Multiband Imaging Research Articles

HOLISMOKES

While supervised neural networks have become state of the art for identifying the rare strong gravitational lenses from large imaging data sets, their selection remains significantly affected by the large number and diversity of non-lens contaminants. This work evaluates and compares systematically the performance of neural networks in order to move towards a rapid selection of galaxy-scale strong lenses with minimal human input in the era of deep, wide-scale surveys. We used multiband images from PDR2 of the Hyper-Suprime Cam (HSC) Wide survey to build test sets mimicking an actual classification experiment, with 189 securely-identified strong lenses from the literature over the HSC footprint and 70 910 non-lens galaxies in COSMOS covering representative lens-like morphologies. Multiple networks were trained on different sets of realistic strong-lens simulations and non-lens galaxies, with various architectures and data preprocessing, mainly using the deepest gri-bands. Most networks reached excellent area under the Receiver Operating Characteristic (ROC) curves on the test set of 71 099 objects, and we determined the ingredients to optimize the true positive rate for a total number of false positives equal to zero or 10 (TPR0 and TPR10). The overall performances strongly depend on the construction of the ground-truth training data and they typically, but not systematically, improve using our baseline residual network architecture presented in Paper VI (Cañameras et al., A&A, 653, L6). TPR0 tends to be higher for ResNets (≃ 10–40%) compared to AlexNet-like networks or G-CNNs. Improvements are found when (1) applying random shifts to the image centroids, (2) using square-root scaled images to enhance faint arcs, (3) adding z-band to the otherwise used gri-bands, or (4) using random viewpoints of the original images. In contrast, we find no improvement when adding g – αi difference images (where α is a tuned constant) to subtract emission from the central galaxy. The most significant gain is obtained with committees of networks trained on different data sets, with a moderate overlap between populations of false positives. Nearly-perfect invariance to image quality can be achieved by using realistic PSF models in our lens simulation pipeline, and by training networks either with large number of bands, or jointly with the PSF and science frames. Overall, we show the possibility to reach a TPR0 as high as 60% for the test sets under consideration, which opens promising perspectives for pure selection of strong lenses without human input using the Rubin Observatory and other forthcoming ground-based surveys.

Spectroscopic and Photometric Confirmation of 3 Globular and 14 Intermediate-age Clusters in the Irr II Galaxy NGC 3077

We present the results from spectroscopic and photometric analysis of 17 globular cluster (GC) candidates in the Irr II galaxy NGC 3077. The GC candidates were selected on the Hubble Space Telescope images and were cleaned of foreground Galatic stars using the GAIA parameters. We carried out aperture photometry using the multiband archival images from the Sloan Digital Sky Survey, Two Micron All Sky Survey of all candidates, and low resolution (R = 1000) spectroscopic observations of 12 GC candidates and three suspected foreground stars using the Optical System for Imaging and Low-Intermediate-Resolution Integrated Spectroscopy/Multi-Object Spectra mode at the Gran Telescopio Canarias. Age, metallicity, and extinction values were determined using both spectroscopic and photometric data, independently. We find three of the 17 candidates are old (age > 10 Gyr), metal-poor ([Fe/H] < −1.0 dex), and massive (mass > 105 M ⊙) GCs with characteristics similar to the classical GCs in the Milky Way. The rest are intermediate-age clusters (IACs) with typical ages of 3–4 Gyr and in general metal-rich clusters. The radial velocities of both populations are within 100 km s−1 of the recessional velocity of the host galaxy. A relatively large population of IACs and low value of GC specific frequency (S N = 0.7) suggest that the preinteraction galaxy was actively forming stars and star clusters, and is unlikely to be a dwarf elliptical as suggested in some previous works.

