Fitting Of Spectra Research Articles

Microstructural and nonlinear optical properties of quaternary gallium-titanium-zinc-oxide transparent conductive semiconductor thin films

Transparent and conductive quaternary gallium-titanium-zinc-oxide films were grown on glass substrates by radio-frequency magnetron sputtering. The effects of growth temperature on structure, morphology, electrical, and nonlinear optical properties of the films were investigated systematically. All the deposited films possess hexagonal wurtzite structure with (002) preferred crystallographic orientation. The obtained optical bandgaps of the deposited films are larger than that of pure zinc oxide, which is ascribed to the reduction in band tail width. The film deposited at growth temperature of [Formula: see text]C exhibits the optimum crystalline quality with the lowest dislocation density of [Formula: see text] nm[Formula: see text], the highest visible light transparency of 82.06%, the minimum sheet resistance of 11.2 [Formula: see text]/sq, and the maximum figure-of-merit of [Formula: see text] [Formula: see text][Formula: see text]. The present findings indicate that the gallium-titanium-zinc-oxide films are promisingly utilized as transparent conductive layer. The refractive index and extinction coefficient of the deposited films were estimated by using spectrum fitting approach. A normal optical dispersion behavior was observed in visible region, while an anomalous dispersion behavior appeared in ultraviolet region. In addition, the nonlinear optical parameters were obtained. This first-hand information is useful for future rational design of multicomponent zinc oxide semiconductor materials for optoelectronic applications.

Single-Slice XRF Mapping of Light Elements in Frozen-Hydrated Allium schoenoprasum via a Self-Absorption-Corrected Hyperspectral Tomographic Reconstruction Approach.

3D and 2D-cross-sectional X-ray fluorescence analysis of biological material is a powerful tool to image the distribution of elements and to understand and quantify metal homeostasis and the distribution of anthropogenic metals and nanoparticles with minimal preparation artifacts. Using tomograms recorded on cryogenically prepared leaves of Allium schoenoprasum, the cross-sectional distribution of physiologically relevant elements like calcium, potassium, manganese, and zinc could be tomographically reconstructed by peak fitting followed by a conventional maximum-likelihood algorithm with self-absorption correction to reveal the quantitative cross-sectional element distribution. If light elements such as S and P are located deep in the sample compared to the escape depth of their characteristic X-ray fluorescence lines, the quantitative reconstruction becomes inaccurate. As a consequence, noise is amplified to a magnitude where it might be misinterpreted as actual concentration. We show that a tomographic MCA hyperspectral reconstruction in combination with a self-absorption correction allows for fitting of the XRF spectra directly in real space, which significantly improves the qualitative and quantitative analysis of the light elements compared to the conventional method as noise and artifacts in the tomographic reconstruction are reduced. This reconstruction approach can substantially improve the quantitative analysis of trace elements as it allows the fitting of summed voxel spectra in anatomical regions of interest. The presented method can be applied to XRF 2D single-slice tomography data and 3D tomograms and is particularly relevant for, but not limited to, biological material in order to help retrieve self-absorption corrected quantitative reconstructions of the spatial distribution of light elements and ultra-trace-elements.

Investigation of the signal uncertainty in laser-induced breakdown spectroscopy based on error propagation considering self-absorption

The relatively high signal uncertainty of laser-induced breakdown spectroscopy (LIBS) is a key obstacle to its analytical performance and large-scale application. Despite the extensive research efforts to reduce signal uncertainty, few fundamental studies have been conducted because of the complexity of the microscopic mechanisms involved in plasma evolution. Recently, error propagation analysis has provided an inspiring perspective by linking signal uncertainty with plasma property fluctuations, while further investigation is urgently needed due to the limitations of the employed plasma diagnostic techniques. In this study, a spectrum fitting model was proposed for optically thick and homogeneous plasmas to provide more reliable plasma properties for error propagation analysis for the first time. The model was applied to laser-induced copper plasmas using a laser wavelength of 1064 nm and a pulse duration of 25 ns. The uncertainty of an atomic copper line was analyzed at different delay times. Our findings revealed that the fluctuation of columnar total number density was the most significant factor under the investigated conditions, and that the correlation term of temperature and columnar total number density made a considerable negative contribution. Furthermore, self-absorption suppressed the magnitudes of major contribution terms for the signal uncertainty of LIBS.

