Spectral Fitting Algorithm Research Articles

Mg/Fe] and variable initial mass function: Revision of [α/Fe] for massive galaxies

Observations of nearby massive galaxies have revealed that they are older and richer in metals and magnesium than their low-mass counterparts. In particular, the overabundance of magnesium compared to iron, [Mg/Fe], is interpreted to reflect the short star formation history that the current massive galaxies underwent early in the Universe. We present a systematic revision of the [Mg/Fe] – velocity dispersion (σ) relation based on stacked spectra of early-type galaxies with a high signal-to-noise ratio from the Sloan Digital Sky Survey. Using the penalized pixel-fitting (pPXF) method and the MILES single stellar population models, we fit a wide optical wavelength range to measure the net α-abundance. The combination of pPXF and α-enhanced MILES models incorrectly leads to an apparently decreasing trend of [α/Fe] with velocity dispersion. We interpret this result as a consequence of variations in the individual abundances of the different α-elements. This warrants caution for a naive use of full spectral fitting algorithms paired with stellar population models that do not take individual elemental abundance variations into account, especially when deriving averaged quantities such as the mean [α/Fe] of a stellar population. In addition, and based on line-strength measurements, we quantify the impact of a non-universal initial mass function on the recovered abundance pattern of galaxies. In particular, we find that a simultaneous fit of the slope of the initial mass function and the [Mg/Fe] results in a shallower [Mg/Fe]–σ relation. Therefore, our results suggest that star formation in massive galaxies lasted longer than what has been reported previously, although it still occurred significantly faster than in the solar neighbourhood.

Spectral diagnosis of underwater microsecond high-current pulsed discharge plasma

Underwater microsecond high-current pulsed discharge can generate powerful shock waves and a significant number of active ions, offering a wide range of applications. To analyse the characteristics of plasma channel formed by the discharge, this study established a comprehensive test platform and conducted spectral diagnosis for underwater high-current pulsed discharge. Considering the randomness of the pulsed arc discharge, the voltage and current waveforms under different discharge cases were measured, and the images and emission spectra of the plasma channel were obtained. The origin of the continuous emission of the initial spectra was analysed. A spectral fitting algorithm was proposed, which could separate the spectral lines into line emission of Hα and continuous background, and correct the self-absorption. The time-varying characteristics of electron density were obtained under three typical discharge cases, the possible errors caused by baseline shift were considered, and the influencing factors of line broadening were analysed. Under the test conditions of this study, the electron density of plasma channel was in the order of 1024–1025 m−3.

The SAMI-Fornax Dwarfs Survey – IV. Star formation histories of dwarf and early-type galaxies: insights from full spectral fitting

ABSTRACT We present a study on the star formation histories (SFHs) of galaxies covering the range 104 < M⋆/M⊙ < 1012, leveraging full spectral fitting algorithms. Our sample consists of 31 dwarf galaxies from the SAMI-Fornax Survey with stellar masses between 107–$10^{9.5} \, {\rm M}_{\odot }$, early-type galaxies from the ATLAS3D project with stellar masses between 1010–$10^{12} \, {\rm M}_{\odot }$, and dwarf galaxies that are satellites of Andromeda and the Milky Way, with 104 < M⋆/M⊙ < 108. We find that galaxies from 107–$10^{8} \, {\rm M}_{\odot }$ exhibit the smallest star formation rates (SFRs), while the SFR increase as we move down or up in mass. In this sense, we find that some $10^{5} \, {\rm M}_{\odot }$ galaxies have cumulative SFHs that are comparable to those of $10^{12} \, {\rm M}_{\odot }$ galaxies. Our study shows that the evolution of giant galaxies is primarily governed by their internal properties, with time-scales that do not depend on their environmental location. In contrast, dwarf galaxies below $10^{8} \, {\rm M}_{\odot }$ can be significantly affected in dense environments, such as the inner regions of a cluster, that severely quench the galaxies before the assembly of their 50 per cent present-day mass. We find that, only dwarfs with stellar masses between 107–$10^{9} \, {\rm M}_{\odot }$ actively form stars nowadays, while less massive galaxies seem to remain unaffected by the environment due to the expulsion of most of their gas at an early stage in their evolution. Our study highlights and corroborates a critical threshold around $10^{8}-10^{9} \, {\rm M}_{\odot }$ in galaxy evolution from previous studies, separating more massive galaxies minimally impacted by the environment from those less massive galaxies quenched by it.

