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At least 1,657 records · Page 92

An Application of Multi-band Forced Photometry to One Square Degree of SERVS: Accurate Photometric Redshifts and Implications for Future Science

We apply The Tractor image modeling code to improve upon existing multi-band photometry for the Spitzer Extragalactic Representative Volume Survey (SERVS). SERVS consists of post-cryogenic Spitzer observations at 3.6 and 4.5 μ m over five well-studied deep fields spanning 18 deg{sup 2}. In concert with data from ground-based near-infrared (NIR) and optical surveys, SERVS aims to provide a census of the properties of massive galaxies out to z ≈ 5. To accomplish this, we are using The Tractor to perform “forced photometry.” This technique employs prior measurements of source positions and surface brightness profiles from a high-resolution fiducial band from the VISTA Deep Extragalactic Observations survey to model and fit the fluxes at lower-resolution bands. We discuss our implementation of The Tractor over a square-degree test region within the XMM Large Scale Structure field with deep imaging in 12 NIR/optical bands. Our new multi-band source catalogs offer a number of advantages over traditional position-matched catalogs, including (1) consistent source cross-identification between bands, (2) de-blending of sources that are clearly resolved in the fiducial band but blended in the lower resolution SERVS data, (3) a higher source detection fraction in each band, (4) a larger number of candidate galaxies in the redshift range 5 < z < 6, and (5) a statistically significant improvement in the photometric redshift accuracy as evidenced by the significant decrease in the fraction of outliers compared to spectroscopic redshifts. Thus, forced photometry using The Tractor offers a means of improving the accuracy of multi-band extragalactic surveys designed for galaxy evolution studies. We will extend our application of this technique to the full SERVS footprint in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Redshifts of radio sources in the Million Quasars Catalogue from machine learning

ABSTRACT With the aim of using machine learning techniques to obtain photometric redshifts based upon a source’s radio spectrum alone, we have extracted the radio sources from the Million Quasars Catalogue. Of these, 44 119 have a spectroscopic redshift, required for model validation, and for which photometry could be obtained. Using the radio spectral properties as features, we fail to find a model which can reliably predict the redshifts, although there is the suggestion that the models improve with the size of the training sample. Using the near-infrared–optical–ultraviolet bands magnitudes, we obtain reliable predictions based on the 12 503 radio sources which have all of the required photometry. From the 80:20 training–validation split, this gives only 2501 validation sources, although training the sample upon our previous SDSS model gives comparable results for all 12 503 sources. This makes us confident that SkyMapper, which will survey southern sky in the u, v, g, r, i, z bands, can be used to predict the redshifts of radio sources detected with the Square Kilometre Array. By using machine learning to impute the magnitudes missing from much of the sample, we can predict the redshifts for 32 698 sources, an increase from 28 to 74 per cent of the sample, at the cost of increasing the outlier fraction by a factor of 1.4. While the ‘optical’ band data prove successful, at this stage we cannot rule out the possibility of a radio photometric redshift, given sufficient data which may be necessary to overcome the relatively featureless radio spectra.

79 ASTRONOMY AND ASTROPHYSICS↗

Optical spectroscopy of molten fluorides: Methods, electronic and vibrational data, structural interpretation, and relevance to radiative heat transfer

In this study, to help address the need for predicting radiative heat transfer (RHT) behavior of molten salts, we conducted a comprehensive review of methods and data from optical spectroscopic measurements on molten fluoride salts. Transmittance, reflectance, and trans-reflectance experimental methods are discussed, along with the corresponding data reduction methodology and the limitations of each technique. Optical spectroscopy is a convenient indirect probe for changes in structural parameters with temperature and composition. Electronic and vibrational absorption data for transition-metal, lanthanide, and actinide solutes and vibrational absorption data for alkali and alkaline earth fluoride solvents are compiled, and the corresponding structural interpretation is discussed and compared with other experimental and theoretical work. We find that solvent and solute vibrational absorption can be significant in the mid-infrared, resulting in near-infrared edges of significance to RHT. Extrapolation and averaging of existing edge data leads to estimated gray absorption coefficient values at 700 °C of 546 m —1 for FLiBe and 276 m —1 for FLiNaK, both within the range of 1 – 6000 m —1 identified to be of engineering relevance for radiative heat transfer analysis.