SMILES Initial Data Release: Unveiling the Obscured Universe with MIRI Multiband Imaging

The James Webb Space Telescope is revolutionizing our view of the Universe through unprecedented sensitivity and resolution in the infrared, with some of the largest gains realized at its longest wavelengths. We present the Systematic Mid-infrared Instrument (MIRI) Legacy Extragalactic Survey (SMILES), an eight-band MIRI survey with Near-Infrared Spectrograph spectroscopic follow-up in the GOODS-S/HUDF region. SMILES takes full advantage of MIRI’s continuous coverage from 5.6 to 25.5 μm over an ∼34 arcmin2 area to greatly expand our understanding of the obscured Universe up to cosmic noon and beyond. This work, together with a companion paper by G. Rieke et al., covers the SMILES science drivers and technical design, early results with SMILES, data reduction, photometric catalog creation, and the first data release. As part of the discussion on early results, we additionally present a high-level science demonstration on how MIRI’s wavelength coverage and resolution will advance our understanding of cosmic dust using the full range of polycyclic aromatic hydrocarbon emission features from 3.3 to 18 μm. Using custom background subtraction, we produce robust reductions of the MIRI imaging that maximize the depths reached with our modest exposure times (∼0.6−2.2 ks per filter). Included in our initial data release are (1) eight MIRI imaging mosaics reaching depths of 0.2−18 μJy (5σ) and (2) a 5−25.5 μm photometric catalog with over 3000 sources. Building upon the rich legacy of extensive photometric and spectroscopy coverage of GOODS-S/HUDF from the X-ray to the radio, SMILES greatly expands our investigative power in understanding the obscured Universe.

Gas thermodynamics meets galaxy kinematics: Joint mass measurements for eROSITA galaxy clusters

The mass of galaxy clusters is a critical quantity for probing cluster cosmology and testing theories of gravity, but its measurement could be biased, given that assumptions are inevitable in order to make use of any approach. In this paper, we employ and compare two mass proxies for galaxy clusters: thermodynamics of the intracluster medium and kinematics of member galaxies. We selected 22 galaxy clusters from the cluster catalog in the first SRG/eROSITA All-Sky Survey (eRASS1) that have sufficient optical and near-infrared observations. We generated multiband images in the energy range of (0.3, 7) keV for each cluster, and derived their temperature profiles, gas mass profiles, and hydrostatic mass profiles using a parametric approach that does not assume dark matter halo models. With spectroscopically confirmed member galaxies collected from multiple surveys, we numerically solved the spherical Jeans equation for their dynamical mass profiles. Our results quantify the correlation between dynamical mass and the line-of-sight velocity dispersion, $ dyn los ^2r_ proj /G) - (3.87 with a root mean square (rms) scatter of 0.14 dex. We find that the two mass proxies lead to roughly the same total mass, with no observed systematic bias. As such, the $ tension is not specific to hydrostatic mass or weak lensing shears, but also appears with galaxy kinematics. Interestingly, the hydrostatic-to-dynamical mass ratios decrease slightly toward large radii, which could possibly be evidence for accreting galaxies in the outskirts. We also compared our hydrostatic masses with the latest weak lensing masses inferred with scaling relations. The comparison shows that the weak lensing mass is significantly higher than our hydrostatic mass by sim 110&lt;!PCT!&gt;. This might explain the significantly larger value of $ from the latest measurement using eRASS1 clusters than almost all previous estimates in the literature. Finally, we tested the radial acceleration relation established in disk galaxies. We confirm the missing baryon problem in the inner region of galaxy clusters using three independent mass proxies for the first time. As ongoing and planned surveys are providing deeper X-ray observations and more galaxy spectra for cluster members, we expect to extend the study to cluster outskirts in the near future.

JWST lensed quasar dark matter survey – II. Strongest gravitational lensing limit on the dark matter free streaming length to date

ABSTRACT This is the second in a series of papers in which we use JWST Mid Infrared Instrument multiband imaging to measure the warm dust emission in a sample of 31 multiply imaged quasars, to be used as a probe of the particle nature of dark matter. We present measurements of the relative magnifications of the strongly lensed warm dust emission in a sample of nine systems. The warm dust region is compact and sensitive to perturbations by populations of haloes down to masses $\sim 10^6$ M$_{\odot }$. Using these warm dust flux-ratio measurements in combination with five previous narrow-line flux-ratio measurements, we constrain the halo mass function. In our model, we allow for complex deflector macromodels with flexible third- and fourth-order multipole deviations from ellipticity, and we introduce an improved model of the tidal evolution of subhaloes. We constrain a WDM model and find an upper limit on the half-mode mass of $10^{7.6}\, {\rm M}_\odot$ at posterior odds of 10:1. This corresponds to a lower limit on a thermally produced dark matter particle mass of 6.1 keV. This is the strongest gravitational lensing constraint to date, and comparable to those from independent probes such as the Ly $\alpha$ forest and Milky Way satellite galaxies.

