Search

We evaluate the effectiveness of early dark energy (EDE) in addressing the Hubble tension using the luminous red galaxy (LRG), quasar (QSO), and emission line galaxy (ELG) samples from the completed eBOSS survey. We perform cosmological parameter measurements based on full shape analysis of the power spectrum employing the effective field theory of large-scale structure (EFTofLSS). EDE is known to strongly suffer from volume projection effects, complicating cosmological constraints' interpretation. To quantify the volume projection effects within an EDE full shape analysis, we explore the impact of different prior choices on the nuisance parameters of EFTofLSS through an extensive mock study. We compare classical Gaussian priors to the non-informative Jeffreys prior, known to mitigate volume projection effects in ΛCDM. Our full shape analysis combines eBOSS and BOSS data with Planck , external Baryon Acoustic Oscillation (BAO), PantheonPlus, and SH0ES supernova data. EDE reduces the tension from 5.2σ to 3σ compared to ΛCDM, yielding |$H_0=71.73_{-0.86}^{+0.82}$| km s−1 Mpc−1 with |$f_\mathrm{EDE} = 0.1179_{-0.022}^{+0.025}$| (Gaussian priors) and |$H_0=72.03_{-0.87}^{+0.82}$| km s−1 Mpc−1 with |$f_\mathrm{EDE} = 0.1399_{-0.022}^{+0.023}$| (Jeffreys prior). Although the Hubble tension is mitigated compared to ΛCDM, the inclusion of eBOSS data amplifies the tension within EDE from 2σ to 3σ, in contrast to the full shape analysis of BOSS data with Planck , external BAO, PantheonPlus, and SH0ES. This highlights the significance of incorporating additional large-scale structure data in discussions concerning models aiming to resolve the Hubble tension. [ABSTRACT FROM AUTHOR]

Understanding the temporal characteristics of data from low-frequency radio telescopes is of importance in devising suitable calibration strategies. Application of time-series analysis techniques to data from radio telescopes can reveal a wealth of information that can aid in calibration. In this paper, we investigate singular spectrum analysis (SSA) as an analysis tool for radio data. We show the intimate connection between SSA and Fourier techniques. We develop the relevant mathematics starting with an idealized periodic dataset and proceeding to include various non-ideal behaviours. We propose a novel technique to obtain long-term gain changes in data, leveraging the periodicity arising from sky drift through the antenna beams. We also simulate several plausible scenarios and apply the techniques to a 30-day time series data collected during 2021 June from SITARA – a short-spacing two element interferometer for global 21-cm detection. Applying the techniques to real data, we find that the first reconstructed component – the trend – has a strong anti-correlation with the local temperature suggesting temperature fluctuations as the most likely origin for the observed variations in the data. We also study the limitations of the calibration in the presence of diurnal gain variations and find that such variations are the likely impediment to calibrating SITARA data with SSA. [ABSTRACT FROM AUTHOR]

We report results on the joint-fit of the NuSTAR and HXMT data for the black hole X-ray binary candidate MAXI J1535-571. The observations were obtained in 2017 when the source evolved through the hard, hard-intermediate, and soft-intermediate states over the rising phase of the outburst. After subtracting continuum components, X-ray reflection signatures are clearly showed in those observations. By modelling the relativistic reflection in detail, we find that the inner radius R in is relatively stable with R in ≲ 1.55 R g during the three states, which implies that the inner radius likely extends to the innermost stable circular orbit even in the bright hard state. When adopting R in = R ISCO, the spin parameter is constrained to be |$0.985_{-0.004}^{+0.002}$| at 90 per cent confidence (statistical only). The best-fitting results reveal that the inclination of the inner accretion disc is ∼70–74 deg, which notably conflicts with the apparent orientation of the ballistic jet (≤45 deg). In addition, both the photon index and the electron temperature increase during the transition from hard to soft state. It seems that the corona evolves from dense low-temperature in the low/hard state to tenuous high-temperature after the state transition, which indicates that the state transition is accompanied by the evolution of the coronal properties. [ABSTRACT FROM AUTHOR]

Empirical estimates of the band power covariance matrix are commonly used in cosmic microwave background (CMB) power spectrum analyses. While this approach easily captures correlations in the data, noise in the resulting covariance estimate can systematically bias the parameter fitting. Conditioning the estimated covariance matrix, by applying prior information on the shape of the eigenvectors, can reduce these biases and ensure the recovery of robust parameter constraints. In this work, we use simulations to benchmark the performance of four different conditioning schemes, motivated by contemporary CMB analyses. The simulated surveys measure the TT ,  TE , and EE power spectra over the angular multipole range 300 ≤ ℓ ≤ 3500 in Δℓ = 50 wide bins, for temperature map-noise levels of 10, 6.4, and |$2\, \mu$| K arcmin. We divide the survey data into N real = 30, 50, or 100 uniform subsets. We show the results of different conditioning schemes on the errors in the covariance estimate, and how these uncertainties on the covariance matrix propagate to the best-fitting parameters and parameter uncertainties. The most significant effect we find is an additional scatter in the best-fitting point, beyond what is expected from the data likelihood. For a minimal conditioning strategy, N real = 30, and a temperature map-noise level of 10 |$\, \mu$| K arcmin, we find the uncertainty on the recovered best-fitting parameter to be ×1.3 larger than the apparent posterior width from the likelihood (×1.2 larger than the uncertainty when the true covariance is used). Stronger priors on the covariance matrix reduce the misestimation of parameter uncertainties to |$\lt 1{{\ \rm per\ cent}}$|⁠. As expected, empirical estimates perform better with higher N real, ameliorating the adverse effects on parameter constraints. [ABSTRACT FROM AUTHOR]

The ensemble of chemical element abundance measurements for stars, along with precision distances and orbit properties, provides high-dimensional data to study the evolution of the Milky Way. With this third data release of the Galactic Archaeology with HERMES (GALAH) survey, we publish 678 423 spectra for 588 571 mostly nearby stars (81.2 per cent of stars are within <2 kpc), observed with the HERMES spectrograph at the Anglo-Australian Telescope. This release (hereafter GALAH+ DR3) includes all observations from GALAH Phase 1 (bright, main, and faint survey, 70 per cent), K2-HERMES (17 per cent), TESS-HERMES (5 per cent), and a subset of ancillary observations (8 per cent) including the bulge and >75 stellar clusters. We derive stellar parameters T eff, log  g , [Fe/H], v mic, v broad, and v rad using our modified version of the spectrum synthesis code Spectroscopy Made Easy (sme) and 1D marcs model atmospheres. We break spectroscopic degeneracies in our spectrum analysis with astrometry from Gaia  DR2 and photometry from 2MASS. We report abundance ratios [X/Fe] for 30 different elements (11 of which are based on non-LTE computations) covering five nucleosynthetic pathways. We describe validations for accuracy and precision, flagging of peculiar stars/measurements and recommendations for using our results. Our catalogue comprises 65 per cent dwarfs, 34 per cent giants, and 1 per cent other/unclassified stars. Based on unflagged chemical composition and age, we find 62 per cent young low- |$\alpha$|⁠ , 9 per cent young high- |$\alpha$|⁠ , 27 per cent old high- |$\alpha$|⁠ , and 2 per cent stars with [Fe/H] ≤ −1. Based on kinematics, 4 per cent are halo stars. Several Value-Added-Catalogues, including stellar ages and dynamics, updated after Gaia eDR3, accompany this release and allow chrono-chemodynamic analyses, as we showcase. [ABSTRACT FROM AUTHOR]