36 MATERIALS SCIENCE↗

Probing Linewidths and Biexciton Quantum Yields of Single Cesium Lead Halide Nanocrystals in Solution

Cesium lead halide (CsPbX 3 , X = Cl, Br, I) perovskite nanocrystals (PNCs) have recently become a promising material for optoelectronic applications due to their high emission quantum yields and facile band gap tunability via both halide composition and size. The spectroscopy of single PNCs enhances our understanding of the effect of confinement on excitations in PNCs in the absence of obfuscating ensemble averaging and can also inform synthetic efforts. However, single PNC studies have been hampered by poor PNC photostability under confocal excitation, precluding interrogation of all but the most stable PNCs, and leading to a lack of understanding of PNCs in the regime of high confinement. Here, we report the first comprehensive spectroscopic investigation of single PNC properties using solution-phase photon-correlation methods, including both highly confined and blue-emitting PNCs, previously inaccessible to single NC techniques. With minimally perturbative solution-phase photon-correlation Fourier spectroscopy (s-PCFS), we establish that the ensemble emission linewidth of PNCs of all sizes and compositions is predominantly determined by the intrinsic single PNC linewidth (homogeneous broadening). The single PNC linewidth, in turn, dramatically increases with increasing confinement, consistent with what has been found for II–VI semiconductor nanocrystals. With solution-phase photon antibunching measurements, we survey the biexciton-to-exciton quantum yield ratio (BX/X QY) in the absence of user-selection bias or photodegradation. Remarkably, the BX/X QY ratio depends both on the PNC size and halide composition, with values between ~2% for highly confined bromide PNCs and ~50% for intermediately confined iodide PNCs. Our results suggest a wide range of underlying Auger rates, likely due to transitory charge carrier separation in PNCs with relaxed confinement.

single nanocrystal spectroscopy↗

Nanoparticle shape evolution and proximity effects during tip-induced electrochemical processes

The voltage spectroscopies in scanning probe microscopy (SPM) techniques are widely used to investigate the electrochemical processes in nanoscale volumes, which are important for current key applications, such as batteries, fuel cells, catalysts, and memristors. The spectroscopic measurements are commonly performed on a grid of multiple points to yield spatially resolved maps of reversible and irreversible electrochemical functionalities. Hence, the spacing between measurement points is an important parameter to be considered, especially for irreversible electrochemical processes. Here, we report nonlocal electrochemical dynamics in chains of Ag particles fabricated by the SPM tip on a silver ion solid electrolyte. When the grid spacing is small compared with the size of the formed Ag particles, anomalous chains of unequally sized particles with double periodicity evolve. This behavior is ascribed to a proximity effect during the tip-induced electrochemical process, specifically, size-dependent silver particle growth following the contact between the particles. In addition, fractal shape evolution of the formed Ag structures indicates that the growth-limiting process changes from Ag + /Ag redox reaction to Ag + -ion diffusion with the increase in the applied voltage and pulse duration. Our study shows that characteristic shapes of the electrochemical products are good indicators for determining the underlying growth-limiting process, and emergence of complex phenomena during spectroscopic mapping of electrochemical functionalities.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Correlating Protein Dynamics and Catalytic Activity of a Model Hydrogenase Using Paramagnetic and Biological Nuclear Magnetic Resonance Spectroscopy

Rational catalyst design remains a significant challenge, with electronic structure, steric, and electrostatic effects known to contribute to activity. Recently, dynamics has been recognized as another factor that impacts catalysis, though identifying and predicting these effects has remained out of reach. Nickel-substituted rubredoxin (NiRd), a protein-based mimic of a hydrogenase enzyme, serves as a model catalytic system in which dynamics can be systematically investigated with respect to activity. While over 30 secondary-sphere mutants of NiRd have been shown to be catalytically active, no significant correlation was observed between the rates and catalytic overpotential or electronic structure, prompting questions about the protein-derived factors that modulate activity. Here, in this work, NMR spectroscopy was used to investigate the roles of substrate accessibility, protein dynamics, and protein stability in controlling catalysis. Significant paramagnetic effects from the nickel center (S = 1) isolate the methylene proton resonances of the metal-coordinating cysteine residues. The sensitivity of resonance positions and linewidths to local environment offers an opportunity to study dynamical molecular changes around the metal center with high resolution. Machine learning algorithms were employed to identify correlations between the catalytic activity and the paramagnetic NMR spectra. These analyses revealed spectroscopic features of specific cysteine protons that report on catalytic overpotential and increased turnover rates, which are further supported by the results obtained using high-field NMR techniques. Collectively, these studies indicate the potential for multifrequency NMR techniques to resolve key contributors to catalytic activity and highlight the importance of local and outer-sphere dynamics.

