in plasma vacuum chambers, where the parameters could be controlled precisely. Diagnostic equipment included spherical Langmuir probes, mass spectrometer, low-noise CCD camera with optical spectrometer, video camera, very sensitive current probe to measure arc current, and a voltage probe to register variations in a conductor potential. All data (except video) were obtained in digital form that allowed us to study the correlation between external parameters (plasma density, additional capacitance, bias voltage, etc) and arc characteristics (arc rate, arc current pulse width and amplitude, gas species partial pressures, and intensities of spectral lines). Arc inception voltages, arc rates, and current collections are measured for samples with different coverglass materials and thickness, interconnect designs, and cell sizes. It is shown that the array with wrapthrough interconnects have the highest arc threshold and the lowest current collection. Coverglass design with overhang results in decrease of current collection and increase of arc threshold. Doubling coverglass thickness causes the increase in arc inception voltage. Both arc inception voltage and current collection increase significantly with increasing a sample temperature to 80 C. Sustained discharges are initiated between adjacent cells with potential differences of 40 V for the sample with 300 m coverglass thickness and 60 V for the sample with 150 m coverglass thickness. Installation of cryogenic pump in large vacuum chamber provided the possibility of considerable outgassing of array surfaces which resulted in significant decrease of arc rate. Arc sites were determined by employing a video-camera, and it is shown that the most probable sites for arc inception are triple-junctions, even though some arcs were initiated in gaps between cells. It is also shown that the arc rate increases with increasing of ion collection current. The analysis of optical spectra (240-800 nm) reveals intensive narrow atomic lines (Ag, H) and wide molecular bands (OH, CH, SiH, SiN) that confirms a complicated mechanism of arc plasma generation. The results obtained seem to be important for the understanding of the arc inception mechanism, which is absolutely essential for progress toward the design of high-voltage solar array for space application.

Vayner, Boris↗

The impact of Maki parameter and spin orbit scattering constant in the WHH model on upper critical magnetic fields in Ni-and co-doped pnictide bulk superconductors

Werthamer, Helfand, and Hohenberg (WHH) model is applied to the measured upper critical magnetic fields of Ni-and Co-doped pnictide bulk superconductors. This approach incorporates both orbital and paramagnetic effects in the upper critical field’s temperature dependence. Additionally, the relative importance of both the orbital and paramagnetic effects in the suppression of the superconductivity is described by the Maki parameter. In most superconductors, the Maki parameter is usually much less than unity suggesting that the influence of the paramagnetic effect is small. However, in materials with heavy electron effective mass, in which the Fermi energy is small, or in layered materials in a magnetic field parallel to the layers, the Maki parameter can be larger than unity. This is the case for our bulk pnictides. By fitting the measured temperature dependence of the upper critical field, we derive the Maki parameter and the spin orbit scattering constant and examine the correlation between the Maki parameter, the spin orbit scattering constant, and the reduced upper critical field for our curve fits vs. temperature. In conclusion, the obtained Maki parameters indicate that the Zeeman pair breaking dominates over the orbital pair breaking and spin-paramagnetic pair-breaking effect is significant. At the same time, our spin orbit scattering constants indicate that spin-orbit scattering needs to be also included in description of the H c2 (T) data in these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microbial sensor variation across biogeochemical conditions in the terrestrial deep subsurface