Rapid Detection of Volatile Organic Compounds by Switch-Scan Tuning of Vernier Quantum-Cascade Lasers.

Volatile organic compounds (VOCs) exhibit typically broad and mutually overlapping ro-vibrational absorption fingerprints. This complexity has so far limited the applicability of laser-based spectroscopy for VOC measurements in complex gas matrices. Here, we exploit a Vernier-type quantum-cascade laser (QCL) as an electrically tunable multiwavelength source for selective and sensitive VOC analysis. This emerging class of lasers provides access to several spectral windows by discrete Vernier tuning ("switching") and continuous coverage within these windows ("scanning"). We present a versatile driving technique that efficiently combines the two tuning mechanisms. Applied to our Vernier QCL, it enables the rapid acquisition (within 360 ms) of high-resolution spectra from six individual spectral windows, distributed over a wide range from 1063 to 1102 cm-1. Gaining access to the broad absorption envelopes of VOCs at multiple frequencies, along with their superimposed fine structure, which are especially pronounced at a reduced sample pressure, offers completely new opportunities in VOC analysis. The potential of this approach is assessed in a direct-laser-absorption setup with acetaldehyde, ethanol, and methanol as benchmark compounds with significant spectral overlaps. A measurement precision of 1-10 ppb is obtained after integration for 10 s at amount fractions below 10 ppm, and excellent linearity is found over at least 3 orders of magnitude. Combined with our dedicated spectral fitting algorithm, we demonstrate highly selective multicompound analyses with less than 3.5% relative expanded uncertainty, even in the presence of a 40× excess of an interfering compound with complete spectral overlap.

Use of machine learning and principal component analysis to retrieve nitrogen dioxide (NO2) with hyperspectral imagers and reduce noise in spectral fitting

Abstract. Nitrogen dioxide (NO2) is an important trace-gas pollutant and climate agent whose presence also leads to spectral interference in ocean color retrievals. NO2 column densities have been retrieved with satellite UV–Vis spectrometers such as the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI) that typically have spectral resolutions of the order of 0.5 nm or better and spatial footprints as small as 3.6 km × 5.6 km. These NO2 observations are used to estimate emissions, monitor pollution trends, and study effects on human health. Here, we investigate whether it is possible to retrieve NO2 amounts with lower-spectral-resolution hyperspectral imagers such as the Ocean Color Instrument (OCI) that will fly on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite set for launch in early 2024. OCI will have a spectral resolution of 5 nm and a spatial resolution of ∼ 1 km with global coverage in 1–2 d. At this spectral resolution, small-scale spectral structure from NO2 absorption is still present. We use real spectra from the OMI to simulate OCI spectra that are in turn used to estimate NO2 slant column densities (SCDs) with an artificial neural network (NN) trained on target OMI retrievals. While we obtain good results with no noise added to the OCI simulated spectra, we find that the expected instrumental noise substantially degrades the OCI NO2 retrievals. Nevertheless, the NO2 information from OCI may be of value for ocean color retrievals. OCI retrievals can also be temporally averaged over timescales of the order of months to reduce noise and provide higher-spatial-resolution maps that may be useful for downscaling lower-spatial-resolution data provided by instruments such as OMI and TROPOMI; this downscaling could potentially enable higher-resolution emissions estimates and be useful for other applications. In addition, we show that NNs that use coefficients of leading modes of a principal component analysis of radiance spectra as inputs appear to enable noise reduction in NO2 retrievals. Once trained, NNs can also substantially speed up NO2 spectral fitting algorithms as applied to OMI, TROPOMI, and similar instruments that are flying or will soon fly in geostationary orbit.

Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2 Imagery of Karimunjawa and Kemujan Island, Central Java Province, Indonesia

Mangrove mapping at the species level enables the creation of a detailed inventory of mangrove forest biodiversity and supports coastal ecosystem management. The Karimunjawa National Park in Central Java Province is one of Indonesia’s mangrove habitats with high biodiversity, namely, 44 species representing 25 true mangroves and 19 mangrove associates. This study aims to (1) classify and group mangrove species by their spectral reflectance characteristics, (2) map mangrove species by applying their spectral reflectance to WorldView-2 satellite imagery with the spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF) algorithms, and (3) assess the accuracy of the produced mangrove species mapping of the Karimunjawa and Kemujan Islands. The collected field data included (1) mangrove species identification, (2) coordinate locations of targeted mangrove species, and (3) the spectral reflectance of mangrove species measured with a field spectrometer. Dendrogram analysis was conducted with the Ward linkage method to classify mangrove species based on the distance between the closest clusters of spectral reflectance patterns. The dendrogram showed that the 24 mangrove species found in the field could be grouped into four levels. They consisted of two, four, and five species groups for Levels 1 to 3, respectively, and individual species for Level 4. The mapping results indicated that the SID algorithm had the highest overall accuracy (OA) at 49.72%, 22.60%, and 15.20% for Levels 1 to 3, respectively, while SFF produced the most accurate results for individual species mapping (Level 4) with an OA of 5.08%. The results suggest that the greater the number of classes to be mapped, the lower the mapping accuracy. The results can be used to model the spatial distribution of mangrove species or the composition of mangrove forests and update databases related to coastal management.

Harmonized Chlorophyll-a Retrievals in Inland Lakes From Landsat-8/9 and Sentinel 2A/B Virtual Constellation Through Machine Learning

Moderate-high resolution satellite missions provide an opportunity to capture subtle spatial variability in lakes; however, the sparsity of time series for individual satellite instruments cannot monitor temporal variation in the lake environment. To date, studies on the joint observations of chlorophyll-a (Chl-a) in inland lakes from multiple missions have been poorly reported. Here, we generated a harmonized Chl-a dataset for the lakes in the Yunnan–Guizhou Plateau in China from 2013 to 2022 by the Landsat 8/9 and Sentinel-2A/B virtual constellation. This study first examined the performance of four atmospheric correction processors to derive remote sensing reflectance (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> ) from Landsat 8/9 Operational Land Imager (OLI) and Sentinel-2A/B multispectral instrument (MSI) images. We determined that the dark spectral fitting algorithm generated better R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> than the other processors, e.g., R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> (561) mean absolute percentage error (MAPE)=15.2%, R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> (665) MAPE=27.5%, and R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> (704) MAPE=25.7%. OLI-derived R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> at five visible and near-infrared bands showed satisfactory agreement with MSI (slope=0.94, MAPE=11.8%). The mixed density network outperformed the six state-of-the-art algorithms and other two machine learning models in retrieving Chl-a [MSI: MAPE=31.4% (N=109), OLI: MAPE=38.0% (N=74)]. The satisfactory agreement of Chl-a retrievals between the synchronous MSI and OLI images (N=2,293,821, MAPE=34.6%) supported the establishment of the virtual constellation. MSI- and OLI- derived Chl-a in nine major lakes in the studied area exhibited apparent seasonal variability from 2013 to 2022, particularly after 2017. Results highlight a solution to establish the Landsat/Sentinel-2 virtual constellation for improving the spatial and temporal resolutions of a database of lake water quality.

The Evolving Interstellar Medium of Star-forming Galaxies, as Traced by Stardust*

