Low-resolution Spectral Data Research Articles

Spectral Retrieval with JWST Photometric data: a Case Study for HIP 65426 b

Half of the JWST high-contrast imaging objects will only have photometric data as of Cycle 2. However, to better understand their atmospheric chemistry that informs formation origin, spectroscopic data are preferred. Using HIP 65426 b, we investigate to what extent planet properties and atmospheric chemical abundance can be retrieved with only JWST photometric data points (2.5–15.5 μm) in conjunction with ground-based archival low-resolution spectral data (1.0–2.3 μm). We find that the data is consistent with an atmosphere with solar metallicity and C/O ratios at 0.40 and 0.55. We rule out 10× solar metallicity and an atmosphere with C/O = 1.0. We also find strong evidence of silicate clouds but no sign of an enshrouding featureless dust extinction. This work offers guidance and cautionary tales on analyzing data in the absence of medium-to-high-resolution spectral data.

Self super-resolution of optical coherence tomography images based on deep learning.

As a medical imaging modality, many researches have been devoted to improving the resolution of optical coherence tomography (OCT). We developed a deep-learning based OCT self super-resolution (OCT-SSR) pipeline to improve the axial resolution of OCT images based on the high-resolution and low-resolution spectral data collected by the OCT system. In this pipeline, the enhanced super-resolution asymmetric generative adversarial networks were built to improve the network outputs without increasing the complexity. The feasibility and effectiveness of the approach were demonstrated by experimental results on the images of the biological samples collected by the home-made spectral-domain OCT and swept-source OCT systems. More importantly, we found the sidelobes in the original images can be obviously suppressed while improving the resolution based on the OCT-SSR method, which can help to reduce pseudo-signal in OCT imaging when non-Gaussian spectra light source is used. We believe that the OCT-SSR method has broad prospects in breaking the limitation of the source bandwidth on the axial resolution of the OCT system.

GaiaData Release 3

Context.Blue (BP) and Red (RP) Photometer low-resolution spectral data are one of the exciting new products inGaiaData Release 3 (GaiaDR3). These data have also been used to derive astrometry and integrated photometry inGaiaEarly Data Release 3 and astrophysical parameters and Solar System object reflectance spectra inGaiaDR3.Aims.In this paper, we give an overview of the processing techniques that allow raw satellite data of multiple transits per source to be converted into combined spectra calibrated to an internal reference system, resulting in low-resolution BP and RP mean spectra. We describe how we overcome challenges due to the complexity of the on-board instruments and to the various observation strategies. Furthermore, we show highlights from our scientific validation of the results. This work covers the internal calibration of BP/RP spectra to a self-consistent mean instrument, while the calibration of the BP/RP spectra to the absolute reference system of physical flux and wavelength is covered by one of the accompanyingGaiaDR3 papers.Methods.We calibrate about 65 billion individual transit spectra onto the same mean BP/RP instrument through a series of calibration steps, including background subtraction, calibration of the CCD geometry, and an iterative procedure for the calibration of CCD efficiency as well as variations of the line-spread function and dispersion across the focal plane and in time. The calibrated transit spectra are then combined for each source in terms of an expansion into continuous basis functions. We discuss the configuration of these basis functions.Results.Time-averaged mean spectra covering the optical to near-infrared wavelength range [330, 1050] nm are published for approximately 220 million objects. Most of these are brighter thanG = 17.65 but some BP/RP spectra are published for sources down toG = 21.43. Their signal-to-noise ratio (S/N) varies significantly over the wavelength range covered, and with magnitude and colour of the observed objects, with sources aroundG = 15 having a S/N above 100 in some wavelength ranges. The top-quality BP/RP spectra are achieved for sources with magnitudes 9 < G < 12, with S/N reaching 1000 in the central part of the RP wavelength range. Scientific validation suggests that the internal calibration was generally successful. However, there is some evidence for imperfect calibrations at the bright endG < 11, where calibrated BP/RP spectra can exhibit systematic flux variations that exceed their estimated flux uncertainties. We also report that, due to long-range noise correlations, BP/RP spectra can exhibit wiggles when sampled in pseudo-wavelength.Conclusions.TheGaiaDR3 data products are the expansion coefficients and corresponding covariance matrices for BP and RP separately. Users are encouraged to work with the data in this format, with full covariance information showing that correlations between coefficients are typically very low. Documentation and instructions on how to access and use BP/RP spectral data from the archive are also provided.