Real-Time Determination of the Glass Transition Temperature during Reversible Network Formation Based on Furan–Maleimide Diels–Alder Cycloadditions Using Dielectric Spectroscopy

The molecular dynamics of the reversible network 4F230-2M230 were studied systematically by dielectric relaxation spectroscopy (DRS) at frequencies between 10–1 and 107 Hz under both isothermal and non-isothermal conditions, focusing on the cooperative segmental dynamics as sensed by the dielectric α-relaxation. This reversible network is based on the furan–maleimide Diels–Alder reaction of a 4-functional furan-functionalized Jeffamine coupled with a 2-functional maleimide. Different strategies for extracting a “dielectric” glass transition temperature (Tg) were employed and compared. First, relaxation times τα were derived by conventional Havriliak–Negami fits of dielectric spectra and then fitted to the Vogel–Fulcher–Tammann (VFT) equation, which yields the dynamic Tg of partially cured samples (approach I). Alternatively, the thermal glass transition temperature was derived from the dielectric spectra ε′(f, T) using a fine structure analysis by bivariate differential sampling. Both the dynamic and thermal Tgs revealed an excellent agreement, confirming the stability of the VFT fits as well as the equivalence of both quantities as usually expected for bulk glass-forming materials. Two attempts were made to find a unique set of VFT parameters based on a global fit considering DRS spectra from partially cured samples during heating from −120 to 100 °C. Via a first procedure (approach II), a unique set of VFT parameters EV and τ∞ was obtained that well describes the relaxation times during non-isothermal cure at temperatures where the effects of ongoing cure kinetics can be neglected. To overcome this restriction, a refined approach III was developed that includes the earlier reported kinetic model for the DA reaction and allows accurate predictions for the relaxation time evolution during both isothermal and non-isothermal cure experiments. Based on this unique description, a new technique for continuous cure monitoring was proposed and tested. This technique allows us to compute in real-time dynamic Tg from the relaxation time τα at any stage of the isothermal or non-isothermal cure process using two unique VFT parameters from the global fit procedure. This approach might stimulate new applications of DRS-based cure monitoring.

A method for modelling polymer electrolyte decomposition during the Li-nucleation process in Li-metal batteries

Elucidating the complex degradation pathways and formed decomposition products of the electrolytes in Li-metal batteries remains challenging. So far, computational studies have been dominated by studying the reactions at inert Li-metal surfaces. In contrast, this study combines DFT and AIMD calculations to explore the Li-nucleation process for studying interfacial reactions during Li-plating by introducing Li-atoms close to the metal surface. These Li-atoms were added into the PEO polymer electrolytes in three stages to simulate the spontaneous reactions. It is found that the highly reactive Li-atoms added during the simulated nucleation contribute to PEO decomposition, and the resulting SEI components in this calculation include lithium alkoxide, ethylene, and lithium ethylene complexes. Meanwhile, the analysis of atomic charge provides a reliable guideline for XPS spectrum fitting in these complicated multicomponent systems. This work gives new insights into the Li-nucleation process, and experimental XPS data supporting this computational strategy. The AIMD/DFT approach combined with surface XPS spectra can thus help efficiently screen potential polymer materials for solid-state battery polymer electrolytes.

Infrared and terahertz studies of phase transitions in the CH3NH3PbBr3 perovskite

We investigated the influence of two structural phase transitions in methylammonium lead tri-bromide ${\mathrm{CH}}_{3}{\mathrm{NH}}_{3}{\mathrm{PbBr}}_{3}$ $({\mathrm{MAPbBr}}_{3})$ single crystals on the activity of polar phonons using time-domain THz transmission and far infrared (IR) reflectance spectra. The fitting using the Lorentz model of damped harmonic oscillators also enables us to determine all the polar phonon parameters, IR response functions, and their temperature dependence. The fit of the far IR spectra provides a nearly perfect quantitative description of the measured reflectance at room temperature using three phonons. On cooling, three IR active phonons of the cubic and tetragonal structures split into 15 separate bands, signaling the transformation to the orthorhombic phase below 150 K. This result is compared with the factor group analysis of the polar phonons in all three crystallographic phases. The absence of a soft optical phonon supports the previously published order-disorder character of the structural phase transitions.