We present Bayesian active galactic nucleus (AGN) Decomposition Analysis for Sloan Digital Sky Survey (SDSS) Spectra, an open source spectral analysis code designed for automatic detailed deconvolution of AGN and host galaxy spectra, implemented in python , and designed for the next generation of large-scale surveys. The code simultaneously fits all spectral components, including power-law continuum, stellar line-of-sight velocity distribution, Fe  ii emission, as well as forbidden (narrow), permitted (broad), and outflow emission line features, all performed using Markov chain Monte Carlo to obtain robust uncertainties and autocorrelation analysis to assess parameter convergence. Our code also utilizes multiprocessing for batch fitting large samples of spectra while efficiently managing memory and computation resources and is currently being used in a cluster environment to fit thousands of SDSS spectra. We use our code to perform a correlation analysis of 63 SDSS type 1 AGNs with evidence of strong non-gravitational outflow kinematics in the [O  iii ] λ5007 emission feature. We confirm findings from previous studies that show the core of the [O  iii ] profile is a suitable surrogate for stellar velocity dispersion σ*, however there is evidence that the core experiences broadening that scales with outflow velocity. We find sufficient evidence that σ*, [O  iii ] core dispersion, and the non-gravitational outflow dispersion of the [O  iii ] profile form a plane whose fit results in a scatter of ∼0.1 dex. Finally, we discuss the implications, caveats, and recommendations when using the [O  iii ] dispersion as a surrogate for σ* for the M BH−σ* relation. [ABSTRACT FROM AUTHOR]

The advent of new time domain surveys and the imminent increase in astronomical data expose the shortcomings of traditional time series analysis (such as power spectra analysis) in characterizing the abundantly varied, complex, and stochastic light curves of Active Galactic Nuclei (AGNs). Recent applications of novel methods from non-linear dynamics have shown promise in characterizing higher modes of variability and time-scales in AGN. Recurrence analysis in particular can provide complementary information about characteristic time-scales revealed by other methods, as well as probe the nature of the underlying physics in these objects. Recurrence analysis was developed to study dynamical trajectories in phase space, which can be constructed from 1D time series such as light curves. We apply the methods of recurrence analysis to two optical light curves of Kepler -monitored AGN. We confirm the detection and period of an optical quasi-periodic oscillation in one AGN, and confirm multiple other time-scales recovered from other methods ranging from 5 to 60 d in both objects. We detect regions in the light curves that deviate from regularity, provide evidence of determinism and non-linearity in the mechanisms underlying one light curve (KIC 9650712), and determine realizations of a linear stochastic process describe the dominant variability in the other light curve (Zwicky 229–015). We discuss possible underlying processes driving the dynamics of the light curves and their diverse classes of variability. [ABSTRACT FROM AUTHOR]

We provide a detailed description of the Herschel /SPIRE Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF). The FF is an automated process designed to extract significant spectral features from SPIRE FTS data products. Optimizing the number of features found in SPIRE-FTS spectra is challenging. The wide SPIRE-FTS frequency range (447–1568 GHz) leads to many molecular species and atomic fine structure lines falling within the observed bands. As the best spectral resolution of the SPIRE-FTS is ∼1.2 GHz, there can be significant line blending, depending on the source type. In order to find, both efficiently and reliably, features in spectra associated with a wide range of sources, the FF iteratively searches for peaks over a number of signal-to-noise ratio (SNR) thresholds. For each threshold, newly identified features are rigorously checked before being added to the fitting model. At the end of each iteration, the FF simultaneously fits the continuum and features found, with the resulting residual spectrum used in the next iteration. The final FF products report the frequency of the features found and the associated SNRs. Line flux determination is not included as part of the FF products, as extracting reliable line flux from SPIRE-FTS data is a complex process that requires careful evaluation and analysis of the spectra on a case-by-case basis. The FF results are 100 per cent complete for features with SNR greater than 10 and 50–70 per cent complete at SNR of 5. The FF code and all FF products are publicly available via the Herschel Science Archive. [ABSTRACT FROM AUTHOR]

The determination of the fundamental properties (mass, separation, age, gravity, and atmospheric properties) of brown dwarf companions allows us to infer crucial informations on their formation and evolution mechanisms. Spectroscopy of substellar companions is available to date only for a limited number of objects (and mostly at very low resolution, R  < 50) because of technical limitations, i.e. contrast and angular resolution. We present medium resolution (R  = 350), coronagraphic long-slit spectroscopic observations with SPHERE of two substellar companions, HD 1160 B and HD 19467 B. We found that HD 1160 B has a peculiar spectrum that cannot be fitted by spectra in current spectral libraries. A good fit is possible only considering separately the Y + J and the H spectral band. The spectral type is between M5 and M7. We also estimated a T eff of 2800–2900 K and a log  g of 3.5–4.0 dex. The low surface gravity seems to favour young age (10–20 Myr) and low mass (∼20 MJup ) for this object. HD 19467 B is instead a fully evolved object with a T eff of ∼1000 K and log  g of ∼5.0 dex. Its spectral type is T6 ± 1. [ABSTRACT FROM AUTHOR]

We propose a new analysis methodology – FourIEr phase SpecTrum Analysis (FIESTA, or |$\mathit {\Phi }$| ESTA) – for the study of spectral line profile variability in Fourier space. The philosophy of |$\mathit {\Phi }$| ESTA is highlighted in its interpretation of a line deformation as various shifts of the composing Fourier modes. With this ability, |$\mathit {\Phi }$| ESTA excels in distinguishing the effects of a bulk shift in a line profile, from changes in a line profile shape. In other words, it can distinguish a radial velocity shift due to orbiting companions like planets, from an apparent radial velocity shift due to stellar variability (often referred to as 'jitter'). Most importantly, it can quantify the radial velocity impact of stellar jitter on each epoch. Our simulations show that (compared to a model that does not account for stellar activity), |$\mathit {\Phi }$| ESTA can almost triple the fraction of planets recovered with orbital parameters measured to within 10 per cent of their input parameters, when extracting a 2 m s−1 amplitude planetary signal in the midst of ∼2 m s−1 amplitude starspot jitter for high signal-to-noise ratio (>200 pixel−1) data. |$\mathit {\Phi }$| ESTA can also be used to identify stellar activity related periods in a periodogram analysis and classify relative amplitudes of stellar jitter and planetary signals, with examples for the analysis of HARPS data of the active star HD 224789 and the active planet-host star HD 103720. In the end, we demonstrate that |$\mathit {\Phi }$| ESTA's framework is working as well as other activity indicators in correlating with stellar jitter. [ABSTRACT FROM AUTHOR]

21 cm power spectrum observations have the potential to revolutionize our understanding of the epoch of reionization and dark energy, but require extraordinarily precise data analysis methods to separate the cosmological signal from the astrophysical and instrumental contaminants. This analysis challenge has led to a diversity of proposed analyses, including delay spectra, imaging power spectra, m-mode analysis, and numerous others. This diversity of approach is a strength, but has also led to a confusion within the community about whether insights gleaned by one group are applicable to teams working in different analysis frameworks. In this paper, we show that all existing analysis proposals can be classified into two distinct families based on whether they estimate the power spectrum of the measured or reconstructed sky. This subtle difference in the statistical question posed largely determines the susceptibility of the analyses to foreground emission and calibration errors, and ultimately the science different analyses can pursue. In this paper, we detail the origin of the two analysis families, categorize the analyses being actively developed, and explore their relative sensitivities to foreground contamination and calibration errors. [ABSTRACT FROM AUTHOR]