Medium Bands, Mega Science: A JWST/NIRCam Medium-band Imaging Survey of A2744

In this paper, we describe the “Medium Bands, Mega Science” JWST Cycle 2 survey (JWST-GO-4111) and demonstrate the power of these data to reveal both the spatially integrated and spatially resolved properties of galaxies from the local Universe to the era of cosmic dawn. Executed in 2023 November, MegaScience obtained ∼30 arcmin2 of deep multiband NIRCam imaging centered on the z ∼ 0.3 A2744 cluster, including 11 medium-band filters and the two shortest-wavelength broadband filters, F070W and F090W. Together, MegaScience and the UNCOVER Cycle 1 treasury program provide a complete set of deep (∼28–30 magAB) images in all NIRCam medium- and broadband filters. This unique data set allows us to precisely constrain photometric redshifts, map stellar populations and dust attenuation for large samples of distant galaxies, and examine the connection between galaxy structures and formation histories. MegaScience also includes ∼17 arcmin2 of NIRISS parallel imaging in two broadband and four medium-band filters from 0.9 to 4.8 μm, expanding the footprint where robust spectral energy distribution (SED) fitting is possible. We provide example SEDs and multiband cutouts at a variety of redshifts, and use a catalog of JWST spectroscopic redshifts to show that MegaScience improves both the scatter and catastrophic outlier rate of photometric redshifts by factors of 2–3. Additionally, we demonstrate the spatially resolved science enabled by MegaScience by presenting maps of the [O iii] line emission and continuum emission in three spectroscopically confirmed z > 6 galaxies. We show that line emission in reionization-era galaxies can be clumpy, extended, and spatially offset from continuum emission, implying that galaxy assembly histories are complex even at these early epochs. We publicly release fully reduced mosaics and photometric catalogs for both the NIRCam primary and NIRISS parallel fields (jwst-uncover.github.io/megascience).

Simultaneous X-Ray and Optical Polarization Observations of the Blazar Mrk 421

We present near-simultaneous X-ray and optical polarization measurements in the high synchrotron peaked (HSP) blazar Mrk 421. The X-ray polarimetric observations were carried out using Imaging X-ray Polarimetry Explorer (IXPE) on 2023 December 6. During IXPE observations, we also carried out optical polarimetric observations using 104 cm Sampurnanand telescope at Nainital and multiband optical imaging observations using 2 m Himalayan Chandra Telescope at Hanle. From model-independent analysis of IXPE data, we detected X-ray polarization with degree of polarization (ΠX) of 8.5% ± 0.5% and an electric vector position angle (ΨX) of 10.°6 ± 1.°7 in the 2−8 keV band. From optical polarimetry on 2023 December 6, in B, V, and R bands, we found values of Π B = 4.27% ± 0.32%, Π V = 3.57% ± 0.31%, and Π R = 3.13% ± 0.25%. The value of Π B is greater than that observed at longer optical wavelengths, with the degree of polarization suggesting an energy-dependent trend, gradually decreasing from higher to lower energies. This is consistent with that seen in other HSP blazars and favors a stratified emission region encompassing a shock front. The emission happening in the vicinity of the shock front will be more polarized due to the ordered magnetic field resulting from shock compression. The X-ray emission, involving high-energy electrons, originates closer to the shock front than the optical emission. The difference in the spatial extension could plausibly account for the observed variation in polarization between X-ray and optical wavelengths. This hypothesis is further supported by the broadband spectral energy distribution modeling of the X-ray and optical data.

