Search

If a hypothetical elementary particle called an axion exists, to solve the strong CP problem, a 57Fe nucleus in the solar core could emit a 14.4-keV monochromatic axion through the M1 transition. If such axions are once more transformed into photons by a 57Fe absorber, a transition edge sensor (TES) X-ray microcalorimeter should be able to detect them efficiently. We have designed and fabricated a dedicated 64-pixel TES array with iron absorbers for the solar axion search. In order to decrease the effect of iron magnetization on spectroscopic performance, the iron absorber is placed next to the TES while maintaining a certain distance. A gold thermal transfer strap connects them. We have accomplished the electroplating of gold straps with high thermal conductivity. The residual resistivity ratio (RRR) was over 23, more than eight times higher than a previous evaporated strap. In addition, we successfully electroplated pure-iron films of more than a few micrometers in thickness for absorbers and a fabricated 64-pixel TES calorimeter structure., 5 pages, 5 figures, published in IEEE Transactions on Applied Superconductivity on 8 March 2023

This work presents a suite of measurement techniques for characterizing the dielectric loss tangent across a wide frequency range from $\sim$1 GHz to 150 GHz using the same test chip. In the first method, we fit data from a microwave resonator at different temperatures to a model that captures the two-level system (TLS) response to extract and characterize both the real and imaginary components of the dielectric loss. The inverse of the internal quality factor is a second measure of the overall loss of the resonator, where TLS loss through the dielectric material is typically the dominant source. The third technique is a differential optical measurement at 150 GHz. The same antenna feeds two microstrip lines with different lengths that terminate in two microwave kinetic inductance detectors (MKIDs). The difference in the detector response is used to estimate the loss per unit length of the microstrip line. Our results suggest a larger loss for SiN$_x$ at 150 GHz of ${\mathrm{\tan \delta\sim 4\times10^{-3}}}$ compared to ${\mathrm{2.0\times10^{-3}}}$ and ${\mathrm{\gtrsim 1\times10^{-3}}}$ measured at $\sim$1 GHz using the other two methods. {These measurement techniques can be applied to other dielectrics by adjusting the microstrip lengths to provide enough optical efficiency contrast and other mm/sub-mm frequency ranges by tuning the antenna and feedhorn accordingly.

The Cosmology Large Angular Scale Surveyor (CLASS) is a polarization-sensitive telescope array located at an altitude of 5,200 m in the Chilean Atacama Desert and designed to measure the polarized Cosmic Microwave Background (CMB) over large angular scales. The CLASS array is currently observing with three telescopes covering four frequency bands: one at 40 GHz (Q); one at 90 GHz (W1); and one dichroic system at 150/220 GHz (HF). During the austral winter of 2022, we upgraded the first 90 GHz telescope (W1) by replacing four of the seven focal plane modules. These new modules contain detector wafers with an updated design, aimed at improving the optical efficiency and detector stability. We present a description of the design changes and measurements of on-sky optical efficiencies derived from observations of Jupiter., 5 pages, 3 figures, to appear in the IEEE Transactions on Applied Superconductivity. arXiv admin note: text overlap with arXiv:2208.05006

Line Intensity Mapping (LIM) is a new observational technique that uses low-resolution observations of line emission to efficiently trace the large-scale structure of the Universe out to high redshift. Common mm/sub-mm emission lines are accessible from ground-based observatories, and the requirements on the detectors for LIM at mm-wavelengths are well matched to the capabilities of large-format arrays of superconducting sensors. We describe the development of an R = 300 on-chip superconducting filter-bank spectrometer covering the 120--180 GHz band optimized for future mm-LIM experiments, focusing on SPT-SLIM, a pathfinder LIM instrument for the South Pole Telescope. Radiation is coupled from the telescope optical system to the spectrometer chip via an array of feedhorn-coupled orthomode transducers. Superconducting microstrip transmission lines then carry the signal to an array of channelizing half-wavelength resonators, and the output of each spectral channel is sensed by a lumped element kinetic inductance detector (leKID). Key areas of development include incorporating new low-loss dielectrics to improve both the achievable spectral resolution and optical efficiency and development of a robust fabrication process to create a galvanic connection between ultra-pure superconducting thin-films to realize multi-material (hybrid) leKIDs. We provide an overview of the spectrometer design, fabrication process, and prototype devices., 7 pages, 7 figures, presented at 2022 Applied Superconductivity Conference

Trajectory optimization of low-thrust perturbed orbit rendezvous is a crucial technology for space missions in low Earth orbits, which is difficult to solve due to its initial value sensitivity, especially when the transfer trajectory has many revolutions. This paper investigated the time-fixed perturbed orbit rendezvous between low-eccentricity orbits and proposed a priori quasi-optimal thrust strategy to simplify the problem into a parametric optimization problem, which significantly reduces the complexity. The optimal trajectory is divided into three stages including transfer to a certain intermediate orbit, thrust-off drifting and transfer from intermediate orbit to the target orbit. In the two transfer stages, the spacecraft is assumed to use a parametric law of thrust. Then, the optimization model can be then obtained using very few unknowns. Finally, a differential evolution algorithm is adopted to solve the simplified optimization model and an analytical correction process is proposed to eliminate the numerical errors. Simulation results and comparisons with previous methods proved this new method's efficiency and high precision for low-eccentricity orbits. The method can be well applied to premilitary analysis and high-precision trajectory optimization of missions such as in-orbit service and active debris removal in low Earth orbits.

This work generalizes the discrete implicit Monte-Carlo (DIMC) method for modeling the radiative transfer equation from a gray treatment to an frequency-dependent one. The classic implicit Monte-Carlo (IMC) algorithm, that has been used for several decades, suffers from a well-known numerical problem, called teleportation, where the photons might propagate faster than the exact solution due to the finite size of the spatial and temporal resolution. The Semi-analog Monte-Carlo algorithm proposed the use of two kinds of particles, photons and material particles that are born when a photon is absorbed. The material particle can `propagate' only by transforming into a photon, due to black-body emission. While this algorithm produces a teleportation-free result, it is noisier results compared to IMC due to the discrete nature of the absorption-emission process. In a previous work [Steinberg and Heizler, ApJS, 258:14 (2022)], proposed a gray version of DIMC, that makes use of two kinds of particles, and therefore has teleportation-free results, but also uses the continuous absorption algorithm of IMC, yielding smoother results. This work is a direct frequency-dependent (energy-dependent) generalization of the DIMC algorithm. We find in several one and two dimensional benchmarks, that the new frequency-dependent DIMC algorithm yields teleportation-free results on one hand, and smooth results with IMC-like noise level., Comment: 22 pages, 6 figures