Transmission spectroscopy of exoplanets has the potential to provide precise measurements of atmospheric chemical abundances, in particular of hot Jupiters whose large sizes and high temperatures make them conducive to such observations. To date, several transmission spectra of hot Jupiters have revealed low amplitude features of water vapour compared to expectations from cloud-free atmospheres of solar metallicity. The low spectral amplitudes in such atmospheres could either be due to the presence of aerosols that obscure part of the atmosphere or due to inherently low abundances of H2O in the atmospheres. A recent survey of transmission spectra of ten hot Jupiters used empirical metrics to suggest atmospheres with a range of cloud/haze properties but with no evidence for H2O depletion. Here, we conduct a detailed and homogeneous atmospheric retrieval analysis of the entire sample and report the H2O abundances, cloud properties, terminator temperature profiles, and detection significances of the chemical species. This study finds that the majority of hot Jupiters have atmospheres consistent with subsolar H2O abundances at their day–night terminators. The best constrained abundances range from log(H2O) of |$-5.04^{+0.46}_{-0.30}$| to |$-3.16^{+0.66}_{-0.69}$|⁠, which compared to expectations from solar-abundance equilibrium chemistry correspond to |$0.018^{+0.035}_{-0.009}\times$| solar to |$1.40^{+4.97}_{-1.11}\times$| solar. Besides H2O we report statistical constraints on other chemical species and cloud/haze properties, including cloud/haze coverage fractions which range from |$0.18^{+0.26}_{-0.12}$| to |$0.76^{+0.13}_{-0.15}$|⁠. The retrieved H2O abundances suggest subsolar oxygen and/or supersolar C/O ratios, and can provide important constraints on the formation and migration pathways of hot giant exoplanets. [ABSTRACT FROM AUTHOR]

Massive companions in close orbits around G dwarfs are thought to undergo rapid orbital decay due to runaway tidal dissipation. We report here the discovery of WASP-128b, a brown dwarf discovered by the WASP survey transiting a G0V host on a |$2.2\, \mathrm{d}$| orbit, where the measured stellar rotation rate places the companion in a regime where tidal interaction is dominated by dynamical tides. Under the assumption of dynamical equilibrium, we derive a value of the stellar tidal quality factor |$\log {Q_\star ^{\prime }} = 6.96 \pm 0.19$|⁠. A combined analysis of ground-based photometry and high-resolution spectroscopy reveals a mass and radius of the host, |$M_\star = 1.16\pm 0.04\, \mathrm{M}_{\odot }$|⁠, |$R_\star = 1.16\pm 0.02\, \mathrm{R}_{\odot }$|⁠, and for the companion, |$M_\mathrm{b} = 37.5\pm 0.8\, M_\mathrm{J}$|⁠, |$R_\mathrm{b} = 0.94\pm 0.02\, R_\mathrm{J}$|⁠, placing WASP-128b in the driest parts of the brown dwarf desert, and suggesting a mild inflation for its age. We estimate a remaining lifetime for WASP-128b similar to that of some ultra-short period massive hot Jupiters, and note it may be a propitious candidate for measuring orbital decay and testing tidal theories. [ABSTRACT FROM AUTHOR]

The Galactic Archaeology with HERMES (GALAH) survey is a large-scale stellar spectroscopic survey of the Milky Way, designed to deliver complementary chemical information to a large number of stars covered by the Gaia mission. We present the GALAH second public data release (GALAH DR2) containing 342 682 stars. For these stars, the GALAH collaboration provides stellar parameters and abundances for up to 23 elements to the community. Here we present the target selection, observation, data reduction, and detailed explanation of how the spectra were analysed to estimate stellar parameters and element abundances. For the stellar analysis, we have used a multistep approach. We use the physics-driven spectrum synthesis of Spectroscopy Made Easy (SME) to derive stellar labels (T eff, log  g, [Fe/H], [X/Fe], v mic, v sin  i, $$A_{K_S}$$) for a representative training set of stars. This information is then propagated to the whole sample with the data-driven method of The Cannon. Special care has been exercised in the spectral synthesis to only consider spectral lines that have reliable atomic input data and are little affected by blending lines. Departures from local thermodynamic equilibrium (LTE) are considered for several key elements, including Li, O, Na, Mg, Al, Si, and Fe, using 1D marcs stellar atmosphere models. Validation tests including repeat observations, Gaia benchmark stars, open and globular clusters, and K2 asteroseismic targets lend confidence to our methods and results. Combining the GALAH DR2 catalogue with the kinematic information from Gaia will enable a wide range of Galactic Archaeology studies, with unprecedented detail, dimensionality, and scope. [ABSTRACT FROM AUTHOR]

The spectrum of a galaxy contains information about its physical properties. Classifying spectra using templates helps to elucidate the nature of a galaxy’s energy sources. In this paper, we investigate the use of self-organizing maps in classifying galaxy spectra against templates. We trained semi-supervised self-organizing map networks using a set of templates covering the wavelength range from far ultraviolet to near-infrared. The trained networks were used to classify the spectra of a sample of 142 galaxies with 0.5 < $$z$$ < 1 and the results compared to classifications performed using K -means clustering, a supervised neural network, and chi-squared minimization. Spectra corresponding to quiescent galaxies were more likely to be classified similarly by all methods while starburst spectra showed more variability. Compared to classification using chi-squared minimization or the supervised neural network, the galaxies classed together by the self-organizing map had more similar spectra. The class ordering provided by the 1D self-organizing maps corresponds to an ordering in physical properties, a potentially important feature for the exploration of large data sets. [ABSTRACT FROM AUTHOR]

We present a detailed analysis of the selection function of the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC). LSS-GAC was designed to obtain low-resolution optical spectra for a sample of more than 3 million stars in the Galactic anti-centre. The second release of value-added catalogues of the LSS-GAC (LSS-GAC DR2) contains stellar parameters, including radial velocity, atmospheric parameters, elemental abundances, and absolute magnitudes deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC between 2011 and 2014. For many studies using this data base, such as those investigating the chemodynamical structure of the Milky Way, a detailed understanding of the selection function of the survey is indispensable. In this paper, we describe how the selection function of the LSS-GAC can be evaluated to sufficient detail and provide selection function corrections for all spectroscopic measurements with reliable parameters released in LSS-GAC DR2. The results, to be released as new entries in the LSS-GAC value-added catalogues, can be used to correct the selection effects of the catalogue for scientific studies of various purposes. [ABSTRACT FROM AUTHOR]

We present ELDAR, a new method that exploits the potential of medium- and narrow-band filter surveys to securely identify active galactic nuclei (AGN) and determine their redshifts. Our methodology improves on traditional approaches by looking for AGN emission lines expected to be identified against the continuum, thanks to the width of the filters. To assess its performance, we apply ELDAR to the data of the ALHAMBRA (Advance Large Homogeneous Area Medium Band Redshift Astronomical) survey, which covered an effective area of 2.38 deg2 with 20 contiguous medium-band optical filters down to F814W ≃ 24.5. Using two different configurations of ELDAR in which we require the detection of at least two and three emission lines, respectively, we extract two catalogues of type-I AGN. The first is composed of 585 sources (79 per cent of them spectroscopically unknown) down to F814W = 22.5 at zphot > 1, which corresponds to a surface density of 209 deg-2. In the second, the 494 selected sources (83 per cent of them spectroscopically unknown) reach F814W= 23 at zphot > 1.5, for a corresponding number density of 176 deg-2. Then, using samples of spectroscopically known AGN in the ALHAMBRA fields, for the two catalogues we estimate a completeness of 73 per cent and 67 per cent, and a redshift precision of 1.01 per cent and 0.86 per cent (with outliers fractions of 8.1 per cent and 5.8 per cent). At z > 2, where our selection performs best, we reach 85 per cent and 77 per cent completeness and we find no contamination from galaxies. [ABSTRACT FROM AUTHOR]

