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At least 361 records · Page 20

Measuring M31 globular cluster ages and metallicities using both photometry and spectroscopy

ABSTRACT The ages and metallicities of globular clusters play an important role not just in testing models for their formation and evolution but also in understanding the assembly history of their host galaxies. Here, we use a combination of imaging and spectroscopy to measure the ages and metallicities of globular clusters in M31, the closest massive galaxy to our own. We use the strength of the near-infrared calcium triplet spectral feature to provide a relatively age-insensitive prior on the metallicity when fitting stellar population models to the observed photometry. While the age–extinction degeneracy is an issue for globular clusters projected on to the disc of M31, we find generally old ages for globular clusters in the halo of M31 and in its satellite galaxy NGC 205 in line with previous studies. We measure ages for a number of outer halo globular clusters for the first time, finding that globular clusters associated with halo substructure extend to younger ages and higher metallicities than those associated with the smooth halo. This is in line with the expectation that the smooth halo was accreted earlier than the substructured halo.

Usher, Christopher (ORCID:0000000273837106)↗

Retrieve Methane from IR sounder measurements Using Machine Learning-Enhanced Physical Inversion

The sensitivity of IR sounder measurements to atmospheric CH 4 is often limited due to interferences from signals of other trace gases, insufficient thermal contrast, and cloud blockage. In order to resolve the geographical and vertical distribution of atmospheric CH 4 profiles, accurate scene-dependent a priori information is critically needed to support an optimal estimation method-based physical inversion scheme. Following the principles of indexing, representation, and retrieval, a spectral fingerprinting methodology is developed to address the needs for both accuracy and computational efficiency in sounder-based CH 4 retrieval. Within this framework, a clustering method based on machine learning is first employed to stratify and identify the a priori state within the pre-constructed database, using optimized spectral radiances as predictors. The corresponding radiative kernel is then used to establish the physical inversion scheme for finding the solution. High-quality data from CH 4 data assimilation systems like the Carbon-Tracker and the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, as well as the state-of-art sounder products are used to build the training database, including radiative kernels. We will demonstrate the results retrieved from CrIS observations and the associated validation work.

Wan Wu↗

Numerical trials of HISSE

The mathematical description and implementation of the statistical estimation procedure known as the Houston integrated spatial/spectral estimator (HISSE) is discussed. HISSE is based on a normal mixture model and is designed to take advantage of spectral and spatial information of LANDSAT data pixels, utilizing the initial classification and clustering information provided by the AMOEBA algorithm. The HISSE calculates parametric estimates of class proportions which reduce the error inherent in estimates derived from typical classify and count procedures common to nonparametric clustering algorithms. It also singles out spatial groupings of pixels which are most suitable for labeling classes. These calculations are designed to aid the analyst/interpreter in labeling patches with a crop class label. Finally, HISSE's initial performance on an actual LANDSAT agricultural ground truth data set is reported.

Peters, C.↗

Further studies of X-ray structure of the Perseus cluster

The X-ray sources in the Perseus cluster have been studied by many authors. Available data on the spatial and spectral distributions are examined and summarized. Based on these observations, a consistent model is proposed for the production of X-rays and gamma-rays in the region around NGC 1275. It is shown that good agreement with observations is obtained by assuming the emission of soft X-rays for thermal bremsstrahlung and of hard X-rays and gamma-rays from the inverse Compton process.

Lau, M. M.↗

The Einstein survey of the young stars in the Orion Nebula

The Orion Nebula is the best studied site of recent star formation in the Galaxy. The complete Einstein Observatory survey of the Orion Nebula covering a 2 deg x 2 deg region centered on the Trapezium is reported. An X-ray mosaic is presented for the Nebula along with a complete X-ray catalogue for this very young cluster. Approximately 150 distinct sources were found in this 4 sq deg region; spectral types and colors were obtained for about 1/2 of the optical counterparts of these sources. Comparison of the variability of the Orion X-ray sources with those found in the Rho Ophiuchi cloud leads to the conclusion that the Orion sources' variability is also likely to result from continual flaring activities. Eleven new late B stars associated with X-ray emission far exceeding that expected from early type stars were discovered. The X-rays may originate from pre-main sequence companions to these stars; a T-Tauri star of the same age would have the correct L sub x. Comparison of the solar type stars in Orion with those in the Pleiades, the Hyades, and the field suggests that the decay of activity with age is most appropriately described by an exponential, rather than a power law fit.

