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Detecting the cosmic 21 cm signal from epoch of reionization has always been a difficult task. Although the Galactic foreground can be regarded as a smooth power-law spectrum, due to the chromaticity of the antenna, additional structure will be introduced into the global spectrum, making the polynomial fitting algorithm perform poorly. In this paper, we introduce an improved polynomial fitting algorithm – the Vari-Zeroth-Order Polynomial (VZOP) fitting and use it to fit the simulation data. This algorithm is developed for the upcoming low-frequency anechoic chamber experiment, yet it is a general method suitable for application in any single antenna-based global 21 cm signal experiment. VZOP defines a 24-h averaged beam model that brings information about the antenna beam into the polynomial model. Assuming that the beam can be measured, VZOP can successfully recover the 21 cm absorption feature, even if the beam is extremely frequency-dependent. In real observations, due to various systematics, the corrected measured beam contains residual errors that are not completely random. Assuming the errors are frequency-dependent, VZOP is capable of recovering the 21 cm absorption feature even when the error reaches 10 per cent. Even in the most extreme scenario where the errors are completely random, VZOP can at least give a fitting result that is not worse than the common polynomial fitting. In conclusion, the fitting effect of VZOP depends on the structure of the error and the accuracy of the beam measurement. [ABSTRACT FROM AUTHOR]

In this paper, we present CALSAGOS : Clustering ALgorithmS Applied to Galaxies in Overdense Systems which is a PYTHON package developed to select cluster members and to search, find, and identify substructures. CALSAGOS is based on clustering algorithms, and was developed to be used in spectroscopic and photometric samples. To test the performance of CALSAGOS , we use the S-PLUS's mock catalogues, and we found an error of 1–6 per cent on member selection depending on the function that is used. Besides, CALSAGOS has a F 1-score of 0.8, a precision of 85 per cent and a completeness of 100 per cent in the identification of substructures in the outer regions of galaxy clusters (r > r 200). The F 1-score, precision, and completeness of CALSAGOS fall to 0.5, 75, and 40 per cent when we consider all substructure identifications (inner and outer) due to the function that searches, finds, and identifies the substructures works in 2D, and cannot resolve the substructures projected over others. [ABSTRACT FROM AUTHOR]

Accurate covariance matrices for two-point functions are critical for inferring cosmological parameters in likelihood analyses of large-scale structure surveys. Among various approaches to obtaining the covariance, analytic computation is much faster and less noisy than estimation from data or simulations. However, the transform of covariances from Fourier space to real space involves integrals with two Bessel integrals, which are numerically slow and easily affected by numerical uncertainties. Inaccurate covariances may lead to significant errors in the inference of the cosmological parameters. In this paper, we introduce a 2D-FFTLog algorithm for efficient, accurate, and numerically stable computation of non-Gaussian real-space covariances for both 3D and projected statistics. The 2D-FFTLog algorithm is easily extended to perform real-space bin-averaging. We apply the algorithm to the covariances for galaxy clustering and weak lensing for a Dark Energy Survey Year 3-like and a Rubin Observatory's Legacy Survey of Space and Time Year 1-like survey, and demonstrate that for both surveys, our algorithm can produce numerically stable angular bin-averaged covariances with the flat sky approximation, which are sufficiently accurate for inferring cosmological parameters. The code CosmoCov for computing the real-space covariances with or without the flat-sky approximation is released along with this paper. [ABSTRACT FROM AUTHOR]

In gravitational microlensing formalism and for modelling binary light curves, the key step is solving the binary lens equation. Currently, a combination of the Newton's and Laguerre's methods which was first introduced by Skowron & Gould (SG) is used while modelling binary light curves. In this paper, we first introduce a fast root-finding algorithm for univariate polynomials based on the Aberth–Ehrlich (AE) method which was first developed in 1967 as an improvement over the Newton's method. AE algorithm has proven to be much faster than Newton's, Laguerre's, and Durand–Kerner methods and unlike other root-finding algorithms, it is able to produce all the roots simultaneously. After improving the basic AE algorithm and discussing its properties, we will optimize it for solving binary lens equations, which are fifth degree polynomials with complex coefficients. Our method is about 1.8–2.0 times faster than the SG algorithm. Since, for calculating magnification factors for point-like or finite source stars, it is necessary to solve the binary lens equation and find the positions of the produced images in the image plane first, this new method will improve the speed and accuracy of binary microlensing modelling. [ABSTRACT FROM AUTHOR]

We explore an alternative method to the usual shear correlation function approach for the estimation of aperture mass statistics in weak-lensing survey data. Our approach builds on the direct estimator method. In this paper, we extend our analysis to statistics of arbitrary order and to the multiscale aperture mass statistics. We show that there always exists a linear order algorithm to retrieve any of these generalized aperture mass statistics from shape catalogues when the direct estimator approach is adopted. We validate our approach through application to a large number of Gaussian mock-lensing surveys where the true answer is known and we do this up to 10th-order statistics. We then apply our estimators to an ensemble of real-world mock catalogues obtained from N -body simulations – the SLICS mocks, and show that one can expect to retrieve detections of higher order clustering up to fourth order in a KiDS-1000 like survey. We expect that these methods will be of most utility for future wide-field surveys like Euclid and the Rubin Telescope. [ABSTRACT FROM AUTHOR]

We review the methodology for measurements of two-point functions of the cosmological observables, both power spectra and correlation functions. For pseudo- C ℓ estimators, we will argue that the window-weighted overdensity field can yield more optimal measurements as the window acts as an inverse noise weight, an effect that becomes more important for surveys with a variable selection function. We then discuss the impact of approximations made in the Master algorithm and suggest improvements, the i Master algorithm, which uses the theoretical model to give unbiased results for arbitrarily complex windows provided that the model satisfies weak accuracy conditions. The methodology of i Master algorithm is also generalized to the correlation functions to reconstruct the binned power spectra, for E/B mode separation, or to properly convolve the correlation functions to account for the scale cuts in the Fourier space model. We also show that the errors in the window estimation lead to both additive and multiplicative effects on the overdensity field. Accurate estimation of window power can be required up to scales of ∼2ℓmax or larger. Mis-estimation of the window power leads to biases in the measured power spectra, which scale as |${\delta C_\ell }\sim M^W_{\ell \ell ^{\prime }}\delta W_{\ell ^{\prime }}$|⁠ , where the |$M^W_{\ell \ell ^{\prime }}$| scales as ∼(2ℓ + 1) C ℓ leading to effects that can be important at high ℓ. While the notation in this paper is geared towards photometric galaxy surveys, the discussion is equally applicable to spectroscopic galaxy, intensity mapping, and Cosmic Microwave Background radiation (CMB) surveys. [ABSTRACT FROM AUTHOR]

