Current and future surveys rely on machine learning classification to obtain large and complete samples of transients. Many of these algorithms are restricted by training samples that contain a limited number of spectroscopically confirmed events. Here, we present the first real-time application of Active Learning to optimise spectroscopic follow-up with the goal of improving training sets of early type Ia supernovae (SNe Ia) classifiers.

Using a photometric classifier for early SN Ia, we apply an Active Learning strategy for follow-up optimisation using the real-time FINK broker processing of the ZTF public stream. We perform follow-up observations at the ANU 2.3m telescope in Australia and obtain 92 spectroscopic classified events that are incorporated in our training set.

We show that our follow-up strategy yields a training set that, with 25% less spectra, improves classification metrics when compared to publicly reported spectra. Our strategy selects in average fainter events and, not only supernovae types, but also microlensing events and flaring stars which are usually not incorporated on training sets.

Our results confirm the effectiveness of active learning strategies to construct optimal training samples for astronomical classifiers. With the Rubin Observatory LSST soon online, we propose improvements to obtain earlier candidates and optimise follow-up. This work paves the way to the deployment of real-time AL follow-up strategies in the era of large surveys.

The parallel and synergistic developments of atomic resolution structural information, new spectroscopic methods, their underpinning formalism, and the application of sophisticated theoretical methods have led to a step function change in our understanding of photosynthetic light harvesting, the process by which photosynthetic organisms collect solar energy and supply it to their reaction centers to initiate the chemistry of photosynthesis. The new spectroscopic methods, in particular multidimensional spectroscopies, have enabled a transition from recording rates of processes to focusing on mechanism. We discuss two ultrafast spectroscopies – two-dimensional electronic spectroscopy and two-dimensional electronic-vibrational spectroscopy – and illustrate their development through the lens of photosynthetic light harvesting. Both spectroscopies provide enhanced spectral resolution and, in different ways, reveal pathways of energy flow and coherent oscillations which relate to the quantum mechanical mixing of, for example, electronic excitations (excitons) and nuclear motions. The new types of information present in these spectra provoked the application of sophisticated quantum dynamical theories to describe the temporal evolution of the spectra and provide new questions for experimental investigation. While multidimensional spectroscopies have applications in many other areas of science, we feel that the investigation of photosynthetic light harvesting has had the largest influence on the development of spectroscopic and theoretical methods for the study of quantum dynamics in biology, hence the focus of this review. We conclude with key questions for the next decade of this review.

The nature of the complexes in aqueous solutions of Cu(II) and Ni(II) with diethylenetriamine (dien) and tetraethylenepentamine tetren) is pH-dependent. At M(II):dien = 2 and M(II):tetren = 1, the main complexes are [M(dien H)2(H2O)2]4+ and [M(tetren H)(H2O)2]3+. In excess ligand (pH = 10.30), the majority species are [M(dien)2]2+ and [M(tetren)(H2O)]2+, and considerable amounts of monoprotonated amines are adsorbed. The surface of hectorite prefers the tetragonally distorted complexes in all cases studied. The complexes readily lose their axially coordinated water molecules to form planar complexes on the interlamellar surface. The planar Ni(II)-complexes are diamagnetic, showing that the surface is a very weak axial ligand. The divalent complexes [M(dien)2]2+ and [M(tetren)(H2O]2+ can also be partially transformed to the corresponding planar forms on the surface, especially in the case of [Cu(dien)2]2+. The driving forces are thought to be the acid nature of the clay-adsorbed water and the gain in crystal field stabilization energy of the transition metal ions.

Tight focusing with very small f-numbers is necessary to achieve the highest at-focus irradiances. However, tight focusing imposes strong demands on precise target positioning in-focus to achieve the highest on-target irradiance. We describe several near-infrared, visible, ultraviolet and soft and hard X-ray diagnostics employed in a ∼1022 W/cm2 laser–plasma experiment. We used nearly 10 J total energy femtosecond laser pulses focused into an approximately 1.3-μm focal spot on 5–20 μm thick stainless-steel targets. We discuss the applicability of these diagnostics to determine the best in-focus target position with approximately 5 μm accuracy (i.e., around half of the short Rayleigh length) and show that several diagnostics (in particular, 3$\omega$ reflection and on-axis hard X-rays) can ensure this accuracy. We demonstrated target positioning within several micrometers from the focus, ensuring over 80% of the ideal peak laser intensity on-target. Our approach is relatively fast (it requires 10–20 laser shots) and does not rely on the coincidence of low-power and high-power focal planes.

