Table of contents

The Interstellar Boundary Explorer (IBEX) has been observing the outer heliosphere and its interactions with the very local interstellar medium (VLISM) via measurements of energetic neutral atoms (ENAs) for over 14 yr. We discovered the IBEX Ribbon—a structure completely unanticipated by any prior theory or model—that almost certainly resides beyond the heliopause in the VLISM. We also characterized the other major source of heliospheric ENAs, the globally distributed flux (GDF), produced largely in the heliosheath between the termination shock and heliopause. In this study, we make three major new contributions. First, we validate, provide, and analyze the most recent 3 yr of IBEX-Hi (0.5–6 keV FWHM) data (2020–2022) for the first time. Second, we link these observations to the prior 11 yr of observations, exploring long-term variations. Finally, we provide the first IBEX team-validated Ribbon/GDF separation scheme and separated maps. Because of the uncertainty in separating different line-of-sight integrated sources, we provide not just best guess (median) maps, but also maps with upper and lower reasonable values of Ribbon and GDF fluxes, along with bounding fluxes that add the uncertainties to the upper and lower values. This allows theories and models to be compared with a range of possible values that the IBEX team believes are consistent with data. These observations, along with the reanalysis of the prior 11 yr of IBEX-Hi data, provide new insights and even further develop our detailed understanding of the heliosphere's interaction with the local interstellar medium unlocked by IBEX.

A key challenge in space weather forecasting is accurately predicting the magnetic field topology of interplanetary coronal mass ejections (ICMEs), specifically the north–south magnetic field component (B_z) for Earth-directed CMEs. Heliospheric MHD models typically use spheromaks to represent the magnetic structure of CMEs. However, when inserted into the ambient interplanetary magnetic field, spheromaks can experience a phenomenon reminiscent of the condition known as the "spheromak tilting instability," causing its magnetic axis to rotate. From the perspective of space weather forecasting, it is crucial to understand the effect of this rotation on predicting B_z at 1 au while implementing the spheromak model for realistic event studies. In this work, we study this by modeling a CME event on 2013 April 11 using the European Heliospheric Forecasting Information Asset. Our results show that a significant spheromak rotation up to 90° has occurred by the time it reaches 1 au, while the majority of this rotation occurs below 0.3 au. This total rotation resulted in poor predicted magnetic field topology of the ICME at 1 au. To address this issue, we further investigated the influence of spheromak density on mitigating rotation. The results show that the spheromak rotation is less for higher densities. Importantly, we observe a substantial reduction in the uncertainties associated with predicting B_z when there is minimal spheromak rotation. Therefore, we conclude that spheromak rotation adversely affects B_z prediction in the analyzed event, emphasizing the need for caution when employing spheromaks in global MHD models for space weather forecasting.

Astrochemical simulations are a powerful tool for revealing chemical evolution in the interstellar medium. Astrochemical calculations require efficient processing of large matrices for the chemical networks. The large chemical reaction networks often present bottlenecks for computation because of time derivatives of chemical abundances. We propose an efficient algorithm using a stoichiometry matrix approach in which this time-consuming part is expressed as a loop, unlike the algorithm used in previous studies. Since stoichiometry matrices are sparse in general, the performances of simulations with our algorithm depend on which sparse-matrix storage format is used. We conducted a performance comparison experiment using the common storage formats, including the coordinate format, the compressed column storage format, the compressed row storage (CRS) format, and the sliced ELLPACK format. Experimental results showed that the simulations with the CRS format are the most suitable for astrochemical simulations and about a factor of 2 faster than those with the algorithm used in previous studies. In addition, our algorithm significantly reduces not only the computation time but also the compilation time. We also explore the beneficial effects of parallelization and sparse-matrix reordering in these algorithms.