This paper proposes a morphostatistical characterization of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC shadow algorithm. This algorithm provides simultaneous parameter estimation and posterior-based inference, hence allowing the derivation of the statistical significance of the obtained results. [ABSTRACT FROM AUTHOR]

The recent observation of the shadow of the supermassive compact object M87* by the Event Horizon Telescope (EHT) collaboration has opened up a new window to probe the strong gravity regime. In this paper, we study shadows cast by two viable alternatives to the Kerr black hole, and compare them with the shadow of M87*. The first alternative is a horizonless compact object (HCO) having radius r 0 and exterior Kerr geometry. The second one is a rotating generalization of the recently obtained one parameter (r 0) static metric by Simpson and Visser. This latter metric, constructed using the Newman–Janis algorithm, is a special case of a parametrized rotating non-Kerr geometry obtained by Johannsen. Here, we constrain the parameter r 0 of these alternatives using the results from M87* observation. We find that, for the mass, inclination angle and the angular diameter of the shadow of M87* reported by the EHT collaboration, the maximum value of the parameter r 0 must be in the range 2.54 r + ≤ r 0, max ≤ 3.51 r + for the dimensionless spin range 0.5 ≤ a * ≤ 0.94, with r + being the outer horizon radius of the Kerr black hole at the corresponding spin value. We conclude that these black hole alternatives having r 0 below this maximum range (i.e. r 0 ≤ r 0, max) is consistent with the size and deviation from circularity of the observed shadow of M87*. [ABSTRACT FROM AUTHOR]

Glitches are the observational manifestations of superfluidity inside neutron stars. The aim of this paper is to describe an automated glitch detection pipeline, which can alert the observers on possible real-time detection of rotational glitches in pulsars. Post alert, the pulsars can be monitored at a higher cadence to measure the post-glitch recovery phase. Two algorithms, namely median absolute deviation and polynomial regression, have been explored to detect glitches in real time. The pipeline has been optimized with the help of simulated timing residuals for both the algorithms. Based on the simulations, we conclude that the polynomial regression algorithm is significantly more effective for real time glitch detection. The pipeline has been tested on a few published glitches. This pipeline is presently implemented at the Ooty Radio Telescope. In the era of upcoming large telescopes like SKA, several hundreds of pulsars will be observed regularly and such a tool will be useful for both real-time detection as well as optimal utilization of observation time for such glitching pulsars. [ABSTRACT FROM AUTHOR]

We present a detailed study of the complex time-frequency structure of a sample of previously reported bursts of FRB 121102 detected with the MeerKAT telescope in September 2019. The wide contiguous bandwidth of these observations have revealed a complex bifurcating structure in some bursts at 1250 MHz. When de-dispersed to their structure-optimized dispersion measures (DMs), two of the bursts show a clear deviation from the cold plasma dispersion relationship below 1250 MHz. We find a differential DM of |${\sim }1{-}2~{\rm pc \, cm^{-3}}$| between the lower and higher frequency regions of each burst. We investigate the possibility of plasma lensing by Gaussian lenses of ∼10 au in the host galaxy, and demonstrate that they can qualitatively produce some of the observed burst morphologies. Other possible causes for the observed frequency dependence, such as Faraday delay, are also discussed. Unresolved sub-components in the bursts, however, may have led to an incorrect DM determination. We hence advise exercising caution when considering bursts in isolation. We analyse the presence of two apparent burst pairs. One of these pairs is a potential example of upward frequency drift. The possibility that burst pairs are echoes is also discussed. The average structure-optimized DM is found to be |$563.5\pm 0.2 (\text{sys}) \pm 0.8 (\text{stat})\, {\rm pc \, cm^{-3}}$| – consistent with the values reported in 2018. We use two independent methods to determine the structure-optimized DM of the bursts: the DM_phase algorithm and autocorrelation functions. The latter – originally developed for pulsar analysis – is applied to fast radio bursts for the first time in this paper. [ABSTRACT FROM AUTHOR]

Cosmic voids and their corresponding redshift-projected mass densities, known as troughs, play an important role in our attempt to model the large-scale structure of the Universe. Understanding these structures enables us to compare the standard model with alternative cosmologies, constrain the dark energy equation of state, and distinguish between different gravitational theories. In this paper, we extend the subspace-constrained mean shift algorithm, a recently introduced method to estimate density ridges, and apply it to 2D weak lensing mass density maps from the Dark Energy Survey Y1 data release to identify curvilinear filamentary structures. We compare the obtained ridges with previous approaches to extract trough structure in the same data, and apply curvelets as an alternative wavelet-based method to constrain densities. We then invoke the Wasserstein distance between noisy and noiseless simulations to validate the denoising capabilities of our method. Our results demonstrate the viability of ridge estimation as a precursor for denoising weak lensing observables to recover the large-scale structure, paving the way for a more versatile and effective search for troughs. [ABSTRACT FROM AUTHOR]

Owing to the limited size and imperfections of the optical components in a spectrometer, aberrations inevitably make their way into 2D multifibre spectral images in the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST), which leads to obvious spatial variation of the point spread functions (PSFs). However, if spatially variant PSFs are estimated directly, the large storage and intensive computational requirements result in the deconvolution spectrum extraction method becoming intractable. In this paper, we propose a novel method to solve the problem of spatial variation of the PSFs through image aberration correction. When CCD image aberrations are corrected, the convolution kernel can be approximated by only one spatially invariant PSF. Specifically, a novel method based on machine learning is proposed to calibrate the distorted spectral images. The method includes many techniques, such as total least squares (TLS) algorithm, self-supervised learning and multilayer feed-forward neural networksnetworks, and it makes use of a special training set sampling scheme combining 2D distortion features in a flat-field spectrum and calibration lamp spectrum. The calibration experiments on the LAMOST CCD images show that the proposed method is feasible. Furthermore, the spectrum extraction results before and after calibration are compared, and the experimental results show that the characteristics of the extracted 1D waveform are closer to those of an ideal optics system after image correction, and that the PSF of the corrected object spectrum estimated by the blind deconvolution method is nearly centrosymmetric, which indicates that our proposed method can significantly reduce the complexity of spectrum extraction and improve extraction accuracy. [ABSTRACT FROM AUTHOR]