Protein Engineering↗

Silica accelerates the selective hydrogenation of CO 2 to methanol on cobalt catalysts

The reaction pathways on supported catalysts can be tuned by optimizing the catalyst structures, which helps the development of efficient catalysts. Such design is particularly desired for CO 2 hydrogenation, which is characterized by complex pathways and multiple products. Here, we report an investigation of supported cobalt, which is known for its hydrocarbon production and ability to turn into a selective catalyst for methanol synthesis in CO 2 hydrogenation which exhibits good activity and stability. The crucial technique is to use the silica, acting as a support and ligand, to modify the cobalt species via Co-O-SiOn linkages, which favor the reactivity of spectroscopically identified *CH 3 O intermediates, that more readily undergo hydrogenation to methanol than the C-O dissociation associated with hydrocarbon formation. Cobalt catalysts in this class offer appealing opportunities for optimizing selectivity in CO 2 hydrogenation and producing high-grade methanol. By identifying this function of silica, we provide support for rationally controlling these reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MOVPE and MBE growth of semiconductor thin films

Fundamental aspects of MBE and MOVPE growth techniques are briefly discussed. The capabilities and limitation of the two epitaxial growth techniques are summarized. A few examples of the MOVPE and MBE growth of high crystalline quality semiconductor thin films are also given including the characterization results obtained from spectroscopic and high resolution x-ray diffraction methods.

36 MATERIALS SCIENCE↗

DETECTING ACTIVE GALACTIC NUCLEI USING MULTI-FILTER IMAGING DATA. II. INCORPORATING ARTIFICIAL NEURAL NETWORKS

This is the second paper of the series Detecting Active Galactic Nuclei Using Multi-filter Imaging Data. In this paper we review shapelets, an image manipulation algorithm, which we employ to adjust the point-spread function (PSF) of galaxy images. This technique is used to ensure the image in each filter has the same and sharpest PSF, which is the preferred condition for detecting AGNs using multi-filter imaging data as we demonstrated in Paper I of this series. We apply shapelets on Canada-France-Hawaii Telescope Legacy Survey Wide Survey ugriz images. Photometric parameters such as effective radii, integrated fluxes within certain radii, and color gradients are measured on the shapelets-reconstructed images. These parameters are used by artificial neural networks (ANNs) which yield: photometric redshift with an rms of 0.026 and a regression R-value of 0.92; galaxy morphological types with an uncertainty less than 2 T types for z ≤ 0.1; and identification of galaxies as AGNs with 70% confidence, star-forming/starburst (SF/SB) galaxies with 90% confidence, and passive galaxies with 70% confidence for z ≤ 0.1. The incorporation of ANNs provides a more reliable technique for identifying AGN or SF/SB candidates, which could be very useful for large-scale multi-filter optical surveys that also include a modest set of spectroscopic data sufficient to train neural networks.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.

36 MATERIALS SCIENCE↗

The clustering of theSDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: measuring the anisotropic baryon acoustic oscillations with redshift weights