Fast radio bursts (FRBs) are mysterious astronomical phenomena, and it is still uncertain whether they consist of multiple types. In this study we use two nonlinear dimensionality reduction algorithms - Uniform Manifold Approximation and Projection (UMAP) and t-distributed stochastic neighbour embedding (t-SNE) - to differentiate repeaters from apparently non-repeaters in FRBs. Based on the first Canadian Hydrogen Intensity Mapping Experiment (CHIME) FRB catalogue, these two methods are applied to standardized parameter data and image data from a sample of 594 sub-bursts and 535 FRBs, respectively. Both methods are able to differentiate repeaters from apparently non-repeaters. The UMAP algorithm using image data produces more accurate results and is a more model-independent method. Our result shows that in general repeater clusters tend to be narrowband, which implies a difference in burst morphology between repeaters and apparently non-repeaters. We also compared our UMAP predictions with the CHIME/FRB discovery of 6 new repeaters, the performance was generally good except for one outlier. Finally, we highlight the need for a larger and more complete sample of FRBs., 10 pages, 9 figures, 4 tables, accepted by MNRAS

We present a generalized estimator for the autocorrelation function, S-ACF, which is an extended version of the standard estimator of the autocorrelation function (ACF). S-ACF is a versatile definition that can robustly and efficiently extract periodicity and signal shape information from a time series, independent of the time sampling and with minimal assumptions about the underlying process. Calculating the autocorrelation of irregularly sampled time series becomes possible by generalizing the lag of the standard estimator of the ACF to a real parameter and introducing the notion of selection and weight functions. We show that the S-ACF reduces to the standard ACF estimator for regularly sampled time series. Using a large number of synthetic time series, we demonstrate that the performance of the S-ACF is as good or better than commonly used Gaussian and rectangular kernel estimators, and is comparable to a combination of interpolation and the standard estimator. We apply the S-ACF to astrophysical data by extracting rotation periods for the spotted star KIC 5110407, and compare our results to Gaussian process (GP) regression and Lomb–Scargle (LS) periodograms. We find that the S-ACF periods typically agree better with those from GP regression than from LS periodograms, especially in cases where there is evolution in the signal shape. The S-ACF has a wide range of potential applications and should be useful in quantitative science disciplines where irregularly sampled time series occur. A python implementation of the S-ACF is available under the MIT license.

Constraints on the formation and evolution of the Milky Way Galaxy require multidimensional measurements of kinematics, abundances, and ages for a large population of stars. Ages for luminous giants, which can be seen to large distances, are an essential component of studies of the Milky Way, but they are traditionally very difficult to estimate precisely for a large data set and often require careful analysis on a star-by-star basis in asteroseismology. Because spectra are easier to obtain for large samples, being able to determine precise ages from spectra allows for large age samples to be constructed, but spectroscopic ages are often imprecise and contaminated by abundance correlations. Here we present an application of a variational encoder–decoder on cross-domain astronomical data to solve these issues. The model is trained on pairs of observations from APOGEE and Kepler of the same star in order to reduce the dimensionality of the APOGEE spectra in a latent space while removing abundance information. The low dimensional latent representation of these spectra can then be trained to predict age with just ∼1000 precise seismic ages. We demonstrate that this model produces more precise spectroscopic ages ($\sim 22~{{\ \rm per\ cent}}$ overall, $\sim 11~{{\ \rm per\ cent}}$ for red-clump stars) than previous data-driven spectroscopic ages while being less contaminated by abundance information (in particular, our ages do not depend on [α/M]). We create a public age catalogue for the APOGEE DR17 data set and use it to map the age distribution and the age-[Fe/H]-[α/M] distribution across the radial range of the Galactic disc.

Current space-based missions, such as the Transiting Exoplanet Survey Satellite (TESS), provide a large database of light curves that must be analysed efficiently and systematically. In recent years, deep learning (DL) methods, particularly convolutional neural networks (CNN), have been used to classify transit signals of candidate exoplanets automatically. However, CNNs have some drawbacks; for example, they require many layers to capture dependencies on sequential data, such as light curves, making the network so large that it eventually becomes impractical. The self-attention mechanism is a DL technique that attempts to mimic the action of selectively focusing on some relevant things while ignoring others. Models, such as the Transformer architecture, were recently proposed for sequential data with successful results. Based on these successful models, we present a new architecture for the automatic classification of transit signals. Our proposed architecture is designed to capture the most significant features of a transit signal and stellar parameters through the self-attention mechanism. In addition to model prediction, we take advantage of attention map inspection, obtaining a more interpretable DL approach. Thus, we can identify the relevance of each element to differentiate a transit signal from false positives, simplifying the manual examination of candidates. We show that our architecture achieves competitive results concerning the CNNs applied for recognizing exoplanetary transit signals in data from the TESS telescope. Based on these results, we demonstrate that applying this state-of-the-art DL model to light curves can be a powerful technique for transit signal detection while offering a level of interpretability.

The light-cone (LC) anisotropy arises due to cosmic evolution of the cosmic dawn 21-cm signal along the line-of-sight (LoS) axis of the observation volume. The LC effect makes the signal statistically non-ergodic along the LoS axis. The multi-frequency angular power spectrum (MAPS) provides an unbiased alternative to the popular 3D power spectrum as it does not assume statistical ergodicity along every direction in the signal volume. Unlike the 3D power spectrum which mixes the cosmic evolution of the 21-cm signal along the LoS $k$ modes, MAPS keeps the evolution information disentangled. Here we first study the impact of different underlying physical processes during cosmic dawn on the behaviour of the 21-cm MAPS using simulations of various different scenarios and models. We also make error predictions in 21-cm MAPS measurements considering only the system noise and cosmic variance for mock observations of HERA, NenuFAR and SKA-Low. We find that $100~{\rm h}$ of HERA observations will be able to measure 21-cm MAPS at $\geq 3\sigma$ for $\ell \lesssim 1000$ with $0.1\,{\rm MHz}$ channel-width. The better sensitivity of SKA-Low allows reaching this sensitivity up to $\ell \lesssim 3000$. Note that due to the difference in the frequency coverage of the various experiements, the CD-EoR model considered for NenuFAR is different than those used for the HERA and SKA-Low predictions. Considering NenuFAR with the new model, measurements $\geq 2\sigma$ are possible only for $\ell \lesssim 600$ with $0.2\,{\rm MHz}$ channel-width and for a ten times longer observation time of $t_{\rm obs} = 1000~{\rm h}$. However, for the range $300 \lesssim \ell \lesssim 600$ and $t_{\rm obs}=1000~{\rm h}$ more than $3\sigma$ measurements are still possible for NenuFAR when combining consecutive frequency channels within a $5 ~{\rm MHz}$ band., Comment: 21 pages, 12 figures, 3 tables, accepted for publication in MNRAS

Polarized synchrotron emission from multiple Faraday depths can be separated by calculating the complex Fourier transform of the Stokes' parameters as a function of the wavelength squared, known as Faraday Synthesis. As commonly implemented, the transform introduces an additional term $\lambda_0^2$, which broadens the real and imaginary spectra, but not the amplitude spectrum. We use idealized tests to investigate whether additional information can be recovered with a clean process restoring beam set to the narrower width of the peak in the real ``full" resolution spectrum with $\lambda_0^2=0$. We find that the $\lambda_0^2$ choice makes no difference, except for the use of a smaller restoring beam. With this smaller beam, the accuracy and phase stability are unchanged for single Faraday components. However, using the smaller restoring beam for multiple Faraday components we find a) better discrimination of the components, b) significant reductions in blending of structures in tomography images, and c) reduction of spurious features in the Faraday spectra and tomography maps. We also discuss the limited accuracy of information on scales comparable to the width of the amplitude spectrum peak, and note a clean-bias, reducing the recovered amplitudes. We present examples using MeerKAT L-band data. We also revisit the maximum width in Faraday depth to which surveys are sensitive, and introduce the variable $W_{max}$, the width for which the power drops by a factor of 2. We find that most surveys cannot resolve continuous Faraday distributions unless the narrower full restoring beam is used., Comment: 17 pages, 23 figures, published in MNRAS