The advent of a new generation of large-scale galaxy surveys is pushing cosmological numerical simulations in an uncharted territory. The simultaneous requirements of high resolution and very large volume pose serious technical challenges, due to their computational and data storage demand. In this paper, we present a novel approach dubbed dynamic zoom simulations – or dzs  – developed to tackle these issues. Our method is tailored to the production of light-cone outputs from N -body numerical simulations, which allow for a more efficient storage and post-processing compared to standard comoving snapshots, and more directly mimic the format of survey data. In dzs , the resolution of the simulation is dynamically decreased outside the light-cone surface, reducing the computational work load, while simultaneously preserving the accuracy inside the light-cone and the large-scale gravitational field. We show that our approach can achieve virtually identical results to traditional simulations at half of the computational cost for our largest box. We also forecast this speedup to increase up to a factor of 5 for larger and/or higher resolution simulations. We assess the accuracy of the numerical integration by comparing pairs of identical simulations run with and without dzs. Deviations in the light-cone halo mass function, in the sky-projected light-cone, and in the 3D matter light-cone always remain below 0.1 per cent. In summary, our results indicate that the dzs technique may provide a highly valuable tool to address the technical challenges that will characterize the next generation of large-scale cosmological simulations. [ABSTRACT FROM AUTHOR]

Wide-area imaging surveys are one of the key ways of advancing our understanding of cosmology, galaxy formation physics, and the large-scale structure of the Universe in the coming years. These surveys typically require calculating redshifts for huge numbers (hundreds of millions to billions) of galaxies – almost all of which must be derived from photometry rather than spectroscopy. In this paper, we investigate how using statistical models to understand the populations that make up the colour–magnitude distribution of galaxies can be combined with machine learning photometric redshift codes to improve redshift estimates. In particular, we combine the use of Gaussian mixture models with the high-performing machine-learning photo-z algorithm GPz and show that modelling and accounting for the different colour–magnitude distributions of training and test data separately can give improved redshift estimates, reduce the bias on estimates by up to a half, and speed up the run-time of the algorithm. These methods are illustrated using data from deep optical and near-infrared data in two separate deep fields, where training and test data of different colour–magnitude distributions are constructed from the galaxies with known spectroscopic redshifts, derived from several heterogeneous surveys. [ABSTRACT FROM AUTHOR]

A catalogue of galaxy clusters was obtained in an area of 414 |$\deg ^2$| up to a redshift z ∼ 0.8 from the Data Release 3 of the Kilo-Degree Survey (KiDS-DR3), using the Adaptive Matched Identifier of Clustered Objects (amico) algorithm. The catalogue and the calibration of the richness–mass relation were presented in two companion papers. Here, we describe the selection of the cluster central galaxy and the classification of blue and red cluster members, and analyse the main cluster properties, such as the red/blue fraction, cluster mass, brightness, and stellar mass of the central galaxy, and their dependence on redshift and cluster richness. We use the Illustris-TNG simulation, which represents the state-of-the-art cosmological simulation of galaxy formation, as a benchmark for the interpretation of the results. A good agreement with simulations is found at low redshifts (z ≤ 0.4), while at higher redshifts the simulations indicate a lower fraction of blue galaxies than what found in the KiDS- amico catalogue: we argue that this may be due to an underestimate of star-forming galaxies in the simulations. The selection of clusters with a larger magnitude difference between the two brightest central galaxies, which may indicate a more relaxed cluster dynamical status, improves the agreement between the observed and simulated cluster mass and stellar mass of the central galaxy. We also find that at a given cluster mass the stellar mass of blue central galaxies is lower than that of the red ones. [ABSTRACT FROM AUTHOR]

This paper presents a catalogue of optimized pointings for differential photometry of 23 779 quasars extracted from the Sloan Digital Sky Survey (SDSS) Catalogue and a Score for each indicating the quality of the Field of View (FoV) associated with that pointing. Observation of millimagnitude variability on a time-scale of minutes typically requires differential observations with reference to an ensemble of reference stars. For optimal performance, these reference stars should have similar colour and magnitude to the target quasar. In addition, the greatest quantity and quality of suitable reference stars may be found by using a telescope pointing which offsets the target object from the centre of the FoV. By comparing each quasar with the stars which appear close to it on the sky in the SDSS Catalogue, an optimum pointing can be calculated, and a figure of merit, referred to as the ' Score ' is calculated for that pointing. Highly flexible software has been developed to enable this process to be automated and implemented in a distributed computing paradigm, which enables the creation of catalogues of pointings given a set of input targets. Applying this technique to a sample of 40 000 targets from the fourth SDSS quasar catalogue resulted in the production of pointings and Scores for 23 779 quasars based on their magnitudes in the SDSS r -band. This catalogue is a useful resource for observers planning differential photometry studies and surveys of quasars to select those which have many suitable celestial neighbours for differential photometry. [ABSTRACT FROM AUTHOR]

Large multiobject spectroscopic surveys require automated algorithms to optimize their observing strategy. One of the most ambitious upcoming spectroscopic surveys is the 4MOST survey. The 4MOST survey facility is a fibre-fed spectroscopic instrument on the VISTA telescope with a large enough field of view to survey a large fraction of the southern sky within a few years. Several Galactic and extragalactic surveys will be carried out simultaneously, so the combined target density will strongly vary. In this paper, we describe a new tiling algorithm that can naturally deal with the large target density variations on the sky and which automatically handles the different exposure times of targets. The tiling pattern is modelled as a marked point process, which is characterized by a probability density that integrates the requirements imposed by the 4MOST survey. The optimal tilling pattern with respect to the defined model is estimated by the tiles configuration that maximizes the proposed probability density. In order to achieve this maximization a simulated annealing algorithm is implemented. The algorithm automatically finds an optimal tiling pattern and assigns a tentative sky brightness condition and exposure time for each tile, while minimizing the total execution time that is needed to observe the list of targets in the combined input catalogue of all surveys. Hence, the algorithm maximizes the long-term observing efficiency and provides an optimal tiling solution for the survey. While designed for the 4MOST survey, the algorithm is flexible and can with simple modifications be applied to any other multiobject spectroscopic survey. [ABSTRACT FROM AUTHOR]

A Kepler solver is an analytical method used to solve a two-body problem. In this paper, we propose a new correction method by slightly modifying the Kepler solver. The only change to the analytical solutions is that the obtainment of the eccentric anomaly relies on the true anomaly that is associated with a unit radial vector calculated by an integrator. This scheme rigorously conserves all integrals and orbital elements except the mean longitude. However, the Kepler energy, angular momentum vector, and Laplace–Runge–Lenz vector for perturbed Kepler problems are slowly varying quantities. However, their integral invariant relations give the quantities high-precision values that directly govern five slowly varying orbital elements. These elements combined with the eccentric anomaly determine the desired numerical solutions. The newly proposed method can considerably reduce various errors for a post-Newtonian two-body problem compared with an uncorrected integrator, making it suitable for a dissipative two-body problem. Spurious secular changes of some elements or quasi-integrals in the outer Solar system may be caused by short integration times of the fourth-order Runge–Kutta algorithm. However, they can be eliminated in a long integration time of 108 yr by the proposed method, similar to Wisdom–Holman second-order symplectic integrator. The proposed method has an advantage over the symplectic algorithm in the accuracy but gives a larger slope to the phase error growth. [ABSTRACT FROM AUTHOR]