CLAP

Obtaining well-calibrated photometric redshift probability densities for galaxies without a spectroscopic measurement remains a challenge. Deep learning discriminative models, typically fed with multi-band galaxy images, can produce outputs that mimic probability densities and achieve state-of-the-art accuracy. However, several previous studies have found that such models may be affected by miscalibration, an issue that would result in discrepancies between the model outputs and the actual distributions of true redshifts. Our work develops a novel method called the Contrastive Learning and Adaptive KNN for Photometric Redshift (CLAP) that resolves this issue. It leverages supervised contrastive learning (SCL) and k-nearest neighbours (KNN) to construct and calibrate raw probability density estimates, and implements a refitting procedure to resume end-to-end discriminative models ready to produce final estimates for large-scale imaging data, bypassing the intensive computation required for KNN. The harmonic mean is adopted to combine an ensemble of estimates from multiple realisations for improving accuracy. Our experiments demonstrate that CLAP takes advantage of both deep learning and KNN, outperforming benchmark methods on the calibration of probability density estimates and retaining high accuracy and computational efficiency. With reference to CLAP, a deeper investigation on miscalibration for conventional deep learning is presented. We point out that miscalibration is particularly sensitive to the method-induced excessive correlations among data instances in addition to the unaccounted-for epistemic uncertainties. Reducing the uncertainties may not guarantee the removal of miscalibration due to the presence of such excessive correlations, yet this is a problem for conventional methods rather than CLAP. These discussions underscore the robustness of CLAP for obtaining photometric redshift probability densities required by astrophysical and cosmological applications. This is the first paper in our series on CLAP.

VEGAS-SSS: Tracing globular cluster populations in the interacting NGC 3640 galaxy group

Context. Globular clusters (GCs) are among the oldest stellar systems in the universe. As such, GC populations are valuable fossil tracers of galaxy formation and interaction history. This paper is part of the VEGAS-SSS series, which focuses on studying the properties of small stellar systems (SSSs) in and around bright galaxies. Aims. We used the multiband wide-field images obtained with the VST to study the properties of the GC population in an interacting pair of galaxies. Methods. We derived ugri photometry over 1.5 × 1.5 sq. degrees centered on the galaxy group composed of two elliptical galaxies: NGC 3640 and its fainter companion NGC 3641. We studied the GC system properties from both the ugri and gri matched catalogs. GC candidates were identified based on a combination of photometric properties (colors and magnitudes) and morphometric criteria (concentration index, elongation, FWHM, etc.), using sources with well-defined classifications from spectroscopic or imaging data available in the literature and numerical simulations as references. The selection criteria were also applied to empty fields to determine a statistical background correction for the number of identified GC candidates. Results. The 2D density maps of GCs appear to align with the diffuse light patches resulting from the merging events of the galaxies. The highest density peak of GCs is observed to be on NGC 3641 rather than NGC 3640, despite the latter being the more massive galaxy. The azimuthal averaged radial density profiles in both galaxies reveal that the GC population extends beyond the galaxy light profile and this indicates the likely presence of an intra-group GC component. A color bimodality in (u − r) and (g − i) is observed for NGC 3641, whereas NGC 3640 shows a broad unimodal distribution. Analysis of the GC luminosity function indicates that both galaxies are roughly located at the same distance (∼27 Mpc). We provide an estimate of the total number of GCs, and determine the specific frequency for NGC 3640, SN = 2.0 ± 0.6, which aligns with expectations, while for NGC 3641 we find a large SN = 4.5 ± 1.6.

Visible-light High-contrast Imaging and Polarimetry with SCExAO/VAMPIRES

We present significant upgrades to the Visible Aperture-Masking Polarimetric Imager/Interferometer for Resolving Exoplanetary Signatures (VAMPIRES) instrument, a visible-light (600–800 nm) high-contrast imaging polarimeter integrated within SCExAO on the Subaru telescope. Key enhancements include new qCMOS detectors, coronagraphs, polarization optics, and a multiband imaging mode, improving sensitivity, resolution, and efficiency. These upgrades position VAMPIRES as a powerful tool for studying sub-stellar companions, accreting protoplanets, circumstellar disks, stellar jets, stellar mass-loss shells, and solar system objects. The instrument achieves angular resolutions from 17 to 21 mas and Strehl ratios up to 60%, with 5σ contrast limits of 10−4 at 0.″1 to 10−6 beyond 0.″5. We demonstrate these capabilities through spectro-polarimetric coronagraphic imaging of the HD 169142 circumstellar disk, ADI+SDI imaging of the sub-stellar companion HD 1160B, narrowband Hα imaging of the R Aqr emission nebula, and spectro-polarimetric imaging of Neptune.