Abstract We analyze the far-infrared (FIR) properties of ∼5000 star-forming galaxies at z &lt; 4.5, drawn from the deepest, super-deblended catalogs in the GOODS-N and COSMOS fields. We develop a novel panchromatic spectral energy distribution fitting algorithm, Stardust, that models the emission from stars, active galactic nuclei (AGNs), and infrared dust emission, without relying on energy balance assumptions. Our code provides robust estimates of the UV−optical and FIR physical parameters, such as the stellar mass (M *), dust mass (M dust), infrared luminosities (L IR) arising from AGN and star formation activity, and the average intensity of the interstellar radiation field (〈U〉). Through a set of simulations we quantify the completeness of our data in terms of M dust, L IR, and 〈U〉 and subsequently characterize the distribution and evolution of these parameters with redshift. We focus on the dust-to-stellar mass ratio (f dust), which we parameterize as a function of cosmic age, stellar mass, and specific star formation rate. The f dust is found to increase by a factor of 10 from z = 0 to z = 2 and appears to remain flat at higher z, mirroring the evolution of the gas fraction. We also find a growing fraction of warm to cold dust with increasing distance from the main sequence, indicative of more intense interstellar radiation fields, higher star formation efficiencies, and more compact star-forming regions for starburst galaxies. Finally, we construct the dust mass functions (DMFs) of star-forming galaxies up to z = 1 by transforming the stellar mass function to DMF through the scaling relations derived here. The evolution of f dust and the recovered DMFs are in good agreement with the theoretical predictions of the Horizon-AGN and IllustrisTNG simulations.

Deuterium MRS of early treatment-induced changes in tumour lactate in vitro.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium (2 H) MRS. Following treatment, changes in the 2 H-labelled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2 H-labelled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukaemia (AML) cells, which had been treated with 10 μg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 h after cisplatin treatment the cells were supplied with 20 mM of [6,6'-2 H2 ]glucose and scanned over 2 h using a two-dimensional 2 H MR spectroscopic imaging sequence. The resulting signals from 2 H-labelled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the Oxford Spectroscopy Analysis MATLAB toolbox. After scanning, the cells were processed for histological stains (terminal deoxynucleotidyl transferase UTP nick end labelling and haematoxylin and eosin) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2 H-labelled lactate were observed in the 48 h treated cells compared with the untreated and 24 h treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2 H-labelled lactate signal, these findings suggest that 2 H MRS of lactate may be valuable in evaluating early tumour response.

ProFit-1D-A 1D fitting software and open-source validation data sets.

Accurate and precise MRS fitting is crucial for metabolite concentration quantification of 1 H-MRS spectra. LCModel, a spectral fitting software, has shown to have certain limitations to perform advanced spectral fitting by previous literature. Herein, we propose an open-source spectral fitting algorithm with adaptive spectral baseline determination and more complex cost functions. The MRS spectra are characterized by several parameters, which reflect the environment of the contributing metabolites, properties of the acquisition sequence, or additional disturbances. Fitting parameters should accurately describe these parameters. Baselines are also a major contributor to MRS spectra, in which smoothness of the spline baselines used for fitting can be adjusted based on the properties of the spectra. Three different cost functions used for the minimization problem were also investigated. The newly developed ProFit-1D fitting algorithm is systematically evaluated for simulations of several types of possible in vivo parameter variations. Although accuracy and precision are tested with simulated spectra, spectra measured in vivo at 9.4T are used for testing precision using subsets of averages. ProFit-1D fitting results are also compared with LCModel. Both ProFit-1D and LCModel fitted the spectra well with induced parameter and baseline variations. ProFit-1D proved to be more accurate than LCModel for simulated spectra. However, LCModel showed a somewhat increased precision for some spectral simulations and for in vivo data. The open-source ProFit-1D fitting algorithm demonstrated high accuracy while maintaining precise metabolite concentration quantification. Finally, through the newly proposed cost functions, new ways to improve fitting were shown.

Analytical characterization of laser induced plasmas towards uranium isotopic analysis in gaseous uranium hexafluoride

To perform direct enrichment assay on gaseous uranium hexafluoride (UF6) with laser induced breakdown spectroscopy (LIBS), the dominant spectral-line features, evolution of the signal and background of the U II 424.437 nm line, and its Stark width and shift, were studied as a function of UF6 gas pressure and pulse energy of a nanosecond Nd:YAG laser. Vapor pressure of UF6 was found to be the most important parameter for LIBS analysis of gaseous UF6. Spectral congestion with numerous U lines of high excitation potential was observed and signal-to-background ratio (SBR) was low for measurements with 80 Torr UF6. Only when both UF6 vapor pressure and laser pulse energy were low, for example, less than 20 Torr pressure and 30 mJ pulse energy, the resultant LIBS spectra from gaseous UF6 resembled those obtained from solid U samples. The experimental data also suggest that U and F atoms recombine back to UF6 after the laser pulse. The U emission was found to decay fast with a persistent background signal, degrading SBR with delay time. Systematic positive biases were found for UF6 enrichment assays performed with the 235U–238U line pair at 424.412–424.437 nm, which was confirmed to be caused by self-absorption. Even with optimization of experimental parameters and incorporation of a self-absorption term into the spectral-fitting algorithm, to reduce and compensate for self-absorption, self-absorption is still a main factor limiting accurate UF6 enrichment assay. The use of another spectral window which contains no resonance lines is a prospective solution for the self-absorption issue.

