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At least 613 records · Page 34

Resolving local structural motifs across the phase evolution of zinc titanates with computational x-ray absorption spectroscopy

Resolving the local structure motifs that characterize phase evolution as a function of composition is a key challenge in structure characterization of complex materials. Here, in this study, we combine first-principles simulations and x-ray absorption near-edge structures (XANES) analysis to gain insights into the structure evolution revealed by measurements across a combinatorial zinc titanate thin film, which was grown with smoothly varying composition over a wide range of the Ti:Zn ratio. Specifically, we propose a cluster blind-signal-separation (cBSS) method for XANES spectral analysis based on a library of the structures and spectra of representative local motifs. In addition to motifs from zinc titanate crystals, two types of Ti-defect models constructed in this study are key to the understanding of the structure characteristics in the Zn-rich region. The cBSS method makes use of both spectral clustering of the simulated site-XANES spectra library and the BSS procedure to construct high-fidelity spectral basis functions from an experimental spectral sequence. The method provides a rigorous measure of the spectral sensitivity and basis completeness. The results of the XANES analysis are corroborated with other experimental modalities, including x-ray diffraction and spectroscopic ellipsometry, to validate the cBSS method. The calculated motif weights resulting from fitting the XANES spectra with the cBSS basis probe the atomic structure characteristics of both crystalline and amorphous phases as a function of the Ti/Zn composition. The insights of the local structure motif evolution are pivotal to the understanding of the nonmonotonic trend in the optical gap, which may lead to potential applications through tuning the optical properties of zinc titanate. The workflow of the XANES spectral analysis developed in this work can be generalized to construct the structure-property relationship in a broad material space.

36 MATERIALS SCIENCE↗

On the Unusually High Temperature of the Cluster of Galaxies 1E 0657-56

A recent X-ray observation of the cluster 1E 0657-56 (z = 0.296) with ASC,4 implied an unusually high temperature of approx. 17 keV. Such a high temperature would make it the hottest known cluster and severely constrain cosmological models since, in a Universe with critical density (Omega = 1) the probability of observing such a cluster is only approx. 4 x 10(exp -5). Here we test the robustness of this observational result since it has such important implications. We analysed the data using a variety of different data analysis methods and spectral analysis assumptions and find a temperature of approx. 11 - 12 keV in all cases, except for one class of spectral fits. These are fits in which the absorbing column density is fixed at the Galactic value. Using simulated data for a 12 keV cluster, we show that a high temperature of approx. 17 keV is artificially obtained if the true spectrum has a stronger low-energy cut-off than that for Galactic absorption only. The apparent extra absorption may be astrophysical in origin, (either intrinsic or line-of-sight), or it may be a problem with the low-energy CCD efficiency. Although significantly lower than previous measurements, this temperature of kT approx. 11 - 12 keV is still relatively high since only a few clusters have been found to have temperatures higher than 10 keV and the data therefore still present some difficulty for an Omega = 1 Universe. Our results will also be useful to anyone who wants to estimate the systematic errors involved in different methods of background subtraction of ASCA data for sources with similar signal-to-noise to that of the IE 0657-56 data reported here.

Yaqoob, Tahir↗

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O<1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M~ 1x10(exp 7) M☉/yr) and the high mass-loss rate AGB star IK Tau (M~5x10(exp 6) M☉/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ~150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v=5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2.We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v1, previously derived for both objects (36 km/s versus v(∞)~17.7 km/s for IK Tau and 23 km/s versus v(∞)~5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond _400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ~3.7 x 10(exp 7) M☉ and ~2 x 10(ex0 8) M☉ for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

Stars: AGB and post-AGB, Stars: mass loss, Stars: ↗

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O < 1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M’ ∼ 1 × 10(exp −7) M/yr) and the high mass-loss rate AGB star IK Tau (M’ ∼ 5 × 10(exp −6) M/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ∼150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v = 5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2. We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v∞, previously derived for both objects (36 km/s versus v(∞) ∼ 17.7 km/s for IK Tau and 23 km/s versus v(∞) ∼ 5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond ∼400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ∼3.7 × 10(exp −7) Mand ∼2 × 10(exp −8) M for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