Survey of gravitationally lensed objects in HSC imaging (SuGOHI) – X. Strong lens finding in the HSC-SSP using convolutional neural networks

ABSTRACT We apply a novel model based on convolutional neural networks (CNN) to identify gravitationally lensed galaxies in multiband imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. The trained CNN assigns a score from 0 to 1, with 1 representing lenses and 0 representing non-lenses. Initially, the CNN selects a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1522 cutouts after removing definite non-lenses for further visual inspection. We discover 43 grade A (definite) and 269 grade B (probable) strong lens candidates, of which 97 are completely new. In addition, we also discover 880 grade C (possible) lens candidates, 289 of which are known systems in the literature. We identify 143 candidates from the known systems of grade C that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems are not included in the training, a sample of 32 SuGOHI-c (i.e. group/cluster-scale systems) lens candidates is retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling.

A Cippus from Turris Libisonis: Evidence for the Use of Local Materials in Roman Painting on Stone in Northern Sardinia

The ancient Roman town of Turris Libisonis was located on the northern coast of Sardinia and was known in the past as an important naval port. Located in the Gulf of Asinara, it was a Roman colony from the 1st century BCE and became one of the richest towns on the island. Among the archaeological finds in the area, the cippus exhibited in the Antiquarium Turritano is of great interest for its well-preserved traces of polychromy. The artefact dates back to the early Imperial Age and could have had a funerary or votive function. The artefact was first examined using a portable and non-invasive protocol involving multi-band imaging (MBI), portable X-ray fluorescence (p-XRF), portable FT-IR in external reflectance mode (ER FT-IR) and Raman spectroscopy. After this initial examination, a few microfragments were collected and investigated by optical microscopy (OM), X-ray powder diffraction (XRPD), Fourier-transform infrared spectroscopy in ATR mode (ATR FT-IR) and micro-ATR mode (μATR FT-IR) and Scanning Electron Microscopy/Energy Dispersive Spectroscopy (SEM-EDS) to improve our knowledge and characterize the materials and to determine their provenience. The results contribute to a better understanding of the provenance of materials and shed light on pigments on stone and their use outside the Italian peninsula and, in particular, Roman Sardinia.

Exploring faint white dwarfs and the luminosity function with Subaru HSC and SDSS in Stripe 82

Abstract We present 5,080 white dwarf (WD) candidates selected from stars matching between the multi-band imaging datasets of the Subaru Hyper Suprime-Cam (HSC) Survey and the Sloan Digital Sky Survey (SDSS) in the Stripe82 region covering about 165 deg2. We select WD candidates from the “reduced proper motion” diagram by combining the apparent magnitude in the range i = 19 – 24 and the proper motion measured from the datasets among a baseline of ∼ 14 years. We refine the WD candidates by fitting blackbody and template WD atmosphere models to HSC photometries for each candidate, enabling the estimation of distance and tangential velocity (vt). The deep HSC data allow us to identify low-temperature (&amp;lt;4000 K) and faint WD candidates down to absolute magnitude, Mbol ≃ 17. We evaluate the selection function of our WD candidates using a mock catalogue of spatial and kinematic distributions of WDs in the (thin and thick) disc and halo regions based on a Galactic model. We construct samples of disc and halo WD candidates by selecting WDs with tangential velocity, 40 &amp;lt; vt/[km s−1] &amp;lt; 80 and 200 &amp;lt; vt/[km s−1] &amp;lt; 500, respectively. The total number densities of the disc and halo WDs are (9.33 ± 0.89) × 10−3 pc−3 and (6.34 ± 2.90) × 10−4 pc−3. Our luminosity functions (LF) extend down to fainter absolute magnitudes compared with previous work. The faint WDs could represent the oldest generation of building blocks over the past ∼10 billion years of the assembly history of our Milky Way.