Hydrodynamical numerical methods that converge with high-order hold particular promise for astrophysical studies, as they can in principle reach prescribed accuracy goals with higher computational efficiency than standard second- or third-order approaches. Here we consider the performance and accuracy benefits of Discontinuous Galerkin (DG) methods, which offer a particularly straightforward approach to reach extremely high order. Also, their computational stencil maps well to modern GPU devices, further raising the attractiveness of this approach. However, a traditional weakness of this method lies in the treatment of physical discontinuities such as shocks. We address this by invoking an artificial viscosity field to supply required dissipation where needed, and which can be augmented, if desired, with physical viscosity and thermal conductivity, yielding a high-order treatment of the Navier-Stokes equations for compressible fluids. We show that our approach results in sub-cell shock capturing ability, unlike traditional limiting schemes that tend to defeat the benefits of going to high order in DG in problems featuring many shocks. We demonstrate exponential convergence of our solver as a function of order when applied to smooth flows, such as the Kelvin-Helmholtz reference problem of arXiv:1509.03630. We also demonstrate excellent scalability of our GPU implementation up to hundreds of GPUs distributed on different compute nodes. In a first application to driven, sub-sonic turbulence, we highlight the accuracy advantages of high-order DG compared to traditional second-order accurate methods, and we stress the importance of physical viscosity for obtaining accurate velocity power spectra., Comment: 27 pages, 22 figures, accepted for publication in MNRAS

The spin evolution of main sequence stars has long been of interest for basic stellar evolution, stellar aging, stellar activity, and consequent influence on companion planets. Observations of older than solar late-type main-sequence stars have been interpreted to imply that a change from a dipole-dominated magnetic field to one with more prominent higher multipoles might be necessary to account for the data. The spin-down models that lead to this inference are essentially tuned to the sun. Here we take a different approach which considers individual stars as fixed points rather than just the Sun. We use a time-dependent theoretical model to solve for the spin evolution of low-mass main-sequence stars that includes a Parker-type wind and a time-evolving magnetic field coupled to the spin. Because the wind is exponentially sensitive to the stellar mass over radius and the coronal base temperature, the use of each observed star as a separate fixed point is more appropriate and, in turn, produces a set of solution curves that produces a solution envelope rather than a simple line. This envelope of solution curves, unlike a single line fit, is consistent with the data and does not unambiguously require a modal transition in the magnetic field to explain it., 8 pages, 4 figures; Accepted for publication in MNRAS

The Search for Extra-Terrestrial Intelligence (SETI) has been conducted for over sixty years, yet no technosignatures have been identified. Previous studies have focused on stars in our galaxy, with few searches in the extragalactic Universe despite a larger volume being available. Civilizations capable of harvesting energy from a star or a galaxy are classified as KII or KIII on the Kardashev scale, respectively. Technosignatures from such advanced civilizations would be extremely luminous and detectable by current radio telescopes, even from distant galaxies. To explore the frontier of extragalactic SETI, we investigate the likely prevalence of extragalactic civilizations possessing a radio transmitter, known as the transmitter rate, based on observational results from the Breakthrough Listen (BL) observations. We calculated the transmitter rate by considering the background galaxies in the field of view of target stars in BL observations. We used a statistical method to derive the total mass of stars in those background galaxies from a galaxy stellar mass function. Our statistical method suggests that less than one in hundreds of trillions of extragalactic civilizations within 969 Mpc possess a radio transmitter above 7.7$\times$10$^{26}$ W of power, assuming one civilization per one-solar-mass stellar system. Additionally, we cross-matched the BL survey fields with the WISE$\times$SuperCOSMOS Photometric Redshift Catalogue and compared with the statistical method. Our result sets the strictest limits to date on the transmitter rate at such high power levels, emphasizing the high efficiency of searching for radio transmitters in galaxies and the rarity of technologically advanced civilizations in our Universe., 5 pages, 1 figure, accepted for publication in MNRAS. A summary video is available: https://www.youtube.com/watch?v=_xaRCnLMjsY&t=21s&ab_channel=NCHUAstronomy

State-of-the-art radio observatories produce large amounts of data which can be used to study the properties of radio galaxies. However, with this rapid increase in data volume, it has become unrealistic to manually process all of the incoming data, which in turn led to the development of automated approaches for data processing tasks, such as morphological classification. Deep learning plays a crucial role in this automation process and it has been shown that convolutional neural networks (CNNs) can deliver good performance in the morphological classification of radio galaxies. This paper investigates two adaptations to the application of these CNNs for radio galaxy classification. The first adaptation consists of using principal component analysis (PCA) during preprocessing to align the galaxies' principal components with the axes of the coordinate system, which will normalize the orientation of the galaxies. This adaptation led to a significant improvement in the classification accuracy of the CNNs and decreased the average time required to train the models. The second adaptation consists of guiding the CNN to look for specific features within the samples in an attempt to utilize domain knowledge to improve the training process. It was found that this adaptation generally leads to a stabler training process and in certain instances reduced overfitting within the network, as well as the number of epochs required for training., 20 pages, 17 figures, this is a pre-copyedited, author-produced PDF of an article accepted for publication in the Monthly Notices of the Royal Astronomical Society

Supermassive black holes (SMBHs) are a key catalyst of galaxy formation and evolution, leading to an observed correlation between SMBH mass $M_{\rm BH}$ and host galaxy velocity dispersion $\sigma_{\rm e}$. Outside the local Universe, measurements of $M_{\rm BH}$ are usually only possible for SMBHs in an active state: limiting sample size and introducing selection biases. Gravitational lensing makes it possible to measure the mass of non-active SMBHs. We present models of the $z=0.169$ galaxy-scale strong lens Abell~1201. A cD galaxy in a galaxy cluster, it has sufficient `external shear' that a magnified image of a $z = 0.451$ background galaxy is projected just $\sim 1$ kpc from the galaxy centre. Using multi-band Hubble Space Telescope imaging and the lens modeling software $\texttt{PyAutoLens}$ we reconstruct the distribution of mass along this line of sight. Bayesian model comparison favours a point mass with $M_{\rm BH} = 3.27 \pm 2.12\times10^{10}\,$M$_{\rm \odot}$ (3$\sigma$ confidence limit); an ultramassive black hole. One model gives a comparable Bayesian evidence without a SMBH, however we argue this model is nonphysical given its base assumptions. This model still provides an upper limit of $M_{\rm BH} \leq 5.3 \times 10^{10}\,$M$_{\rm \odot}$, because a SMBH above this mass deforms the lensed image $\sim 1$ kpc from Abell 1201's centre. This builds on previous work using central images to place upper limits on $M_{\rm BH}$, but is the first to also place a lower limit and without a central image being observed. The success of this method suggests that surveys during the next decade could measure thousands more SMBH masses, and any redshift evolution of the $M_{\rm BH}$--$\sigma_{\rm e}$ relation. Results are available at https://github.com/Jammy2211/autolens_abell_1201., Comment: Accepted in MNRAS, 27 pages, 22 figures