ABSTRACT Microbes can be found in abundance many kilometers underground. While microbial metabolic capabilities have been examined across different geochemical settings, it remains unclear how changes in subsurface niches affect microbial needs to sense and respond to their environment. To address this question, we examined how microbial extracellular sensor systems vary with environmental conditions across metagenomes at different Deep Mine Microbial Observatory (DeMMO) subsurface sites. Because two-component systems (TCSs) directly sense extracellular conditions and convert this information into intracellular biochemical responses, we expected that this sensor family would vary across isolated oligotrophic subterranean environments that differ in abiotic and biotic conditions. TCSs were found at all six subsurface sites, the service water control, and the surface site, with an average of 0.88 sensor histidine kinases (HKs) per 100 genes across all sites. Abundance was greater in subsurface fracture fluids compared with surface-derived fluids, and candidate phyla radiation (CPR) bacteria presented the lowest HK frequencies. Measures of microbial diversity, such as the Shannon diversity index, revealed that HK abundance is inversely correlated with microbial diversity ( r 2 = 0.81). Among the geochemical parameters measured, HK frequency correlated most strongly with variance in dissolved organic carbon ( r 2 = 0.82). Taken together, these results implicate the abiotic and biotic properties of an ecological niche as drivers of sensor needs, and they suggest that microbes in environments with large fluctuations in organic nutrients (e.g., lacustrine, terrestrial, and coastal ecosystems) may require greater TCS diversity than ecosystems with low nutrients (e.g., open ocean). IMPORTANCE The ability to detect extracellular environmental conditions is a fundamental property of all life forms. Because microbial two-component sensor systems convert information about extracellular conditions into biochemical information that controls their behaviors, we evaluated how two-component sensor systems evolved within the deep Earth across multiple sites where abiotic and biotic properties vary. We show that these sensor systems remain abundant in microbial consortia at all subterranean sampling sites and observe correlations between sensor system abundances and abiotic (dissolved organic carbon variation) and biotic (consortia diversity) properties. These results suggest that multiple environmental properties may drive sensor protein evolution and highlight the need for further studies of metagenomic and geochemical data in parallel to understand the drivers of microbial sensor evolution.

response regulator↗

Bias corrections of GOSAT SWIR XCO 2 and XCH 4 with TCCON data and their evaluation using aircraft measurement data

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO 2 (XCO 2 ) and CH 4 (XCH 4 ) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO 2 and XCH 4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO 2 /XCH 4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

54 ENVIRONMENTAL SCIENCES↗

Experiment design for pilot identification in compensatory tracking tasks

A design criterion for input functions in laboratory tracking tasks resulting in efficient parameter estimation is formulated. The criterion is that the statistical correlations between pairs of parameters be reduced in order to minimize the problem of nonuniqueness in the extraction process. The effectiveness of the method is demonstrated for a lower order dynamic system.

Wells, W. R.↗

Oxygen Affinity: The Missing Link Enabling Prediction of Proton Conductivities in Doped Barium Zirconates

Proton-conducting oxides, specifically doped barium zirconates, have garnered much attention as electrolytes for solid-state electrochemical devices operable at intermediate temperatures (400–600 °C). In chemical terms, hydration energy, E hyd , and proton–dopant association energy, E as , are two key parameters that determine whether an oxide exhibits fast proton conduction, but to date ab initio studies have for the most part studied each parameter separately, with no clear correlation with proton conductivity identified in either case. Here, we demonstrate that the oxygen affinity, E O.dopant , defined as the energy released when an oxide ion enters an oxygen vacancy close to a dopant atom, is the missing link between these two parameters and correlates well with experimental proton conductivities in doped barium zirconates. Ab initio calculations of point defects and their complexes in Sc-, In-, Lu-, Er-, Y-, Gd-, and Eu-doped barium zirconates are used to determine E hyd , E as , E O.dopant , and the hydrogen affinity, E H.host , of each system. These four energy terms are related by E hyd = E O.dopant + 2E H.host + 2E as . Complementary impedance spectroscopy measurements reveal that the stronger the calculated oxygen affinity of a system, the higher the proton conductivity at 350 °C. Although the proton trapping site is also an important factor, the results show that oxygen affinity is an excellent predictor of proton conductivity in these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Testing non-minimally coupled inflation with CMB data: a Bayesian analysis