In this paper, an efficient algorithm is developed to automatically detect and extract coronal loops. First of all, in the algorithm, three characteristics associated with coronal loops are used to construct a match filter able to enhance the loops. Secondly, the method combining a high-pass filter (unsharp-mask enhancement) with a global threshold is used to further enhance and segment the loops. Thirdly, to extract every individual coronal loop and obtain their parameters (the 2D projected space coordinates and lengths) from the segmented loops, a clustering method of the pixels with approximate local direction and connected domain is further used. Fourthly, to evaluate the performance of the developed algorithm, images observed by the Transition Region and Coronal Explorer (TRACE), the Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO) and the High-Resolution Coronal Imager (Hi-C) are used, and comparison experiments between the existing algorithms and the developed algorithm are performed. Finally, it is found that the developed algorithm is commensurate with the two most promising algorithms, oriented coronal curved loop tracing (OCCULT) and its improved version, OCCULT-2, in performance. Therefore, for scientific applications associated with coronal loops, the developed algorithm will be a powerful tool. [ABSTRACT FROM AUTHOR]

ABSTRACT A companion paper presents an algorithm for estimating the actions of orbits in axisymmetric potentials. This algorithm is fast enough for it to be feasible to fit automatically a parametrized distribution function to observational data for the solar neighbourhood. We explore the predictive power of these models and the extent to which global models are constrained by data confined to the solar cylinder. We adopt a gravitational potential that is generated by three discs (gas and both thin and thick stellar discs), a bulge and a dark halo, and fit the thin-disc component of the distribution function to the solar-neighbourhood velocity distribution from the Geneva-Copenhagen survey. We find that the disc's vertical density profile is in good agreement with data at z ≲ 500 pc. The thick-disc component of the distribution function is then used to extend the fit to data from Gilmore & Reid for z ≲ 2.5 kpc. The resulting model predicts excellent fits to the profile of the vertical velocity dispersion σ z( z) from the RAVE survey and to the distribution of vφ velocity components at | z| ∼ 1 kpc from the Sloan Digital Sky Survey. The ability of this model to predict successfully data that were not used in the fitting process suggests that the adopted gravitational potential (which is close to a maximum-disc potential) is close to the true one. We show that if another plausible potential is used, the predicted values of σ z are too large. The models imply that in contrast to the thin disc, the thick disc has to be hotter vertically than radially, a prediction that it will be possible to test in the near future. When the model parameters are adjusted in an unconstrained manner, there is a tendency to produce models that predict unexpected radial variations in quantities such as scale height. This finding suggests that to constrain these models adequately one needs data that extends significantly beyond the solar cylinder. The models presented in this paper might prove useful to the interpretation of data for external galaxies that have been taken with an integral field unit. [ABSTRACT FROM AUTHOR]

ABSTRACT In a companion paper, we have presented an algorithm for simulating two-fluid gas and dust mixtures in smoothed particle hydrodynamics (SPH). In this paper, we develop an implicit timestepping method that preserves the exact conservation of the both linear and angular momenta in the underlying SPH algorithm, but unlike previous schemes, allows the iterations to converge to arbitrary accuracy and is suited to the treatment of non-linear drag regimes. The algorithm presented in Paper I is also extended to deal with realistic astrophysical drag regimes, including both linear and non-linear Epstein and Stokes drag. The scheme is benchmarked against the test suite presented in Paper I, including (i) the analytic solutions of the dustybox problem and (ii) solutions of the dustywave, dustyshock, dustysedov and dustydisc obtained with explicit timestepping. We find that the implicit method is 1-10 times faster than the explicit temporal integration when the ratio r between the timestep and the drag stopping time is 1 ≲ r≲ 1000. [ABSTRACT FROM AUTHOR]

ABSTRACT We present a new cluster-detection algorithm designed for the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) survey but with generic application to any multiband data. The method makes no prior assumptions about the properties of clusters other than (i) the similarity in colour of cluster galaxies (the 'red sequence'); and (ii) an enhanced projected surface density. The detector has three main steps: (i) it identifies cluster members by photometrically filtering the input catalogue to isolate galaxies in colour-magnitude space; (ii) a Voronoi diagram identifies regions of high surface density; and (iii) galaxies are grouped into clusters with a Friends-of-Friends technique. Where multiple colours are available, we require systems to exhibit sequences in two colours. In this paper, we present the algorithm and demonstrate it on two data sets. The first is a 7-deg2 sample of the deep Sloan Digital Sky Survey (SDSS) equatorial stripe (Stripe 82), from which we detect 97 clusters with z≤ 0.6. Benefitting from deeper data, we are 100 per cent complete in the maxBCG optically selected cluster catalogue (based on shallower single-epoch SDSS data) and find an additional 78 previously unidentified clusters. The second data set is a mock Medium Deep Survey Pan-STARRS catalogue, based on the Λ cold dark matter (ΛCDM) model and a semi-analytic galaxy formation recipe. Knowledge of galaxy-halo memberships in the mock catalogue allows for the quantification of algorithm performance. We detect 305 mock clusters in haloes with mass >1013 h−1 M⊙ at z≲ 0.6 and determine a spurious detection rate of <1 per cent, consistent with tests on the Stripe 82 catalogue. The detector performs well in the recovery of model ΛCDM clusters. At the median redshift of the catalogue, the algorithm achieves >75 per cent completeness down to halo masses of 1013.4 h−1 M⊙ and recovers >75 per cent of the total stellar mass of clusters in haloes down to 1013.8 h−1 M⊙. A companion paper presents the complete cluster catalogue over the full 270-deg2 Stripe 82 catalogue. [ABSTRACT FROM AUTHOR]

