bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulating the night-time astronomical seeing at Dome A using Polar WRF
Authors: Yang Qike , Wu Xiaoqing , Wang Zhiyuan , Hu Xiaodan , Guo Yiming , Qing Chun 
Published: July 2022

ABSTRACT
In Antarctica, excellent astronomical observing conditions have been measured at Dome A during night-time (or polar winter). This study investigates the performance of the Polar-optimized version of the Weather Research and Forecasting (Polar WRF, PWRF hereafter) for simulating the night-time astronomical seeing at Dome A. The seeing values were estimated by a seeing model, which used the PWRF-simulated wind speed and temperature as inputs. Furthermore, three methods to obtain the boundary layer height in the seeing model have been examined. The estimated seeing agrees well with 50-d measurements from the KunLun Differential Image Motion Monitor at Dome A during the night-time of 2019; the correlation coefficients range from 0.62 to 0.71. The PWRF-simulated meteorological parameters indicate that low wind speed and strong temperature inversion (when a large gradient Richardson number always occurs) near the ground can lead to good seeing condition. The results suggest that the PWRF model could be a reliable tool for scheduling observational astronomy at Dome A during night-time.
The DESI N-body simulation project – I. Testing the robustness of simulations for the DESI dark time survey
Authors: Grove Cameron , Chuang Chia-Hsun , Devi Ningombam Chandrachani , Garrison Lehman , L’Huillier Benjamin , Feng Yu , Helly John , Hernández-Aguayo César , Alam Shadab , Zhang Hanyu , Yu Yu , Cole Shaun , Eisenstein Daniel , Norberg Peder , Wechsler Risa , Brooks David , Dawson Kyle , Landriau Martin , Meisner Aaron , Poppett Claire , Tarlé Gregory , Valenzuela Octavio 
Published: July 2022

ABSTRACT
Analysis of large galaxy surveys requires confidence in the robustness of numerical simulation methods. The simulations are used to construct mock galaxy catalogues to validate data analysis pipelines and identify potential systematics. We compare three N-body simulation codes, abacus, gadget-2, and swift, to investigate the regimes in which their results agree. We run N-body simulations at three different mass resolutions, 6.25 × 108, 2.11 × 109, and 5.00 × 109 h−1 M⊙, matching phases to reduce the noise within the comparisons. We find systematic errors in the halo clustering between different codes are smaller than the Dark Energy Spectroscopic Instrument (DESI) statistical error for $s\ \gt\ 20\ h^{-1}$ Mpc in the correlation function in redshift space. Through the resolution comparison we find that simulations run with a mass resolution of 2.1 × 109 h−1 M⊙ are sufficiently converged for systematic effects in the halo clustering to be smaller than the DESI statistical error at scales larger than $20\ h^{-1}$ Mpc. These findings show that the simulations are robust for extracting cosmological information from large scales which is the key goal of the DESI survey. Comparing matter power spectra, we find the codes agree to within 1 per cent for k ≤ 10 h Mpc−1. We also run a comparison of three initial condition generation codes and find good agreement. In addition, we include a quasi-N-body code, FastPM, since we plan use it for certain DESI analyses. The impact of the halo definition and galaxy–halo relation will be presented in a follow-up study.
Modelling the galaxy–halo connection with machine learning
Authors: Delgado Ana Maria , Wadekar Digvijay , Hadzhiyska Boryana , Bose Sownak , Hernquist Lars , Ho Shirley 
Published: July 2022

ABSTRACT
To extract information from the clustering of galaxies on non-linear scales, we need to model the connection between galaxies and haloes accurately and in a flexible manner. Standard halo occupation distribution (HOD) models make the assumption that the galaxy occupation in a halo is a function of only its mass, however, in reality; the occupation can depend on various other parameters including halo concentration, assembly history, environment, and spin. Using the IllustrisTNG hydrodynamical simulation as our target, we show that machine learning tools can be used to capture this high-dimensional dependence and provide more accurate galaxy occupation models. Specifically, we use a random forest regressor to identify which secondary halo parameters best model the galaxy–halo connection and symbolic regression to augment the standard HOD model with simple equations capturing the dependence on those parameters, namely the local environmental overdensity and shear, at the location of a halo. This not only provides insights into the galaxy formation relationship but also, more importantly, improves the clustering statistics of the modelled galaxies significantly. Our approach demonstrates that machine learning tools can help us better understand and model the galaxy–halo connection, and are therefore useful for galaxy formation and cosmology studies from upcoming galaxy surveys.
Impacts of zonal winds on planetary oscillations and Saturn ring seismology
Authors: Dewberry Janosz W , Mankovich Christopher R , Fuller Jim 
Published: July 2022