Study on canopy extraction method for narrowband spectral images based on superpixel color gradation skewness distribution features

BackgroundCrop phenotype extraction devices based on multiband narrowband spectral images can effectively detect the physiological and biochemical parameters of crops, which plays a positive role in guiding the development of precision agriculture. Although the narrowband spectral image canopy extraction method is a fundamental algorithm for the development of crop phenotype extraction devices, developing a highly real-time and embedded integrated narrowband spectral image canopy extraction method remains challenging owing to the small difference between the narrowband spectral image canopy and background.MethodsThis study identified and validated the skewed distribution of leaf color gradation in narrowband spectral images. By introducing kurtosis and skewness feature parameters, a canopy extraction method based on a superpixel skewed color gradation distribution was proposed for narrowband spectral images. In addition, different types of parameter combinations were input to construct two classifier models, and the contribution of the skewed distribution feature parameters to the proposed canopy extraction method was evaluated to confirm the effectiveness of introducing skewed leaf color skewed distribution features.ResultsLeaf color gradient skewness verification was conducted on 4200 superpixels of different sizes, and 4190 superpixels conformed to the skewness distribution. The intersection over union (IoU) between the soil background and canopy of the expanded leaf color skewed distribution feature parameters was 90.41%, whereas that of the traditional Otsu segmentation algorithm was 77.95%. The canopy extraction method used in this study performed significantly better than the traditional threshold segmentation method, using the same training set, Y1 (without skewed parameters) and Y2 (with skewed parameters) Bayesian classifier models were constructed. After evaluating the segmentation effect of introducing skewed parameters, the average classification accuracies Acc_Y1 of the Y1 model and Acc_Y2 of the Y2 model were 72.02% and 91.76%, respectively, under the same test conditions. This indicates that introducing leaf color gradient skewed parameters can significantly improve the accuracy of Bayesian classifiers for narrowband spectral images of the canopy and soil background.ConclusionsThe introduction of kurtosis and skewness as leaf color skewness feature parameters can expand the expression of leaf color information in narrowband spectral images. The narrowband spectral image canopy extraction method based on superpixel color skewness distribution features can effectively segment the canopy and soil background in narrowband spectral images, thereby providing a new solution for crop canopy phenotype feature extraction.

A new census of dust and polycyclic aromatic hydrocarbons at z = 0.7–2 with JWST MIRI

Aims. This paper utilises the James Webb Space Telescope (JWST) Mid-Infrared Instrument (MIRI) to extend the observational studies of dust and polycyclic aromatic hydrocarbon (PAH) emission to a new mass and star formation rate (SFR) parameter space beyond our local Universe. The combination of fully sampled spectral energy distributions (SEDs) with multiple mid-infrared (mid-IR) bands and the unprecedented sensitivity of MIRI allows us to investigate dust obscuration and PAH behaviour from z = 0.7 up to z = 2 in typical main-sequence galaxies. Our focus is on constraining the evolution of PAH strength and the dust-obscured luminosity fraction before and during cosmic noon, the epoch of peak star formation activity in the Universe. Methods. In this study, we utilise MIRI multi-band imaging data from the SMILES survey (5 to 25 μm), complemented with NIRCam photometry from the JADES survey (1 to 5 μm), available HST photometry (0.4 to 0.9 μm), and spectroscopic redshifts from the FRESCO and JADES surveys in GOODS-S for 443 star-forming (without dominant active galactic nucleus (AGN)) galaxies at z = 0.7 − 2.0. This redshift range was chosen to ensure that the MIRI data cover mid-IR dust emission. Our methodology involved employing ultraviolet (UV) to IR energy balance SED fitting to robustly constrain the fraction of dust mass in PAHs and dust-obscured luminosity. Additionally, we inferred dust sizes from MIRI 15 μm imaging data, enhancing our understanding of the physical characteristics of dust within these galaxies. Results. We find a strong correlation between the fraction of dust in PAHs (PAH fraction, qPAH) with stellar mass. Moreover, the sub-sample with robust qPAH measurements (N = 216) shows a similar behaviour between qPAH and gas-phase metallicity to that at z ∼ 0, suggesting a universal relation: qPAH is constant (∼3.4%) above a metallicity of Z ∼ 0.5 Z⊙ and decreases to &lt; 1% at metallicities ≲0.3 Z⊙. This indicates that metallicity is a good indicator of the interstellar medium properties that affect the balance between the formation and destruction of PAHs. The lack of a redshift evolution from z ∼ 0 − 2 also implies that above Z ∼ 0.5 Z⊙ the PAH emission effectively traces obscured luminosity and the previous locally calibrated PAH-SFR calibrations remain applicable in this metallicity regime. We observe a strong correlation between the obscured UV luminosity fraction (ratio of obscured to total luminosity) and stellar mass. Above the stellar mass of M* &gt; 5 × 109 M⊙, on average, more than half of the emitted luminosity is obscured, while there exists a non-negligible population of lower-mass galaxies with &gt; 50% obscured fractions. At a fixed mass, the obscured fraction correlates with SFR surface density. This is a result of higher dust covering fractions in galaxies with more compact star-forming regions. Similarly, galaxies with high IRX (IR to UV luminosity) at a given mass or UV continuum slope (β) tend to have higher ΣSFR and shallower attenuation curves, owing to their higher effective dust optical depths and more compact star-forming regions.