The dynamical ages and some other physical parameters of the opposite lobes of 20 subjectively selected giant radio galaxies (GRGs), as well as of their environment, are estimated using the algorithm of Machalski et al. These data, supplemented with the relevant data determined for another 10 GRGs in Paper III, are used to analyse the aspects of the apparent length and luminosity asymmetries in the lobes in view of their dynamical evolution. As in Paper III, the fits give slightly different dynamical ages and other model parameters for the opposite lobes modelled independently of each other. Therefore, demanding similar values of the jet power and the radio core density for the same source, a self-consistent age solution for the opposite lobes is considered, which results in different density profiles along the lobes and different initial energy distributions of the emitting particles at their heads. The analysis shows the following. (i) The age of the longer lobe, fitted independently, tends to be younger than that for the shorter lobe. This contradicts with the axial expansion expected in a symmetrical environment (a halo) surrounding the source and strongly supports the self-consistent solution with different ambient density profiles along the opposite lobes. In the frame of the latter solution, the difference between the ages of the opposite lobes almost always diminishes, compared to that found with the independent fits, not exceeding a factor of ∼1.25. (ii) There is a clear correlation between the age ratio and the difference in radio spectra: longer lobes with a steeper spectrum in most cases are older; however, longer lobes having a flatter spectrum are mostly younger. The age difference is always larger than that expected from the unknown inclination of the jets' axis to the observer's line of sight and a pure kinematic effect. (iii) The slope of the injected (initial) radio spectrum, , has a narrow distribution around a value of 0.5. Its value tends to be lower in the longer lobe than in the shorter lobe. The difference between the values of in the opposite lobes is very low; a standard deviation of ∼0.02 from the mean is found. This difference increases about three times in the self-consistent solution, but always within the relatively narrow range of 0.46-0.62. (iv) There is a strong correlation between the difference in values of β (the exponent describing the external density profile) for the opposite lobes and the ratio of their volume. This is much stronger than a dependence of on the ratio of the lobes' length. This likely suggests that the environment of the GRGs is non-uniform or clumpy. [ABSTRACT FROM AUTHOR]

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 |$E(B-V) \gtrsim 0.2$|⁠, 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 AV < 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 converge as signal to noise increases, as one would expect. We also show how the very output of the code provides ways of diagnosing anomalies in the fits. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm,trimor, to analyse multi-order spectra of triple systems. The algorithm is an extension oftricor, the three-dimensional correlation technique that derives the radial velocities of triple stellar systems from single-order spectra. The combined correlation derived from many orders enables the detection and the measurement of radial velocities of faint tertiary companions. The paper appliedtrimor to the already available spectra of HD 188753, a well-known triple system, yielding the radial velocities of the faintest star in the system. This rendered the close pair of the triple system a double-lined spectroscopic binary, which led to a precise mass ratio and an estimate of its inclination. The close-pair inclination is very close to the inclination of the wide orbit, consistent with the assertion that this triple system has a close to coplanar configuration. [ABSTRACT FROM AUTHOR]

zobov (ZOnes Bordering On Voidness) is an algorithm that finds density depressions in a set of points, without any free parameters, or assumptions about shape. It uses the Voronoi tessellation to estimate densities, which it uses to find both voids and subvoids. It also measures probabilities that each void or subvoid arises from Poisson fluctuations. This paper describes thezobov algorithm, and the results from its application to the dark matter particles in a region of the Millennium simulation. Additionally, the paper points out an interesting high-density peak in the probability distribution of dark matter particle densities. [ABSTRACT FROM AUTHOR]

In two previous papers (Papers I and II), we have described an algorithm for solving the equations of Magnetohydrodynamics (MHD) using the Smoothed Particle Hydrodynamics (SPH) method. The algorithm uses dissipative terms in order to capture shocks and has been tested on a wide range of one-dimensional problems in both adiabatic and isothermal MHD. In this paper, we investigate multidimensional aspects of the algorithm, refining many of the aspects considered in Papers I and II and paying particular attention to the code's ability to maintain the constraint associated with the magnetic field. In particular, we implement a hyperbolic divergence cleaning method recently proposed by Dedner et al. in combination with the consistent formulation of the MHD equations in the presence of non-zero magnetic divergence derived in Papers I and II. Various projection methods for maintaining the divergence-free condition are also examined. Finally, the algorithm is tested against a wide range of multidimensional problems used to test recent grid-based MHD codes. A particular finding of these tests is that in Smoothed Particle Magnetohydrodynamics (SPMHD), the magnitude of the divergence error is dependent on the number of neighbours used to calculate a particle's properties and only weakly dependent on the total number of particles. Whilst many improvements could still be made to the algorithm, our results suggest that the method is ripe for application to problems of current theoretical interest, such as that of star formation. [ABSTRACT FROM AUTHOR]

In this paper we show how a Lagrangian variational principle can be used to derive the Smoothed Particle Magnetohydrodynamics (SPMHD) equations for ideal Magnetohydrodynamics (MHD). We also consider the effect of a variable smoothing length in the Smoothed Particle Hydrodynamics (SPH) kernels, after which we demonstrate by numerical tests that the consistent treatment of terms relating to the gradient of the smoothing length in the SPMHD equations significantly improves the accuracy of the algorithm. Our results complement those obtained in the companion paper for non-ideal MHD where artificial dissipative terms were included to handle shocks. [ABSTRACT FROM AUTHOR]

STREAMFINDER is a new algorithm that we have built to detect stellar streams in an automated and systematic way in astrophysical datasets that possess any combination of positional and kinematic information. In Paper I, we introduced the methodology and the workings of our algorithm and showed that it is capable of detecting ultra-faint and distant halo stream structures containing as few as ∼15 members (ΣG ∼ 33.6 mag arcsec−2) in the Gaia dataset. Here, we test the method with real proper motion data from the Pan-STARRS1 survey, and by selecting targets down to r 0 = 18.5 mag we show that it is able to detect the GD-1 stellar stream, whereas the structure remains below a useful detection limit when using a Matched Filter technique. The radial velocity solutions provided by STREAMFINDER for GD-1 candidate members are found to be in good agreement with observations. Furthermore, our algorithm detects a $${\sim } 40^{^\circ }$$ long structure approximately parallel to GD-1, and which fans out from it, possibly a sign of stream-fanning due to the triaxiality of the Galactic potential. This analysis shows the promise of this method for detecting and analysing stellar streams in the upcoming Gaia DR2 catalogue. [ABSTRACT FROM AUTHOR]

The convolution of galaxy images by the point spread function (PSF) is the dominant source of bias for weak gravitational lensing studies, and an accurate estimate of the PSF is required to obtain unbiased shape measurements. The PSF estimate for a galaxy depends on its spectral energy distribution (SED), because the instrumental PSF is generally a function of the wavelength. In this paper we explore various approaches to determine the resulting 'effective' PSF using broad-band data. Considering the Euclid mission as a reference, we find that standard SED template fitting methods result in biases that depend on source redshift, although this may be remedied if the algorithms can be optimized for this purpose. Using a machine learning algorithm we show that, at least in principle, the required accuracy can be achieved with the current survey parameters. It is also possible to account for the correlations between photometric redshift and PSF estimates that arise from the use of the same photometry. We explore the impact of errors in photometric calibration, errors in the assumed wavelength dependence of the PSF model, and limitations of the adopted template libraries. Our results indicate that the required accuracy for Euclid can be achieved using the data that are planned to determine photometric redshifts. [ABSTRACT FROM AUTHOR]

