bluuebunny/crossref_metadata_2025_split huggingface dataset:
Arecibo observations of a burst storm from FRB 20121102A in 2016
Authors: Hewitt D M , Snelders M P , Hessels J W T , Nimmo K , Jahns J N , Spitler L G , Gourdji K , Hilmarsson G H , Michilli D , Ould-Boukattine O S , Scholz P , Seymour A D 
Published: July 2022

ABSTRACT
FRB 20121102A is the first known fast radio burst (FRB) from which repeat bursts were detected, and one of the best-studied FRB sources in the literature. Here we report on the analysis of 478 bursts (333 previously unreported) from FRB 20121102A using the 305-m Arecibo telescope – detected during approximately 59 hours of observations between December 2015 and October 2016. The majority of bursts are from a burst storm around September 2016. This is the earliest available sample of a large number of FRB 20121102A bursts, and it thus provides an anchor point for long-term studies of the source’s evolving properties. We observe that the bursts separate into two groups in the width-bandwidth-energy parameter space, which we refer to as the low-energy bursts (LEBs) and high-energy bursts (HEBs). The LEBs are typically longer duration and narrower bandwidth than the HEBs, reminiscent of the spectro-temporal differences observed between the bursts of repeating and non-repeating FRBs. We fit the cumulative burst rate-energy distribution with a broken power law and find that it flattens out toward higher energies. The sample shows a diverse zoo of burst morphologies. Notably, burst emission seems to be more common at the top than the bottom of our 1150–1730 MHz observing band. We also observe that bursts from the same day appear to be more similar to each other than to those of other days, but this observation requires confirmation. The wait times and burst rates that we measure are consistent with previous studies. We discuss these results, primarily in the context of magnetar models.
The viability of the optically thick wind model in accreting white dwarfs at high accretion rates
Authors: Cui Yingzhen , Meng Xiangcun 
Published: July 2022

ABSTRACT
The single degenerate (SD) model is one of the leading models for the progenitors of Type Ia supernovae (SNe Ia). The optically thick wind (OTW) model is considered to be essential for the SD model. In this article, we aim to constrain the condition for the occurrence of the OTW. Using the stellar evolution code, Modules for Experiments in Stellar Astrophysics, we carried out a series of one-dimensional hydrodynamical simulations with different accretion rates and different white dwarf (WD) masses to simulate the dynamical ejection process on the accreting WDs. We find that, by neglecting interaction with the accreted material, we can get a similar result to the previous works using steady-state method, i.e. the OTW occurs. However, if we consider the interaction between the accreted and the outflowing materials, whether the OTW can occur or not becomes strongly dependent on the accretion rate. For a given WD mass, the higher the accretion rate, the less likely the OTW can occur. In addition, the WD masses can also affect the occurrence of the OTW, i.e. the higher the WD mass, the easier the OTW can occur. As a result, the OTW in novae may occur because the accretion rate is low enough, while in the SD progenitor system of SNe Ia, a high accretion rate is likely to prevent the occurrence of the OTW.
Dynamical fates of S-type planetary systems in embedded cluster environments
Authors: Ellithorpe Elizabeth A , Kaib Nathan A 
Published: July 2022

ABSTRACT
The majority of binary star systems that host exoplanets will spend the first portion of their lives within a star-forming cluster that may drive dynamical evolution of the binary-planet system. We perform numerical simulations of S-type planets, with masses and orbital architecture analogous to the Solar system’s four gas giants, orbiting within the influence of a $0.5\, \mathrm{M}_{\odot }$ binary companion. The binary-planet system is integrated simultaneously with an embedded stellar cluster environment. ∼10 per cent of our planetary systems are destabilized when perturbations from our cluster environment drive the binary periastron towards the planets. This destabilization occurs despite all of our systems being initialized with binary orbits that would allow stable planets in the absence of the cluster. The planet–planet scattering triggered in our systems typically results in the loss of lower mass planets and the excitement of the eccentricities of surviving higher mass planets. Many of our planetary systems that go unstable also lose their binary companions prior to cluster dispersal and can therefore masquerade as hosts of eccentric exoplanets that have spent their entire histories as isolated stars. The cluster-driven binary orbital evolution in our simulations can also generate planetary systems with misaligned spin–orbit angles. This is typically done as the planetary system precesses as a rigid disc under the influence of an inclined binary, and those systems with the highest spin–orbit angles should often retain their binary companion and possess multiple surviving planets.
Extreme giant molecular clouds in the luminous infrared galaxy NGC 3256
Authors: Brunetti Nathan , Wilson Christine D 
Published: July 2022