Semidetached binaries are in the stage of mass transfer and play a crucial role in studying the physics of mass transfer between interacting binaries. Large-scale time-domain surveys provide many light curves of binary systems, while Gaia offers high-precision astrometric data. In this paper, we develop, validate, and apply a pipeline that combines the Markov Chain Monte Carlo method with a forward model and DBSCAN clustering to search for semidetached binaries and estimate the inclination, relative radius, mass ratio, and temperature ratio of each using light curves. We train our model on the mock light curves from Physics of Eclipsing Binaries (PHOEBE), which provides broad coverage of light-curve simulations for semidetached binaries. Applying our pipeline to Transiting Exoplanet Survey Satellite sectors 1–26, we have identified 77 semidetached binary candidates. Utilizing the distance from Gaia, we determine their masses and radii with median fractional uncertainties of ∼26% and ∼7%, respectively. With the added 77 candidates, the catalog of semidetached binaries with orbital parameters has been expanded by approximately 20%. The comparison and statistical results show that our semidetached binary candidates align well with the compiled samples and the PARSEC model in T_eff–L and M–R relations. Combined with the literature samples, comparative analysis with stability criteria for conserved mass transfer indicates that ∼97.4% of samples are undergoing nuclear-timescale mass transfer, and two samples (GO Cyg and TIC 454222105) are located within the limits of stability criteria for dynamical- and thermal-timescale mass transfer, and are currently undergoing thermal-timescale mass transfer. Additionally, one system (IR Lyn) is very close to the upper limit of delayed dynamical-timescale mass transfer.

We present full Stokes MeerKAT L-band (856–1712 MHz) observations of 36 high-latitude supernova remnants (SNRs). Sensitive, high-dynamic-range images show a wealth of structure. G15.1−1.6 appears to be a H ii region rather than an SNR. G30.7−2.0 consists of three background extragalactic sources which appear to form an arc when imaged with much lower resolution. At least half of the remnants in the sample contain "blowouts" or "ears," showing these to be a common feature. Analysis of the polarimetric data reveals details of the magnetic field structure in the emitting regions of the remnants as well as magnetized thermal plasma in front of polarized emission. The chance alignment of G327.6+14.6 with a background active galactic nucleus with very extended polarized jets allows testing for the presence of Faraday effects in the interior of the remnant. Scant evidence of Faraday rotating material is found in the interior of this remnant.

Variability is a prominent observational feature of blazars. The high-energy radiation mechanism of jets has always been important but is still unclear. In this work, we performed a detailed analysis using Fermi-LAT data across 15 yr and obtained GeV light-curve information for 78 TeV blazars detected by Fermi. We provided annual GeV fluxes and corresponding spectral indices for the 78 TeV blazars and thorough monthly GeV fluxes for a subsample of 41 bright blazars. Our results suggest a strong correlation between the γ-ray photon index and $\mathrm{log}{L}_{\gamma }$ for the flat spectrum radio quasars (FSRQs) and high-energy peaked BL Lacs. Fourteen sources in our sample show significant GeV outbursts/flares above the relatively stable, low-flux light curve, with six of them showing a clear sharp peak profile in their 5 day binned light curves. We quantified the variability utilizing the fractional variability parameter F_var, and found that the flux of the FSRQs showed significantly stronger variability than that of the BL Lacs. The 41 bright blazars in this work are best fit by a log-normal flux distribution. We checked the spectral behavior and found 11 out of the 14 sources show a bluer-when-brighter trend, suggesting this spectral behavior for these TeV blazars at the GeV band arises from the mechanism in which the synchrotron-self Compton process dominates the GeV emission. Our research offers a systematic analysis of the GeV variability properties of TeV blazars and serves as a helpful resource for further associated blazar studies.

Accurately measuring the Hubble parameter is vital for understanding the expansion history and properties of the Universe. In this paper, we propose a new method that supplements the covariance between redshift pairs to improve the reconstruction of the Hubble parameter using the observational Hubble data set. Our approach uses a cosmological model-independent radial basis function neural network to effectively describe the Hubble parameter as a function of redshift. Our experiments show that this method results in a reconstructed Hubble parameter of H₀ = 67.1 ± 9.7 km s⁻¹ Mpc⁻¹, which is more noise resistant and fits the ΛCDM model at high redshifts better. Providing the covariance between redshift pairs in subsequent observations will significantly improve the reliability and accuracy of Hubble parametric data reconstruction. Future applications of this method could help overcome the limitations of previous methods and lead to new advances in our understanding of the Universe.