Characterization of PbWO4 thin films formed by the pulsed laser welding technique

Herein thin films of PbWO4 were formed from bilayers of Pb/WO3 by the pulse laser welding technique (PLW) within couple of seconds in an argon atmosphere. Thin films of Pb (100 nm)/WO3 (500 nm) were deposited by the thermal evaporation technique under a vacuum pressure of 10−5 mbar. The films were then exposed to a pulse laser beam of fixed amplitude and variable pulse width (0.1–10 ms). The produced films were characterized by means of X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy and optical spectrophotometry techniques. An almost pure phase (∼90%) of tetragonal PbWO4 was achieved after the pulse width exceeds 5.0 ms. PbWO4 thin films produced by the PLW technique exhibited a direct and indirect energy band gaps of 2.27 eV and 3.52 eV, respectively. Energy band tails of widths of 1.35 eV were found dominant in these films. In addition fitting of the dielectric resonance spectra for Pb/WO3 and PbWO4 thin films indicated that the formation of PbWO4 was accompanied with a decrease in the high frequency dielectric constant, a decrease in the free hole concentration and an increase in the electronic friction in the films. The fast method of obtaining PbWO4 thin films and the formation of the direct band gap being 2.27 eV together with the nonlinear dielectric and optical properties make the PbWO4 films obtained by the PLW technique suitable for optoelectronic technology.

Kinematics of stellar substructures in the small magellanic cloud

ABSTRACT We present a kinematic analysis of the Small Magellanic Cloud using 3700 spectra extracted from the European Southern Observatory archive. We used data from Gaia and near-infrared photometry to select stellar populations and discard Galactic foreground stars. The sample includes main-sequence red giant branch and red clump stars, observed with Fibre Large Array Multi Wavelength Spectrograph. The spectra have a resolving power λ/Δλ from 6500 to 38 000. We derive radial velocities by employing a full spectrum fitting method using a penalized pixel fitting routine. We obtain a mean radial velocity for the galaxy of 159 ± 2 km s−1, with a velocity dispersion of 33 ± 2 km s−1. Our velocities agree with literature estimates for similar (young or old) stellar populations. The radial velocity of stars in the Wing and bar-like structures differ as a consequence of the dynamical interaction with the Large Magellanic Cloud. The higher radial velocity of young main-sequence stars in the bar compared to that of supergiants can be attributed to star formation around 40 Myr ago from gas already influenced by tidal stripping. Similarly, young main-sequence stars in the northern part of the bar, resulting from a prominent star forming episode 25 Myr ago, have a higher radial velocity than stars in the southern part. Radial velocity differences between the northern and southern bar overdensities are also traced by giant stars. They are corroborated by studies of the cold gas and proper motion indicating stretching/tidal stripping of the galaxy.

Evaluating Atmospheric Correction Methods for Sentinel−2 in Low−to−High−Turbidity Chinese Coastal Waters