ABSTRACT
We present a cloud decomposition of 12CO (2–1) observations of the merger and nearest luminous infrared galaxy, NGC 3256. 185 spatially and spectrally resolved clouds are identified across the central ≈130 kpc2 at 90 pc resolution and completeness is estimated. We compare our cloud catalogue from NGC 3256 to ten galaxies observed in the PHANGS-ALMA survey. Distributions in NGC 3256 of cloud velocity dispersions (median 23 km s−1), luminosities (1.5 × 107 K km s−1 pc2), CO-estimated masses (2.1 × 107 M⊙), mass surface densities (470 M⊙ pc−2), virial masses (5.4 × 107 M⊙), virial parameters (4.3), size-linewidth coefficients (6.3 km2 s−2 pc−1), and internal turbulent pressures ( 1.0 × 10 7K cm−3$\, k_{\mathrm{B}}^{-1}$) are significantly higher than in the PHANGS-ALMA galaxies. Cloud radii (median 88 pc) are slightly larger in NGC 3256 and free-fall times (4.1 Myr) are shorter. The distribution of cloud eccentricities in NGC 3256 (median of 0.8) is indistinguishable from many PHANGS-ALMA galaxies, possibly because the dynamical state of clouds in NGC 3256 is similar to that of nearby spiral galaxies. However, the narrower distribution of virial parameters in NGC 3256 may reflect a narrower range of dynamical states than in PHANGS-ALMA galaxies. No clear picture of cloud alignment is detected, despite the large eccentricities. Correlations between cloud properties point to high external pressures in NGC 3256 keeping clouds bound and collapsing given such high velocity dispersions and star-formation rates. A fit to the cloud mass function gives a high-mass power-law slope of $-2.75^{+0.07}_{-0.01}$, near the average from PHANGS-ALMA galaxies. We also compare our results to a pixel-based analysis of these observations and find molecular-gas properties agree qualitatively, though peak brightness temperatures are somewhat higher and virial parameters and free-fall times are somewhat lower in this cloud-based analysis.
Redshift and stellar mass dependence of intrinsic shapes of disc-dominated galaxies from COSMOS observations below z = 1.0
Authors: Hoffmann K , Laigle C , Chisari N E , Tallada-Crespí P , Teyssier R , Dubois Y , Devriendt J 
Published: July 2022

ABSTRACT
The high abundance of disc galaxies without a large central bulge challenges predictions of current hydrodynamic simulations of galaxy formation. We aim to shed light on the formation of these objects by studying the redshift and mass dependence of their intrinsic 3D shape distributions in the COSMOS galaxy survey below redshift z = 1.0. This distribution is inferred from the observed distribution of 2D shapes, using a reconstruction method which we test using hydrodynamic simulations. Our tests reveal a moderate bias for the inferred average disc circularity and relative thickness, but a large bias on the dispersion of these quantities. Applying the reconstruction method on COSMOS data, we find variations of the average disc circularity and relative thickness with redshift of around ∼1 per cent and ∼10 per cent, respectively, which is comparable to the error estimates on these quantities. The average relative disc thickness shows a significant mass dependence which can be accounted for by the scaling of disc radius with galaxy mass. We conclude that our data provides no evidence for a strong dependence of the average circularity and absolute thickness of disc-dominated galaxies on redshift and mass that is significant with respect to the statistical uncertainties in our analysis. These findings are expected in the absence of disruptive merging or feedback events that would affect galaxy shapes. They hence support a scenario where present-day discs form early ( z &gt; 1.0) and subsequently undergo a tranquil evolution in isolation. However, more data and a better understanding of systematics are needed to reaffirm our results.
Spherical accretion of collisional gas in modified gravity I: self-similar solutions and a new cosmological hydrodynamical code
Authors: Zhang Han , Weinzierl Tobias , Schulz Holger , Li Baojiu 
Published: July 2022