We describe an OctTree algorithm for the MPI parallel, adaptive mesh refinement code FLASH, which can be used to calculate the gas self-gravity, and also the angle-averaged local optical depth, for treating ambient diffuse radiation. The algorithm communicates to the different processors only those parts of the tree that are needed to perform the tree-walk locally. The advantage of this approach is a relatively low memory requirement, important in particular for the optical depth calculation, which needs to process information from many different directions. This feature also enables a general tree-based radiation transport algorithm that will be described in a subsequent paper, and delivers excellent scaling up to at least 1500 cores. Boundary conditions for gravity can be either isolated or periodic, and they can be specified in each direction independently, using a newly developed generalization of the Ewald method. The gravity calculation can be accelerated with the adaptive block update technique by partially re-using the solution from the previous time-step. Comparison with the FLASH internal multigrid gravity solver shows that tree-based methods provide a competitive alternative, particularly for problems with isolated or mixed boundary conditions. We evaluate several multipole acceptance criteria (MACs) and identify a relatively simple approximate partial error MAC which provides high accuracy at low computational cost. The optical depth estimates are found to agree very well with those of the RADMC-3D radiation transport code, with the tree-solver being much faster. Our algorithm is available in the standard release of the FLASH code in version 4.0 and later. [ABSTRACT FROM AUTHOR]

The error in the Solar system ephemeris will lead to dipolar correlations in the residuals of pulsar timing array for widely separated pulsars. In this paper, we utilize such correlated signals, and construct a Bayesian data-analysis framework to detect the unknown mass in the Solar system and to measure the orbital parameters. The algorithm is designed to calculate the waveform of the induced pulsar-timing residuals due to the unmodelled objects following the Keplerian orbits in the Solar system. The algorithm incorporates a Bayesian-analysis suit used to simultaneously analyse the pulsar-timing data of multiple pulsars to search for coherent waveforms, evaluate the detection significance of unknown objects, and to measure their parameters. When the object is not detectable, our algorithm can be used to place upper limits on the mass. The algorithm is verified using simulated data sets, and cross-checked with analytical calculations. We also investigate the capability of future pulsar-timing-array experiments in detecting the unknown objects. We expect that the future pulsar-timing data can limit the unknown massive objects in the Solar system to be lighter than 10-11-10-12 M☉, or measure the mass of Jovian system to a fractional precision of 10-8-10-9. [ABSTRACT FROM AUTHOR]

Adaptive Optics Lucky Imager (AOLI) is a state-of-the-art instrument that combines adaptive optics (AO) and lucky imaging (LI) with the objective of obtaining diffraction-limited images in visible wavelength at mid- and big-size ground-based telescopes. The key innovation of AOLI is the development and use of the new Two Pupil Plane Positions Wavefront Sensor (TP3-WFS). The TP3-WFS, working in visible band, represents an advance over classical wavefront sensors such as the Shack-Hartmann WFS because it can theoretically use fainter natural reference stars, which would ultimately provide better sky coverages to AO instruments using this newer sensor. This paper describes the software, algorithms and procedures that enabled AOLI to become the first astronomical instrument performing real-time AO corrections in a telescope with this new type of WFS, including the first control-related results at the William Herschel Telescope. [ABSTRACT FROM AUTHOR]

Atmospheric turbulence presents a fundamental challenge to Fourier phase recovery in optical interferometry. Typical reconstruction algorithms employ Bayesian inference techniques which rely on prior knowledge of the scene under observation. In contrast, redundant spacing calibration (RSC) algorithms employ redundancy in the baselines of the interferometric array to directly expose the contribution of turbulence, thereby enabling phase recovery for targets of arbitrary and unknown complexity. Traditionally RSC algorithms have been applied directly to single-exposure measurements, which are reliable only at high photon flux in general. In scenarios of low photon flux, such as those arising in the observation of dim objects in space, one must instead rely on time-averaged, atmosphere-invariant quantities such as the bispectrum. In this paper, we develop a novel RSC-based algorithm for prior-less phase recovery in which we generalize the bispectrum to higher order atmosphere-invariants (nspectra) for improved sensitivity. We provide a strategy for selection of a high-signal-to-noise ratio set of n-spectra using the graph-theoretic notion of the minimum cycle basis. We also discuss a key property of this set (wrap-invariance), which then enables reliable application of standard linear estimation techniques to recover the Fourier phases from the 2π-wrapped n-spectra phases. For validation, we analyse the expected shot-noise-limited performance of our algorithm for both pairwise and Fizeau interferometric architectures, and corroborate this analysis with simulation results showing performance near an atmosphere-oracle Cramer-Rao bound. Lastly, we apply techniques from the field of compressed sensing to perform image reconstruction from the estimated complex visibilities. [ABSTRACT FROM AUTHOR]

We present Spin-SILC, a new foreground component separation method that accurately extracts the cosmic microwave background (CMB) polarization E and B modes from raw multifrequency Stokes Q and U measurements of the microwave sky. Spin-SILC is an internal linear combination method that uses spin wavelets to analyse the spin-2 polarization signal P = Q + iU. The wavelets are additionally directional (non-axisymmetric). This allows different morphologies of signals to be separated and therefore the cleaning algorithm is localized using an additional domain of information. The advantage of spin wavelets over standard scalar wavelets is to simultaneously and self-consistently probe scales and directions in the polarization signal P = Q + iU and in the underlying E and B modes, therefore providing the ability to perform component separation and E-B decomposition concurrently for the first time. We test Spin-SILC on full-mission Planck simulations and data and show the capacity to correctly recover the underlying cosmological E and B modes. We also demonstrate a strong consistency of our CMB maps with those derived from existing component separation methods. Spin-SILC can be combined with the pseudo- and pure E-B spin wavelet estimators presented in a companion paper to reliably extract the cosmological signal in the presence of complicated sky cuts and noise. Therefore, it will provide a computationally efficient method to accurately extract the CMB E and B modes for future polarization experiments. [ABSTRACT FROM AUTHOR]

Wide field images taken in several photometric bands allow simultaneous measurement of redshifts for thousands of galaxies. A variety of algorithms to make this measurement have appeared in the last few years, the majority of which can be classified as either template- or training-based methods. Among the latter, nearest neighbour estimators stand out as one of the most successful, in terms of both precision and the quality of error estimation. In this paper we describe the Directional Neighbourhood Fitting (DNF) algorithm based on the following: a new neighbourhood metric (Directional Neighbourhood), a photo-z estimation strategy (Neighbourhood Fitting) and a method for generating the photo-z probability distribution function.We compare DNF with other well-known empirical photometric redshift tools using different public data sets (Sloan Digital Sky Survey, VIMOS VLT Deep Survey and Photo-z Accuracy Testing). DNF achieves high-quality results with reliable error. [ABSTRACT FROM AUTHOR]