Spectra observed with the Ultraviolet and Visual Echelle Spectrograph on the European Southern Observatory's VLT exhibit long-range wavelength distortions. These distortions impose a systematic error on high-precision measurements of the fine-structure constant, α, derived from intervening quasar absorption systems. If the distortion is modelled using a model that is too simplistic, the resulting bias in Δα/α away from the true value can be larger than the statistical uncertainty on the α measurement. If the effect is ignored altogether, the same is true. If the effect is modelled properly, accounting for the way in which final spectra are generally formed from the co-addition of exposures made at several different instrumental settings, the effect can be accurately removed and the correct Δα/α recovered. [ABSTRACT FROM AUTHOR]

This study presents a temporal and spectral analysis of the prompt emission of two high-redshift gamma-ray bursts (GRBs), 120521C at z ~ 6 and 130606A at z ~ 5.91, using data obtained from the Swift-XRT/BAT and the Suzaku-WAM simultaneously. Based on followup XRT observations, the longest durations of the prompt emissions were approximately 80 s (120521C) and 360 s (130606A) in the rest-frames of the two GRBs. These objects are thus categorized as long-duration GRBs; however, the durations are short compared with the predicted duration of GRBs originating from first-generation stars. Because of the wide bandpass of the instruments, covering the ranges 15 keV-5MeV (BAT-WAM) and 0.3 keV-5.0 MeV (XRT-BAT-WAM), we could successfully determine the νFν peak energies Esrcpeak in the rest-frame and isotropic-equivalent radiated energies Eiso; Esrcpeak = 682-207+845 keV and Eiso = (8.25-1.96+2.24) × 1052 erg for 120521C, and Epeaksrc = 1209-304+553 keV and Eiso = (2.82-0.71+0.17) × 1053 erg for 130606A. These obtained characteristic parameters are in accordance with the well-known relationship between Epeaksrc and Eiso (Amati relationship). In addition, we examined the relationships between Epeaksrc and the 1-s peak luminosity, Lp, and between Epeaksrc and the geometrical corrected radiated energy, Eγ, and confirmed the Epeaksrc-Lp (Yonetoku) and Epeaksrc-Eγ (Ghirlanda) relationships. The results imply that these high-redshift GRBs at z ~ 6, which are expected to have radiated during the reionization epoch, have properties similar to those of low-redshift GRBs regarding X-ray prompt emission. [ABSTRACT FROM AUTHOR]

We present two wide-field catalogues of photometrically selected emission line galaxies (ELGs) at z ≈ 0.8 covering about 2800 deg²over the south galactic cap. The catalogues were obtained using a Fisher discriminant technique described in a companion paper. The two catalogues differ by the imaging used to define the Fisher discriminant: the first catalogue includes imaging from the Sloan Digital Sky Survey and the Wide-field Infrared Survey Explorer, the second also includes information from the South Galactic Cap U-band Sky Survey. Containing respectively 560 045 and 615 601 objects, they represent the largest ELG catalogues available today and were designed for the ELG programme of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We study potential sources of systematic variation in the angular distribution of the selected ELGs due to fluctuations of the observational parameters. We model the influence of the observational parameters using a multivariate regression and implement a weighting scheme which allows effective removal of all of the systematic errors induced by the observational parameters. We show that fluctuations in the imaging zero-points of the photometric bands have minor impact on the angular distribution of objects in our catalogues. We compute the angular clustering of both catalogues and show that our weighting procedure effectively removes spurious clustering on large scales. We fit a model to the small-scale angular clustering, showing that the selections have similar biases of 1.35/Da(z) and 1.28/Da(z). Both catalogues are publicly available. [ABSTRACT FROM AUTHOR]

Since the volume accessible to galaxy surveys is fundamentally limited, it is extremely important to analyse available data in the most optimal fashion. One way of enhancing the cosmological information extracted from the clustering of galaxies is by weighting the galaxy field. The most widely used weighting schemes assign weights to galaxies based on the average local density in the region (FKP weights) and their bias with respect to the dark matter field (PVP weights). They are designed to minimize the fractional variance of the galaxy power-spectrum. We demonstrate that the currently used bias dependent weighting scheme can be further optimized for specific cosmological parameters. We develop a procedure for computing the optimal weights and test them against mock catalogues for which the values of all fitting parameters, as well as the input power-spectrum are known. We show that by applying these weights to the joint power-spectrum of emission line galaxies and luminous red galaxies from the Dark Energy Spectroscopic Instrument survey, the variance in the measured growth rate parameter can be reduced by as much as 36 per cent. [ABSTRACT FROM AUTHOR]

Based on the XMM-Newton large programme on SN1006 and our newly developed tools for spatially resolved spectroscopy analysis as described in Li et al. (Paper I), we study the thermal emission from interstellar medium (ISM) and ejecta of SN1006 by analysing the spectra extracted from 583 tessellated regions dominated by thermal emission. With some key improvements in spectral analysis as compared to Paper I, we obtain much better spectral fitting results with significantly less residuals. The spatial distributions of the thermal and ionization states of the ISM and ejecta show significantly different features, which are in general consistent with a scenario that the ISM (ejecta) is heated and ionized by the forward (reverse) shock propagating outward (inward). Different heavy elements show different spatial distributions so different origins, with Ne mostly from the ISM, Si and S mostly from the ejecta, and O and Mg from both the ISM and ejecta. Fe L-shell line emissions are only detected in a small shell-like region south-east (SE) to the centre of SN1006, indicating that most of the Fe-rich ejecta has not yet or just recently been reached by the reverse shock. The overall abundance patterns of the ejecta for most of the heavy elements, except for Fe and sometimes for S, are consistent with typical Type Ia SN products. The north-west (NW) half of the supernova remnant interior between theNWshell and the soft X-ray brighter SE half probably represents a region with turbulently mixed ISM and ejecta, so has enhanced emission from O, Mg, Si, and S, lower ejecta temperature, and a large diversity of ionization age. In addition to the asymmetric ISM distribution, an asymmetric explosion of the progenitor star is also needed to explain the asymmetric ejecta distribution. [ABSTRACT FROM AUTHOR]

The existence of multiple subclasses of Type Ia supernovae (SNe Ia) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate identification of subtypes of SNe Ia through the establishment of a hierarchical group structure in the continuous space of spectral diversity formed by these objects. Using deep learning, we were capable of performing such identification in a four-dimensional feature space (+1 for time evolution), while the standard principal component analysis barely achieves similar results using 15 principal components. This is evidence that the progenitor system and the explosion mechanism can be described by a small number of initial physical parameters. As a proof of concept, we show that our results are in close agreement with a previously suggested classification scheme and that our proposed method can grasp the main spectral features behind the definition of such subtypes. This allows the confirmation of the velocity of lines as a first-order effect in the determination of SN Ia subtypes, followed by 91bg-like events. Given the expected data deluge in the forthcoming years, our proposed approach is essential to allow a quick and statistically coherent identification of SNe Ia subtypes (and outliers). All tools used in this work were made publicly available in the PYTHON package Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy (DRACULA) and can be found within COINtoolbox. [ABSTRACT FROM AUTHOR]