Inaccuracies in the atmospheric correction (AC) of data on coastal waters significantly limit the ability to quantify the parameters of water quality. Many studies have compared the effects of the atmospheric correction of data provided by the Sentinel−2 satellites, but few have investigated this issue for coastal waters in China owing to a limited amount of in situ spectral data. The authors of this study compared four processors for the atmospheric correction of data provided by Sentinel−2—the Atmospheric Correction for OLI ‘lite’(ACOLITE), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System (SeaDAS), Polynomial-based algorithm applied to MERIS (POLYMER), and Case 2 Regional Coast Colour (C2RCC)—to identify the most suitable one for water bodies with different turbidities along the coast of China. We tested the algorithms used in these processors for turbid waters and compared the resulting inversion of the remote sensing reflectance (Rrs) using in situ reflectance data from three stations with varying levels of coastal turbidity (HTYZ, DONG’OU, and MUPING). All processors significantly underestimated the results on data from the HTYZ station, which is located along waters with high turbidity, with the SeaDAS delivering the best performance, with an average band RMSE of 0.0146 and an average MAPE of 29.80%. It was followed by ACOLITE, with an average band RMSE of 0.0213 and an average MAPE of 43.43%. The performance of two AC algorithms used in ACOLITE, dark spectrum fitting (DSF) and exponential extrapolation (EXP), was also evaluated by comparing their results with in situ measurements at the HTYZ site. The ACOLITE-EXP algorithm delivered a slight improvement in results for the blue band compared with the DSF algorithm in highly turbid water, but led to no significant improvement in the green and red bands. C2RCC delivered the best performance on data from the DONG’OU station, which is located along water with medium turbidity, and from the MUPING station (water with low turbidity), with values of the MAPE of 18.58% and 28.41%, respectively.

Electrical, optical and dielectric properties of polyvinylpyrrolidone/graphene nanoplatelet nanocomposites

In this study, polyvinylpyrrolidone (PVP) nanocomposite films containing GnP in four different volume fractions (φ = 0.00, 2.00, 4.08, and 5.91) were prepared by the solution casting method. UV–Vis absorbance spectroscopy, reflectance spectroscopy, and two-point probe resistivity measurement techniques were used to examine the optical, electrical, and dielectric properties of these films. Optical band gap energies of the PVP/GnP nanocomposites were obtained using the most commonly used Tauc, Kubelka-Munk (K-M), Absorbance Spectrum Fitting (ASF), and Derivative (DM) methods. The results obtained by Tauc, K-M, and ASF methods were found to be consistent with each other. In addition, basic optical parameters such as Urbach energy (Eu), refractive index (n), optical conductivity (σopt) and dielectric constant (ε) of the PVP/GnP nanocomposites were investigated. As the GnP volume fraction increased in the nanocomposites, the electrical conductivity, Eu, n, σopt and ε increased whereas Eg decreased. These nanocomposites produced by varying the GnP volume fraction are promising for using optics, electricity, optoelectronics, and many other industrial applications.

Source-Parameter Estimation after Attenuation Correction through the Use of Q Tomography

ABSTRACT The measurement of earthquake source parameters is affected by large uncertainties, and different approaches lead to large variability in results. One crucial aspect is the trade-off between attenuation (Q) and corner frequency (fc) in spectral fitting: The source corner frequency, inversely proportional to the fault size, can be severely masked by attenuation and site effects. In this article, we describe a method to solve the trade-off based on the fit of displacement spectra to find the source characteristics (corner frequency, fc, and the signal moment, Ω0) and the single-station attenuation operator (t*), in addition to the site response. We follow a parametric approach based on the use of 3D Q seismic tomography and a bootstrap-based method for selecting the best spectra fit. The correction of attenuation with synthetic values derived by 3D attenuation tomography efficiently deals with the trade-off between source and path terms, leading to small uncertainties in the determination of source unknowns (fc and signal moment, Ω0), thus yielding constrained estimates of source parameters for low- to medium-magnitude earthquakes. We show an application to the Emilia 2012 seismic sequence, for which we computed the source parameters for 1240 aftershocks (from an initial dataset of 1748) with local magnitude ranging from 2.0 to 4.7 using the spectral fit from P and S waves. About 80% of stress-drop estimations are characterized by relatively low uncertainties (within 20% of the estimated values), with maximum values of about 40% for the remaining 20%. The attenuation correction is effective to determine source parameters for small-magnitude earthquakes; hence, we obtain reliable estimates of source parameters for the entire aftershock sequence. This approach gives the opportunity to infer the mechanical state of a complete fault system by taking advantage of the larger number of low-magnitude events (with respect to the largest ones) that always follow a major earthquake.