Observations of gravitational waves (GW) provide us with a new probe to study the Universe. GW events can be used as standard sirens if their redshifts are measured. Normally, standard sirens can be divided into bright/dark sirens according to whether the redshifts are measured by electromagnetic (EM) counterpart observations. First, we investigate the capability of the 2.5 m Wide-Field Survey Telescope (WFST) to take follow-up observations of kilonova counterparts. For binary neutron star (BNS) bright sirens, WFST is expected to observe 10–20 kilonovae per year in the second-generation GW detection era. As for neutron star–black hole (NSBH) mergers, when a BH spin is extremely high and the neutron star (NS) is stiff, the observation rate is ∼10 per year. Combining optical and GW observations, the bright sirens are expected to constrain the Hubble constant H₀ to ∼2.8% in five years of observations. As for dark sirens, the tidal effects of NSs during merging provide us with a cosmological model-independent approach to measure the redshifts of GW sources. Then we investigate the applications of tidal effects in redshift measurements. We find in the third generation era, the host galaxy groups of around 45% BNS mergers at z < 0.1 can be identified through this method, if the equation of state is ms1, which is roughly equivalent to the results from luminosity distant constraints. Therefore, tidal effect observations provide a reliable and cosmological model-independent method of identifying BNS mergers' host galaxy groups. Using this method, the BNS/NSBH dark sirens can constrain H₀ to 0.2%/0.3% over a five-year observation period.

We investigate the feasibility of using the comoving Lagrangian acceleration (COLA) technique to efficiently generate galaxy mock catalogs that can accurately reproduce the statistical properties of observed galaxies. Our proposed scheme combines the subhalo abundance-matching (SHAM) procedure with COLA simulations, using only three free parameters: the scatter magnitude (σ_scat) in SHAM, the initial redshift (z_init) of the COLA simulation, and the time stride (da) used by COLA. In this proof-of-concept study, we focus on a subset of BOSS CMASSNGC galaxies within the redshift range z ∈ [0.45, 0.55]. We perform GADGET simulation and low-resolution COLA simulations with various combinations of (z_init, da), each using 1024³ particles in an 800 h⁻¹ Mpc box. By minimizing the difference between COLAmock and CMASSNGC galaxies for the monopole of the two-point correlation function (2PCF), we obtain the optimal σ_scat. We have found that by setting z_init = 29 and da = 1/30, we achieve a good agreement between COLAmock and CMASSNGC galaxies within the range of 4–20 h⁻¹ Mpc, with a computational cost lower by 2 orders of magnitude than that of the GADGETN-body code. Moreover, a detailed verification is performed by comparing various statistical properties, such as anisotropic 2PCF, three-point clustering, and power spectrum multipoles, which shows a similar performance of the GADGETmock and COLAmock catalogs with the CMASSNGC galaxies. Furthermore, we assess the robustness of the COLAmock catalogs for different cosmological models, demonstrating consistent results in the resulting 2PCFs. Our findings suggest that COLA simulations are a promising tool for efficiently generating mock catalogs for emulators and machine-learning analyses to explore the large-scale structure of the Universe.

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ∼ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on Hα, Hβ, and Mg ii at z ≤ 0.75 and Mg ii, C iii], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 Hα, 34 Hβ, 9 Mg ii, 18 C iii], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (∼30%) and would be conducive to exploring the underlying physical mechanism.