The Impacts of Phenological Stages within the Annual Cycle on Mapping Forest Stock Volume Using Multi-Band Dual-Polarization SAR Images in Boreal Forests

SAR images with two polarizations show strong potential for mapping forest stock volume (FSV) combined with limited samples. However, accurately mapping FSV still presents challenges in selecting the optimal acquisition date to obtain the SAR images during specific phenological stages within the annual forest cycle (growth and dormant stages). To clarify the impacts of phenological stages within the annual cycle on FSV mapping, SAR images with various polarization models and bands (Sentinel-1(S), GaoFen-3(GF-3 (G)) and ALOS-2(A)) were acquired within the growth and dormant stages of an annual cycle in a boreal evergreen coniferous forest (Chinese pine) and a deciduous coniferous forest (Larch). Subsequently, single-band (G, S, and A) and multi-band combined alternative variable sets (A + G, A + S, S + G, and A + S + G) were extracted within the same stage, respectively. Finally, the forward selection approach was utilized in conjunction with four different models (MLR, KNN, RF, and SVR) to obtain the most suitable variable sets and generate FSV mapping. The results demonstrated a strong correlation between the intensity of backscattering coefficients and the phenological stages of the forest. Within the dormant stage, there was a significant decrease in the gaps of backscattering coefficients obtained from the same polarization compared to those within the growth stage. Furthermore, the results also revealed that more signals from inside the canopy could be detected during the dormant stage in both evergreen coniferous forests and deciduous coniferous forests. Subsequently, the accuracy in mapping FSV obtained from single-band SAR images within the dormant stage are slightly higher than that within the growth stage, and the accuracy was still significantly affected by both overestimation and underestimation. Moreover, the combined effects of different bands significantly improve the reliability of mapped FSV. The rRMSE values in four multi-band combinations ranged from 22.37% to 29.40% for Chinese pine forests and from 21.27% to 34.38% for Larch forests, and the optimal result was observed from combinations of A + S + G acquired within the dormant stage. It is confirmed that SAR signal and their sensitivity to FSV depends on the stages of forest annual growth cycle. In comparison to the growth period, dual-polarization SAR data acquired during the dormant stage is more suitable for estimating FSV in boreal forests.

The Pre-perihelion Evolution of the Activity of Comet C/2017 K2 (Pan-STARRS) during the Water Ice-line Crossover

Comets, relics from the early solar system, consist of dust and ice. The ice sublimates as comets approach the Sun, ejecting dust from their nuclei seen as activity. Different volatiles sublimate at different Sun–comet distances and eject dust of unique sizes, structures, and compositions. In this study, we present new polarimetric observations of Oort cloud comet C/2017 K2 (Pan-STARRS) in R- and I-filter domains before, during, and after its crossover of the water-ice sublimation regime at phase angles of 15.°9, 10.°5, and 20.°0, respectively. Combining multiband optical imaging data covering a wide range of heliocentric distances (∼14−2.3 au), we aim to characterize the pre-perihelion evolution of cometary activity as well as the properties of its coma dust. Two discontinuous brightening events were observed: at ∼6 au presumably associated with changes in CO-like supervolatile ice activity, and at ∼2.9 au when water ice took over. Particularly, the latter activation is accompanied by changes in coma morphology and color whose trends differ between the inner (∼103 km) and outer (∼104 km) parts of the coma. No polarimetric discontinuities on the comet were observed over the inner coma region, all epochs showing phase-angle and wavelength dependencies compatible with those of active comets observed in similar observing geometry. During this period, the underlying dust continuum overwhelmed Hα emission at around 656.3 nm, suggesting less water ice on the comet’s surface than expected. We discuss K2's coma environment by combining numerical simulations of light scattered by dust and place the observations within the context of the comet’s evolution.