Many physical parameters in astrophysics are derived using the ratios of two observed quantities. If the relative uncertainties on measurements are small enough, uncertainties can be propagated analytically using simplifying assumptions, but for large normally distributed uncertainties, the probability distribution of the ratio become skewed, with a modal value offset from that expected in Gaussian uncertainty propagation. Furthermore, the most likely value of a ratio A/B is not equal to the reciprocal of the most likely value of B/A. The effect is most pronounced when the uncertainty on the denominator is larger than that on the numerator. We show that this effect is seen in an analysis of 12 126 spectra from the Sloan Digital Sky Survey (SDSS). The intrinsically fixed ratio of the [O III] lines at 4959 and 5007 Å is conventionally expressed as the ratio of the stronger line to the weaker line. Thus, the uncertainty on the denominator is larger, and non-Gaussian probability distributions result. By taking this effect into account, we derive an improved estimate of the intrinsic 5007/4959 ratio. We obtain a value of 3.012 ± 0.008, which is slightly but statistically significantly higher than the theoretical value of 2.98. We further investigate the suggestion that fluxes measured from emission lines in noisy spectra are strongly biased upwards. We were unable to detect this effect in the SDSS line flux measurements, and we could not reproduce the results of Rola and Pelat who first described this bias. We suggest that the magnitude of this effect may depend strongly on the specific fitting algorithm used. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine the values of radiative parameters for Ag II by means of a semi-empirical method. The calculated values of oscillator strengths and lifetimes are, in majority of cases, in a very good agreement with accurate experimental data. Our calculation procedures allowed us to obtain the values of transition integrals and predict the values of oscillator strengths for the transitions in a wide spectral range and radiative lifetimes for excited levels. Moreover, the predicted values will be useful when the experimental values are not known. [ABSTRACT FROM AUTHOR]

It is important to correctly subtract point sources from radio-interferometric data in order to measure the power spectrum of diffuse radiation like the Galactic synchrotron or the Epoch of Reionization 21-cm signal. It is computationally very expensive and challenging to image a very large area and accurately subtract all the point sources from the image. The problem is particularly severe at the sidelobes and the outer parts of the main lobe where the antenna response is highly frequency dependent and the calibration also differs from that of the phase centre. Here, we show that it is possible to overcome this problem by tapering the sky response. Using simulated 150MHz observations, we demonstrate that it is possible to suppress the contribution due to point sources from the outer parts by using the Tapered Gridded Estimator to measure the angular power spectrum Cl of the sky signal. We also show from the simulation that this method can self-consistently compute the noise bias and accurately subtract it to provide an unbiased estimation of Cl. [ABSTRACT FROM AUTHOR]

I present the automated line fitting algorithm, ALFA, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which require the identification of spectral features suspected to be emission lines, ALFA instead uses a list of lines which are expected to be present to construct a synthetic spectrum. The parameters used to construct the synthetic spectrum are optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. I show that the results are in excellent agreement with those measured manually for a number of spectra. Where discrepancies exist, the manually measured fluxes are found to be less accurate than those returned by ALFA. Together with the code NEAT, ALFA provides a powerful way to rapidly extract physical information from observations, an increasingly vital function in the era of highly multiplexed spectroscopy. The two codes can deliver a reliable and comprehensive analysis of very large data sets in a few hours with little or no user interaction. [ABSTRACT FROM AUTHOR]

We present a new 'supercalibration' technique for measuring systematic distortions in the wavelength scales of high-resolution spectrographs. By comparing spectra of 'solar twin' stars or asteroids with a reference laboratory solar spectrum, distortions in the standard thorium-argon calibration can be tracked with ~10ms-1 precision over the entire optical wavelength range on scales of both echelle orders (~50-100Å) and entire spectrographs arms (~1000-3000Å). Using archival spectra from the past 20 yr, we have probed the supercalibration history of the Very Large Telescope-Ultraviolet and Visible Echelle Spectrograph (VLT-UVES) and Keck-High Resolution Echelle Spectrograph (HIRES) spectrographs. We find that systematic errors in their wavelength scales are ubiquitous and substantial, with long-range distortions varying between typically ±200ms-1 per 1000Å. We apply a simple model of these distortions to simulated spectra that characterize the large UVES and HIRES quasar samples which previously indicated possible evidence for cosmological variations in the fine-structure constant, a. The spurious deviations in a produced by the model closely match important aspects of the VLT-UVES quasar results at all redshifts and partially explain the HIRES results, though not self-consistently at all redshifts. That is, the apparent ubiquity, size and general characteristics of the distortions are capable of significantly weakening the evidence for variations in a from quasar absorption lines. [ABSTRACT FROM AUTHOR]

Cross-correlating the Planck High Frequency Instrument maps against quasars from the Sloan Digital Sky Survey DR7, we estimate the intensity distribution of the cosmic infrared background (CIB) over the redshift range 0 < z < 5. We detect redshift-dependent spatial crosscorrelations between the two data sets using the 857,545, and 353 GHz channels and we obtain upper limits at 217 GHz consistent with expectations. At all frequencies with detectable signal we infer a redshift distribution peaking around z ~ 1.2 and find the recovered spectrum to be consistent with emission arising from star-forming galaxies. By assuming simple modified blackbody and Kennicutt relations, we estimate dust and star formation rate density as a function of redshift, finding results consistent with earlier multiwavelength measurements over a large portion of cosmic history. However, we note that, lacking mid-infrared coverage, we are not able to make an accurate determination of the mean temperature for the dust responsible for the CIB. Our results demonstrate that clustering-based redshift inference is a valuable tool for measuring the entire evolution history of the cosmic star formation rate from a single and homogeneous data set. [ABSTRACT FROM AUTHOR]

We investigate the potential and accuracy of clustering-based redshift estimation using the method proposed by Ménard et al. This technique enables the inference of redshift distributions from measurements of the spatial clustering of arbitrary sources, using a set of reference objects for which redshifts are known. We apply it to a sample of spectroscopic galaxies from the Sloan Digital Sky Survey (SDSS) and show that, after carefully controlling the sampling efficiency over the sky, we can estimate redshift distributions with high accuracy. Probing the full colour space of the SDSS galaxies, we show that we can recover the corresponding mean redshifts with an accuracy ranging from δz = 0.001 to 0.01. We indicate that this mapping can be used to infer the redshift probability distribution of a single galaxy. We show how the lack of information on the galaxy bias limits the accuracy of the inference and show comparisons between clustering redshifts and photometric redshifts for this data set. This analysis demonstrates, using real data, that clustering-based redshift inference provides a powerful data-driven technique to explore the redshift distribution of arbitrary data sets, without any prior knowledge of the spectral energy distribution of the sources. [ABSTRACT FROM AUTHOR]