We present an analysis of Epoch of Reionization data from Phase II of the Murchison Widefield Array using the \texttt{simpleDS} delay spectrum pipeline. Prior work analyzed the same observations using the FHD/$\varepsilon$ppsilon imaging pipeline, and so the present analysis represents the first time that both principal types of 21 cm cosmology power spectrum estimation approaches have been applied to the same data set. Our limits on the 21 cm power spectrum amplitude span a range in $k$ space of $|k| < 1~h_{100}{\rm Mpc}^{-1}$ with a lowest measurement of $\Delta^2(k) \leq$ $4.58\times10^3$ mK$^2$ at $k = 0.190 h_{100}\rm{Mpc}^{-1}$ and $z = 7.14$. In order to achieve these limits, we need to mitigate a previously unidentified common mode systematic in the data set. If not accounted for, this systematic introduces an overall \emph{negative} bias that can make foreground contaminated measurements appear as stringent, noise-limited constraints on the 21 cm signal amplitude. The identification of this systematic highlights the risk in modeling systematics as positive-definite contributions to the power spectrum and in ``conservatively'' interpreting all measurements as upper limits., Comment: 19 pages, 12 figures, Accepted by MNRAS; Updated to match published version

Small Solar System bodies are pristine remnants of Solar System formation, which provide valuable insights for planetary science and astronomy. Their discovery and cataloging also have strong practical implications to life on Earth as the nearest asteroids could pose a serious impact threat. Concurrently with dedicated observational projects, searches for small bodies have been performed on numerous archival data sets from different facilities. Here, we present a framework to increase the scientific return of an exoplanet transit-search survey by recovering serendipitous detections of small bodies in its daily and archival data using a GPU-based synthetic tracking algorithm. As a proof of concept, we analysed $12 \times 12 \mathrm{arcmin^2}$ sky fields observed by the 1-m telescopes of the SPECULOOS survey. We analysed 90 sky fields distributed uniformly across the sky as part of the daily search for small bodies and 21 archival fields located within 5 deg from the ecliptic plane as part of the archival search (4.4 deg$^2$ in total). Overall, we identified 400 known objects of different dynamical classes from Inner Main-belt Asteroids to Jupiter Trojans and 43 potentially new small bodies with no priors on their motion. We were able to reach limiting magnitude for unknown objects of $V$=23.8 mag, and a retrieval rate of $\sim$80% for objects with $V, Accepted for publication in MNRAS (Monthly Notices of the Royal Astronomical Society), 11 pages, 11 figures

We present the results of determining the coordinates of the vertices of various stellar systems, the centroids of which are located in the Galactic plane. To do this, the positions, parallaxes, proper motions, and radial velocities of red giants and subgiants contained in the $Gaia$~DR3 catalogue have been used. When determining the components of the deformation velocity tensors in local coordinate systems, we found the coordinates of the vertices of the stellar systems under study. It turned out that there is a complex dependence of vertex deviations $l_{xy}$ in Galactocentric cylindrical ($R, \theta$) and Galactic rectangular ($X,Y$) coordinates. Based on the approach proposed in this paper, heliocentric distances to vertices have been determined for the first time. The results obtained show that in addition to the fact that the angular coordinates of the Galactic center and the vertices of stellar systems do not coincide, their heliocentric distances do not coincide as well. This presumably indicates that there are structures in the Galaxy that noticeably affect its axisymmetry., Comment: 10 pages, 14 figures, 1 tables

The determination of distance is fundamental in astrophysics. Gamma-ray sources are poorly characterized in this sense, as the limited angular resolution and poor photon-count statistics in gamma-ray astronomy makes it difficult to associate them to a multiwavelength object with known redshift. Taking the 1794 active galactic nuclei (AGNs) with known redshift from the Fermi-LAT latest AGN catalog, 4LAC-DR3, we employ machine learning techniques to predict the distance of the rest of AGNs based on their spectral and spatial properties. The state-of-the-art CatBoost algorithm reaches an average 0.56 R2 score with 0.46 root-mean-squared error (RMSE), predicting an average redshift value of $z_{avg}=0.63$, with a maximum $z_{max}=1.97$. We use the SHAP explainer package to gain insights into the variables influence on the outcome, and also study the extragalactic bakground light (EBL) implications. In a second part, we use this regression model to predict the redshift of the unassociated sample of the latest LAT point-source catalog, 4FGL-DR3, using the results of a previous paper to determine the possible AGNs within them., 7 pages, 7 figures. Matches the accepted MNRAS version

Nested sampling (NS) is a popular algorithm for Bayesian computation. We investigate statistical errors in NS both analytically and numerically. We show two analytic results. First, we show that the leading terms in Skilling's expression using information theory match the leading terms in Keeton's expression from an analysis of moments. This approximate agreement was previously only known numerically and was somewhat mysterious. Second, we show that the uncertainty in single NS runs approximately equals the standard deviation in repeated NS runs. Whilst intuitive, this was previously taken for granted. We close by investigating our results and their assumptions in several numerical examples, including cases in which NS uncertainties increase without bound., 12 pages + appendices, 3 figures

The homologous collapse from rest of a uniform density sphere under its self gravity is a well-known toy model for the formation dynamics of astronomical objects ranging from stars to galaxies. Equally well-known is that the evolution of the radius with time cannot be explicitly obtained because of the transcendental nature of the differential equation solution. Rather, both radius and time are written parametrically in terms of the development angle $\theta$. We here present an explicit integral solution for radius as a function of time, exploiting methods from complex analysis recently applied to the mathematically-similar 'geometric goat problem'. Our solution can be efficiently evaluated using a Fast Fourier Transform and allows for arbitrary sampling in time, with a simple Python implementation that is $\sim$$100\times$ faster than using numerical root-finding to achieve arbitrary sampling. Our explicit solution is advantageous relative to the usual approach of first generating a uniform grid in $\theta$, since this latter results in a non-uniform radial or time sampling, less useful for applications such as generation of sub-grid physics models., Comment: 4 pages, 3 figures, submitted to MNRAS. Python implementation available at https://gist.github.com/oliverphilcox/559f086f1bf63b23d55c508b2f47bad3

In this paper, we introduce our open source implementation of the Coupled Discrete Unified Gas Kinetic Scheme (CDUGKS) of https://journals.aps.org/pre/abstract/10.1103/PhysRevE.98.053310, a phase space scheme capable of handling a wide range of flow regimes. We demonstrate its performance on several problems including a number of well known test problems from the astrophysical fluid dynamics literature such as the 1D Sod shock tube, 2D Kelvin-Helmholtz instability, 1D thermoacoustic wave, a triangular Gresho vortex, a sine wave velocity perturbation. For these problems, we show that the code can simulate flows ranging from the inviscid/Eulerian regime to the free-streaming regime, capturing shocks and emergent diffusive processes in the appropriate regimes. We also use a variety of Prandtl numbers to demonstrate the scheme's ability to simulate different thermal conductivities at fixed viscosity. The scheme is second-order accurate in space and time and, unlike many solvers, uses a time step that is independent of the mean free path of the gas. Our code (MP-CDUGKS) is public under a CC0 1.0 Universal license and is available on https://github.com/alvarozamora/CDUGKS