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

Efficient facial expression recognition via convolution neural network and infrared imaging technology

Facial expression recognition is an important research topic in the field of human-machine interaction. Infrared imaging technology has illustrated good potential in the applications of facial expression recognition and computer vision. But the low-resolution spectral data has limited its applications, such as band overlap and random noises. To address the problems, a rapid blind restoration model with discrete beamlet transforms regularization is presented to reconstruct the infrared spectrum. To compare the sparsity between the observed infrared spectrum and ground-truth one in frequency domain, the discrete beamlet transforms is applied to analyze the different of their coefficients distributions. We propose an IR spectral deconvolution model with the sparsity coefficients regularization by L0-norm. We execute the proposed algorithm on the simulated and actual IR spectrum data, and the results demonstrate that can effectively suppress the Poisson noises and retain infrared spectral structure. The high-resolution IR spectrum can raise the recognition rate of facial expression classification task.

Spectrophotometric Redshifts in the Faint Infrared Grism Survey: Finding Overdensities of Faint Galaxies

Abstract We improve the accuracy of photometric redshifts by including low-resolution spectral data from the G102 grism on the Hubble Space Telescope (HST), which assists in redshift determination by further constraining the shape of the broadband spectral energy distribution (SED) and identifying spectral features. The photometry used in the redshift fits includes near-infrared photometry from FIGS+CANDELS, as well as optical data from ground-based surveys and HST ACS, and mid-IR data from Spitzer. We calculated the redshifts through the comparison of measured photometry with template galaxy models, using the EAZY photometric redshift code. For objects with F105W < 26.5 AB mag with a redshift range of 0 < z < 6, we find a typical error of Δz = 0.03 ∗ (1 + z) for the purely photometric redshifts; with the addition of FIGS spectra, these become Δz = 0.02 ∗ (1 + z), an improvement of 50%. Addition of grism data also reduces the outlier rate from 8% to 7% across all fields. With the more accurate spectrophotometric redshifts (SPZs), we searched the FIGS fields for galaxy overdensities. We identified 24 overdensities across the four fields. The strongest overdensity, matching a spectroscopically identified cluster at z = 0.85, has 28 potential member galaxies, of which eight have previous spectroscopic confirmation, and features a corresponding X-ray signal. Another corresponding to a cluster at z = 1.84 has 22 members, 18 of which are spectroscopically confirmed. Additionally, we find four overdensities that are detected at an equal or higher significance in at least one metric to the two confirmed clusters.

RESOLVED NEAR-INFRARED SPECTROSCOPY OF WISE J104915.57–531906.1AB: A FLUX-REVERSAL BINARY AT THE L DWARF/T DWARF TRANSITION

We report resolved near-infrared spectroscopy and photometry of the recently identified brown dwarf binary WISE J104915.57-531906.1AB, located 2.02+/-0.15 pc from the Sun. Low-resolution spectral data from Magellan/FIRE and IRTF/SpeX reveal strong H2O and CO absorption features in the spectra of both components, with the secondary also exhibiting weak CH4 absorption at 1.6 micron and 2.2 micron. Spectral indices and comparison to low-resolution spectral standards indicate component types of L7.5 and T0.5, the former consistent with the optical classification of the primary. Relative photometry reveals a flux reversal between the J- and K-bands, with the T dwarf component being brighter in the 0.95--1.3 micron range. As with other L/T transition binaries, this reversal likely reflects significant depletion of condensate opacity across the transition, a behavior that may be enhanced in WISE J1049-5319AB if the unusual red color of its L dwarf component is indicative of thick clouds. On the other hand, differing cloud properties may have modified the evolutionary paths of these two components, and we propose a scenario in which the cooler secondary could be the more massive of the two components. Fortunately, the proximity, brightness and small separation (3.12+/-0.25 AU) of this system make it amenable to astrometric and radial velocity orbit measurement during its estimated 25 yr orbit, providing a rare opportunity for the direct determination of individual brown dwarf masses and a unique benchmark for studying cloud evolution across the L dwarf/T dwarf transition.