The accuracy and precision of multi-line NO-LIF thermometry in a wide range of pressures and temperatures

An automated spectral fitting algorithm (named Thermo NO-LIF) designed for the extraction of temperature information from experimental NO-LIF spectra is presented and analysed. With the aid of the Thermo NO-LIF, the high-accuracy (0.5%) of multi-line NO-LIF thermometry are demonstrated in the burnt-gases region of a near-adiabatic Bunsen-type premixed flame. The results are compared with the temperature measured using N2 spontaneous Raman scattering (SRS). The current study also applies and analyses the algorithm and the thermometry technique in a premixed flat-flame under various sub-atmospheric pressures. The results suggest that choosing a long excitation scan range with as few overlapping lines as possible can maximise the performance of the multi-line NO-LIF thermometry. The uncertainty arising from the overlapping lines is especially crucial at atmospheric pressure. Additionally, the current study compares the performance of multi-line NO-LIF thermometry using narrowband and broadband lasers. Thermo NO-LIF is available to anyone interested in applying multi-line NO-LIF thermometry.

Reflecting on siliceous rocks in central Australia: Using advanced remote sensing to map ancient “tool‐stone” resources

AbstractHyMap™ airborne hyperspectral imagery was used to discriminate and map hydrated silica mineralization in the Dalhousie Springs area of central Australia. A spectral feature fitting algorithm was used to match laboratory reference spectra with image pixel spectra, producing a scaled goodness‐of‐fit raster map of silicified “tool‐stone” sources in our study area. Subsequent fieldwork indicated that the algorithm mapped silcrete, a rock composed of hydrated silica, and incidentally, the most frequently utilized raw material for stone artifact manufacture in this area of the Australian arid zone. The soundness of our hydrated silica mineralization map is supported with field observations and spectroscopic analysis of collected silcrete samples. Independent siliceous rock mapping produced by the Commonwealth Scientific and Industry Research Organization offers additional corroboration of our results. Based on the success of our approach, we suggest that archaeologists working in Australia and in similar arid environments elsewhere have much to benefit in using advanced remote sensing products to map lithic resources, including time and cost‐saving advantages for field logistics, enriched assessments of land suitability for archaeological site types, and an improved understanding of resource distributions.

Estimation of pO2 histogram from a composite EPR Spectrum of multiple random implants.

Electron paramagnetic resonance (EPR) spectroscopy using oxygen-sensing implants can provide reliable and repeated measurements of the partial pressure of oxygen (pO2) over a period of months or longer; however, it does not provide accurate information about the distribution of tissue oxygenation. While EPR imaging has the capability to provide spatially resolved oxygen data, it is time-consuming and not optimized for discrete number of implants. Previous reports suggest multi-site algorithms, which would require either the implants to be aligned in a certain way so as to deconvolve them using a linear magnetic field gradient or sparse imaging of the implants from a small number of 3D projections. In this paper, we present a simpler and much faster method to estimate the pO2 histogram from a composite, single-scan EPR spectrum measured without applying field gradients to separate the EPR signals from multiple randomly placed oxygen-sensing implants. The method is optimized for a discrete number of implants, validated using simulations, experimental phantoms and in animal models. The results established the composite spectral fitting algorithm as a reliable and robust tool for multi-site oximetry.