Removing optical and atmospheric blur from galaxy images significantly improves galaxy shape measurements for weak gravitational lensing and galaxy evolution studies. This ill-posed linear inverse problem is usually solved with deconvolution algorithms enhanced by regularisation priors or deep learning. We introduce a so-called ’physics-informed deep learning’ approach to the Point Spread Function (PSF) deconvolution problem in galaxy surveys. We apply algorithm unrolling and the Plug-and-Play technique to the Alternating Direction Method of Multipliers (ADMM), in which a neural network learns appropriate hyperparameters and denoising priors from simulated galaxy images. We characterize the time-performance trade-off of several methods for galaxies of differing brightness levels, as well as our method’s robustness to systematic PSF errors and network ablations. We show an improvement in reduced shear ellipticity error of 38.6 per cent (SNR=20)/45.0 per cent (SNR=200) compared to classic methods and 7.4 per cent (SNR=20)/33.2 per cent (SNR = 200) compared to modern methods (https://github.com/Lukeli0425/Galaxy-Deconv).

Direct imaging of exoplanets will allow us to directly observe the planet in reflected light. Such a scenario may eventually allow for the possibility to scan the planetary surface for the presence of artificial structures made by alien civilizations. Detectability of planetary scale structures, called megastructures, has been previously explored. In this work, we show that it is possible to detect structures of much smaller scale on exoplanetary surfaces by searching for the specular reflection of host starlight from the corresponding structures. As the planet rotates, these reflections can manifest as an optical transient riding atop the rotational light curve of the planet. Due to the directional nature of specular reflection, the reflected signal is very strong, and it is comparable to the planetary flux for surfaces covering only few ppm (parts per million) of the total planet surface area. By tracking the planet around its orbit, it should be possible to scan the planetary surface for any such structures covering a size larger than a few ppm of planetary surface. The proposed method will aid in the search for extra-terrestrial intelligence in the era of direct imaging of exoplanets., Comment: 2 figures, 4 pages, published in Astrobiology

A new water-Cherenkov radiation detector, located at the Argentine Marambio Antarctic Base (64.24S-56.62W), has been monitoring the variability of galactic cosmic ray (GCR) flux since 2019. One of the main aims is to provide experimental data necessary to study interplanetary transport of GCRs during transient events at different space/time scales. In this paper we present the detector and analyze observations made during one full year. After the analysis and correction of the GCR flux variability due to the atmospheric conditions (pressure and temperature), a study of the periodicities is performed in order to analyze modulations due to heliospheric phenomena. We can observe two periods: (a) 1 day, associated with the Earth's rotation combined with the spatial anisotropy of the GCR flux; and (b) $\sim$ 30 days due to solar impact of stable solar structures combined with the rotation of the Sun. From a superposed epoch analysis, and considering the geomagnetic effects, the mean diurnal amplitude is $\sim$ 0.08% and the maximum flux is observed in $\sim$ 15 hr local time (LT) direction in the interplanetary space. In such a way, we determine the capability of Neurus to observe anisotropies and other interplanetary modulations on the GCR flux arriving at the Earth., Comment: to be published in Advances in Space Research

Between the mid-eighteenth and mid-nineteenth centuries, long-haul oceanic voyages of exploration and discovery routinely carried astronomical tent observatories to support land-based longitude determinations using heavy and cumbersome astronomical regulators and transit telescopes. Following James Cook's deployment of a pilot tent observatory on his first voyage to the Pacific in 1768-1771, the tent design was altered by William Bayly for more convenient use on Cook's second and third voyages to the Pacific. Bayly's design became the standard structure of tent observatories assigned to shipboard astronomers during the Age of Sail. By the middle of the nineteenth century, a subtle shift in focus had occurred, with tent observatories now being deployed to observe specific celestial events (such as the 1882 Venus transit or a variety of eclipses), while longitude determinations increasingly relied on the novel, compact and improved box chronometers of the day. A further shift in the application of tent observatories occurred towards the end of the nineteenth century, when astronomical applications largely gave way to a renewed focus on meteorological measurements., Comment: 21 pages; Journal of Astronomical History and Heritage, in press (March 2023 issue)

Exoplanet detection by direct imaging is a difficult task: the faint signals from the objects of interest are buried under a spatially structured nuisance component induced by the host star. The exoplanet signals can only be identified when combining several observations with dedicated detection algorithms. In contrast to most of existing methods, we propose to learn a model of the spatial, temporal and spectral characteristics of the nuisance, directly from the observations. In a pre-processing step, a statistical model of their correlations is built locally, and the data are centered and whitened to improve both their stationarity and signal-to-noise ratio (SNR). A convolutional neural network (CNN) is then trained in a supervised fashion to detect the residual signature of synthetic sources in the pre-processed images. Our method leads to a better trade-off between precision and recall than standard approaches in the field. It also outperforms a state-of-the-art algorithm based solely on a statistical framework. Besides, the exploitation of the spectral diversity improves the performance compared to a similar model built solely from spatio-temporal data., accepted to EUSIPCO 2023

We present a method to reconstruct the initial linear-regime matter density field from the late-time non-linearly evolved density field in which we channel the output of standard first-order reconstruction to a convolutional neural network (CNN). Our method shows dramatic improvement over the reconstruction of either component alone. We show why CNNs are not well-suited for reconstructing the initial density directly from the late-time density: CNNs are local models, but the relationship between initial and late-time density is not local. Our method leverages standard reconstruction as a preprocessing step, which inverts bulk gravitational flows sourced over very large scales, transforming the residual reconstruction problem from long-range to local and making it ideally suited for a CNN. We develop additional techniques to account for redshift distortions, which warp the density fields measured by galaxy surveys. Our method improves the range of scales of high-fidelity reconstruction by a factor of 2 in wavenumber above standard reconstruction, corresponding to a factor of 8 increase in the number of well-reconstructed modes. In addition, our method almost completely eliminates the anisotropy caused by redshift distortions. As galaxy surveys continue to map the Universe in increasingly greater detail, our results demonstrate the opportunity offered by CNNs to untangle the non-linear clustering at intermediate scales more accurately than ever before.