We present an anisotropic analysis of baryon acoustic oscillation (BAO) signal from the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. The sample consists of 147 000 quasars distributed over a redshift range of 0.8 < z < 2.2. We apply the redshift weights technique to the clustering of quasars in this sample and achieve a 4.6 per cent measurement of the angular distance measurement DM at z = 2.2 and Hubble parameter H at z = 0.8. We parametrize the distance-redshift relation, relative to a fiducial model, as a Taylor series. The coefficients of this expansion are used to reconstruct the distance-redshift relation and obtain distance and Hubble parameter measurements at all redshifts within the redshift range of the sample. Reporting the result at two characteristic redshifts, we determine DM(z = 1) = 3405 ± 305 (rd/rd, fid) Mpc, H(z=1) = 120.7± 7.3 (r_d,fid / r_d) km s^{-1} Mpc^{-1} and DM(z = 2) = 5325 ± 249 (rd/rd, fid) Mpc, H(z=2) = 189.9± 32.9 (r_d,fid / r_d) km s^{-1} Mpc^{-1}. These measurements are highly correlated. We assess the outlook of BAO analysis from the final quasar sample by testing the method on a set of mocks that mimic the noise level in the final sample. We demonstrate on these mocks that redshift weighting shrinks the measurement error by over 25 per cent on average. We conclude redshift weighting can bring us closer to the cosmological goal of the final quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Final Scientific/Technical Report

The ultimate goal of this project was to better understand the nature of dark energy. Dark energy is a mysterious component of the Universe that is causing the acceleration of the cosmic expansion rate. The best measurements of this rate are consistent with dark energy in the form of a cosmological constant. This means that the component responsible for the expansion has not changed in strength in the history of the universe, although it did not appear make a significant impact on the expansion rate for the first half of cosmic history. As almost nothing is known about dark energy other than that the expansion rate is presently accelerating, there are many substantial efforts underway to obtain better data to determine if dark energy is truly consistent with a cosmological constant, or if there is any evidence of evolution. The Dark Energy Spectroscopic Instrument (DESI) is a new survey planned to begin in 2019 that will obtain substantially better measurements of the cosmic expansion rate than previous surveys. The main technique it will use is Baryon Acoustic Oscillations (BAO). The BAO scale corresponds to a fixed physical length scale or ‘standard ruler’ that was imprinted on the distribution of baryons in the early universe. DESI will measure this scale over most of the age of the universe, and will consequently provide the best measurement of the dark energy contribution. At the earliest times, DESI will use measurements of rare but luminous quasars for the BAO measurements through observations of neutral Hydrogen absorption along the line of sight to each quasar. While supported by these funds, I contributed to the construction of the DESI spectrographs that will record these measurements. I also became deeply involved in other aspects of the DESI experiment, and was chosen to become the Instrument Scientist for the entire DESI Project. During the project period I also worked on quasar selection techniques with data from the Dark Energy Survey (DES), which may be adopted by DESI.

79 ASTRONOMY AND ASTROPHYSICS↗

The calibration of photographic and spectroscopic films. The utilization of the digital image processor in the determination of aging of the surf clam (Spisula solidissima)

The age of the surf clam (Spisula solidissima) can be determined with the use of the Digital Image Processor. This technique is used in conjunction with a modified method for aging, refined by John Ropes of the Woods Hole Laboratory, Massachusetts. This method utilizes a thinned sectioned chondrophore of the surf clam which contains annual rings. The rings of the chondrophore are then counted to determine age. By digitizing the chondrophore, the Digital Image Processor is clearly able to separate these annual rings more accurately. This technique produces an easier and more efficient way to count annual rings to determine the age of the surf clam.

Peters, Kevin A.↗

Non-Invasive Biophysical Techniques to Monitor the Structural Plasticity of the Photosynthetic Machinery of Live Diatom Cells

The photosynthetic performance of diatoms depends largely on the organization and structural flexibility of their thylakoid membranes, the densely packed, highly organized membrane vesicles in which light reactions of photosynthesis occur. Different regulatory mechanisms that fine tune the photosynthetic functions affect the organization of the photosynthetic machinery at different levels of structural complexity, from the level of individual protein complexes to the macroarray of membrane proteins and the remodeling of the entire thylakoid membrane system. To monitor these reorganizations, non-invasive techniques are of special value. In this chapter, we focus our attention on three of these techniques, which have been demonstrated to provide unique and useful information on the structure and structural and functional plasticity of live diatom cells: (i) circular dichroism (CD) spectroscopy, which has provided unique information on the chiral (macro-)organization of protein complexes and on their rapid, reversible reorganizations, fine-tuning the light-harvesting processes, as well as on variations in the short-range excitonic interactions in the antenna complexes; (ii) small-angle neutron scattering (SANS), which has been used to determine the periodic organization of the thylakoid membranes and to monitor reversible ultrastructural changes on the time-scale of minutes, induced by variations in the environmental conditions such as changes in temperature or light intensity; and (iii) electrochromic shift absorbance transients (ΔA ECS ), a spectroscopic tool which has been shown to be capable of identifying distinct functional groups of the light-harvesting carotenoid fucoxanthin in different diatoms and in cells exposed to different light intensities. Future use of these techniques will most certainly contribute to the deeper understanding of key regulatory mechanisms of photosynthesis in diatoms.