ABSTRACT
The spherical collapse scenario has great importance in cosmology since it captures several crucial aspects of structure formation. The presence of self-similar solutions in the Einstein-de Sitter (EdS) model greatly simplifies its analysis, making it a powerful tool to gain valuable insights into the real and more complicated physical processes involved in galaxy formation. While there has been a large body of research to incorporate various additional physical processes into spherical collapse, the effect of modified gravity (MG) models, which are popular alternatives to the Λ cold dark matter paradigm to explain the cosmic acceleration, is still not well understood in this scenario. In this paper, we study the spherical accretion of collisional gas in a particular MG model, which is a rare case that also admits self-similar solutions. The model displays interesting behaviours caused by the enhanced gravity and a screening mechanism. Despite the strong effects of MG, we find that its self-similar solution agrees well with that of the EdS model. These results are used to assess a new cosmological hydrodynamical code for spherical collapse simulations introduced here, which is based on the hyperbolic partial differential equation engine ExaHyPE 2. Its good agreement with the theoretical predictions confirms the reliability of this code in modelling astrophysical processes in spherical collapse. We will use this code to study the evolution of gas in more realistic MG models in future work.
Morphology, colour–magnitude, and scaling relations of galaxies in Abell 426
Authors: Khanday Sheeraz A , Saha Kanak , Iqbal Nasser , Dhiwar Suraj , Pahwa Isha 
Published: July 2022

ABSTRACT
We present photometric properties of 183 member galaxies in the Abell 426 cluster using the Sloan Digital Sky Survey (SDSS) imaging and spectroscopic observation. Detailed morphology based on visual classification followed by multicomponent image decomposition of 179 galaxies is presented in the SDSS g, r, i bands. More than 80 per cent of the members are early-type galaxies (ETGs), with elliptical, dwarf elliptical (dE), and lenticular morphology and follow the red-sequence in the colour–magnitude diagram (CMD). With a few dEs and spirals in the blue cloud, the cluster CMD is nearly unimodal. The dEs are ∼2-mag fainter and follow a different Sersic index and central velocity dispersion distribution than their bright counterparts. Further, we establish the Kormendy relation (KR) and the fundamental plane relation (FPR) for five different samples of ETGs constructed based on derived physical parameters such as Sersic index, concentration, central velocity dispersion in g, r, i bands. The mean r-band slope and zero-point of the KR are 3.02 ± 0.1 and 18.65 ± 0.03 in close agreement to other cluster ellipticals in the local and higher redshift. Kinematics-based ETG sample produces the least scatter in KR with zero-point getting brighter by ∼1.3 mag from g to i band. The dEs and other low-mass ETGs follow the KR with a similar slope but with ∼1.3 mag fainter zero-point and form a parallel KR. The bright ellipticals follow an FPR with a = 1.37 ± 0.003, b = 0.35 ± 0.05, and c = −9.37 ± 0.02 in the r band; galaxies tend to deviate from this relation at the low-mass end. A catalogue with morphology and 2D structural analysis is available online.
Machine learning for galactic archaeology: a chemistry-based neural network method for identification of accreted disc stars
Authors: Tronrud Thorold , Tissera Patricia B , Gómez Facundo A , Grand Robert J J , Pakmor Ruediger , Marinacci Federico , Simpson Christine M 
Published: July 2022

ABSTRACT
We develop a method (‘Galactic Archaeology Neural Network’, gann) based on neural network models (NNMs) to identify accreted stars in galactic discs by only their chemical fingerprint and age, using a suite of simulated galaxies from the Auriga Project. We train the network on the target galaxy’s own local environment defined by the stellar halo and the surviving satellites. We demonstrate that this approach allows the detection of accreted stars that are spatially mixed into the disc. Two performance measures are defined – recovery fraction of accreted stars, frecov and the probability that a star with a positive (accreted) classification is a true-positive result, P(TP). As the NNM output is akin to an assigned probability (Pa), we are able to determine positivity based on flexible threshold values that can be adjusted easily to refine the selection of presumed-accreted stars. We find that gann identifies accreted disc stars within simulated galaxies, with high frecov and/or high P(TP). We also find that stars in Gaia–Enceladus–Sausage (GES) mass systems are over 50 per cent recovered by our NNMs in the majority (18/24) of cases. Additionally, nearly every individual source of accreted stars is detected at 10 per cent or more of its peak stellar mass in the disc. We also demonstrate that a conglomerated NNM, trained on the halo and satellite stars from all of the Auriga galaxies provides the most consistent results, and could prove to be an intriguing future approach as our observational capabilities expand.
Distinguishing between ΛCDM and f(R) gravity models using halo ellipticity correlations in simulations
Authors: Chuang Yao-Tsung , Okumura Teppei , Shirasaki Masato 
Published: July 2022