Interlayer cations and moisture content greatly influence the molecular vibrations of H2O in montmorillonite as shown through reflectance spectroscopy in the infrared. The absorptions due to H2O have been studied in montmorillonites exchanged with H, Na, Ca, Mg and Fe3+ interlayer cations under variable moisture environments. Band assignments have been made for absorptions in the 3 µm region due to structural OH vibrations, symmetric and asymmetric H2O stretching vibrations and the H2O bending overtone. Changes in the energies of the absorptions due to H2O stretching vibrations were observed as the samples were dehydrated by reducing the atmospheric pressure. Absorptions near 3620 cm−1 and 3550 cm−1 have been assigned to water bound directly to cations (inner sphere) and surface-bonded H2O and absorptions near 3450 cm−1 and 3350 cm−1 have been assigned to additional adsorbed water molecules. Band assignments have been made for combination bands in the near-infrared as well. Absorptions near 1.41 μm and 1.91 μm are assigned to bound H2O combination bands, while the shoulders near 1.46μm and 1.97 μm are assigned to combinations of additional H2O molecules adsorbed in the interlayer regions and along grain surfaces.

Using 19F magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy, we show that most of the fluoride present in the KGa-lb reference kaolinite from Washington County, Georgia, occurs as a surface-adsorbed species bonded to Al. This surface fluoride can be removed from the <2 µm fraction by acid wash, but is largely retained in the coarse fraction. Correlation of integrated 19F NMR peak intensities with fluoride sorption experiments indicates a bulk F content of ∼144 ppm for KGa-1b, of which ∼30% substitutes for hydroxyl sites in the mineral structure and the remaining 70% occurs adsorbed on particle surfaces, corresponding to an edge surface fluoride density of ∼0.7 F− nm−2. 19F{27Al} TRAPDOR (TRAnsfer of Populations in DOuble Resonance) NMR data for the original kaolinite and for products of F− sorption experiments at pH 4 show that all of the observed 19F signals arise from fluoride bonded to Al atoms. Furthermore, bridging Al-F-Al sites and terminal Al-F give distinctly different TRAPDOR fractions allowing assignment of resolved peaks based on the number of Al in the first coordination sphere. This result was confirmed for fluoride adsorbed to the surface of gibbsite from aqueous suspension. No evidence was found for Si-F-type environments on the kaolinite surfaces.

Reflectance spectroscopy is a rapid, non-destructive technique capable of characterizing mineral and organic components within geologic materials at spatial scales that range from μm to km. The degree to which reflectance spectra can be used to provide quantitative information about organic compounds remains poorly understood, particularly for rocks with low organic content that are common in the Earth’s ancient rock record and that may be present on other planetary bodies, such as Mars. In the present study, reflectance spectra (0.35–25 μm) were acquired for a suite of Proterozoic shales and the kerogen was isolated to assess how spectral properties of aliphatic and aromatic C-H absorption bands can be used to predict organic matter abundance (total organic content, TOC, and H/C ratio). A number of spectral parameters were evaluated for organic absorption bands observed in the 3–4 μm wavelength region for comparison with independently measured TOC and H/C values. Ratios of the strengths of aliphatic to aromatic absorption bands were directly correlated to H/C values, but the reflectance spectra for pure kerogens with H/C < 0.2 lacked clear evidence for C-H absorption bands in this spectral region. Organic absorption bands are routinely observed for bulk rock powders with >1 wt.% TOC, but the detection limits of reflectance spectra for TOC may be <1 wt.% or as high as 10 wt.%. Organic detection limits for reflectance spectra are, thus, controlled by both TOC and H/C values, but these parameters can be predicted for clay-rich, kerogen-dominated samples for a range of values that are relevant to drill cores, outcrops, meteorites, and planetary surfaces.