Class-based spectral reconstruction based on unmixing of low-resolution spectral information

This paper proposes a class-based spectral estimation method for high-resolution red, green, and blue (RGB) images and corresponding low-resolution spectral data. Each spectrum in the low-resolution data is assumed to be a mixture of spectra of different classes. Then, the spectral estimation matrix for every class is derived using a regression approach, in which the clustering results of the high-resolution RGB image are used to incorporate spectral unmixing. Experiments confirm reduced normalized root mean squared error for the spectral images if the number of classes in the clustering is appropriately selected. In addition, the experimental results show that the spectra are accurately reconstructed even when they are observed as mixed spectra in the low-resolution data.

INFRARED SPECTROGRAPH CHARACTERIZATION OF A DEBRIS DISK AROUND AN M-TYPE STAR IN NGC 2547

We present 5 to 15 micron Spitzer Infrared Spectrograph (IRS) low resolution spectral data of a candidate debris disk around an M4.5 star identified as a likely member of the ~40 Myr old cluster NGC2547. The IRS spectrum shows a silicate emission feature, indicating the presence of warm, small, (sub)micron-sized dust grains in the disk. Of the fifteen previously known candidate debris disks around M-type stars, the one we discuss in this paper is the first to have an observed mid-infrared spectrum and is also the first to have measured silicate emission. We combined the IRS data with ancillary data (optical, JHKs, and Spitzer InfraRed Array Camera and 24 micron data) to build the spectral energy distribution (SED) of the source. Monte Carlo radiation transfer modeling of the SED characterized the dust disk as being very flat (h100=2AU) and extending inward within at least 0.13AU of the central star. Our analysis shows that the disk is collisionally dominated and is likely a debris disk.

Far Ultraviolet Spectroscopic Explorer and Hopkins Ultraviolet Telescope Observations of Radiative Shocks in the Cygnus Loop

We report a combination of high and low spectral resolution far-ultraviolet spectral data for several groupings of bright radiative shock filaments in the Cygnus Loop supernova remnant. The high-resolution spectra were obtained with the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite and cover the 905-1187 A spectral region at 0.1-0.3 A resolution, depending on observing aperture. The low-resolution data were obtained with the Hopkins Ultraviolet Telescope (HUT) and cover the 850-1850 A spectral region at ~3 A resolution. These data sets complement each other, with the HUT data providing the broader context of a wider range of emission lines and the FUSE data resolving line profiles from nearby airglow emissions and allowing detailed line profiles to be studied. Relative line intensities and line profiles change on a wide variety of spatial scales. O VI λλ1032, 1038 emission is much more generally distributed than the optical filaments. The FUSE data provide direct insight into the effects and variability of self-absorption in the strong resonance lines of O VI and C III λ977. Variability of the central reversals in O VI with position indicate a patchy O VI distribution, with self-absorption occurring locally within the remnant. Self-absorption in C III could be due to the interstellar medium, the local regions of the remnant, or a combination. We also find evidence for overlying molecular hydrogen absorption effects on some lines and suggest an interstellar (foreground) origin. It is likely that these effects have had significant impacts on many previous investigations that based their results on the interpretation of low-resolution spectral data where these effects could not be seen.

Application of robust fitting analysis techniques to low-resolution spectral data

A recently developed spectral analysis methodology, RobWin, is applied to low-resolution spectra from room-temperature semiconductor instrumentation to get a first look at its ability to identify the presence of nuclides in these spectra. The method, which builds upon non-linear robust fitting techniques from RobFit spectral analysis software, emphasizes adding structure gradually to the entire spectrum background shape function after accounting for re-optimized combinations of full-spectrum photopeak functions for a user-defined set of nuclides at each iteration. This feature makes RobWin well suited for the identification of weak-strength nuclides in high-background environments. The analysis approach emphasizes modeling the continuum for the entire spectrum as a single, continuous curve composed of cubic splines with optimized knot locations and coefficients. Peak shapes can be derived from actual data, a feature particularly useful with room temperature semiconductor materials. In its peak-search mode, RobWin can choose the best match from up to 10 different peak shapes for each unidentified peak. The data were collected with CZT-based detectors and were provided by the IAEA so that an initial look at the use of the RobWin methodology for analysis of room-temperature semiconductor spectra could be performed. The analysis methodology is briefly described and initial results are presented.