The Presolar Grain Database (PGD) contains the vast majority of isotope data (published and unpublished) on presolar grains and was first released as a collection of spreadsheets in 2009. It has been a helpful tool used by many researchers in cosmochemistry and astrophysics. However, over the years, accumulated errors compromised major parts of the PGD. Here, we provide a fresh start, with the PGD for silicon carbide (SiC) grains rebuilt from the ground up. We also provide updated rules for SiC grain type classification to unify previous efforts, taking into account newly discovered grain types. We also define a new grain type D, which includes some grains previously classified as ungrouped. Future work will focus on rebuilding the PGD for other kinds of presolar grains: graphite, oxides, silicates, and rarer phases.

We present the evolution and the explosion of two massive stars, 15 and 25 M_⊙, spanning a wide range of initial rotation velocities (from 0 to 800 km s⁻¹) and three initial metallicities: Z = 0 ([Fe/H] = −∞), 3.236 × 10⁻⁷ ([Fe/H] = −5), and 3.236 × 10⁻⁶ ([Fe/H] = −4). A very large nuclear network of 524 nuclear species extending up to Bi has been adopted. Our main findings may be summarized as follows: (a) rotating models above Z = 0 are able to produce nuclei up to the neutron closure shell N = 50, and in a few cases up to N = 82; (b) rotation drastically inhibits the penetration of the He convective shell in the H-rich mantle, a phenomenon often found in zero metallicity nonrotating massive stars; (c) vice versa, rotation favors the penetration of the O convective shell in the C-rich layers with the consequence of significantly altering the yields of the products of the C, Ne, and O burning; (d) none of the models that reach the critical velocity while in H burning lose more the 1 M_⊙ in this phase; (e) conversely, almost all models able to reach their Hayashi track exceed the Eddington luminosity and dynamically lose almost all their H-rich mantle. These models suggest that rotating massive stars may have contributed significantly to the synthesis of the heavy nuclei in the first phase of enrichment of the interstellar medium, i.e., at early times.

According to a standard initial mass function, stars in the range 7–12 M_⊙ constitute ∼50% (by number) of the stars more massive than ∼7 M_⊙, but in spite of this, their evolutionary properties, and in particular their final fate, are still scarcely studied. In this paper, we present a detailed study of the evolutionary properties of solar metallicity nonrotating stars in the range 7–15 M_⊙, from the pre-main-sequence phase up to the presupernova stage or an advanced stage of the thermally pulsing phase, depending on the initial mass. We find that (1) the 7.00 M_⊙ star develops a degenerate CO core and evolves as a classical asymptotic giant branch (AGB) star in the sense that it does not ignite the C-burning reactions, (2) stars with initial mass M ≥ 9.22 M_⊙ end their lives as core-collapse supernovae, (3) stars in the range 7.50 ≤ M/M_⊙ ≤ 9.20 develop a degenerate ONeMg core and evolve through the thermally pulsing super-AGB phase, (4) stars in the mass range 7.50 ≤ M/M_⊙ ≤ 8.00 end their lives as hybrid CO/ONeMg or ONeMg WDs, and (5) stars with initial mass in the range 8.50 ≤ M/M_⊙ ≤ 9.20 may potentially explode as electron-capture supernovae.

We develop a general description of how information propagates through a magnetohydrodynamic (MHD) system based on the method of characteristics and use that to formulate numerical boundary conditions that are intrinsically consistent with the MHD equations. Our formulation includes two major advances for simulations of the Sun. First, we derive data-driven boundary conditions that optimally match the state of the plasma inferred from a time series of observations of a boundary (e.g., the solar photosphere). Second, our method directly handles random noise and systematic bias in the observations, and finds a solution for the boundary evolution that is strictly consistent with MHD and maximally consistent with the observations. We validate the method against a Ground Truth (GT) simulation of an expanding spheromak. The data-driven simulation can reproduce the GT simulation above the photosphere with high fidelity when driven at high cadence. Errors progressively increase for lower driving cadence until a threshold cadence is reached and the driven simulation can no longer accurately reproduce the GT simulation. However, our characteristic formulation of the boundary conditions still requires adherence of the boundary evolution to the MHD equations even when the driven solution departs from the true solution in the driving layer. That increasing departure clearly indicates when additional information at the boundary is needed to fully specify the correct evolution of the system. The method functions even when no information about the evolution of some variables on the lower boundary is available, albeit with a further decrease in fidelity.