The analysis of gamma-ray burst (GRB) spectra with multicomponent emission models has become an important part of the field. In particular, multicomponent analysis where one component is a blackbody representing emission from a photosphere has enabled both a more detailed understanding of the energy content of the jet as well as the ability to examine the dynamic structure of the outflow. While the existence of a blackbody-like component has been shown to be significant and not a byproduct of background fluctuations, it is very possible that it can be an artefact of spectral evolution of a single component that is being poorly resolved in time. Herein, this possibility is tested by simulating a single component evolving in time and then folding the spectra through the Fermi detector response to generate time-tagged event Gamma-ray Burst Monitor (GBM) data. We then fit both the time-integrated and -resolved generated spectral data with a multicomponent model using standard tools. It is found that in time-integrated spectra, a blackbody can be falsely identified due to the spectral curvature introduced by the spectral evolution. However, in a time-resolved analysis defined by time bins that can resolve the evolution of the spectra, the significance of the falsely identified blackbody is very low. Additionally, the evolution of the artificial blackbody parameters does not match the recurring behaviour that has been identified in the actual observations. These results reinforce the existence of the blackbody found in time-resolved analysis of GRBs and stress the point that caution should be taken when using time-integrated spectral analysis for identifying physical properties of GRBs. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method for the extraction of astronomical spectra from two-dimensional (2D) multifibre spectrographs based on the regularized least-squares QR-factorization (LSQR) algorithm. We address two issues: we propose a modified Gaussian point spread function (PSF) for modelling the 2D PSF from multi-emission-line gas-discharge lamp images (arc images), and we develop an efficient deconvolution method to extract spectra in real circumstances. The proposed modified 2D Gaussian PSF model can fit various types of 2D PSFs, including different radial distortion angles and ellipticities. We adopt the regularized LSQR algorithm to solve the sparse linear equations constructed from the sparse convolution matrix, which we designate the deconvolution spectrum extraction method. Furthermore, we implement a parallelized LSQR algorithm based on graphics processing unit programming in the Compute Unified Device Architecture to accelerate the computational processing. Experimental results illustrate that the proposed extraction method can greatly reduce the computational cost and memory use of the deconvolution method and, consequently, increase its efficiency and practicability. In addition, the proposed extraction method has a stronger noise tolerance than other methods, such as the boxcar (aperture) extraction and profile extraction methods. Finally, we present an analysis of the sensitivity of the extraction results to the radius and full width at half-maximum of the 2D PSF. [ABSTRACT FROM PUBLISHER]

Accurate parametrization of galaxies detected in the 21-cm H i emission is of fundamental importance to the measurement of commonly used indicators of galaxy evolution, including the Tully–Fisher relation and the H i mass function. Here, we propose a new analytic function, named the ‘busy function’, that can be used to accurately describe the characteristic double-horn H i profile of many galaxies. The busy function is a continuous, differentiable function that consists of only two basic functions, the error function, erf(x), and a polynomial, |x|n, of degree n ≥ 2. We present the basic properties of the busy function and illustrate its great flexibility in fitting a wide range of H i profiles from the Gaussian profiles of dwarf galaxies to the broad, asymmetric double-horn profiles of spiral galaxies. Applications of the busy function include the accurate and efficient parametrization of observed H i spectra of galaxies and the construction of spectral templates for simulations and matched-filtering algorithms. We demonstrate the busy function's power by automatically fitting it to the H i spectra of 1000 galaxies from the HI Parkes All-Sky Survey (HIPASS) Bright Galaxy Catalog, using our own c/c++ implementation, and comparing the resulting parameters with the catalogued ones. We also present two methods for determining the uncertainties of observational parameters derived from the fit. [ABSTRACT FROM AUTHOR]

Determining accurate redshift distributions for very large samples of objects has become increasingly important in cosmology. We investigate the impact of extending cross-correlation based redshift distribution recovery methods to include small-scale clustering information. The major concern in such work is the ability to disentangle the amplitude of the underlying redshift distribution from the influence of evolving galaxy bias. Using multiple simulations covering a variety of galaxy bias evolution scenarios, we demonstrate reliable redshift recoveries using linear clustering assumptions well into the non-linear regime for redshift distributions of narrow redshift width. Including information from intermediate physical scales balances the increased information available from clustering and the residual bias incurred from relaxing of linear constraints. We discuss how breaking a broad sample into tomographic bins can improve estimates of the redshift distribution, and present a simple bias removal technique using clustering information from the spectroscopic sample alone. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, we study how the spectral information is transmitted through a 1:61 photonic lantern (PL) when illuminating the multimode (MM) end with a point source. We found that the spectrum undergoes two major effects between the MM input and the independent single-mode (SM) outputs of the PL. First, at resolution R = 775 (at 1550 nm), the overall output spectrum envelope strongly differs from SM to SM outputs. The spectra measured at the 61 SM outputs also vary when the small point object (10 μm in diameter, compared with the 100 μm diameter MM core) is moved across the MM fibre end-face of the PL. However, the sum of all the spectra measured at the SM outputs is very close to the spectrum of the point source, and is insensitive to the position of the point source. Secondly, at resolution R = 77 500 a fine 150 pm periodic structure was observed at the SM outputs. We found that a PL in the MM-SM configuration (i.e. MM input/SM outputs) is a very stable system regarding variations of the transmitted spectra when it is left mechanically non-perturbated and only submitted to environment-related changes, compared to a conventional step-index MM fibre of same core diameter. The latter clearly shows characteristic modal noise. Furthermore, we showed that at resolution R = 77 500 the sum of the spectra measured at 61 the SM outputs is very close to the spectrum of the point source, and does not present the 150 pm periodic oscillations. We also studied two PLs spliced together in the MM-SM-MM configuration and the results showed that the spliced PLs perform very well as mode scramblers, especially under conditions where conventional step-index MM fibres usually fail at performing effective scrambling. [ABSTRACT FROM AUTHOR]

ABSTRACT We present the results of a spectroscopic survey performed in the outskirts of the globular cluster NGC 1851 with VIsible MultiObject Spectrograph (VIMOS)/Very Large Telescope (VLT). The radial velocities of 107 stars in a region between 12 and 33 arcmin around the cluster have been derived. We clearly identify the cluster stellar population over the entire field of view, indicating the presence of a significant fraction of stars outside the tidal radius predicted by King models. We also find tentative evidence of a cold (σv ≤ 20 km s−1) peak in the distribution of velocities at vr ∼ 180 km s−1 constituted mainly by main-sequence stars whose location in the colour-magnitude diagram is compatible with a stream at a similar distance to this cluster. If confirmed, this evidence would strongly support the extragalactic origin of this feature. [ABSTRACT FROM AUTHOR]

ABSTRACT Using the gamma-ray bursts (GRBs) simultaneously detected by Swift/Burst Alert Telescope (BAT) and Fermi/Gamma-ray Burst Monitor (GBM), we performed a joint spectral and temporal analysis of the prompt emission data and confirmed the rough correlation between the BAT-band photon index ΓBAT and the peak spectral energy Epeak. With the redshift-known subsample, we derived the isotropic gamma-ray energy Eγ, iso and also confirmed the Eγ,iso − Epeak,rest relation, with a larger scatter than the Amati sample but consistent with GBM team analyses. We also compare the T90 values derived in the GBM band with those derived in the BAT band and find that for long GRBs the BAT T90 is usually longer than the GBM T90, while for short GRBs the trend reverses. This is consistent with the soft/hard nature of long/short GRBs and suggests the importance of an energy-dependent temporal analysis of GRBs. [ABSTRACT FROM AUTHOR]