A Novel Atmospheric Correction for Turbid Water Remote Sensing

For the remote sensing of turbid waters, the atmospheric correction (AC) is a key issue. The “black pixel” assumption helps to solve the AC for turbid waters. It has proved to be inaccurate to regard all water pixels in the SWIR (Short Wave Infrared) band as black pixels. It is necessary to perform atmospheric correction in the visible bands after removing the radiation contributions of water in the SWIR band. Here, the modified ACZI (m-ACZI) algorithm was developed. The m-ACZI assumes the spatial homogeneity of aerosol types and employs the BPI (Black Pixel Index) and PIFs (Pseudo-Invariant Features) to identify the “black pixel”. Then, the radiation contributions of waters in the SWIR band are removed to complete the atmospheric correction for turbid waters. The results showed that the m-ACZI had better performance than the SeaDAS (SeaWiFS Data Analysis System) -SWIR and the EXP (exponential extrapolation) algorithm in the visible band (sMAPE < 30.71%, RMSE < 0.0111 sr−1) and is similar to the DSF (Dark Spectrum Fitting) algorithm in floating algae waters. The m-ACZI algorithm is suitable for turbid inland waters.

XANTHO – A simple basic program for fitting X-ray spectra

A code XANTHO for fitting X-ray spectra induced by photons or charge particles was developed as a Lazarus application. Background subtraction is performed by iterative filtering (brushing) of the source spectrum, based on the adapted Kolmogorov-Zurbenko approach. For comparison, a code with top-hat filtering was also developed. Critical comparison was made for a glass standard at PIXE analysis. XANTHO is intended for accurate fitting of individual spectra during analytical work and for sequential fitting at mapping experiments.

Under High Radon Environment α Energy Spectrum Analysis

Energy spectrum processing technology is one of the key technologies to realize the rapid monitoring of artificial radioactive aerosol. At present, most commercial aerosol continuous monitoring equipment are suitable for the measurement of artificial radioactive aerosol under natural radon background. The energy spectrum processor technology used is also aimed at the situation of low radon background, which is not suitable for the measurement of artificial radioactive aerosol in high radon environment. In this paper, the combination of energy spectrum fitting (fitting method) and variable tailing proportional coefficient method (ratio deduction method) is used, and the program written on MATLAB platform is used to analyze α by deducting radon daughters in the energy spectrum, the energy spectrum measurement in high radon environment can be realized. By analyzing the energy spectrum of mixed samples of U and Ra with different concentrations and comparing with the measurement results after cooling, it shows good consistency, which verifies the feasibility of understanding the spectrum method and provides a reference for the energy spectrum analysis in high radon environment α Energy spectrum analysis provides an important technical means.

Tissue-variation of iron stable isotopes in marine fish coupled with speciation analysis using X-ray absorption fine structure

The Fe stable isotope ratio (δ56Fe) in tissues is a potential parameter for examining the Fe metabolism in marine fish. Although the effect of ferritin storage has been proposed as a possible cause of heavy isotope (56Fe) enrichment in the liver, no speciation and stable isotope ratio coupling data are available. Here, we report the δ56Fe values measured by multicollector ICP-MS and the result of Fe K-edge X-ray absorption near-edge structure (XANES) analysis of multiple tissues obtained from a skipjack tuna (Katsuwonus pelamis) and a chub mackerel (Scomber japonicus). Apparent isotopic fractionation between the liver and the muscle samples (Δ56FeL–M = δ56Feliver − δ56Femuscle) from these species was observed (0.85 ‰ and 0.57 ‰, respectively). The dominant Fe species in the muscle was heme Fe (the sum of methemoglobin, oxyhemoglobin, and deoxyhemoglobin), while ferritin was not detected according to the linear combination fitting of the XANES spectra. In the liver, ferritin contribution was ca. 28 %–54 % of the total Fe content. The apparent difference in δ56Fe between heme Fe and ferritin was estimated to range from 1.41 ‰ to 1.52 ‰ based on the tissue-specific δ56Fe values and the XANES results. These results indicate that the Fe storage as ferritin does not induce the lowering of δ56Fe in the muscle, considering the low contribution of the liver Fe to the total Fe content in the body.