Solar energetic particles (SEPs) are associated with extreme solar events that can cause major damage to space- and ground-based life and infrastructure. High-intensity SEP events, particularly ∼100 MeV SEP events, can pose severe health risks for astronauts owing to radiation exposure and affect Earth's orbiting satellites (e.g., Landsat and the International Space Station). A major challenge in the SEP event prediction task is the lack of adequate SEP data because of the rarity of these events. In this work, we aim to improve the prediction of ∼30, ∼60, and ∼100 MeV SEP events by synthetically increasing the number of SEP samples. We explore the use of a univariate and multivariate time series of proton flux data as input to machine-learning-based prediction methods, such as time series forest (TSF). Our study covers solar cycles 22, 23, and 24. Our findings show that using data augmentation methods, such as the synthetic minority oversampling technique, remarkably increases the accuracy and F1-score of the classifiers used in this research, especially for TSF, where the average accuracy increased by 20%, reaching around 90% accuracy in the ∼100 MeV SEP prediction task. We also achieved higher prediction accuracy when using the multivariate time series data of the proton flux. Finally, we build a pipeline framework for our best-performing model, TSF, and provide a comprehensive hierarchical classification of the ∼100, ∼60, and ∼30 MeV and non-SEP prediction scenarios.

We provide a catalog of atmospheric parameters for 1,806,921 cool dwarfs from Gaia Data Release 3 (DR3) that lie within the range covered by LAMOST cool dwarf spectroscopic parameters: 3200 K < T_eff < 4300 K, −0.8 < [M/H] < 0.2 dex, and 4.5 < log g < 5.5 dex. Our values are derived based on machine-learning models trained with multiband photometry corrected for dust. The photometric data comprise optical data from the Sloan Digital Sky Survey r, i, and z bands, near-infrared data from the Two Micron All Sky Survey J, H, and K bands, and mid-infrared data from the ALLWISE W1 and W2 bands. We used both random forest and light gradient boosting machine machine-learning models and found similar results from both, with an error dispersion of 68 K, 0.22 dex, and 0.05 dex for T_eff, [M/H], and log g, respectively. Assessment of the relative feature importance of different photometric colors indicated W1 − W2 as most sensitive to both T_eff and log g, with J − H being most sensitive to [M/H]. We find that our values show a good agreement with the Apache Point Observatory Galactic Evolution Experiment, but are significantly different to those provided as part of Gaia DR3.

The MeerKAT Absorption Line Survey (MALS) has observed 391 telescope pointings at the L band (900–1670 MHz) at δ ≲ +20°. We present radio continuum images and a catalog of 495,325 (240,321) radio sources detected at a signal-to-noise ratio (S/N) > 5 over an area of 2289 deg² (1132 deg²) at 1006 MHz (1381 MHz). Every MALS pointing contains a central bright radio source (S_{1 GHz} ≳ 0.2 Jy). The median spatial resolution is 12'' (8''). The median rms noise away from the pointing center is 25 μJy beam⁻¹ (22 μJy beam⁻¹) and is within ∼15% of the achievable theoretical sensitivity. The flux density scale ratio and astrometric accuracy deduced from multiply observed sources in MALS are <1% (8% scatter) and 1'', respectively. Through comparisons with NVSS and FIRST at 1.4 GHz, we establish the catalog's accuracy in the flux density scale and astrometry to be better than 6% (15% scatter) and 08, respectively. The median flux density offset is higher (9%) for an alternate beam model based on holographic measurements. The MALS radio source counts at 1.4 GHz are in agreement with literature. We estimate spectral indices (α) of a subset of 125,621 sources (S/N > 8), confirm the flattening of spectral indices with decreasing flux density, and identify 140 ultra-steep-spectrum (α < −1.3) sources as prospective high-z radio galaxies (z > 2). We have identified 1308 variable and 122 transient radio sources comprising primarily active galactic nuclei that demonstrate long-term (26 yr) variability in their observed flux densities. The MALS catalogs and images are publicly available at https://mals.iucaa.in.