Merging galaxy systems provide observational evidence of the existence of dark matter and constraints on its properties. Therefore, statistically uniform samples of merging systems would be a powerful tool for several studies. In this paper, we present a new methodology for the identification of merging systems and the results of its application to galaxy redshift surveys. We use as a starting point a mock catalogue of galaxy systems, identified using friends-of-friends algorithms, that have experienced a major merger, as indicated by its merger tree. By applying machine learning techniques in this training sample, and using several features computed from the observable properties of galaxy members, it is possible to select galaxy groups that have a high probability of having experienced a major merger. Next, we apply a mixture of Gaussian techniques on galaxy members in order to reconstruct the properties of the haloes involved in such mergers. This methodology provides a highly reliable sample of merging systems with low contamination and precisely recovered properties. We apply our techniques to samples of galaxy systems obtained from the Sloan Digital Sky Survey Data Release 7, the Wide-Field Nearby Galaxy-Cluster Survey (WINGS) and the Hectospec Cluster Survey (HeCS). Our results recover previously known merging systems and provide several new candidates. We present their measured properties and discuss future analysis on current and forthcoming samples. [ABSTRACT FROM AUTHOR]

Images of stars adopt shapes far from the ideal Airy pattern due to atmospheric density fluctuations. Hence, diffraction-limited images can only be achieved by telescopes without atmospheric influence, e.g. spatial telescopes, or by using techniques like adaptive optics or lucky imaging. In this paper, we propose a new computational technique based on the evaluation of the COvariancE of Lucky Images (COELI). This technique allows us to discover companions to main stars by taking advantage of the atmospheric fluctuations. We describe the algorithm and we carry out a theoretical analysis of the improvement in contrast. We have used images taken with 2.2-m Calar Alto telescope as a test bed for the technique resulting that, under certain conditions, telescope diffraction limit is clearly reached. [ABSTRACT FROM AUTHOR]

We present the Signal Detection using Random-Forest Algorithm (SIDRA). SIDRA is a detection and classification algorithm based on the Machine Learning technique (Random Forest). The goal of this paper is to show the power of SIDRA for quick and accurate signal detection and classification.We first diagnose the power of the method with simulated light curves and try it on a subset of the Kepler space mission catalogue.We use five classes of simulated light curves (CONSTANT, TRANSIT, VARIABLE, MLENS and EB for constant light curves, transiting exoplanet, variable, microlensing events and eclipsing binaries, respectively) to analyse the power of the method. The algorithm uses four features in order to classify the light curves. The training sample contains 5000 light curves (1000 from each class) and 50 000 random light curves for testing. The total SIDRA success ratio is ≥90 per cent. Furthermore, the success ratio reaches 95-100 per cent for the CONSTANT, VARIABLE, EB and MLENS classes and 92 per cent for the TRANSIT class with a decision probability of 60 per cent. Because the TRANSIT class is the one which fails the most, we run a simultaneous fit using SIDRA and a Box Least Square (BLS)-based algorithm for searching for transiting exoplanets. As a result, our algorithm detects 7.5 per cent more planets than a classic BLS algorithm, with better results for lower signal-to-noise light curves. SIDRA succeeds to catch 98 per cent of the planet candidates in the Kepler sample and fails for 7 per cent of the false alarms subset. SIDRA promises to be useful for developing a detection algorithm and/or classifier for large photometric surveys such as TESS and PLATO exoplanet future space missions. [ABSTRACT FROM AUTHOR]

The detection and characterization of filamentary structures in the cosmic web allows cosmologists to constrain parameters that dictate the evolution of the Universe. While many filament estimators have been proposed, they generally lack estimates of uncertainty, reducing their inferential power. In this paper, we demonstrate how one may apply the subspace constrained mean shift (SCMS) algorithm (Ozertem & Erdogmus 2011; Genovese et al. 2014) to uncover filamentary structure in galaxy data. The SCMS algorithm is a gradient ascent method that models filaments as density ridges, one-dimensional smooth curves that trace high-density regions within the point cloud. We also demonstrate how augmenting the SCMS algorithm with bootstrap-based methods of uncertainty estimation allows one to place uncertainty bands around putative filaments.We apply the SCMS first to the data set generated from the Voronoi model. The density ridges show strong agreement with the filaments from Voronoi method.We then apply the SCMS method data sets sampled from a P3M N-body simulation, with galaxy number densities consistent with SDSS and WFIRST-AFTA, and to LOWZ and CMASS data from the Baryon Oscillation Spectroscopic Survey (BOSS). To further assess the efficacy of SCMS, we compare the relative locations of BOSS filaments with galaxy clusters in the redMaPPer catalogue, and find that redMaPPer clusters are significantly closer (with p-values <10-9) to SCMS-detected filaments than to randomly selected galaxies. [ABSTRACT FROM AUTHOR]

POLYCHORD is a novel nested sampling algorithm tailored for high-dimensional parameter spaces. This paper coincides with the release of POLYCHORD v1.6, and provides an extensive account of the algorithm. POLYCHORD utilizes slice sampling at each iteration to sample within the hard likelihood constraint of nested sampling. It can identify and evolve separate modes of a posterior semi-independently, and is parallelized using OPENMPI. It is capable of exploiting a hierarchy of parameter speeds such as those present in COSMOMC and CAMB, and is now in use in the COSMOCHORD and MODECHORD codes. POLYCHORD is available for download from http://ccpforge.cse.rl.ac.uk/gf/project/polychord/. [ABSTRACT FROM AUTHOR]

We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, which can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitude less storage space. The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular neural network code (ANNZ). In our use case, this improvement reaches 50 percent for high-redshift objects (z ≥ 0.75). We show that using these more accurate photometric redshift PDFs will lead to a reduction in the systematic biases by up to a factor of 4, when compared with less accurate PDFs obtained from commonly used methods. The cosmological analyses we examine and find improvement upon are the following: gravitational lensing cluster mass estimates, modelling of angular correlation functions and modelling of cosmic shear correlation functions. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel approach to the estimation of strongly varying backgrounds in astronomical images by means of small-objects removal and subsequent missing pixels interpolation. The method is based on the analysis of a pixel local neighbourhood and utilizes the morphological distance transform. In contrast to popular background-estimation techniques, our algorithm allows for accurate extraction of complex structures, like galaxies or nebulae. Moreover, it does not require multiple tuning parameters, since it relies on physical properties of CCD image sensors -- the gain and the readout noise characteristics. The comparison with other widely used background estimators revealed higher accuracy of the proposed technique. The superiority of the novel method is especially significant for the most challenging fluctuating backgrounds. The size of filtered-out objects is tunable; therefore, the algorithm may eliminate a wide range of foreground structures, including the dark current impulses, cosmic rays or even entire galaxies in deep field images. [ABSTRACT FROM AUTHOR]