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 idealised 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 June 2021 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., Comment: Accepted for publication in MNRAS

Studying coupling between different galactic components is a challenging problem in galactic dynamics. Using basis function expansions (BFEs) and multichannel singular spectrum analysis (mSSA) as a means of dynamical data mining, we discover evidence for two multi-component disc-halo dipole modes in a Milky-Way-like simulated galaxy. One of the modes grows throughout the simulation, while the other decays throughout the simulation. The multi-component disc-halo modes are driven primarily by the halo, and have implications for the structural evolution of galaxies, including observations of lopsidedness and other non-axisymmetric structure. In our simulation, the modes create surface density features up to 10 per cent relative to the equilibrium model stellar disc. While the simulated galaxy was constructed to be in equilibrium, BFE+mSSA also uncovered evidence of persistent periodic signals incited by aphysical initial conditions disequilibrium, including rings and weak two-armed spirals, both at the 1 per cent level. The method is sensitive to distinct evolutionary features at and even below the 1 per cent level of surface density variation. The use of mSSA produced clean signals for both modes and disequilibrium, efficiently removing variance owing to estimator noise from the input BFE time series. The discovery of multi-component halo-disc modes is strong motivation for application of BFE+mSSA to the rich zoo of dynamics of multi-component interacting galaxies., Submitted to MNRAS, comments welcome

Radio spectroscopy provides a unique inspection perspective for solar and space weather research, which can reveal the plasma and energetic electron information in the solar corona and inner heliosphere. However, radio-frequency interference (RFI) from human activities affects sensitive radio telescopes, and significantly affects the quality of observation. Thus, RFI detection and mitigation for the observations is necessary to obtain high quality science-ready data. The flagging of RFI is particularly challenging for the solar and space weather observations at low frequency, because the solar radio bursts can be brighter than the RFI, and may show similar temporal behaviour. In this work, we investigate RFI flagging methods for solar and space weather observations, including a strategy for aolagger, and a novel method that makes use of a morphology convolution. These algorithms can effectively flag RFI while preserving solar radio bursts.

A large number of unidentified sources found by astronomical surveys and other observations necessitate the use of an automated classification technique based on machine learning methods. The aim of this paper is to find a suitable automated classifier to identify the point X-ray sources in the Chandra Source Catalogue (CSC) 2.0 in the categories of active galactic nuclei (AGN), X-ray emitting stars, young stellar objects (YSOs), high-mass X-ray binaries (HMXBs), low-mass X-ray binaries (LMXBs), ultra luminous X-ray sources (ULXs), cataclysmic variables (CVs), and pulsars. The catalogue consists of approx 3,17,000 sources, out of which we select 2,77,069 point sources based on the quality flags available in CSC 2.0. In order to identify unknown sources of CSC 2.0, we use multi-wavelength features, such as magnitudes in optical/UV bands from Gaia-EDR3, SDSS and GALEX, and magnitudes in IR bands from 2MASS, WISE and MIPS-Spitzer, in addition to X-ray features (flux and variability) from CSC 2.0. We find the Light Gradient Boosted Machine, an advanced decision tree-based machine learning classification algorithm, suitable for our purpose and achieve $93\%$ precision, $93\%$ recall score and 0.91 Mathew's Correlation coefficient score. With the trained classifier, we identified 54,770 (14,066) sources with more than $3{\sigma}$ (4${\sigma}$) confidence, out of which there are 32,600 (8,574) AGNs, 16,148 (5,166) stars, 5,184 (208) YSOs, 439 (46) HMXBs, 197 (71) LMXBs, 50 (0) ULXs, 89 (1) CVs, and 63 (0) pulsars. This method can also be useful for identifying sources of other catalogues reliably., Comment: 12 pages, 6 figures, 9 tables, accepted for publication in Monthly Notices of the Royal Astronomical Society

We present a comprehensive simulation-based study of the BayesEoR code for 21 cm power spectrum recovery when analytically marginalizing over foreground parameters. To account for covariance between the 21 cm signal and contaminating foreground emission, BayesEoR jointly constructs models for both signals within a Bayesian framework. Due to computational constraints, the forward model is constructed using a restricted field-of-view (FoV) in the image domain. When the only EoR contaminants are noise and foregrounds, we demonstrate that BayesEoR can accurately recover the 21 cm power spectrum when the component of sky emission outside this forward-modelled region is downweighted by the beam at the level of the dynamic range between the foreground and 21 cm signals. However, when all-sky foreground emission is included along with a realistic instrument primary beam with sidelobes above this threshold extending to the horizon, the recovered power spectrum is contaminated by unmodelled sky emission outside the restricted FoV model. Expanding the combined cosmological and foreground model to cover the whole sky is computationally prohibitive. To address this, we present a modified version of BayesEoR that allows for an all-sky foreground model, while the modelled 21 cm signal remains only within the primary FoV of the telescope. With this modification, it will be feasible to run an all-sky BayesEoR analysis on a sizeable compute cluster. We also discuss several future directions for further reducing the need to model all-sky foregrounds, including wide-field foreground subtraction, an image-domain likelihood utilizing a tapering function, and instrument primary beam design., 14 pages, 8 figures

We present the deconvolved distribution estimator (DDE), an extension of the voxel intensity distribution (VID), in the context of future observations proposed as part of the CO Mapping Array Project (COMAP). The DDE exploits the fact that the observed VID is a convolution of correlated signal intensity distributions and uncorrelated noise or interloper intensity distributions. By deconvolving the individual VID of two observables away from their joint VID in a Fourier-space operation, the DDE suppresses sensitivity to interloper emission while maintaining sensitivity to correlated components. The DDE thus improves upon the VID by reducing the relative influence of uncorrelated noise and interloper biases, which is useful in the context of COMAP observations that observe different rotational transitions of CO from the same comoving volume in different observing frequency bands. Fisher forecasts suggest that the theoretical sensitivity in the DDE allows significant improvements in constraining power compared to either the cross power spectrum or the individual VID data, and matches the constraining power of the combination of all other one- and two-point summary statistics. Future work should further investigate the covariance and model-dependent behaviour of this novel one-point cross-correlation statistic., Comment: 11 pages + acknowledgements/bibliography/appendix (12 pages total); 10 figures, 2 tables; v3 reflects the version accepted for publication in MNRAS

Phosphine could be a key molecule in the understanding of exotic chemistry happening in (exo)planetary atmospheres. While it has been detected in the Solar System's giant planets, it has not been observed in exoplanets yet. In the exoplanetary context however it has been theorized as a potential biosignature molecule. The goal of our study is to identify which illustrative science cases for PH3 chemistry are observable with a space-based mid-infrared nulling interferometric observatory like the LIFE (Large Interferometer For Exoplanets) concept. We identified a representative set of scenarios for PH3 detections in exoplanetary atmospheres varying over the whole dynamic range of the LIFE mission. We used chemical kinetics and radiative transfer calculations to produce forward models of these informative, prototypical observational cases for LIFEsim, our observation simulator software for LIFE. In a detailed, yet first order approximation it takes a mission like LIFE: (i) about 1h to find phosphine in a warm giant around a G star at 10 pc, (ii) about 10 h in H2 or CO2 dominated temperate super-Earths around M star hosts at 5 pc, (iii) and even in 100h it seems very unlikely that phosphine would be detectable in a Venus-Twin with extreme PH3 concentrations at 5 pc. Phosphine in concentrations previously discussed in the literature is detectable in 2 out of the 3 cases and about an order of magnitude faster than comparable cases with JWST. We show that there is a significant number of objects accessible for these classes of observations. These results will be used to prioritize the parameter range for the next steps with more detailed retrieval simulations. They will also inform timely questions in the early design phase of a mission like LIFE and guide the community by providing easy-to-scale first estimates for a large part of detection space of such a mission., Comment: In press. Accepted for publication in Astrobiology on 02 November 2022. 26 pages, 5 figures and 8 tables