ABSTRACT
There is a growing interest in utilizing intrinsic alignment (IA) of galaxy shapes as a geometric and dynamical probe of cosmology. In this paper, we present the first measurements of IA in a modified gravity model using the gravitational shear-intrinsic ellipticity correlation (GI) and intrinsic ellipticity-ellipticity correlation (II) functions of dark-matter haloes from f(R) gravity simulations. By comparing them with the same statistics measured in Lambda cold dark matter (ΛCDM) simulations, we find that the IA statistics in different gravity models show distinguishable features, with a trend similar to the case of conventional galaxy clustering statistics. Thus, the GI and II correlations are found to be useful in distinguishing between the ΛCDM and f(R) gravity models. More quantitatively, IA statistics enhance detectability of the imprint of f(R) gravity on large-scale structures by $\sim 40{{\ \rm per\ cent}}$ when combined with the conventional halo clustering in redshift space. We also find that the correlation between the axial ratio and orientation of haloes becomes stronger in f(R) gravity than that in ΛCDM. Our results demonstrate the usefulness of IA statistics as a probe of gravity beyond a consistency test of ΛCDM and general relativity.
Grain growth during protostellar disc formation
Authors: Tu Yisheng , Li Zhi-Yun , Lam Ka Ho 
Published: July 2022

ABSTRACT
Recent observations indicate that mm/cm-sized grains may exist in the embedded protostellar discs. How such large grains grow from the micron size (or less) in the earliest phase of star formation remains relatively unexplored. In this study, we take a first step to model the grain growth in the protostellar environment, using 2D (axisymmetric) radiation hydrodynamic and grain growth simulations. We show that the grain growth calculations can be greatly simplified by the ‘terminal velocity approximation’, where the dust drift velocity relative to the gas is proportional to its stopping time, which is proportional to the grain size. We find that the grain–grain collision from size-dependent terminal velocity alone is too slow to convert a significant fraction of the initially micron-sized grains into mm/cm sizes during the deeply embedded Class 0 phase. Substantial grain growth is achieved when the grain–grain collision speed is enhanced by a factor of 4. The dust growth above and below the disc midplane enables the grains to settle faster towards the midplane, which increases the local dust-to-gas ratio, which, in turn, speeds up further growth there. How this needed enhancement can be achieved is unclear, although turbulence is a strong possibility that deserves further exploration.
Time-delay estimation in unresolved lensed quasars
Authors: Biggio L , Domi A , Tosi S , Vernardos G , Ricci D , Paganin L , Bracco G 
Published: July 2022

ABSTRACTTime-delay cosmography can be used to infer the Hubble parameter H0 by measuring the relative time delays between multiple images of gravitationally lensed quasars. A few of such systems have already been used to measure H0: Their time delays were determined from the light curves of the multiple images obtained by regular, years long, monitoring campaigns. Such campaigns can hardly be performed by any telescope: many facilities are often oversubscribed with a large amount of observational requests to fulfill. While the ideal systems for time-delay measurements are lensed quasars whose images are well resolved by the instruments, several lensed quasars have a small angular separation between the multiple images, and would appear as a single, unresolved, image to a large number of telescopes featuring poor angular resolutions or located in not privileged geographical sites. Methods allowing to infer the time delay also from unresolved light curves would boost the potential of such telescopes and greatly increase the available statistics for H0 measurements. This work presents a study of unresolved lensed quasar systems to estimate the time delay using a deep learning-based approach that exploits the capabilities of one-dimensional convolutional neural networks. Experiments on state-of-the-art simulations of unresolved light curves show the potential of the proposed method and pave the way for future applications in time-delay cosmography.
A new reference catalogue for the very metal-poor Universe: +150 OB stars in Sextans A
Authors: Lorenzo M , Garcia M , Najarro F , Herrero A , Cerviño M , Castro N 
Published: July 2022