Fourier transform Raman assignment of guaiacyl and syringyl marker bands for lignin determination

A near infrared fourier transform Raman (NIR-FTR) spectroscopic technique was utilized to characterize lignin in wood. The Raman bands for CC stretching derived from 4-hydroxy-3-methoxyphenyl (guaiacyl) nuclei and from 3,5-dimethoxy-4-hydroxyphenyl (syringyl) nuclei exist independently. The NIR-FTR analysis of a series of lignin model compounds indicated that a syringyl band was shifted to a lower frequency compared to a guaiacyl band. This shift was also observed in chemically synthesized lignin (DHP). Syringyl DHP, in which all the aromatic nuclei consist of syringyl type, exhibited a CC stretching band at 1594 cm −1, while guaiacyl DHP exhibited the band at 1599 cm −1. These bands were designated as syringyl and guaiacyl marker bands, respectively. Chemical and physical treatment of hardwood and softwood exhibited different characteristics. One of the reasons is the chemical structure of lignin. Softwood mainly contains only guaiacyl lignin, while hardwood contains both guaiacyl and syringyl lignin, and the syringyl/guaiacyl ( S G ) ratio varies among species. Under high-resolution conditions (1 cm −1), the NIR-FTR spectra of 10 hardwoods (wood meal samples) revealed that both syringyl and guaiacyl marker bands existed. On the other hand, the spectra of softwoods contained only a guaiacyl marker bands existed. On the other hand, the spectra of softwoods contained only a guaiacyl marker band. The S G ratio in hardwood calculated from the peak area intensity ratio of two marker bands shows a linear relationship with the S G ratio obtained from conventional nitrobenzene oxidation analysis with the correlation factor>0.96. Furthermore, if peak component separation analysis was combined, low-resolution spectral data gave a similar S G ratio. Either syringyl of guaiacyl marker bands can be assigned in the NIR-FTR spectra of wood blocks (saw-cut surface). This spectral technique may provide an easy-handling and non-destructive analytical method for lignin determination.

Observations of the Galactic Plane by the Zodiacal Infrared Project

The two rocket flights of the Zodiacal Infrared Project (ZIP), flown 18 August 1980 and 31 July 1981, were intended to provide data on the near-infrared thermal emission of the interplanetary dust cloud over a broad range of ecliptic coordinates (latitudes -60 to +85 degrees, solar elongation angles 22 to 90 degrees and 140 to 180 degrees). In addition, their multiple crossings of the Galactic plane provided low resolution spectral data (delta lambda/lambda ranging from 1. to 0.1, for effective wavelengths from 3 to 30 microns) for most of the first quadrant (longitudes 30 to 100 degrees). Examples are displayed. Having made a thorough reanalysis of the calibration of the ZIP database, researchers present the salient features of the Galactic plane as observed by ZIP. The binned, in-plane data, corrected for zodiacal emission, generally show an exponential decrease with increasing longitude. The fitted exponential scale-length is 0.038/degree, and can be inverted to derive a radial density profile. Channel ratios are converted to temperatures by using model spectra in which thermal emitters with emissivity approx. 1/lambda are convolved with the filter responses. The results for channels 5 (11 microns) and 12 (21 microns) are shown, along with similarly derived temperatures from Infrared Astronomy Satellite (IRAS) 12 microns and 25 microns data. The ZIP data show little variation with longitude, consistent with IRAS results. A narrow spectral feature at 13 microns appears consistently in data for the plane (uncorrected for zodiacal emission). However, this is strongly contaminated by calibration problems for channel 8. Researchers suggest that residual emission at 13 microns arises from the (NeII) line at 12.8 microns.

Redshifts of southern radio sources. VII

Redshifts and low-resolution spectral data are presented for 47 objects, most of which are QSOs identified with flat-spectrum radio sources from the Parkes 2.7 GHz survey. These data were taken with the 3.9 m Anglo-Australian Telescope using both the IPCS and FORS spectrographs. The total spectral coverage is 3200-9500 A. Three objects are optical counterparts identified with IRAS sources.