The Microchannel X-ray Telescope (MXT) will be the first focusing X-ray telescope based on a "Lobster-Eye" optical design to be flown on Sino-French mission SVOM. SVOM will be dedicated to the study of Gamma-Ray Bursts and more generally time-domain astrophysics. The MXT telescope is a compact (focal length ~ 1.15 m) and light (< 42 kg) instrument, sensitive in the 0.2--10 keV energy range. It is composed of an optical system, based on micro-pore optics (MPOs) of 40 micron pore size, coupled to a low-noise pnCDD X-ray detector. In this paper we describe the expected scientific performance of the MXT telescope, based on the End-to-End calibration campaign performed in fall 2021, before the integration of the SVOM payload on the satellite., 22 pages, 12 figures, accepted for publication in Experimental Astronomy

As we observe a rapidly growing number of astrophysical transients, we learn more about the diverse host galaxy environments in which they occur. Host galaxy information can be used to purify samples of cosmological Type Ia supernovae, uncover the progenitor systems of individual classes, and facilitate low-latency follow-up of rare and peculiar explosions. In this work, we develop a novel data-driven methodology to simulate the time-domain sky that includes detailed modeling of the probability density function for multiple transient classes conditioned on host galaxy magnitudes, colours, star formation rates, and masses. We have designed these simulations to optimize photometric classification and analysis in upcoming large synoptic surveys. We integrate host galaxy information into the SNANA simulation framework to construct the Simulated Catalogue of Optical Transients and Correlated Hosts (SCOTCH), a publicly-available catalogue of 5 million idealized transient light curves in LSST passbands and their host galaxy properties over the redshift range $0, Comment: 30 pages, 21 figures. Updated to reflect version published in MNRAS Vol. 520, Issue 2. This version improves the treatment of transient-host offsets and AGN host correlations. Associated SCOTCH files are available through Zenodo at https://doi.org/10.5281/zenodo.7563623

We present a systematic study of the unbinned, photon-by-photon likelihood technique which can be used as an alternative method to analyse phase-dependent, X-ray spectro-polarimetric observations obtained with IXPE and other photo-electric polarimeters. We apply the unbinned technique to models of the luminous X-ray pulsar Hercules X-1, for which we produce simulated observations using ixpeobssim package. We consider minimal knowledge about the actual physical process responsible for the polarized emission from the accreting pulsar and assume that the observed phase-dependent polarization angle can be described by the rotating vector model. Using the unbinned technique, the detector's modulation factor, and the polarization information alone, we found that both the rotating vector model and the underlying spectro-polarimetry model can reconstruct equally well the geometric configuration angles of the accreting pulsar. However, the measured polarization fraction becomes biased with respect to underlying model unless the energy dispersion and effective area of the detector are also taken into account. To this end, we present an energy-dispersed likelihood estimator that is proved to be unbiased. For different analyses, we obtain posterior distributions from multiple ixpeobssim realizations and show that the unbinned technique yields $\sim 10\%$ smaller error bars than the binned technique. We also discuss alternative sources, such as magnetars, in which the unbinned technique and the rotating vector model might be applied., 11 pages, 9 figures. Accepted for publication in MNRAS. Source code available at https://github.com/UBC-Astrophysics/Unbinned-Xray-polarimetry

Transmission spectroscopy of exoplanets has revealed signatures of water vapor, aerosols, and alkali metals in a few dozen exoplanet atmospheres. However, these previous inferences with the Hubble and Spitzer Space Telescopes were hindered by the observations' relatively narrow wavelength range and spectral resolving power, which precluded the unambiguous identification of other chemical species$-$in particular the primary carbon-bearing molecules. Here we report a broad-wavelength 0.5-5.5 $\mu$m atmospheric transmission spectrum of WASP-39 b, a 1200 K, roughly Saturn-mass, Jupiter-radius exoplanet, measured with JWST NIRSpec's PRISM mode as part of the JWST Transiting Exoplanet Community Early Release Science Team program. We robustly detect multiple chemical species at high significance, including Na (19$\sigma$), H$_2$O (33$\sigma$), CO$_2$ (28$\sigma$), and CO (7$\sigma$). The non-detection of CH$_4$, combined with a strong CO$_2$ feature, favours atmospheric models with a super-solar atmospheric metallicity. An unanticipated absorption feature at 4$\mu$m is best explained by SO$_2$ (2.7$\sigma$), which could be a tracer of atmospheric photochemistry. These observations demonstrate JWST's sensitivity to a rich diversity of exoplanet compositions and chemical processes., Comment: 41 pages, 4 main figures, 10 extended data figures, 4 tables. Under review in Nature

In time-domain astronomy, a substantial number of transients will be discovered by multi-wavelength and multi-messenger observatories, posing a great challenge for follow-up capabilities. We have thus proposed an intelligent X-ray constellation, the Chasing All Transients Constellation Hunters (CATCH) space mission. Consisting of 126 micro-satellites in three types, CATCH will have the capability to perform follow-up observations for a large number of different types of transients simultaneously. Each satellite in the constellation will carry lightweight X-ray optics and use a deployable mast to increase the focal length. The combination of different optics and detector systems enables different types of satellites to have multiform observation capabilities, including timing, spectroscopy, imaging, and polarization. Controlled by the intelligent system, different satellites can cooperate to perform uninterrupted monitoring, all-sky follow-up observations, and scanning observations with a flexible field of view (FOV) and multi-dimensional observations. Therefore, CATCH will be a powerful mission to study the dynamic universe. Here, we present the current design of the spacecraft, optics, detector system, constellation configuration and observing modes, as well as the development plan., Accepted for publication in Experimental Astronomy. 43 pages, 15 figures, 4 tables

The European Open Science Cloud aims to make all data Findable, Accessible, Interoperable and Reusable. By far the largest community of users of the European Open Science Cloud is the science-inclined public. These users need a more curated experience of open science than subject specialists, but nevertheless make very substantial research contributions in open science, especially in crowdsourced data mining, i.e. citizen science. This short, non-technical invited review presents applications of citizen science in the European Open Science Cloud, with a particular focus on astrophysics and astroparticle physics., Published in Europhysics News, vol. 54(2), 2023, pages 20-23. 4 pages, published version