Evaluation of eight band SuperDove imagery for aquatic applications.

Planet's SuperDove constellation is evaluated for remote sensing of water targets. SuperDoves are small satellites with on board eight band PlanetScope imagers that add four new bands compared to the previous generations of Doves. The Yellow (612 nm) and Red Edge (707 nm) bands are of particular interest to aquatic applications, for example in aiding the retrieval of pigment absorption. The dark spectrum fitting (DSF) algorithm is implemented in ACOLITE for processing of SuperDove data, and its outputs are compared to matchup data collected using an autonomous pan-and-tilt hyperspectral radiometer (PANTHYR) installed in the turbid waters of the Belgian Coastal Zone (BCZ). Results for 35 matchups from 32 unique SuperDove satellites indicate on average low differences with PANTHYR observations for the first seven bands (443-707 nm), with mean absolute relative differences (MARD) 15-20%. The mean average differences (MAD) are between -0.01 and 0 for the 492-666 nm bands, i.e. DSF results show a negative bias, while the Coastal Blue (444 nm) and Red Edge (707 nm) show a small positive bias (MAD 0.004 and 0.002). The NIR band (866 nm) shows a larger positive bias (MAD 0.01), and larger relative differences (MARD 60%). Root mean squared differences (RMSD) are rather flat at around 0.01 with peaks in the bands with highest water reflectance of around 0.015. The surface reflectance products as provided by Planet (PSR) show a similar average performance to DSF, with slightly larger and mostly positive biases, except in both Green bands, where the MAD is close to 0. MARD in the two Green bands is a bit lower for PSR (9.5-10.6%) compared to DSF (9.9-13.0%). Higher scatter is found for the PSR (RMSD 0.015-0.020), with some matchups showing large, spectrally mostly flat differences, likely due to the external aerosol optical depth (τa) inputs not being representative for these particular images. Chlorophyll a absorption (aChl) is retrieved from PANTHYR measurements, and the PANTHYR data are used to calibrate aChl retrieval algorithms for SuperDove in the BCZ. Various Red band indices (RBI) and two neural networks are evaluated for aChl estimation. The best performing RBI algorithm, i.e. the Red band difference (RBD), showed a MARD of 34% for DSF and 25% for PSR with positive biases of 0.11 and 0.03 m-1 respectively for 24 PANTHYR aChl matchups. The difference in RBD performance between DSF and PSR can be largely explained by their respective average biases in the Red and Red Edge bands, which are opposite signs for DSF (negative bias in the red), and positive for both bands for PSR. Mapping of turbid water aChl and hence chlorophyll a concentration (C) using SuperDove is demonstrated for coastal bloom imagery, showing how SuperDove data can supplement monitoring programmes.

CRB Weighted Source Localization Method Based on Deep Neural Networks in Multi-UAV Network

With the advent of the Internet of Things (IoT) era, the multi-unmanned aerial vehicle (UAV) networks have attracted great attention in the fields of source detection and localization. However, as a real-time signal processing performance of the UAV is limited by the computing speed and accuracy of the embedded hardware, the effectiveness of source localization is greatly reduced. Aiming at improving the accuracy and computational efficiency of source localization, a Cramer-Rao bound (CRB) weighted multi-UAV network source localization method is proposed based on the deep neural networks (DNN) and spatial spectrum fitting (SSF). The proposed source localization system is composed of UAVs equipped with a radar array. The source location can be achieved using the DOA of the sources signals of UAVs, but the accuracy and real-time performance of the conventional DOA estimation algorithms are not satisfactory, and the data fusion strategy of the conventional cross-location framework needs further improvement. In the proposed method, a DNN-based SSF denoted as the deep SSF (DeepSSF), is designed to achieve accurate DOA estimation. In the DeepSSF, the DOA estimation performance is guaranteed by the DNN’s strong nonlinear fitting ability and highly parallel structure. In addition, based on the obtained DOA information, the source is located once by every two UAVs. Finally, the source localization is realized based on the weighted CRB according to the principle that the more the DOA distribution deviates from zero, the lower the estimation accuracy. The simulation results verify the efficiency of the proposed method.