Pre-processing of galaxies in cosmic filaments around AMASCFI clusters in the CFHTLS

Context. Galaxy clusters and groups are thought to accrete material along the preferred direction of cosmic filaments. These structures have proven difficult to detect because their contrast is low, however, and only a few studies have focused on cluster infall regions. Aims. We detect cosmic filaments around galaxy clusters using photometric redshifts in the range 0.15 &lt; z &lt; 0.7. We characterise galaxy populations in these structures to study the influence of pre-processing by cosmic filaments and galaxy groups on star formation quenching. Methods. We detected cosmic filaments in the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) T0007 data, focusing on regions around clusters of the AMASCFI CFHTLS cluster sample. The filaments were reconstructed with the discrete persistent structure extractor (DISPERSE) algorithm in photometric redshift slices. We show that this reconstruction is reliable for a CFHTLS-like survey at 0.15 &lt; z &lt; 0.7 using a mock galaxy catalogue. We split our galaxy catalogue into two populations (passive and star forming) using the LePhare spectral energy density fitting algorithm and worked with two redshift bins (0.15 &lt; z ≤ 0.4 and 0.4 &lt; z &lt; 0.7). Results. We showed that the AMASCFI cluster connectivity (i.e. the number of filaments that is connected to a cluster) increases with cluster mass M200. Filament galaxies outside R200 are found to be closer to clusters at low redshift, regardless of the galaxy type. Passive galaxies in filaments are closer to clusters than star-forming galaxies in the low redshift bin alone. The passive fraction of galaxies decreases with increasing clustercentric distance up to d ∼ 5 cMpc. Galaxy groups and clusters that are not located at nodes of our reconstruction are mainly found inside cosmic filaments. Conclusions. These results give clues for pre-processing in cosmic filaments that could be due to smaller galaxy groups. This trend could be further explored by applying this method to larger photometric surveys such as the Hyper Suprime-Cam Subaru Strategic Program (HSC-SPP) or Euclid.

Evolutionary Population Synthesis model with binary stars – Yunnan-II model

AbstractBy considering a modified version of the evolutionary population synthesis (EPS) model for stellar populations (SPs) comprising binary stars, the retrieved galaxy and HII-region parameters/properties differ from the case of neglecting binary stars. The retrieved age, stellar metallicity and mass of galaxies increase (e.g. ∼ 0.2 dex when using spectral fitting algorithm), whilst the star formation rate decreases (∼0.2 dex). The radiation fields from intermediate-age SPs with binary stars could be potentially important ionizing sources in HII regions. Under this possibility, the theoretical division between star forming galaxy and AGN on the diagnostic diagrams would move towards the up-right corner and the retrieved gaseous metallicity would decrease.Our prediction for the birth rate of binary neutron stars in SPs ranges from 10−9 to 10−6${\M {^\minus 1_\odot}} $ yr−1 when the kick velocity is from 0 to 190 km s−1.

Filamentary Accretion Flows in the Infrared Dark Cloud G14.225–0.506 Revealed by ALMA

Abstract Filaments are ubiquitous structures in molecular clouds and play an important role in the mass assembly of stars. We present results of dynamical stability analyses for filaments in the infrared dark cloud G14.225−0.506, where a delayed onset of massive star formation was reported in the two hubs at the convergence of multiple filaments of parsec length. Full-synthesis imaging is performed with the Atacama Large Millimeter/submillimeter Array to map the emission in two hub-filament systems with a spatial resolution of ∼0.034 pc. Kinematics are derived from a sophisticated spectral fitting algorithm that accounts for line blending, large optical depth, and multiple velocity components. We identify five velocity coherent filaments and derive their velocity gradients with principal component analysis. The mass accretion rates along the filaments are up to and are significant enough to affect the hub dynamics within one freefall time (∼105 yr). The filaments are in equilibrium with virial parameter α vir ∼ 1.2. We compare α vir measured in the filaments, filaments, 870 μm dense clumps, and 3 mm dense cores. The decreasing trend in α vir with decreasing spatial scales persists, suggesting an increasingly important role of gravity at small scales. Meanwhile, α vir also decreases with decreasing nonthermal motions. In combination with the absence of high-mass protostars and massive cores, our results are consistent with the global hierarchical collapse scenario.