ABSTRACT
The excitation of density and bending waves in Saturn’s C ring by planetary oscillation modes presents a unique opportunity to learn about gas giant interiors and rotation. However, theoretical complications related to Saturn’s rapid and differential rotation pose a barrier to the full utilization of ring wave detections. We calculate oscillation modes using a complete, non-perturbative treatment of differential rotation modelled after Saturn’s zonal winds in self-consistently computed, polytropic equilibria. We find that previous, approximate treatments of the effects of differential rotation in Saturn overestimate shifts in the frequencies of fundamental modes (f modes) thought to be responsible for the majority of the waves detected in the C ring, due to an omitted modification of the equilibrium shape and structure of the planet by differential rotation. The bias introduced by these frequency overestimates is small, but significant relative to the uncertainties afforded by Cassini data. We additionally consider the non-perturbative effects of Saturn-like differential rotation on the rotational mixing of f modes and internal gravity modes (g modes), which is relevant to detections of multiple density waves with very closely split pattern speeds. We find that higher-order rotational effects can produce orders-of-magnitude enhancements in the surface gravitational perturbations of g modes dominated by large spherical harmonic degrees ℓ, regardless of frequency separation from the sectoral f mode. Despite this enhancement, we find that the observed fine splitting of density waves is unlikely to involve g modes dominated by ℓ ≳ 10. This restriction may aid in the inference of possible internal structures for Saturn.
The stellar parameters and elemental abundances from low-resolution spectra – I. 1.2 million giants from LAMOST DR8
Authors: Li Zhuohan , Zhao Gang , Chen Yuqin , Liang Xilong , Zhao Jingkun 
Published: July 2022

ABSTRACT
As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data. In this study, we built a deep convolutional neural network (NN) to estimate basic stellar parameters $T\rm {_{eff}}$, log g, metallicity ([M/H] and [Fe/H]) and [α/M] along with nine individual elemental abundances ([C/Fe], [N/Fe], [O/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], [Ca/Fe], [Mn/Fe], and [Ni/Fe]). The NN is trained using common stars between the APOGEE survey and the LAMOST survey. We used low-resolution spectra from LAMOST survey as input, and measurements from APOGEE as labels. For stellar spectra with the signal-to-noise ratio in g band larger than 10 in the test set, the mean absolute error (MAE) is 29 K for $T\rm {_{eff}}$, 0.07 dex for log g, 0.03 dex for both [Fe/H] and [M/H], and 0.02 dex for [α/M]. The MAE of most elements is between 0.02 and 0.04 dex. The trained NN was applied to 1210 145 giants, including sub-giants, from LAMOST DR8 within the range of stellar parameters 3500 K &lt; $T\rm {_{eff}}$ &lt; 5500 K, 0.0 dex &lt; log g &lt; 4.0 dex, −2.5 dex &lt; [Fe/H] &lt; 0.5 dex. The distribution of our results in the chemical spaces is highly consistent with APOGEE labels and stellar parameters show consistency with external high-resolution measurements from GALAH. The results in this study allow us to further studies based on LAMOST data and deepen our understanding of the accretion and evolution history of the Milky Way. The electronic version of the value added catalog is available at http://www.lamost.org/dr8/v1.1/doc/vac.
Extended planetary chaotic zones
Authors: Shevchenko Ivan I 
Published: July 2022

ABSTRACT
We consider the chaotic motion of low-mass bodies in two-body high-order mean-motion resonances with planets in model planetary systems, and analytically estimate the Lyapunov and diffusion time-scales of the motion in multiplets of interacting subresonances corresponding to the mean-motion resonances. We show that the densely distributed (though not overlapping) high-order mean-motion resonances, when certain conditions on the planetary system parameters are satisfied, may produce extended planetary chaotic zones – ‘zones of weak chaotization,’ – much broader than the well-known planetary connected chaotic zone, the Wisdom gap. This extended planetary chaotic zone covers the orbital range between the 2/1 and 1/1 resonances with the planet. On the other hand, the orbital space inner (closer to the host star) with respect to the 2/1 resonance location is essentially long-term stable. This difference arises because the adiabaticity parameter of subresonance multiplets specifically depends on the particle’s orbit size. The revealed effect may control the structure of planetesimal discs in planetary systems: the orbital zone between the 2/1 and 1/1 resonances with a planet should be normally free from low-mass material (only that occasionally captured in the first-order 3/2 or 4/3 resonances may survive); whereas any low-mass population inner to the 2/1 resonance location should be normally long-lived (if not perturbed by secular resonances, which we do not consider in this study).
Astrophysical gravitational-wave echoes from galactic nuclei
Authors: Gondán László , Kocsis Bence 
Published: July 2022