ABSTRACT We propose a method to estimate non-Gaussian error bars on the matter power spectrum from galaxy surveys in the presence of non-trivial survey selection functions. The estimators are often obtained from formalisms like Feldmann, Kaiser and Peacock (FKP) and pseudo-Karhunen-Loève (PKL), which rely on the assumption that the underlying field is Gaussian. The Monte Carlo method is more accurate but involves the tedious process of running and cross-correlating a large number of N-body simulations, in which the survey volume is embedded. From 200 N-body simulations, we extract a non-linear covariance matrix as a function of two scales and of the angle between two Fourier modes. All the non-Gaussian features of that matrix are then simply parametrized in terms of a few fitting functions and eigenvectors. We furthermore develop a fast and accurate strategy that combines our parametrization with a general galaxy survey selection function, and incorporate non-Gaussian Poisson uncertainty. We describe how to incorporate these two distinct non-Gaussian contributions into a typical analysis pipeline, and apply our method with the selection function from the 2dFGRS. We find that the observed Fourier modes correlate at much larger scales than that predicted by both FKP formalism or pure N-body simulations in a 'top hat' selection function. In particular, the observed Fourier modes are already 50 per cent correlated at k∼ 0.1 h Mpc−1, and the non-Gaussian fractional variance on the power spectrum [] is about a factor of 3.0 larger than the FKP prescription. At k∼ 0.4 h Mpc−1, the deviations are an order of magnitude. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper describes the duchamp source finder, a piece of software designed to find and describe sources in three-dimensional, spectral-line data cubes. duchamp has been developed with H i (neutral hydrogen) observations in mind, but is widely applicable to many types of astronomical images. It features efficient source detection and handling methods, noise suppression via smoothing or multi-resolution wavelet reconstruction, and a range of graphical and text-based outputs to allow the user to understand the detections. This paper details some of the key algorithms used and illustrates the effectiveness of the finder on different data sets. [ABSTRACT FROM AUTHOR]

We present the frequency-resolved energy spectra (FRS) of the low-mass X-ray binary dipper XB during persistent emission in four different frequency bands using an archival XMM–Newton observation. FRS method helps to probe the inner zones of an accretion disc. XB is an Atoll source and a type-I burster. We find that the FRS is well described by a single blackbody component with kT in a range 1.0–1.4 keV responsible for the source variability in the frequency ranges of 0.002–0.04 and 0.07–0.3 Hz. We attribute this component to the accretion disc and possibly emission from an existing boundary layer supported by radiation pressure. The appearance of the blackbody component in the lower frequency ranges and disappearance towards the higher frequencies suggests that it may also be a disc-blackbody emission. We detect a different form of FRS for the higher frequency ranges of 0.9–6 and 8–30 Hz which is modelled best with a power law and a Gaussian emission line at keV with an equivalent width of and keV for the two frequency ranges, respectively. This iron fluorescence line detected in the higher frequency ranges of spectra shows the existence of reflection in this system within the inner disc regions. The conventional spectrum of the source also shows a weak broad emission line around 6.6 keV. In addition, we find that the 0.9–6 Hz frequency band shows two quasi-periodic oscillation (QPO) peaks at and Hz at about 2.8σ–3.1σ confidence level. These are consistent with the previously detected ∼1 Hz QPO from this source. We believe they relate to the reflection phenomenon. The emission from the reflection region, being a variable spectral component in this system, originates from the inner regions of the disc with a maximum size of and a minimum size of calculated using light travel time considerations and our frequency-resolved spectra. [ABSTRACT FROM AUTHOR]

We describe an exact, flexible and computationally efficient algorithm for a joint inference of the large-scale structure and its power spectrum, building on a Gibbs sampling framework and present its implementationares (Algorithm for REconstruction and Sampling).ares is designed to reconstruct the 3D power spectrum together with the underlying dark matter density field in a Bayesian framework, under the reasonable assumption that the long-wavelength Fourier components are Gaussian distributed. As a resultares does not only provide a single estimate but samples from the joint posterior of the power spectrum and density field conditional on a set of observations. This enables us to calculate any desired statistical summary, in particular we are able to provide joint uncertainty information. We apply our method to mock catalogues, with highly structured observational masks and selection functions, in order to demonstrate its ability to infer the power spectrum from real data sets, while fully accounting for any mask induced mode coupling. [ABSTRACT FROM AUTHOR]

We present a semi-analytical method to investigate the systematic effects and statistical uncertainties of the calculated angular power spectrum when incomplete spherical maps are used. The computed power spectrum suffers in particular a loss of angular frequency resolution, which can be written as , where is the effective maximum extent of the partial spherical maps. We propose a correction algorithm to reduce systematic effects on the estimated , as obtained from the partial map projection on the spherical harmonic basis. We have derived near-optimal bands and weighting functions in -space for the power spectrum calculation using small maps, and a correction algorithm for partially masked spherical maps that contain information on the angular correlations on all scales. [ABSTRACT FROM AUTHOR]

We present a comparison between Gaussian processes (GPs) and artificial neural networks (ANNs) as methods for determining photometric redshifts for galaxies, given training-set data. In particular, we compare their degradation in performance as the training-set size is degraded in ways which might be caused by the observational limitations of spectroscopy. Using publicly available regression codes, we find that performance with large, complete training sets is very similar, although the ANN achieves slightly smaller rms errors. Training sets with brighter magnitude limits than the test data do not strongly affect the performance of either algorithm, until the limits are so severe that they remove almost all of the high-redshift training objects. Similarly, the introduction of a plausible number (up to 10 per cent) of inaccurate redshifts into the training set has little effect on either method. However, if the size of the training set is reduced by random sampling, the rms errors of both methods increase, but they do so to a lesser extent and in a much smoother manner for the case of GP regression; for the example presentedannz has rms errors 20 per cent worse than GP regression in the small training-set limit. Also, when training objects are removed at redshifts , to simulate the effects of the ‘redshift desert’ of optical spectroscopy, the GP regression is successful at interpolating across the redshift gap, while the ANN suffers from strong bias for test objects in this redshift range. Overall, GP regression has attractive properties for photometric redshift estimation, particularly for deep, high-redshift surveys where it is difficult to obtain a large, complete training set. At present, unlike the ANN code, public GP regression codes do not take account of inhomogeneous measurement errors on the photometric data, and thus cannot estimate reliable uncertainties on the predicted redshifts. However, a better treatment of errors is in principle possible, and the promising results in this paper suggest that such improved GP algorithms should be pursued. [ABSTRACT FROM AUTHOR]

Literature photometry and new high-resolution spectroscopy of V831 Cen are presented and analysed. Light and radial velocity curve fittings confirm the central pair of this young multiple system to be close to contact. Absolute parameters are found as follows: = 13 000 ± 300 K, T2= 11 800 ± 300 K; distance of 110 ± 10 pc and age of . Detailed examination of the spectrograms indicates the third component (V831 Cen B) to be an Ap star. The orbit of the third star about the close binary is analysed using historic astrometric measurements. This allows an estimate of the third star's mass to be about 2.5 M⊙, but this is sensitive to the adopted distance and inclination values. It is, however, confirmed by the measured radial velocity of the third star. To some extent, such analysis can also be applied to the fourth star (V831 Cen C). The derived properties can be checked against the system's membership of the Scorpius–Centaurus OB2 association. [ABSTRACT FROM AUTHOR]