We present a comprehensive analysis of the Hubble Space Telescope observations of the atmosphere of WASP-121 b, an ultra-hot Jupiter. After reducing the transit, eclipse, and phase-curve observations with a uniform methodology and addressing the biases from instrument systematics, sophisticated atmospheric retrievals are used to extract robust constraints on the thermal structure, chemistry, and cloud properties of the atmosphere. Our analysis shows that the observations are consistent with a strong thermal inversion beginning at ∼10⁴ Pa on the dayside, solar to subsolar metallicity Z (i.e., $-0.77\lt \mathrm{log}({\text{}}Z)\lt 0.05$), and supersolar C/O ratio (i.e., 0.59 < C/O < 0.87). More importantly, utilizing the high signal-to-noise ratio and repeated observations of the planet, we identify the following unambiguous time-varying signals in the data: (i) a shift of the putative hotspot offset between the two phase curves and (ii) varying spectral signatures in the transits and eclipses. By simulating the global dynamics of WASP-121 b's atmosphere at high resolution, we show that the identified signals are consistent with quasiperiodic weather patterns, hence atmospheric variability, with signatures at the level probed by the observations (∼5% to ∼10%) that change on a timescale of ∼5 planet days; in the simulations, the weather patterns arise from the formation and movement of storms and fronts, causing hot (as well as cold) patches of atmosphere to deform, separate, and mix in time.

Deuterated molecules are valuable probes for investigating the evolution and the kinematics in the earliest stages of star formation. In this study, we conduct a comprehensive investigation by performing a single-point survey of 101 starless clump candidates, and carrying out on-the-fly (OTF) observations of 11 selected sources, focusing on deuterated molecular lines using the IRAM 30 m telescope. In the single-point observation, we make 46 detections for DCO⁺J = 1−0, 12 for DCN J = 1−0, 51 for DNC J = 1−0, 7 for N₂D⁺J = 1−0, 20 for DCO⁺J = 2−1, and 10 for DCN J = 2−1. The starless clump candidates with deuterated molecule detections exhibit lower median kinetic temperatures and a narrower H₂CO (1_(0,1)−0_(0,0)) median full width at half maximum compared to those without such detections, while simultaneously displaying similar median values of 1.1 mm intensity, mass, and distance. Furthermore, our OTF observations reveal that deuterated molecules predominantly have peaks near the 1.1 mm continuum peaks, with the DCO⁺J = 1−0 emission demonstrating higher intensity in the deuterated peak region compared to the DCN and DNC J = 1−0 emissions. Additionally, the majority of emissions from deuterated molecules and ¹³C isotopologues exhibit peak positions close to those of the 1.1 mm continuum peaks. By analyzing the 20'' × 20'' regions with strongest deuterated emissions in the OTF observations, we estimated deuterated abundances of 0.004−0.045, 0.011−0.040, and 0.004−0.038 for D_frac(HCN), D_frac(HCO⁺), and D_frac(HNC), respectively. The differential detection of deuterated molecular lines in our OTF observations could be attributed to variations in critical densities and formation pathways.

Rapid advances in deep learning have brought not only a myriad of powerful neural networks, but also breakthroughs that benefit established scientific research. In particular, automatic differentiation (AD) tools and computational accelerators like GPUs have facilitated forward modeling of the Universe with differentiable simulations. Based on analytic or automatic backpropagation, current differentiable cosmological simulations are limited by memory, and thus are subject to a trade-off between time and space/mass resolution, usually sacrificing both. We present a new approach free of such constraints, using the adjoint method and reverse time integration. It enables larger and more accurate forward modeling at the field level, and will improve gradient-based optimization and inference. We implement it in an open-source particle-mesh (PM) N-body library pmwd (PM with derivatives). Based on the powerful AD system JAX, pmwd is fully differentiable, and is highly performant on GPUs.