The aim of this paper is to describe a novel non-parametric noise reduction technique from the point of view of Bayesian inference that may automatically improve the signal-to-noise ratio of one- and two-dimensional data, such as e.g. astronomical images and spectra. The algorithm iteratively evaluates possible smoothed versions of the data, the smooth models, obtaining an estimation of the underlying signal that is statistically compatible with the noisy measurements. Iterations stop based on the evidence and the $\chi^2$ statistic of the last smooth model, and we compute the expected value of the signal as a weighted average of the whole set of smooth models. In this paper, we explain the mathematical formalism and numerical implementation of the algorithm, and we evaluate its performance in terms of the peak signal to noise ratio, the structural similarity index, and the time payload, using a battery of real astronomical observations. Our Fully Adaptive Bayesian Algorithm for Data Analysis (FABADA) yields results that, without any parameter tuning, are comparable to standard image processing algorithms whose parameters have been optimized based on the true signal to be recovered, something that is impossible in a real application. State-of-the-art non-parametric methods, such as BM3D, offer slightly better performance at high signal-to-noise ratio, while our algorithm is significantly more accurate for extremely noisy data (higher than $20-40\%$ relative errors, a situation of particular interest in the field of astronomy). In this range, the standard deviation of the residuals obtained by our reconstruction may become more than an order of magnitude lower than that of the original measurements. The source code needed to reproduce all the results presented in this report, including the implementation of the method, is publicly available at https://github.com/PabloMSanAla/fabada, Comment: 13 pages, 6 figures. Accepted for publication in RAS Techniques and Instruments

The Event Horizon Telescope (EHT) has recently released high-resolution images of accretion flows onto two supermassive black holes. Our physical understanding of these images depends on accuracy and precision of numerical models of plasma and radiation around compact objects. The goal of this work is to speed up radiative-transfer simulations used to create mock images of black holes for comparison with the EHT observations. A ray-tracing code for general relativistic and fully polarized radiative transfer through plasma in strong gravity is ported onto a graphics processing unit (GPU). We describe our GPU implementation and carry out speedup tests using models of optically thin advection-dominated accretion flow (ADAF) onto a black hole realised semi-analytically and in 3D general relativistic magnetohydrodynamics simulations, low and very high image pixel resolutions, and two different sets of CPU+GPUs. We show that a GPU with high double precision computing capability can significantly reduce the image production computational time, with a speedup factor of up to approximately 1200. The significant speedup facilitates, e.g., dynamic model fitting to the EHT data, including polarimetric data. The method extension may enable studies of emission from plasma with nonthermal particle distribution functions for which accurate approximate synchrotron emissivities are not available. The significant speedup reduces the carbon footprint of the generation of the EHT image libraries by at least an order of magnitude., 6 pages, 1 table, 2 figures, Accepted to ApJS, after editorial corrections

The problem of detecting a sinusoidal signal with randomly varying frequency has a long history. It is one of the core problems in signal processing, arising in many applications including, for example, underwater acoustic frequency line tracking, demodulation of FM radio communications, laser phase drift in optical communications and, recently, continuous gravitational wave astronomy. In this paper we describe a Markov Chain Monte Carlo based procedure to compute a specific detection posterior density. We demonstrate via simulation that our approach results in an up to $25$ percent higher detection rate than Hidden Markov Model based solutions, which are generally considered to be the leading techniques for these problems., Comment: 6 pages, 4 figures, 12th IFAC Symposium on Nonlinear Control Systems

Ground-level particle detection is now a well-established approach to TeV gamma-ray astronomy. Detection of Cherenkov light produced in water-filled detection units is a proven and cost-effective method. Here we discuss the optimization of the units towards the future Southern Wide-field Gamma-ray Observatory (SWGO). In this context, we investigate a new type of configuration in which each water Cherenkov detector (WCD) unit in the array comprises two chambers with black or reflective walls and a single photomultiplier tube (PMT) in each chamber. We find that this is a cost-effective approach that improves the performance of the WCD array with respect to current approaches. A shallow lower chamber with a PMT facing downwards enables muon tagging and the identification of hadron-induced air showers, which are the primary source of background in gamma-ray astronomy. We investigate how gamma/hadron separation power and achievable angular resolution depend on the geometry and wall reflectivity of the detector units in this configuration. We find that excellent angular resolution, background rejection power and low-energy response are achievable in this double-layer configuration, with the aid of reflective surfaces in both chambers., 17 pages, 20 figures

Dust is a major component of the interstellar medium. Through scattering, absorption and thermal re-emission, it can profoundly alter astrophysical observations. Models for dust composition and distribution are necessary to better understand and curb their impact on observations. A new approach for serial and computationally inexpensive production of such models is here presented. Traditionally these models are studied with the help of radiative transfer modelling, a critical tool to understand the impact of dust attenuation and reddening on the observed properties of galaxies and active galactic nuclei. Such simulations present, however, an approximately linear computational cost increase with the desired information resolution. Our new efficient model generator proposes a denoising variational autoencoder (or alternatively PCA), for spectral compression, combined with an approximate Bayesian method for spatial inference, to emulate high information radiative transfer models from low information models. For a simple spherical dust shell model with anisotropic illumination, our proposed approach successfully emulates the reference simulation starting from less than 1% of the information. Our emulations of the model at different viewing angles present median residuals below 15% across the spectral dimension, and below 48% across spatial and spectral dimensions. EmulART infers estimates for ~85% of information missing from the input, all within a total running time of around 20 minutes, estimated to be 6x faster than the present target high information resolution simulations, and up to 50x faster when applied to more complicated simulations., Comment: 85 pages, 33 figures, 9 tables

The diffuse medium in and around galaxies can exist in a multi-phase state: small, cold gas clouds contributing significantly to the total mass embedded in pressure equilibrium with a hotter, more diffuse volume-filling component. Modeling this multi-phase state in cosmological simulations poses a significant challenge due to the requirements to spatially resolve the clouds and consequently the interactions between the phases. In this paper, we present a novel method to model this gas state in cosmological hydrodynamical simulations. We solve the compressible two-fluid hydrodynamic equations using a moving-mesh finite-volume method and define mass, momentum and energy exchange terms between the phases as operator-split source terms. Using a stratified flow model, our implementation is able to maintain volume fraction discontinuities in pressure equilibrium to machine precision, allowing for the treatment of both resolved and unresolved multi-phase fluids. The solver remains second order accurate on smooth hydrodynamics problems. We use the source and sink terms of an existing two-phase model for the interstellar medium to demonstrate the value of this type of approach in simulations of galaxy formation, compare it to its effective equation of state implementation, and discuss its advantages in future large-scale simulations of galaxy formation., Comment: 16 pages, 19 figures, accepted in MNRAS, comments welcome

In the era of huge astronomical surveys, machine learning offers promising solutions for the efficient estimation of galaxy properties. The traditional, `supervised' paradigm for the application of machine learning involves training a model on labelled data, and using this model to predict the labels of previously unlabelled data. The semi-supervised `pseudo-labelling' technique offers an alternative paradigm, allowing the model training algorithm to learn from both labelled data and as-yet unlabelled data. We test the pseudo-labelling method on the problems of estimating redshift, stellar mass, and star formation rate, using COSMOS2015 broad band photometry and one of several publicly available machine learning algorithms, and we obtain significant improvements compared to purely supervised learning. We find that the gradient-boosting tree methods CatBoost, XGBoost, and LightGBM benefit the most, with reductions of up to ~15% in metrics of absolute error. We also find similar improvements in the photometric redshift catastrophic outlier fraction. We argue that the pseudo-labellng technique will be useful for the estimation of redshift and physical properties of galaxies in upcoming large imaging surveys such as Euclid and LSST, which will provide photometric data for billions of sources., 10 pages, 6 figures, accepted for publication in MNRAS