Drought Quantification in Africa Using Remote Sensing, Gaussian Kernel, and Machine Learning

Effective drought management requires precise measurement, but this is challenging due to the variety of drought indices and indicators, each with unique methods and specific uses, and limited ground data availability. This study utilizes remote sensing data from 2001 to 2020 to compute drought indices categorized as meteorological, agricultural, and hydrological. A Gaussian kernel convolves these indices into a denoised, multi-band composite image. Further refinement with a Gaussian kernel enhances a single drought index from each category: Reconnaissance Drought Index (RDI), Soil Moisture Agricultural Drought Index (SMADI), and Streamflow Drought Index (SDI). The enhanced index, encompassing all bands, serves as a predictor for classification and regression tree (CART), support vector machine (SVM), and random forest (RF) machine learning models, further improving the three indices. CART demonstrated the highest accuracy and error minimization across all drought categories, with root mean square error (RMSE) and mean absolute error (MAE) values between 0 and 0.4. RF ranked second, while SVM, though less reliable, achieved values below 0.7. The results show persistent drought in the Sahel, North Africa, and southwestern Africa, with meteorological drought affecting 30% of Africa, agricultural drought affecting 22%, and hydrological drought affecting 21%.

A MULTI-ANALYTICAL INVESTIGATION OF AN IRANIAN LITHOGRAPHY BOOK FROM THE QAJAR PERIOD

The lithography books of Iran, despite their historical importance, have received relatively little attention. This study aims to comprehensively examine an Iranian lithography book from the Qajar period titled Hayat al-Qolub, to identify its materials. The paper pulp, sizing, inks and leather of the bookbinding were analyzed through various methods, including staining tests for identifying paper pulp, light microscopy, FTIR, Raman spectroscopy, Micro-spectrophotometry, multi-band imaging, SEM-EDS and LC-MS. The findings suggest that the book was made of rag paper composed of linen and cotton fibers, while animal glue and gypsum were used for paper sizing and filling, respectively. Carbon black was used as black printing ink and cochineal was used for red ink. The leather cover of the book was made of goat skin that was tanned with gallotannins and unhaired with lime. Evidence of the use of liming in the unhairing process was also observed in this leather. This research enhances our understanding of paper and bookmaking techniques of the Qajar period in Iran.

XLSSC 122 caught in the act of growing up

Context. How protoclusters evolved from sparse galaxy overdensities to mature galaxy clusters is still not well understood. In this context, detecting and characterizing the hot intracluster medium (ICM) at high redshifts (z ∼ 2) is key to understanding how the continuous accretion from the filamentary large-scale structure and the mergers along it impact the first phases of cluster formation. Aims. We study the dynamical state and morphology of the z = 1.98 galaxy cluster XLSSC 122 with high-resolution observations (≈5″) of the ICM through the Sunyaev–Zeldovich (SZ) effect. XLSSC 122 is the highest redshift optically confirmed galaxy cluster found in an unbiased, widefield survey. Methods. Via Bayesian forward modeling, we mapped the ICM on scales from the virial radius down to the core of the cluster. To constrain such a broad range of spatial scales, we employed a new technique that jointly forward-models parametric descriptions of the pressure distribution to interferometric ACA and ALMA observations and multiband imaging data from ACT. Results. We detect the SZ effect with 11σ significance in the ALMA+ACA observations and find a flattened inner pressure profile that is consistent with a noncool core classification with a significance of ≥3σ. In contrast to the previous works, we find better agreement between the SZ effect signal and the X-ray emission as well as the cluster member distribution. Further, XLSSC 122 exhibits an excess of SZ flux in the south of the cluster where no X-ray emission is detected. By reconstructing the interferometric observations and modeling in the uv-plane, we obtain a tentative detection of an infalling group or filamentary-like structure in the southeast that is believed to boost and heat up the ICM while the density of the gas is still low. In addition to characterizing the dynamical state of the cluster, we provide an improved SZ mass estimate M500,c = 1.66−0.20+0.23 × 1014 M⊙. Conclusions. Altogether, the observations indicate that we see XLSSC 122 in a dynamic phase of cluster formation while a large reservoir of gas is already thermalized.