ABSTRACT
Galactic nuclei (GNs) are dense stellar environments abundant in gravitational-wave (GW) sources for the Laser Interferometer Gravitational-Wave Observatory (LIGO), Virgo, and Kamioka Gravitational Wave Detector (KAGRA). The GWs may be generated by stellar-mass black hole (BH) or neutron star mergers following gravitational bremsstrahlung, dynamical scattering encounters, Kozai–Lidov-type oscillations driven by the central supermassive black hole (SMBH), or gas-assisted mergers if present. In this paper, we examine a smoking gun signature to identify sources in GNs: the GWs scattered by the central SMBH. This produces a secondary signal, an astrophysical GW echo, which has a very similar time–frequency evolution as the primary signal but arrives after a time delay. We determine the amplitude and time-delay distribution of the GW echo as a function of source distance from the SMBH. Between ${\sim} 10{{\ \rm per\ cent}}\hbox{ and }90{{\ \rm per\ cent}}$ of the detectable echoes arrive within ${\sim} (1\hbox{--}100)M_6\, \mathrm{s}$ after the primary GW for sources between 10 and 104 Schwarzschild radius, where $M_6=M_{{\rm SMBH},z}/(10^6\, \mathrm{M}_{\odot })$, and MSMBH, z is the observer-frame SMBH mass. The echo arrival times are systematically longer for high signal-to-noise ratio (SNR) primary GWs, where the GW echo rays are scattered at large deflection angles. In particular, ${\sim} 10{{\ \rm per\ cent}}\hbox{--}90{{\ \rm per\ cent}}$ of the distribution is shifted to ${\sim} (5\hbox{--}1800)M_6\, \mathrm{s}$ for sources, where the lower limit of echo detection is 0.02 of the primary signal amplitude. We find that ${\sim} 5{{\ \rm per\ cent}}\hbox{--}30{{\ \rm per\ cent}}$ (${\sim} 1{{\ \rm per\ cent}}\hbox{--}7{{\ \rm per\ cent}}$) of GW sources have an echo amplitude larger than 0.2–0.05 times the amplitude of the primary signal if the source distance from the SMBH is 50 (200) Schwarzschild radius. Non-detections can rule out that a GW source is near an SMBH.
On the accretion of a new group of galaxies on to Virgo – II. The effect of pre-processing on the stellar population content of dEs
Authors: Bidaran Bahar , La Barbera Francesco , Pasquali Anna , Peletier Reynier , van de Ven Glenn , Grebel Eva K , Falcón-Barroso Jesus , Sybilska Agnieszka , Gadotti Dimitri A , Coccato Lodovico 
Published: July 2022

ABSTRACT
Using MUSE spectra, we investigate how pre-processing and accretion on to a galaxy cluster affect the integrated stellar population properties of dwarf early-type galaxies (dEs). We analyse a sample of nine dEs with stellar masses of $\rm \sim 10^9 \, M_\odot$, which were accreted (∼ 2–3 Gyr ago) on to the Virgo cluster as members of a massive galaxy group. We derive their stellar population properties, namely age, metallicity ([M/H]), and the abundance ratio of α elements ([α/Fe]), by fitting observed spectral indices with a robust, iterative procedure, and infer their star formation history (SFH) by means of full spectral fitting. We find that these nine dEs are more metal-poor (at the 2–3σ level) and significantly more α-enhanced than dEs in the Virgo and Coma clusters with similar stellar mass, clustercentric distance, and infall time. Moreover, for six dEs, we find evidence for a recent episode of star formation during or right after the time of accretion on to Virgo. We interpret the high [α/Fe] of our sample of dEs as the result of the previous exposure of these galaxies to an environment hostile to star formation, and/or the putative short burst of star formation they underwent after infall into Virgo. Our results suggest that the stellar population properties of low-mass galaxies may be the result of the combined effect of pre-processing in galaxy groups and environmental processes (such as ram-pressure triggering star formation) acting during the early phases of accretion on to a cluster.
Impulsively generated kink wave trains in solar coronal slabs
Authors: Guo Mingzhe , Li Bo , Van Doorsselaere Tom , Shi Mijie 
Published: July 2022