L. Decin↗

X-ray color analysis of the spectra of active galactic nuclei

The identification and detection of X-ray absorption and emission features depends on the resolution and the signal-to-noise ratio (S/N) of the observation, the understanding of the instrument response, and the Galactic line-of-sight absorption. Since many of the active galactic nucleus (AGN) data sets are limited in their S/N and full modeling of the physical conditions is rather complicated, we suggest a new analysis method based on 'X-ray colors.' The two sets of X-ray colors, defined for low (ROSAT Position Sensitive Proportional Counter (PSPC)) and medium (Broad Band X-Ray Telescope (BBXRT)) and ASCA Solid-State Imaging Spectrometers (SIS) resolution experiments, are used to separate regions of different physical conditions in a two-dimensional color-color plane. They are similar but superior to previous methods using the X-ray 'hardness ratio' in being able to reveal more of the physical properties of the source. We illustrate the use of such diagrams by studying a number of AGNs suspected of showing absorption features. A sample of 14 AGNs observed by the ROSAT PSPC is presented which includes several objects with suspected 'warm absorbers' along the line-of-sight to the nucleus, several others exhibiting intrinsic continuum variations, and a number of control objects thought to be featureless. Our new observations show, for the first time, the color variation as a function of time for three of the Seyfert 1 sources: NGC 4051, Mrk 335, and Mrk 766. The variations suggest that in two sources we are witnessing real changes in continuum shape, while one (NGC 4051) is consistent with having a warm absorber. Four of the objects observed by BBXRT are reanalyzed using our X-ray colors. Out of these, we discuss in detail the case of NGC 4151 and show that the color-color analysis agrees very well with previous, detailed spectral fitting methods. In particular, we confirm that the observed BBXRT observation of this source is not consistent with the warm absorber explanation and must be interpreted as a combination of a variable hard component and another component. We explain the limitations in measuring low-energy emission features in ASCA SIS observations and present color-color diagrams which can be used as a powerful diagnostic tool in the analysis of data collected by this experiment.

Netzer, Hagai↗

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Markus, Thorsten↗

Comparing field data using Alpert multi-wavelets

In this paper we introduce a method to compare sets of full-field data using Alpert tree-wavelet transforms. The Alpert tree-wavelet methods transform the data into a spectral space allowing the comparison of all points in the fields by comparing spectral amplitudes. The methods are insensitive to translation, scale and discretization and can be applied to arbitrary geometries. This makes them especially well suited for comparison of field data sets coming from two different sources such as when comparing simulation field data to experimental field data. We have developed both global and local error metrics to quantify the error between two fields. Additionally, we verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. Furthermore, we then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.

42 ENGINEERING↗

A physics-informed operator regression framework for extracting data-driven continuum models

The application of deep learning toward discovery of data-driven models requires careful application of inductive biases to obtain a description of physics which is both accurate and robust. We present here a framework for discovering continuum models from high fidelity molecular simulation data. Our approach applies a neural network parameterization of governing physics in modal space, allowing a characterization of differential operators while providing structure which may be used to impose biases related to symmetry, isotropy, and conservation form. Here, we demonstrate the effectiveness of our framework for a variety of physics, including local and nonlocal diffusion processes and single and multiphase flows. For the flow physics we demonstrate this approach leads to a learned operator that generalizes to system characteristics not included in the training sets, such as variable particle sizes, densities, and concentration.