ABSTRACT
Local Group (LG) very metal-poor massive stars are the best proxy for the First Stars of the Universe and fundamental to modelling the evolution of early galaxies. These stars may follow new evolutionary pathways restricted to very low metallicities, such as chemically homogeneous evolution (CHE). However, given the great distance leap needed to reach very metal-poor galaxies of the LG and vicinity, no comprehensive spectroscopic studies have been carried out at metallicities lower than the Small Magellanic Cloud (SMC; Z = 1/5 Z⊙) until now. After five observing campaigns at the 10.4-m Gran Telescopio Canarias, we have assembled a low-resolution (R ∼ 1000) spectroscopic collection of more than 150 OB stars in the 1/10 Z⊙ galaxy Sextans A, increasing by an order of magnitude the number of massive stars known in this galaxy. The catalogue includes 38 BA-type supergiants, four red supergiants, and the first candidate 1/10 Z⊙ binary systems, CHE sources and systems hosting stripped stars. The sample massive stars mainly overlap the higher concentrations of neutral gas of Sextans A. However, we find some sources in low H i column-density regions. The colour–magnitude diagram of the galaxy presents large dispersion, which suggests uneven, internal extinction in Sextans A. This is the largest catalogue of OB-type stars ever produced at sub-SMC metallicities. This sample constitutes a fundamental first step to unveiling the evolutionary pathways and fates of very metal-poor massive stars, analyzing the dependence of radiation-driven winds with metallicity, and studying binary systems in an environment analogue to the early Universe.
Red Dragon: a redshift-evolving Gaussian mixture model for galaxies
Authors: Black William K , Evrard August 
Published: July 2022

ABSTRACT
Precision-era optical cluster cosmology calls for a precise definition of the red sequence (RS), consistent across redshift. To this end, we present the Red Dragon algorithm: an error-corrected multivariate Gaussian mixture model (GMM). Simultaneous use of multiple colours and smooth evolution of GMM parameters result in a continuous RS and blue cloud (BC) characterization across redshift, avoiding the discontinuities of red fraction inherent in swapping RS selection colours. Based on a mid-redshift spectroscopic sample of SDSS galaxies, an RS defined by Red Dragon selects quiescent galaxies (low specific star formation rate) with a balanced accuracy of over $90{{\ \rm per\ cent}}$. This approach to galaxy population assignment gives more natural separations between RS and BC galaxies than hard cuts in colour–magnitude or colour–colour spaces. The Red Dragon algorithm is publicly available at bitbucket.org/wkblack/red-dragon-gamma/.
Classification of cosmic structures for galaxies with deep learning: connecting cosmological simulations with observations
Authors: Inoue Shigeki , Si Xiaotian , Okamoto Takashi , Nishigaki Moka 
Published: July 2022

ABSTRACT
We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments, and knots, according to distribution and kinematics of dark matter (DM), and galaxies are also classified according to the segmentation. However, observational studies cannot adopt this classification method using DM. In this study, we demonstrate that deep learning can bridge the gap between the simulations and observations. Our models are based on 3D convolutional neural networks and trained with data of distribution of galaxies in a simulation to deduce the structure classes from the galaxies rather than DM. Our model can predict the class labels as accurate as a previous study using DM distribution for the training and prediction. This means that galaxy distribution can be a substitution for DM for the cosmic-structure classification, and our models using galaxies can be directly applied to wide-field survey observations. When observational restrictions are ignored, our model can classify simulated galaxies into the four classes with an accuracy (macro-averaged F1-score) of 64 per cent. If restrictions such as limiting magnitude are considered, our model can classify SDSS galaxies at ∼100 Mpc with an accuracy of 60 per cent. In the binary classification distinguishing void galaxies from the others, our model can achieve an accuracy of 88 per cent.