Zoonematkermani, S.↗

Scaling Relations from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High-Redshift Galaxy Clusters

We present Sunyaev-Zel'dovich Effect (SZE) scaling relations for 38 massive galaxy clusters at redshifts 0.14 less than or equal to z less than or equal to 0.89, observed with both the Chandra X-ray Observatory and the centimeter-wave SZE imaging system at the BIMA and OVRO interferometric arrays. An isothermal ,Beta-model with central 100 kpc excluded from the X-ray data is used to model the intracluster medium and to measure global cluster properties. For each Cluster, we measure the X-ray spectroscopic temperature, SZE gas mass, total mass. and integrated Compton-gamma parameters within r(sub 2500). Our measurements are in agreement with the expectations based on a simple self-similar model of cluster formation and evolution. We compare the cluster properties derived from our SZE observations with and without Chandra spatial and spectral information and find them to be in good agreement: We compare our results with cosmological numerical simulations, and find that simulations that include radiative cooling, star formation and feedback match well both the slope and normalization of our SZE scaling relations.

Bonamente, Massimiliano↗

Scaling Relations from Sunyaev-Zel'dovich Effect and Chandra X-Ray Measurements of High-Redshift Galaxy Clusters

We present Sunyaev-Zel'dovich Effect (SZE) scaling relations for 38 massive galaxy clusters at redshifts 0.14 less than or equal to z less than or equal to 0.89, observed with both the Chandra X-ray Observatory and the centimeter-wave SZE imaging system at the BIMA and OVRO interferometric arrays. An isothermal Beta-model with the central 100 kpc excluded from the X-ray data is used to model the intracluster medium and to measure global cluster properties. For each cluster, we measure the X-ray spectroscopic temperature, SZE gas mass, total mass, and integrated Compton gamma-parameters within r(sub 2500). Our measurements are in agreement with the expectations based on a simple self-similar model of cluster formation and evolution. We compare the cluster properties derived from our SZE observations with and without Chandra spatial and spectral information and find them to be in good agreement. We compare our results with cosmological numerical simulations and find that simulations that include radiative cooling, star formation, and feedback match well both the slope and normalization of our SZE scaling relations.

Bonamente, Massimiliano↗

Sensor Technology at Submillimeter Wavelengths for Space Applications

Our universe is most luminous at far-infrared and submillimeter wavelengths (100 GHz - 10 THz) after the Cosmic Microwave Background (CMB) radiation. This region of the electromagnetic spectrum provides critical tracers for the study of a wide range of astrophysical and planetary phenomena. This spectral range contains information on the origin of the planets, stars, galaxies, and clusters; the geometry and matter/energy content of the Universe, atmospheric constituents and dynamics of the planets and comets and tracers for global monitoring and the ultimate health of the Earth. Sensors at far-infrared and submillimeter wavelengths provide unprecedented sensitivity for astrophysical, planetary, and earth observing instruments. Very often, for a spaced based platform where the instruments are not limited by atmospheric losses and absorption, the overall instrument sensitivity is dictated by the sensitivity of the sensors themselves. Moreover, some of the cryogenic sensors at submillimeter wavelengths provide almost quantum-limited sensitivity. This paper provides an overview of the submillimeter-wave sensors and their performance and capabilities for space applications.

terahertz↗

Predictions of launch-induced, near-field acoustics of clustered rocket engines using a scaling approach

A scaling technique is proposed for the prediction of clustered rocket engine, near-field acoustics. Scaling equations predict the mean square pressures and power spectral density (PSD) of an unknown vehicle, using near-field measurements from a similar vehicle. Separation of nonhomogeneous Shuttle acoustics into Space Shuttle Main Engine (SSME) and Solid Rocket Booster (SRB) component acoustics forms the basis for verification of the proposed scaling equations. Three separate models, based on the total Shuttle PSD, a three-SSME vehicle PSD, and a two-SRB vehicle PSD, are recommended for the Advanced Launch System (ALS) near-field predictions. Acoustic efficiency, equivalent diameter of closely/widely spaced clustered engines, and the use of a distance-dependent spectra for scaling ALS vehicle near-field acoustics are briefly addressed.