Szabo, Milan↗

Laboratory analyses of micron-sized solid grains: Experimental techniques and recent results

Morphological and spectrophotometric investigations have been extensively applied in the past years to various kinds of micron and/or submicron-sized grains formed by materials which are candidate to be present in space. The samples are produced in the laboratory and then characterized in their physio-chemical properties. Some of the most recent results obtained on various kinds of carbonaceous materials are reported. Main attention is devoted to spectroscopic results in the VUV and IR wavelength ranges, where many of the analyzed samples show typical fingerprints which can be identified also in astrophysical and cometary materials. The laboratory methodologies used so far are also critically discussed in order to point out capabilities and present limitations, in the view of possible application to returned comet samples. Suggestions are given to develop new techniques which should overcome some of the problems faced in the manipulation and analysis of micron solid samples.

Colangeli, L.↗

Development Fiber Optic Distributed System for Direct Detection of Subsurface Gases Leakages

Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.

organic↗

Glass-based confined structures enabling light control

When a luminescent ion is confined in a system characterized by one or more specific properties such as spatial size, geometrical dimension and shape, refractive index, local crystal field, cut-off vibrational energy and so on, it's possible to control its emission. The control of branching ratios as a function of the composition, the luminescence enhancement induced by a photonic crystal, or the laser action in a microresonator, are well known examples of light control. Photonic glass-based structures are extremely viable systems to exploit the above mentioned properties and in our research team we have successfully fabricated luminescent photonic structures by different techniques, including sol-gel, rf sputtering, drawing, melting, and physical vapour deposition. Here we will discuss some of them with the aim to make the reader aware of the chemical-physical properties related to each specific system. We will demonstrate that glass ceramic waveguides in some cases present superior spectroscopic properties in respect to the parent glass, that compositional properties can play a positive role in reducing luminescence quenching and in developing novel planar waveguides and fibers, that colloids allow to obtain high internal quantum efficiency and that photonic crystals, microcavities and microresonators can enable the handling of the rare earth luminescence. Finally, the pros and cons of the systems and of the different techniques employed for their fabrication will be discussed and some perspectives concerning the glass photonics will be proposed looking at both possible applications and investigation of physical properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Classifying supernovae using only galaxy data

We present a new method for probabilistically classifying supernovae (SNe) without using SN spectral or photometric data. Unlike all previous studies to classify SNe without spectra, this technique does not use any SN photometry. Instead, the method relies on host-galaxy data. We build upon the well-known correlations between SN classes and host-galaxy properties, specifically that core-collapse SNe rarely occur in red, luminous, or early-type galaxies. Using the nearly spectroscopically complete Lick Observatory Supernova Search sample of SNe, we determine SN fractions as a function of host-galaxy properties. Using these data as inputs, we construct a Bayesian method for determining the probability that an SN is of a particular class. This method improves a common classification figure of merit by a factor of >2, comparable to the best light-curve classification techniques. Of the galaxy properties examined, morphology provides the most discriminating information. We further validate this method using SN samples from the Sloan Digital Sky Survey and the Palomar Transient Factory. We demonstrate that this method has wide-ranging applications, including separating different subclasses of SNe and determining the probability that an SN is of a particular class before photometry or even spectra can. Since this method uses completely independent data from light-curve techniques, there is potential to further improve the overall purity and completeness of SN samples and to test systematic biases of the light-curve techniques. Further enhancements to the host-galaxy method, including additional host-galaxy properties, combination with light-curve methods, and hybrid methods, should further improve the quality of SN samples from past, current, and future transient surveys.

79 ASTRONOMY AND ASTROPHYSICS↗