We present the first spectroscopic observations for the galaxies ESO 089−G018 (hereafter G18, an Sb(?)-type galaxy seen nearly edge-on) and ESO 089−G019 (hereafter G19, an SA(s): a peculiar galaxy), extracted from the sample of ring-shaped galaxies compiled in Faúndez-Abans & de Oliveira-Abans. The main goal of this work is to investigate the spectral classification using the three line-ratio diagrams, called diagnostic diagrams, of Veilleux & Osterbrock. However, in order to separate the different types of galaxies [H ii galaxies, Seyfert 2 galaxies and low-ionization nuclear emission-line region galaxies (LINERs)] we have to used empirical boundaries between them. Based on the observed spectra, we suggest G18 is a ‘weak-[O i] LINER’ or even a ‘transition object’ or LINER/H ii. In the case of G19, we see Hβ in absorption and no [O iii] lines, impeding the [O iii]/Hβ ratio to be estimated. However, other lines ratios have been evaluated for the discussion. We classify the nature of G19 as ambiguous, because of the difficulty in determining its ionizing source (narrow-line active galactic nuclei or H ii galaxies) in different diagnostic diagrams. The errors in the fluxes were mostly caused by uncertainties in the placement of the continuum level. We have estimated nuclear redshift of (G18) and (G19), corresponding to a heliocentric velocity of 10 246 and 11 734 km s−1, respectively. Some other physical parameters have been derived whenever possible. All spectra were reduced and analysed in a homogeneous way with the standardiraf procedures. [ABSTRACT FROM AUTHOR]

Many astrophysical sources, especially compact accreting sources, show strong, random brightness fluctuations with broad power spectra in addition to periodic or quasi-periodic oscillations (QPOs) that have narrower spectra. The random nature of the dominant source of variance greatly complicates the process of searching for possible weak periodic signals. We have addressed this problem using the tools of Bayesian statistics; in particular, using Markov Chain Monte Carlo techniques to approximate the posterior distribution of model parameters, and posterior predictive model checking to assess model fits and search for periodogram outliers that may represent periodic signals. The methods developed are applied to two example data sets, both long XMM–Newton observations of highly variable Seyfert 1 galaxies: and Mrk 766. In both cases, a bend (or break) in the power spectrum is evident. In the case of the previously reported QPO is found but with somewhat weaker statistical significance than reported in previous analyses. The difference is due partly to the improved continuum modelling, better treatment of nuisance parameters and partly to different data selection methods. [ABSTRACT FROM AUTHOR]

In this paper, we present a foreground analysis of the Wilkinson Microwave Anisotropy Probe ( WMAP) 5-year data using thefastica algorithm, improving on the treatment of the WMAP 3-year data in Bottino et al. We determine coupling coefficients between the WMAP data and templates commonly used to trace the dominant foreground emissions, and use them to study the spectral properties of the diffuse emissions and subsequently to clean the data. We confirm the dependence of the values of these scaling factors on the extension of the mask used in the analysis and we again demonstrate some anomalies when the mask is adopted that remain unexplained. We also revisit the nature of the free–free spectrum with the emphasis on attempting to confirm or otherwise the spectral feature claimed in Dobler et al. and explained in terms of spinning dust emission in the warm ionized medium. With the application of different Galactic cuts, the index is always flatter than the canonical value of 2.14 except for the mask which is steeper. Irrespective of this, we cannot confirm the presence of any feature in the free–free spectrum. We experiment with a more extensive approach to the cleaning of the data, introduced in connection with the iterative application offastica. We confirm the presence of a residual foreground whose spatial distribution is concentrated along the Galactic plane, with pronounced emission near the Galactic Centre. This is consistent with the WMAP haze detected in Finkbeiner et al. Finally, we attempted to perform the same analysis on full-sky (FS) maps. The code returns good results even for those regions where the cross-talk among the components is high. However, slightly better results in terms of the possibility of reconstructing an FS CMB map are achieved with a simultaneous analysis of both the five WMAP maps and foreground templates. None the less, some residuals are still present and detected in terms of an excess in the cosmic microwave background power spectrum, on small angular scales. Therefore, a minimal mask for the brightest regions of the plane is necessary, and has been defined. [ABSTRACT FROM AUTHOR]

We use signal enhancement techniques and a matched filter analysis to search for the K-band spectroscopic absorption signature of the close orbiting extrasolar giant planet, HD 189733b. With time-series observations taken with the Near Infrared Spectrometer (NIRSPEC) at Keck II, we investigate the relative abundances of H2O and carbon bearing molecules, which have now been identified in the dayside spectrum of HD 189733b. We detect a candidate planet signature with a low level of significance, close to the ∼153 km s−1 velocity amplitude of HD 189733b. However, some systematic variations, mainly due to imperfect telluric line removal, remain in the residual spectral time series in which we search for the planetary signal. Using principal components analysis, the effects of this pattern noise may be reduced. Since a balance between the optimum systematic noise removal and minimum planetary signal attenuation must be struck, we find that residuals, which are able to give rise to candidate planet signatures, remain. The robustness of our candidate signature is therefore assessed, enabling us to conclude that it is not possible to confirm the presence of any planetary signal which appears at contrasts deeper than the 95.4 per cent confidence level. Our search does not enable us to detect the planet at a contrast ratio of with 99.9 per cent confidence. Finally, we investigate the effect of model uncertainties on our ability to reliably recover a planetary signal. The use of incorrect temperature, model opacity wavelengths and model temperature-pressure profiles have important consequences for the least squares deconvolution procedure that we use to boost the signal-to-noise ratio (S/N) in our spectral time-series observations. We find that mismatches between the empirical and model planetary spectrum may weaken the significance of a detection by ∼30–60 per cent, thereby potentially impairing our ability to recover a planetary signal with high confidence. [ABSTRACT FROM AUTHOR]

The form of the primordial power spectrum has the potential to differentiate strongly between competing models of perturbation generation in the early universe and so is of considerable importance. The recent release of five years of Wilkinson Microwave Anisotropy Probe observations have confirmed the general picture of the primordial power spectrum as deviating slightly from scale invariance with a spectral tilt parameter of . None the less, many attempts have been made to isolate further features such as breaks and cut-offs using a variety of methods, some employing more than ∼10 varying parameters. In this paper, we apply the robust technique of the Bayesian model selection to reconstruct the optimal degree of structure in the spectrum. We model the spectrum simply and generically as piecewise linear in between ‘nodes’ in k space whose amplitudes are allowed to vary. The number of nodes and their k-space positions are chosen by the Bayesian evidence so that we can identify both the complexity and location of any detected features. Our optimal reconstruction contains, perhaps, surprisingly few features, the data preferring just three nodes. This reconstruction allows for a degree of scale dependence of the tilt with the ‘turn-over’ scale occurring around . More structure is penalized by the evidence as overfitting the data, so there is currently little point in attempting reconstructions that are more complex. [ABSTRACT FROM AUTHOR]

To further our knowledge of the complex physical process of galaxy formation, it is essential that we characterize the formation and evolution of large data bases of galaxies. The spectral synthesisstarlight code of Cid Fernandes et al. was designed for this purpose. Results ofstarlight are highly dependent on the choice of input basis of simple stellar population (SSP) spectra. Speed of the code, which uses random walks through the parameter space, scales as the square of the number of the basis spectra, making it computationally necessary to choose a small number of SSPs that are coarsely sampled in age and metallicity. In this paper, we develop methods based on a diffusion map that, for the first time, choose appropriate bases of prototype SSP spectra from a large set of SSP spectra designed to approximate the continuous grid of age and metallicity of SSPs of which galaxies are truly composed. We show that our techniques achieve better accuracy of physical parameter estimation for simulated galaxies. Specifically, we show that our methods significantly decrease the age–metallicity degeneracy that is common in galaxy population synthesis methods. We analyse a sample of 3046 galaxies in Sloan Digital Sky Survey Data Release 6 and compare the parameter estimates obtained from different basis choices. [ABSTRACT FROM AUTHOR]