42 ENGINEERING↗

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗

Large‐Eddy Simulations of a Convection Cloud Chamber: Sensitivity to Bin Microphysics and Advection

Abstract Bin microphysics schemes are useful tools for cloud simulations and are often considered to provide a benchmark for model intercomparison. However, they may experience issues with numerical diffusion, which are not well quantified, and the transport of hydrometeors depends on the choice of advection scheme, which can also change cloud simulation results. Here, an atmospheric large‐eddy simulation model is adapted to simulate a statistically steady‐state cloud in a convection cloud chamber under well‐constrained conditions. Two bin microphysics schemes, a spectral bin method and the method of moments, as well as several advection methods for the transport of the microphysical variables are employed for model intercomparison. Results show that different combinations of microphysics and advection schemes can lead to considerable differences in simulated cloud properties, such as cloud droplet number concentration. We find that simulations using the advection scheme that suffers more from numerical diffusion tends to have a smaller droplet number concentration and liquid water content, while simulation with the microphysics scheme that suffers more from numerical diffusion tends to have a broader size distribution and thus larger mean droplet sizes. Sensitivities of simulations to bin resolution, spatial resolution, and temporal resolution are also tested. We find that refining the microphysical bin resolution leads to a broader cloud droplet size distribution due to the advection of hydrometeors. Our results provide insight for using different advection and microphysics schemes in cloud chamber simulations, which might also help understand the uncertainties of the schemes used in atmospheric cloud simulations.

54 ENVIRONMENTAL SCIENCES↗

The Flux-Differencing Discontinuous Galerkin Method Applied to an Idealized Fully Compressible Nonhydrostatic Dry Atmosphere

Dynamical cores used to study the circulation of the atmosphere employ various numerical methods ranging from finite-volume, spectral element, global spectral, and hybrid methods. In this work, we explore the use of Flux-Differencing Discontinuous Galerkin (FDDG) methods to simulate a fully compressible dry atmosphere at various resolutions. We show that the method offers a judicious compromise between high-order accuracy and stability for large-eddy simulations and simulations of the atmospheric general circulation. In particular, filters, divergence damping, diffusion, hyperdiffusion, or sponge-layers are not required to ensure stability; only the numerical dissipation naturally afforded by FDDG is necessary. We apply the method to the simulation of dry convection in an atmospheric boundary layer and in a global atmospheric dynamical core in the standard benchmark of Held and Suarez

54 ENVIRONMENTAL SCIENCES↗

Impact of particle arrays on phase separation composition patterns

We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surfaces have a preferential affinity for one of the components. Our phase-field simulations indicate that the phase separation morphology in the presence of particle arrays can be tuned to have a continuous, droplet, lamellar, or hybrid morphology depending on the interparticle spacing, blend composition, and time. In particular, when the interparticle spacing is large compared to the spinodal wavelength, a transient target pattern composed of alternate rings of preferred and non-preferred phases emerges at early times, tending to adopt the symmetry of the particle configuration. We reveal that such target patterns stabilize for certain characteristic length, time, and composition scales characteristic of the pure phase-separating mixture. To illustrate the general range of phenomena exhibited by mixture-particle systems, we simulate the effects of single-particle, multi-particle, and cluster–particle systems having multiple geometrical configurations of the particle characteristic of pattern substrates on phase separation. Our simulations show that tailoring the particle configuration, or substrate pattern configuration, a relative fluid-particle composition should allow the desirable control of the phase separation morphology as in block copolymer materials, but where the scales accessible to this approach of organizing phase-separated fluids usually are significantly larger. Limited experiments confirm the trends observed in our simulations, which should provide some guidance in engineering patterned blend and other mixtures of technological interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Broadband 2DES detection of vibrational coherence in the S x state of canthaxanthin