ABSTRACT
We numerically follow the response of density-enhanced slabs to impulsive, localized, transverse velocity perturbations by working in the framework of ideal magnetohydrodynamics (MHD). Both linear and non-linear regimes are addressed. Kink wave trains are seen to develop along the examined slabs, sharing the characteristics that more oscillatory patterns emerge with time and that the apparent wavelength increases with distance at a given instant. Two features none the less arise due to non-linearity, one being a density cavity close to the exciter and the other being the appearance of shocks both outside and inside the nominal slab. These features may be relevant for understanding the interaction between magnetic structures and such explosive events as coronal mass ejections. Our numerical findings on kink wave trains in solar coronal slabs are discussed in connection with typical measurements of streamer waves.
Forecasting the solar cycle 25 using a multistep Bayesian neural network
Authors: Bizzarri I , Barghini D , Mancuso S , Alessio S , Rubinetti S , Taricco C 
Published: July 2022

ABSTRACTPredicting the solar activity of upcoming cycles is crucial nowadays to anticipate potentially adverse space weather effects on the Earth’s environment produced by coronal transients and traveling interplanetary disturbances. The latest advances in deep learning techniques provide new paradigms to obtain effective prediction models that allow to forecast in detail the evolution of cosmogeophysical time series. Because of the underlying complexity of the dynamo mechanism in the solar interior that is at the origin of the solar cycle phenomenon, the predictions offered by state-of-the-art machine learning algorithms represent valuable tools for our understanding of the cycle progression. As a plus, Bayesian deep learning is particularly compelling thanks to recent advances in the field that provide improvements in both accuracy and uncertainty quantification compared to classical techniques. In this work, a deep learning long short-term memory model is employed to predict the complete profile of Solar Cycle 25, thus forecasting also the advent of the next solar minimum. A rigorous uncertainty estimation of the predicted sunspot number is obtained by applying a Bayesian approach. Two different model validation techniques, namely the Train-Test split and the time series k-fold cross-validation, have been implemented and compared, giving compatible results. The forecasted peak amplitude is lower than that of the preceding cycle. Solar Cycle 25 will last 10.6 ± 0.7 yr, reaching its maximum in the middle of the year 2024. The next solar minimum is predicted in 2030 and will be as deep as the previous one.
On the moment of inertia of PSR J0737-3039 A from LIGO/Virgo and NICER
Authors: Miao Zhiqiang , Li Ang , Dai Zi-Gao 
Published: July 2022

ABSTRACT
We perform a Bayesian analysis of neutrons star moment of inertia by utilizing the available gravitational-wave data from LIGO/Virgo (GW170817 and GW190425) and mass-radius measurements from the Neutron Star Interior Composition Explorer (PSR J0030+0415 and PSR J0740 + 6620), incorporating the possible phase transition in the pulsar inner core. We find that the moment of inertia of pulsar A in the double pulsar binary J0737-3039 is $\sim 1.30\times 10^{45}\, {\rm g\, cm^2}$, which only slightly depends on the employed hadronic equation of states. We also demonstrate how a moment of inertia measurement would improve our knowledge of the equation of state and the mass–radius relation for neutron stars and discuss whether a quark deconfinement phase transition is supported by the available data and forthcoming data that could be consistent with this hypothesis. We find that if pulsar A is a quark star, its moment of inertia is a large value of $\sim 1.55\times 10^{45}\, {\rm g\, cm^2}$ suggesting the possibility of distinguishing it from (hybrid-)neutron stars with measurements of PSR J0737-3039A moment of inertia. We finally demonstrate the moment-of-inertia-compactness universal relations and provide analytical fits for both (hybrid-)neutron star and quark star results based on our analysis.
SDSS-IV MaNGA: global properties of kinematically misaligned galaxies
Authors: Zhou Yuren , Chen Yanmei , Shi Yong , Bizyaev Dmitry , Guo Hong , Bao Min , Xu Haitong , Yu Xiaoling , Brownstein Joel R 
Published: July 2022