The Al-clay-rich rock units at Mawrth Vallis, Mars, have been identified as mixtures of multiple components based on their spectral reflectance properties and the known spectral character of pure clay minerals. In particular, the spectral characteristics associated with the ~2.2 μm feature in Martian reflectance spectra indicate that mixtures of AlOH- and SiOH-bearing minerals are present. The present study investigated the spectral reflectance properties of the following binary mixtures to aid in the interpretation of remotely acquired reflectance spectra of rocks at Mawrth Vallis: kaolinite-opal-A, kaolinite-montmorillonite, montmorillonite-obsidian, montmorillonite-hydrated silica (opal), and glass-illite-smectite (where glass was hydrothermally altered to mixed-layer illite-smectite). The best spectral matches with Martian data from the present study’s laboratory experiments are mixtures of montmorillonite and obsidian having ~50% montmorillonite or mixtures of kaolinite and montmorillonite with ~30% kaolinite. For both of these mixtures the maximum inflection point on the long wavelength side of the 2.21 μm absorption feature is shifted to longer wavelengths, and in the case of the kaolinite-montmorillonite mixtures the 2.17 μm absorption found in kaolinite is of similar relative magnitude to that feature as observed in CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) data. The reflectance spectra of clay mixed with opal and of hydrothermally altered glass-illite-smectite did not represent the Martian spectra observed in this region as well. A spectral comparison of linear vs. intimate mixtures of kaolinite and montmorillonite indicated that for these sieved samples, the intimate mixtures are very similar to the linear mixtures with the exception of the altered glass-illite-smectite samples. However, the 2.17 μm kaolinite absorption is stronger in the intimate mixtures than in the equivalent linear mixture. Modified Gaussian Modeling of absorption features observed in reflectance spectra of the kaolinite-montmorillonite mixtures indicated a strong correlation between percent kaolinite in the mixture and the ratio of the area of the 2.16 μm band found in kaolinite to the area of the 2.20 μm band found in montmorillonite.

The minerals of carletonite group, fluorcarletonite, KNa4Ca4[Si8O18](CO3)4(F,OH)·H2O and carletonite, Na4Ca4[Si8O18](CO3)4(OH,F)·H2O, were investigated using a multi-method approach. A detailed comparative chemical study of the minerals was carried out using electron probe microanalysis and Fourier transform infrared spectroscopy. Using X-ray techniques and the results obtained, geometrical and distortion characteristics of the mineral structures are calculated and the successful crystal-structure refinement of these two natural compounds are given. Using spectroscopic and luminescence methods and ab initio calculations, it is shown that hole defects (CO3)•– are responsible for the colouration of the samples studied. Luminescence due to 5d–4f transition in Ce3+ ions is observed in both investigated compounds. Moreover, luminescence attributed to intrinsic luminescence, corresponding to the decay of electronic excitations of (CO3)2– complexes in the carletonite sample, is registered for the first time in phyllosilicates. An analysis of the optical absorption spectra and g-tensor values suggests that (CO3)•– defects in the crystal structure are localised in the C1 positions. Identification of these specific properties for these sheet silicates, with a two-dimensional infinite tetrahedral polymerisation, indicates that carletonites could be prospective materials for novel phosphors and luminophores.

The evaluation of the genetic quality of a seed lot is crucial for the quality control process in its production and commercialization, as well as in the identification of superior genotypes and the verification of the correct crossing in plant breeding programmes. Current techniques, based on the identification of seed morphological characteristics, require skilled analysts, while biochemical methods are time-consuming and costly. The application of spectral imaging analysis, which combines digital imaging with spectroscopy, is gaining ground as a fast, accurate and non-destructive method. The success of this technique is closely linked to chemometric techniques, which use statistical and mathematical tools in data processing. The aim of the work was to evaluate the main procedures in terms of spectral image analysis and chemometric procedures applied in seed phenotyping and its practical application. A systematic review was conducted using the PRISMA methodology, in which a total of 1304 articles were identified and screened to the inclusion of 44 articles pertaining to the scope. It was concluded that spectral image analysis has a high ability to classify seeds of different genotypes (93.33%) in a range of situations: between cultivars; hybrids and progenitors; and hybrids and lines, as well as in the separation of coated seeds. Accurate classification can be obtained by different strategies, such as the choice of the equipment type, the spectrum range and extra features, guided by the characteristics of the species, as well as in the choice of algorithms and dimensionality reduction procedures for the optimization of models when there is a large amount of data. Despite the fact that the practical application of this technique in seed phenotyping still needs to be developed for use in laboratories with large volumes of analyses, lots, genotypes and harvests. Research has been accelerated to overcome the practical challenges of this method, as seen in works using model update algorithms, online classification systems, and real-time classification maps. Thus, there are strong indications that the application of multispectral image analysis will reach the routine of seed analysis laboratories.

Gaia space mission of the European Space Agency was launched at the end of 2013 and will continue operations until 2025. The published data releases revolutionize the view of the Milky Way galaxy and beyond thanks to its unprecedented astrometry, photometry and spectroscopy. The paper reviews the products of the last data release of the Gaia mission and some of the scientific impacts of the data. We also discuss the future perspectives of Galaxy astrometry from space.