The nonadiabatic mechanism that mediates nonradiative decay of the bright S 2 state to the dark S 1 state of carotenoids involves population of a bridging intermediate state, S x , in several examples. The nature of S x remains to be determined definitively, but it has been recently suggested that S x corresponds to conformationally distorted molecules evolving along out-of-plane coordinates of the isoprenoid backbone near a low barrier between planar and distorted conformations on the S 2 potential surface. Here, the electronic and vibrational dynamics accompanying the formation of S x in toluene solutions of the ketocarotenoid canthaxanthin (CAN) are characterized with broadband two-dimensional electronic spectroscopy (2DES) with 7.8 fs excitation pulses and detection of the linear polarization components of the third-order nonlinear optical signal. A stimulated-emission cross peak in the 2DES spectrum accompanies the formation of S x in <20 fs following excitation of the main absorption band. S x is prepared instantaneously, however, with excitation of hot-band transitions associated with distorted conformations of CAN’s isoprenoid backbone in the low frequency onset of the main absorption band. Vibrational coherence oscillation maps and modulated anisotropy transients show that S x undergoes displacements from the Franck–Condon S 2 state along out-of-plane coordinates as it passes to the S 1 state. The results are consistent with the conclusion that CAN’s carbonyl-substituted β-ionone rings impart an intramolecular charge-transfer character that frictionally slows the passage from S x to S 1 compared to carotenoids lacking carbonyl substitution. Despite the longer lifetime, the S 1 state of CAN is formed with retention of vibrational coherence after passing through a conical intersection seam with the S x state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-sensitivity electronic Stark spectrometer featuring a laser-driven light source

We report developmental details of a high-sensitivity Stark absorption spectrometer featuring a laser-driven light source. The light source exhibits intensity fluctuations of ~0.3% over timescales ranging from 1 min to 12 h, minimal drift (≤0.1%/h), and very little 1/f noise at frequencies greater than 200 Hz, which are comparable to or better than an arc-driven light source. Additional features of the spectrometer include balanced detection with multiplex sampling, which yielded lower noise in A, and constant wavelength or wavenumber (energy) spectral bandpass modes. We achieve noise amplitudes of ~7 × 10 –4 and ~6 × 10 –6 in measurements of single A and ΔA spectra (with 92 data points) taking ~7 and ~19 min, respectively.

47 OTHER INSTRUMENTATION↗

A self-consistent Hamiltonian model of the ponderomotive force and its structure preserving discretization

In the presence of an inhomogeneous oscillatory electric field, charged particles experience a net force, averaged over the oscillatory timescale, known as the ponderomotive force. We derive a one-dimensional Hamiltonian model which self-consistently couples the electromagnetic field to a plasma which experiences the ponderomotive force. We derive a family of structure preserving discretizations of the model of varying order in space and time using conforming and broken finite element exterior calculus spectral element methods. In all variants of our discretization framework, the method is found to conserve the Casimir invariants of the continuous model to machine precision and the energy to the order of the splitting method used.

Physics↗

Deep Multimodal Networks for M-type Star Classification with Paired Spectrum and Photometric Image

Abstract Traditional stellar classification methods include spectral and photometric classification separately. Although satisfactory results can be achieved, the accuracy could be improved. In this paper, we pioneer a novel approach to deeply fuse the spectra and photometric images of the sources in an advanced multimodal network to enhance the model’s discriminatory ability. We use Transformer as the fusion module and apply a spectrum–image contrastive loss function to enhance the consistency of the spectrum and photometric image of the same source in two different feature spaces. We perform M-type stellar subtype classification on two data sets with high and low signal-to-noise ratio (S/N) spectra and corresponding photometric images, and the F1-score achieves 95.65% and 90.84%, respectively. In our experiments, we prove that our model effectively utilizes the information from photometric images and is more accurate than advanced spectrum and photometric image classifiers. Our contributions can be summarized as follows: (1) We propose an innovative idea for stellar classification that allows the model to simultaneously consider information from spectra and photometric images. (2) We discover the challenge of fusing low-S/N spectra and photometric images in the Transformer and provide a solution. (3) The effectiveness of Transformer for spectral classification is discussed for the first time and will inspire more Transformer-based spectral classification models.

Astronomy & Astrophysics↗