ABSTRACT
We select 456 gas–star kinematically misaligned galaxies from the internal Product Launch-10 of MaNGA survey, including 74 star-forming (SF), 136 green-valley (GV), and 206 quiescent (QS) galaxies. We find that the distributions of difference between gas and star position angles for galaxies have three local peaks at ∼0°, 90°, and 180°. The fraction of misaligned galaxies peaks at log (M*/M⊙) ∼ 10.5 and declines to both low- and high-mass end. This fraction decreases monotonically with increasing star formation rate and specific star formation rate. We compare the global parameters including gas kinematic asymmetry Vasym, H i detection rate and mass fraction of molecular gas, effective radius Re, Sérsic index n as well as spin parameter $\lambda _{R_e}$ between misaligned galaxies and their control samples. We find that the misaligned galaxies have lower H i detection rate and molecular gas mass fraction, smaller size, higher Sérsic index, and lower spin parameters than their control samples. The SF and GV misaligned galaxies are more asymmetric in gas velocity fields than their controls. These pieces of observational evidence point to the gas accretion scenario followed by angular momentum redistribution from gas–gas collision, leading to gas inflow and central star formation for the SF and GV misaligned galaxies. We propose three possible origins of the misaligned QS galaxies: (1) external gas accretion, (2) merger, and (3) GV misaligned galaxies evolve into QS galaxies.
The K2 Galactic Archaeology Program: Overview, target selection, and survey properties
Authors: Sharma Sanjib , Stello Dennis , Zinn Joel C , Reyes Claudia , Hon Marc , Bland-Hawthorn Joss 
Published: July 2022

ABSTRACT
K2 was a community-driven NASA mission where all targets were proposed through guest observer programmes. Here we provide an overview of one of the largest of these endeavours, the K2 Galactic Archaeology Programme (K2GAP), with about 25 per cent of the observed targets being allocated to this programme. K2GAP provides asteroseismic parameters for about 23 000 giant stars across the Galaxy, which together with spectroscopic stellar parameters can give age and masses of stars. We discuss in detail the target selection procedure and provide a python program that implements the selection function (github.com/sanjibs/k2gap). Broadly speaking, the targets were selected on 2MASS colour J − Ks &gt; 0.5, with finely tuned adjustments for each campaign. We discuss the detection completeness of the asteroseismic parameters νmax and Δν. About 14 per cent of giants were found to miss νmax detections and it was difficult to detect Δν for RC stars. Making use of the selection function, we compare the observed distribution of asteroseismic masses to theoretical predictions. The median asteroseismic mass is higher by about 4 per cent compared to predictions. We provide a selection-function-matched mock catalogue of stars based on a synthetic model of the Galaxy for the community to use in subsequent analyses of the K2GAP data set (physics.usyd.edu.au/k2gap/download/).
Response approach to the integrated shear 3-point correlation function: the impact of baryonic effects on small scales
Authors: Halder Anik , Barreira Alexandre 
Published: July 2022

ABSTRACT
The integrated shear 3-point correlation function ζ± is a higher-order statistic of the cosmic shear field that describes the modulation of the 2-point correlation function ξ± by long-wavelength features in the field. Here, we introduce a new theoretical model to calculate ζ± that is accurate on small angular scales, and that allows to take baryonic feedback effects into account. Our model builds on the realization that the small-scale ζ± is dominated by the non-linear matter bispectrum in the squeezed limit, which can be evaluated accurately using the non-linear matter power spectrum and its first-order response functions to density and tidal field perturbations. We demonstrate the accuracy of our model by showing that it reproduces the small-scale ζ± measured in simulated cosmic shear maps. The impact of baryonic feedback enters effectively only through the corresponding impact on the non-linear matter power spectrum, thereby permitting to account for these astrophysical effects on ζ± similarly to how they are currently accounted for on ξ±. Using a simple idealized Fisher matrix forecast for a DES-like survey we find that, compared to ξ±, a combined $\xi _{\pm }\ \&\ \zeta _{\pm }$ analysis can lead to improvements of order $20\!-\!40{{\ \rm per\ cent}}$ on the constraints of cosmological parameters such as σ8 or the dark energy equation of state parameter w0. We find similar levels of improvement on the constraints of the baryonic feedback parameters, which strengthens the prospects for cosmic shear data to obtain tight constraints not only on cosmology but also on astrophysical feedback models. These encouraging results motivate future works on the integrated shear 3-point correlation function towards applications to real survey data.