We use the most recent cosmic microwave background (CMB) data to perform a Bayesian statistical analysis and discuss the observational viability of inflationary models with a non-minimal coupling, ξ, between the inflaton field and the Ricci scalar. We particularize our analysis to two examples of small and large field inflationary models, namely, the Coleman-Weinberg and the chaotic quartic potentials. We find that ( i ) the ξ parameter is closely correlated with the primordial amplitude ; ( ii ) although improving the agreement with the CMB data in the r − n {sub s} plane, where r is the tensor-to-scalar ratio and n {sub s} the primordial spectral index, a non-null coupling is strongly disfavoured with respect to the minimally coupled standard ΛCDM model, since the upper bounds of the Bayes factor (odds) for ξ parameter are greater than 150:1.

79 ASTRONOMY AND ASTROPHYSICS↗

Borehole Tool for the Comprehensive Characterization of Hydrate-bearing Sediments

Reservoir characterization and simulation require reliable parameters to anticipate hydrate deposits responses and production rates. The acquisition of the required fundamental properties currently relies on wireline logging, pressure core testing, and/or laboratory observations of synthesized specimens, which are challenged by testing capabilities and innate sampling disturbances. The project reviews hydrate-bearing sediments, properties, and inherent sampling effects, albeit lessen with the developments in pressure core technology, in order to develop robust correlations with index parameters. The resulting information is incorporated into a tool for optimal field characterization and parameter selection with uncertainty analyses. Ultimately, the project develops a borehole tool for the comprehensive characterization of hydrate-bearing sediments at in situ, with the design recognizing past developments and characterization experience and benefited from the inspiration of nature and sensor miniaturization.

03 NATURAL GAS↗

Thunderstorm hazards flight research - Program overview

The NASA thunderstorm hazards research program, designed to study the effects of lightning strikes on the design and operation of aircraft, is described. An all-weather F-106B is instrumented to document the EM characteristics of direct and nearby strikes, measure the field parameters and analyze the ambient atmospheric content, and film the strikes; X-ray detectors are also on board, along with instrumentation for determining the frequency of visible light waveforms. Data is either recorded on-board or sent by telemetry to base, while ground based telemetry is used to direct the pilot and craft into regions of optimal lightning activity. The sensing apparatus is described, and ongoing programs to correlate different storm parameters are reviewed, along with operational procedures and safety precautions. Continued use of the craft through 152 storms and 16 direct hits, with no fatalities or circuit breaker throw, confirms the ability of metal skinned aircraft to withstand lightning strikes; data gathered from flights during 1980 are provided.

Deal, P. L.↗

Predicting Outcome in Mammary Phyllodes Tumors: Relevance of Clinicopathological Features

Background: Phyllodes tumors (PTs) of the breast are uncommon fibroepithelial neoplasms. Most behave in a benign fashion but they also have the potential to recur locally or to metastasize. Methods: In the current study involving 290 PTs (181 benign, 76 borderline, and 33 malignant) from three hospitals over an 11-year period, we assessed the relationship between histologic parameters (including histologic features affecting grade and surgical margin status), postoperative adjuvant treatment, and local recurrences and distant metastases. Results: An involved surgical margin was the only factor associated with increased risk of local recurrences (hazard ratio [HR] 4.673, p = 0.003), but not for distant metastases. For local recurrences, a wider margin did not confer additional benefits. None of the histologic factors were predictive for local recurrences. In contrast, distant metastases were correlated with histologic parameters, particularly an infiltrative border (HR 10.935, p = 0.012) and the presence of necrosis (HR 15.311, p = 0.007). In this series, all local recurrences were found in patients without radiotherapy, regardless of surgical margin status. Conclusion: A negative surgical margin is mandatory for the effective local control of PT recurrence, and a minimal margin clearance may be sufficient. For distant metastases, the inherent characteristics of PTs are important, thus it may be prudent to evaluate additional histologic features, including necrosis, for patients’ prognostication.

62 RADIOLOGY AND NUCLEAR MEDICINE↗