Validation of tissue optical properties measurement using diffuse reflectance spectroscopy (DRS).

The effectiveness of photodynamic treatment depends on several factors including an accurate knowledge of optical properties of the tissue to be treated. Transmittance and diffuse reflectance spectroscopic techniques are commonly used to determine tissue optical properties. Although transmittance spectroscopy technique is accurate in determining tissue optical properties, it is only valid in an infinite medium and can only be used for interstitial measurements. Diffuse reflectance spectroscopy, on the other hand, is easily adapted to most tissue geometries including skin measurements that involve semi-infinte medium. However, the accuracy of the measured optical properties can be affected by uncertainty in the measurements themselves and/or due to the uncertainty in the fitting algorithm. In this study, we evaluate the accuracy of optical properties determination using diffuse reflectance spectroscopy implemented using a contact probe setup. We characterized the error of the optical properties fitted using two fitting algorithms, a wavelength wise fitting algorithm and a full reflectance spectral fitting algorithm. By conducting systematic investigation of the measurements and fitting algorithm of DRS, we gained an understanding of the uncertainties in the measured optical properties and outlined improvement measures to minimize these errors.

‘The Brick’ is not abrick: a comprehensive study of the structure and dynamics of the central molecular zone cloud G0.253+0.016

In this paper we provide a comprehensive description of the internal dynamics of G0.253+0.016 (a.k.a. 'the Brick'); one of the most massive and dense molecular clouds in the Galaxy to lack signatures of widespread star formation. As a potential host to a future generation of high-mass stars, understanding largely quiescent molecular clouds like G0.253+0.016 is of critical importance. In this paper, we reanalyse Atacama Large Millimeter Array cycle 0 HNCO $J=4(0,4)-3(0,3)$ data at 3 mm, using two new pieces of software which we make available to the community. First, scousepy, a Python implementation of the spectral line fitting algorithm scouse. Secondly, acorns (Agglomerative Clustering for ORganising Nested Structures), a hierarchical n-dimensional clustering algorithm designed for use with discrete spectroscopic data. Together, these tools provide an unbiased measurement of the line of sight velocity dispersion in this cloud, $\sigma_{v_{los}, {\rm 1D}}=4.4\pm2.1$ kms$^{-1}$, which is somewhat larger than predicted by velocity dispersion-size relations for the Central Molecular Zone (CMZ). The dispersion of centroid velocities in the plane of the sky are comparable, yielding $\sigma_{v_{los}, {\rm 1D}}/\sigma_{v_{pos}, {\rm 1D}}\sim1.2\pm0.3$. This isotropy may indicate that the line-of-sight extent of the cloud is approximately equivalent to that in the plane of the sky. Combining our kinematic decomposition with radiative transfer modelling we conclude that G0.253+0.016 is not a single, coherent, and centrally-condensed molecular cloud; 'the Brick' is not a \emph{brick}. Instead, G0.253+0.016 is a dynamically complex and hierarchically-structured molecular cloud whose morphology is consistent with the influence of the orbital dynamics and shear in the CMZ.

On tests of full spectral fitting algorithms

A recent paper by Ge et al. performs a series of experiments with two full spectral fitting codes, pPXF and starlight, finding that the two yield consistent results when the input spectrum is not heavily reddened. For E(B-V) > 0.2, however, they claim starlight leads to severe biases in the derived properties. Counterintuitively, and at odds with previous simulations, they find that this behaviour worsens significantly as the signal-to-noise ratio of the input spectrum increases. This communication shows that this is entirely due to an A_V < 1 mag condition imposed while initializing the Markov chains in the code. This choice is normally irrelevant in real-life galaxy work but can become critical in artificial experiments. Alleviating this usually harmless initialization constraint changes the Ge et al. results completely, as was explained to the authors before their publication. We replicate their spectral fitting experiments, finding much smaller biases. Furthermore both bias and scatter in the derived properties all converge as S/N increases, as one would expect. We also show how the very output of the code provides ways of diagnosing anomalies in the fits. The code behaviour has been documented in careful and extensive experiments in the literature, but the biased analysis of Ge et al. is just not representative of starlight at all.