Sepcenko, Valentin↗

57 Fe nuclear resonance vibrational spectroscopic studies of tetranuclear iron clusters bearing terminal iron( III )–oxido/hydroxido moieties

57 Fe nuclear resonance vibrational spectroscopy (NRVS) has been applied to study a series of tetranuclear iron ([Fe 4 ]) clusters based on a multidentate ligand platform (L 3− ) anchored by a 1,3,5-triarylbenzene linker and pyrazolate or (tertbutylamino)pyrazolate ligand (PzNH t Bu − ). These clusters bear a terminal Fe(III)–O/OH moiety at the apical position and three additional iron centers forming the basal positions. The three basal irons are connected with the apical iron center via a μ 4 -oxido ligand. Detailed vibrational analysis via density functional theory calculations revealed that strong NRVS spectral features below 400 cm −1 can be used as an oxidation state marker for the overall [Fe 4 ] cluster core. The terminal Fe(III)–O/OH stretching frequencies, which were observed in the range of 500–700 cm −1 , can be strongly modulated (energy shifts of 20–40 cm −1 were observed) upon redox events at the three remote basal iron centers of the [Fe 4 ] cluster without the change of the terminal Fe(III) oxidation state and its coordination environment. Therefore, the current study provides a quantitative vibrational analysis of how the remote iron centers within the same iron cluster exert exquisite control of the chemical reactivities and thermodynamic properties of the specific iron site that is responsible for small molecule activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AICCA: AI-Driven Cloud Classification Atlas

Clouds play an important role in the Earth’s energy budget, and their behavior is one of the largest uncertainties in future climate projections. Satellite observations should help in understanding cloud responses, but decades and petabytes of multispectral cloud imagery have to date received only limited use. This study describes a new analysis approach that reduces the dimensionality of satellite cloud observations by grouping them via a novel automated, unsupervised cloud classification technique based on a convolutional autoencoder, an artificial intelligence (AI) method good at identifying patterns in spatial data. Our technique combines a rotation-invariant autoencoder and hierarchical agglomerative clustering to generate cloud clusters that capture meaningful distinctions among cloud textures, using only raw multispectral imagery as input. Cloud classes are therefore defined based on spectral properties and spatial textures without reliance on location, time/season, derived physical properties, or pre-designated class definitions. We use this approach to generate a unique new cloud dataset, the AI-driven cloud classification atlas (AICCA), which clusters 22 years of ocean images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua and Terra instruments—198 million patches, each roughly 100 km × 100 km (128 × 128 pixels)—into 42 AI-generated cloud classes, a number determined via a newly-developed stability protocol that we use to maximize richness of information while ensuring stable groupings of patches. AICCA thereby translates 801 TB of satellite images into 54.2 GB of class labels and cloud top and optical properties, a reduction by a factor of 15,000. The 42 AICCA classes produce meaningful spatio-temporal and physical distinctions and capture a greater variety of cloud types than do the nine International Satellite Cloud Climatology Project (ISCCP) categories—for example, multiple textures in the stratocumulus decks along the West coasts of North and South America. We conclude that our methodology has explanatory power, capturing regionally unique cloud classes and providing rich but tractable information for global analysis. AICCA delivers the information from multi-spectral images in a compact form, enables data-driven diagnosis of patterns of cloud organization, provides insight into cloud evolution on timescales of hours to decades, and helps democratize climate research by facilitating access to core data.

97 MATHEMATICS AND COMPUTING↗

Radio Sources in Galaxy Clusters at 28.5 GHz

We present serendipitous observations of radio sources at 28.5 GHz (1 cm), which resulted from our program to image thermal Sunyaev-Zeldovich (SZ) effect in 56 galaxy clusters. In a total area of about 0.8 degrees sq., we find 64 radio sources with fluxes down to - 0.4 mJy (> 4sigma,), and within 250" from the pointing centers. The spectral indices (S varies as v(sup -alpha) of 54 sources with published low frequency flux densities range from -0.6 approximately < alpha and alpha approximately < 2 with a mean of 0.77 +/- 0.06, and a median of 0.84. Extending low frequency surveys of radio sources towards galaxy clusters CL 0016+16, Abell 665, and Abell 2218 to 28.5 GHz, and selecting sources with S(sub l.4GHz) >/= 7 mJy to form an unbiased sample, we find a mean spectral index of 0.71 +/- 0.08 and a median of 0.71. We find 4 to 7 times more sources predicted from a low frequency survey in areas without galaxy clusters. This excess cannot be accounted for by gravitational lensing of a background radio population by cluster potentials, indicating most of the detected sources are associated with galaxy clusters. The differential source count slope, gamma is approximately 1.96 (dN/dS varies as S(exp -gamma)), is flatter than what is expected for a nonevolving Euclidean population (gamma = 2.5). For the cluster Abell 2218, the presence of unsubtracted radio sources with S(sub 28.5GHz) is approximately < 0.5 mJy (- 5 sigma), can only contribute to temperature fluctuations at a level of DeltaT is approximately 10 to 25 microK. The corresponding error due to radio point source contamination in the Hubble constant derived through a combined analysis of 28.5 GHz SZ images and X-ray emission observations ranges from 1% to 6%.