Exploring the impact of PbO/CdO composition on the structural, optical, and gamma ray shielding properties of dense PbO–TeO2–CdO glasses

Through the melt-quenching process, thick, transparent, and light yellow PbO–TeO2–CdO glasses were fabricated, with sample densities ranging from 5.576 to 6.082 g/cm3. X-ray diffraction (XRD) spectra showed that the material was amorphous, while Fourier transform infrared (FTIR) spectra demonstrated multiple bond stretching modes and vibrational frequencies. With an increase in the mol% of PbO concentration, the derivative of absorption spectra fitting (DASF) method showed a reduction in the bandgap energies to 3.520 eV, 3.457 eV, 3.433 eV, and 3.394 eV for Pb70, Pb72.5, Pb75, and Pb77.5, respectively. For the Pb70 and Pb77.5 glasses, the transmission factor (TF) decreased with thickness. The Pb77.5 glass had the highest radiation protection efficiency (RPE), with an RPE range of 66–70% for a thickness of 1.25 cm. Moreover, the addition of PbO improved the transparency, density, and gamma-ray shielding abilities of the glasses.

Automated Atmospheric Correction of Nanosatellites Using Coincident Ocean Color Radiometer Data

Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually possess the wavelength combinations required to atmospherically correct upwelling radiance data for oceanographic applications; however, nanosatellites do provide superior ground-viewing spatial resolution (~3 m). Coincident multispectral data from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi NPP VIIRS; referred to herein as “VIIRS”) were used to remove atmospheric contamination at each of the nanosatellite’s visible wavelengths to yield an estimate of spectral water-leaving radiance [Lw(l)], which is the basis for surface ocean optical products. Machine learning (ML) algorithms (KNN, decision tree regressors) were applied to determine relationships between Lw and top-of-atmosphere (Lt)/Rayleigh (Lr) radiances within VIIRS training data, and then applied to test cases for (1) the Marine Optical Buoy (MOBY) in Hawaii and (2) the AErosol RObotic Network Ocean Color (AERONET-OC), Venice, Italy. For the test cases examined, ML-based methods appeared to improve statistical results when compared to alternative dark spectrum fitting (DSF) methods. The results suggest that ML-based sensor convolution techniques offer a viable path forward for the oceanographic application of nanosatellite data streams.

Age-divided mean stellar populations from full spectrum fitting as the simplified star formation and chemical evolution history of a galaxy: methodology and reliability

ABSTRACT We introduce a practical methodology for investigating the star formation and chemical evolution history of a galaxy: age-divided mean stellar populations (ADPs) from full spectrum fitting. In this method, the mass-weighted mean stellar populations and mass fractions (fmass) of young and old stellar components in a galaxy are separately estimated, which are divided with an age cut (selected to be 109.5 yr ≈3.2 Gyr in this paper). To examine the statistical reliability of ADPs, we generate 10 000 artificial galaxy spectra, each of which consists of five random simple stellar population components. Using the Penalized PiXel-Fitting (ppxf) package, we conduct full spectrum fitting to the artificial spectra with noise as a function of wavelength, imitating the real noise of Sydney-Australian Astronomical Observatory Multi-object Integral field spectrograph (SAMI) galaxies. As a result, the Δ (= output − input) of age and metallicity appears to significantly depend on not only signal-to-noise ratio (S/N), but also luminosity fractions (flum) of young and old components. At given S/N and flum, Δ of young components tends to be larger than Δ of old components; e.g. σ(Δ[M/H]) ∼ 0.40 versus 0.23 at S/N = 30 and flum = 50 per cent. The age-metallicity degeneracy appears to be insignificant, but Δlog(age/yr) shows an obvious correlation with Δfmass for young stellar components ($\mathcal {R}\sim 0.6$). The impact of dust attenuation and emission lines appears to be mostly insignificant. We discuss how this methodology can be applied to spectroscopic studies of the formation histories of galaxies, with a few examples of SAMI galaxies.