Masses of clusters of galaxies from weak gravitational lensing analyses of ever larger samples are increasingly used as the reference to which baryonic scaling relations are compared. In this paper we revisit the analysis of a sample of 50 clusters studied as part of the Canadian Cluster Comparison Project. We examine the key sources of systematic error in cluster masses. We quantify the robustness of our shape measurements and calibrate our algorithm empirically using extensive image simulations. The source redshift distribution is revised using the latest state-of-the-art photometric redshift catalogues that include new deep near-infrared observations. None the less we find that the uncertainty in the determination of photometric redshifts is the largest source of systematic error for our mass estimates. We use our updated masses to determine b, the bias in the hydrostatic mass, for the clusters detected by Planck. Our results suggest 1 - b = 0.76 ± 0.05 (stat) ± 0.06 (syst), which does not resolve the tension with the measurements from the primary cosmic microwave background. [ABSTRACT FROM AUTHOR]

Juno is a NASA mission launched in 2011 with the goal of studying Jupiter. The probe will arrive to the planet in 2016 and will be placed for one year in a polar high-eccentric orbit to study the composition of the planet, the gravity and the magnetic field. The Italian Space Agency (ASI) provided the radio science instrument KaT (Ka-Band Translator) used for the gravity experiment, which has the goal of studying the Jupiter's deep structure by mapping the planet's gravity: such instrument takes advantage of synergies with a similar tool in development for BepiColombo, the ESA cornerstone mission to Mercury. The Celestial Mechanics Group of the University of Pisa, being part of the Juno Italian team, is developing an orbit determination and parameters estimation software for processing the real data independently from NASA software ODP. This paper has a twofold goal: first, to tell about the development of this software highlighting the models used, secondly, to perform a sensitivity analysis on the parameters of interest to the mission. [ABSTRACT FROM AUTHOR]

We applied computational tools for automatic detection of peculiar galaxy pairs. We first detected in Sloan Digital Sky Survey DR7 ∼400 000 galaxy images with i magnitude <18 that had more than one point spread function, and then applied a machine learning algorithm that detected ∼26 000 galaxy images that had morphology similar to the morphology of galaxy mergers. That data set was mined using a novelty detection algorithm, producing a short list of 500 most peculiar galaxies as quantitatively determined by the algorithm. Manual examination of these galaxies showed that while most of the galaxy pairs in the list were not necessarily peculiar, numerous unusual galaxy pairs were detected. In this paper, we describe the protocol and computational tools used for the detection of peculiar mergers, and provide examples of peculiar galaxy pairs that were detected. [ABSTRACT FROM PUBLISHER]

The spherical Jeans equation is widely used to estimate the mass content of stellar systems with apparent spherical symmetry. However, this method suffers from a degeneracy between the assumed mass density and the kinematic anisotropy profile, β(r). In a previous work, we laid the theoretical foundations for an algorithm that combines smoothing B splines with equations from dynamics to remove this degeneracy. Specifically, our method reconstructs a unique kinematic profile of $\sigma _{{\rm rr}}^2$ and $\sigma _{{\rm tt}}^2$ for an assumed free functional form of the potential and mass density (Φ, ρ) and given a set of observed line-of-sight velocity dispersion measurements, $\sigma _{\rm los}^2$. In Paper I, we demonstrated the efficiency of our algorithm with a very simple example and we commented on the need for optimum smoothing of the B-spline representation; this is in order to avoid unphysical variational behaviour when we have large uncertainty in our data. In the current contribution, we present a process of finding the optimum smoothing for a given data set by using information of the behaviour from known ideal theoretical models. Markov Chain Monte Carlo methods are used to explore the degeneracy in the dynamical modelling process. We validate our model through applications to synthetic data for systems with constant or variable mass-to-light ratio ϒ. In all cases, we recover excellent fits of theoretical functions to observables and unique solutions. Our algorithm is a robust method for the removal of the mass–anisotropy degeneracy of the spherically symmetric Jeans equation for an assumed functional form of the mass density. [ABSTRACT FROM PUBLISHER]

With the commissioning year of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST), the data archive of one-dimensional spectra is being released gradually. Searching for special objects like cataclysmic variables (CVs) in the data is one of LAMOST's objectives. This paper presents a novel method to identify CVs from optical spectra by using the support-vector machine (SVM) technique combined with principal-component analysis (PCA). After dimension reduction and feature extraction by PCA, spectral data are classified by SVM and most non-CVs are excluded. The final reduced list can be identified manually or by a template-matching algorithm. Experiments show that this data-mining method can find CVs from the LAMOST data base in an effective and efficient manner. We report the identification of 10 cataclysmic variables, of which two are new discoveries. In addition, this method is also applicable to mining other special celestial objects in sky-survey telescope data. [ABSTRACT FROM PUBLISHER]

We have performed an extensive search for planet candidates in the publicly available Kepler long cadence data from quarters Q1 through Q6. The search method consists of initial de-trending of the data, applying the trend filtering algorithm, searching for transit signals with the Box Least Squares fitting method in three frequency domains, visual inspection of the potential transit candidates and an in-depth analysis of the shortlisted candidates. In this paper we present 150 new periodic planet candidates and seven single transit events, 72 of which are in multiple systems. The periods of these planet candidates vary from ∼0.17 to ∼440 d. 124 of the planet candidates have radii smaller than 3 R⊕. We recover 82.5 per cent of the Batalha et al. Kepler Objects of Interest (KOI) catalogue. We also report 40 newly identified false positives – systems that look like transiting planets, but are probably due to blended eclipsing binaries. Our search improves the statistics in the short-period and small-planet radii parameter ranges. [ABSTRACT FROM PUBLISHER]

In this paper an algorithm to deal with the singularity problem in the orbital mechanics is proposed. Lagrangian and Gaussian equations of motion are transformed into singularity-free ones by multiplying the so-called singular factors to the individual equations and the intermediate solutions can be derived by indefinite integration. Two criteria are introduced to decide how to transform the intermediate solutions into the solutions of the original problems inversely. Two examples, orbit solutions disturbed by the solar oblateness and the solar radiation pressure, are given to show the applicability of the algorithm. A similar method to solve the so-called critical inclination problem is also discussed with an example. Comments on the traditional variable transformations used to solve the singularity problem are also addressed. [ABSTRACT FROM AUTHOR]