Cooray, Asantha R.↗

Stratification of Landsat data by clustering

Full realization of the potential advantages of the synoptic coverage provided by Landsat will require the development and use of data analysis techniques which take into account the large variation and diversity of patterns found over many Landsat scenes. Stratification of the scene into units which are internally homogeneous is recommended as a first step in the analysis of data for whole or multiple frames of Landsat data. The use of clustering as an objective and efficient method of dividing scenes into areas which are spectrally similar (strata) is discussed and initial results, including classification performances and comparisons of spectral strata with major physical factors, are presented.

Bauer, M. E.↗

Novel laser gain and time-resolved FTIR studies of photochemistry

Several techniques are discussed which can be used to explore laboratory photochemical processes and kinetics relevant to planetary atmospheres; these include time-resolved laser gain-versus-absorption spectroscopy and time-resolved Fourier transform infrared (FTIR) emission studies. The laser gain-versus-absorption method employed tunable diode and F-center lasers to determine the yields of excited photofragments and their kinetics. The time-resolved FTIR technique synchronizes the sweep of a commercial FTIR with a pulsed source of light to obtain emission spectra of novel transient species in the infrared. These methods are presently being employed to investigate molecular photodissociation, the yields of excited states of fragments, their subsequent reaction kinetics, Doppler velocity distributions, and velocity-changing collisions of translationally fast atoms. Such techniques may be employed in future investigations of planetary atmospheres, for example to study polycyclic aromatic hydrocarbons related to cometary emissions, to analyze acetylene decomposition products and reactions, and to determine spectral features in the near infrared and infrared wavelength regions for planetary molecules and clusters.

Leone, Stephen R.↗

Coronal Physics and the Chandra Emission Line Project

With the launch of the Chandra X-ray Observatory, high resolution X-ray spectroscopy of cosmic sources has begun. Early, deep observations of three stellar coronal sources will provide not only invaluable calibration data, but will also give us benchmarks for plasma spectral modeling codes. These codes are to interpret data from stellar coronae, galaxies and clusters of galaxies. supernova remnants and other astrophysical sources, but they have been called into question in recent years as problems with understanding moderate resolution ASCA and EUVE data have arisen. The Emission Line Project is a collaborative effort to improve the models, with Phase 1 being the comparison of models with observed spectra of Capella, Procyon, and HR, 1099. Goals of these comparisons are (1) to determine and verify accurate and robust diagnostics and (2) to identify and prioritize issues in fundamental spectroscopy which will require further theoretical and/or laboratory work. A critical issue in exploiting the coronal data for these purposes is to understand the extent to which common simplifying assumptions (coronal equilibrium, time-independence, negligible optical depth) apply. We will discuss recent advances in our understanding of stellar coronae in this context.

Brickhouse, Nancy↗

Coronal Physics and the Chandra Emission Line Project

With the launch of the Chandra X-ray Observatory, high resolution X-ray spectroscopy of cosmic sources has begun. Early, deep observations of three stellar coronal sources Capella, Procyon, and HR 1099 are providing not only invaluable calibration data, but also benchmarks for plasma spectral models. These models are needed to interpret data from stellar coronae, galaxies and clusters of galaxies, supernova, remnants and other astrophysical sources. They have been called into question in recent years as problems with understanding low resolution ASCA and moderate resolution Extreme Ultraviolet Explorer Satellite (EUVE) data have arisen. The Emission Line Project is a collaborative effort, to improve the models, with Phase I being the comparison of models with observed spectra of Capella, Procyon, and HR 1099. Goals of these comparisons are (1) to determine and verify accurate and robust diagnostics and (2) to identify and prioritize issues in fundamental spectroscopy which will require further theoretical and/or laboratory work. A critical issue in exploiting the coronal data for these purposes is to understand the extent, to which common simplifying assumptions (coronal equilibrium, negligible optical depth) apply. We will discuss recent, advances in our understanding of stellar coronae, in this context.

Brickhouse, N. S.↗