Related papers: Disk Wind Feedback from High-mass Protostars. V. A…
Large Language Models (LLMs) have significantly advanced molecular discovery, but existing multimodal molecular architectures fundamentally rely on autoregressive (AR) backbones. This strict left-to-right inductive bias is sub-optimal for…
Understanding and predicting microstructure evolution is fundamental to materials science, as it governs the resulting properties and performance of materials. Traditional simulation methods, such as phase-field models, offer high-fidelity…
For a binary protostellar outflow system in which its members are located so close to each other (the separation being smaller than the addition of the widths of the flows) and with large opening angles, the collision seems unavoidable…
Recent vision-language pre-training models have exhibited remarkable generalization ability in zero-shot recognition tasks. Previous open-vocabulary 3D scene understanding methods mostly focus on training 3D models using either image or…
ALMA's high-resolution images allow to resolve the filamentary structure of the ISM down to few thousand au at kpc distances. We aim to systematically quantify the impact of the interferometric response and the effects of the short-spacing…
[Abridged] Gas kinematics is a new and unique way to study planet-forming environments by an accurate characterization of disk velocity fields. High angular resolution ALMA observations allow deep kinematical analysis of disks, by observing…
The origin of outflows and their exact impact on disk evolution and planet formation remain crucial open questions. DG Tau B is a Class I protostar associated with a rotating conical CO outflow and a structured disk. Hence it is an ideal…
A physical model and two-dimensional numerical method for computing the evolution and spectra of protostellar clouds are described. The physical model is based on a system of magneto-gasdynamical equations, including ohmic and ambipolar…
Protostellar outflows display wide-angle winds and collimated jets, the magnetocentrifugal launching of which enables accretion onto the protostar. The majority of the outflow mass is likely ejected or entrained molecular H$_2$, which can…
We compute the molecular line emission of massive protostellar disks by solving the equation of radiative transfer through the cores and disks produced by the recent radiation-hydrodynamic simulations of Krumholz, Klein, & McKee. We find…
Wind power prediction is of vital importance in wind power utilization. There have been a lot of researches based on the time series of the wind power or speed, but In fact, these time series cannot express the temporal and spatial changes…
Evidence suggests that protostellar outbursts likely play a critical role in the stellar mass assembly process, but the extent of this contribution is not well understood. Using the proposed observing program of PRIMA, a concept far-IR…
Understanding the mechanisms underlying deep neural networks remains a fundamental challenge in machine learning and computer vision. One promising, yet only preliminarily explored approach, is feature inversion, which attempts to…
As part of the EU-funded Center of Excellence SPACE (Scalable Parallel Astrophysical Codes for Exascale), seven commonly used astrophysics simulation codes are being optimized to exploit exascale computing platforms. Exascale cosmological…
We present a dynamical model of supernova feedback which follows the evolution of pressurised bubbles driven by supernovae in a multi-phase interstellar medium (ISM). The bubbles are followed until the point of break-out into the halo,…
Mass-loss from massive stars is fundamental to stellar and galactic evolution and enrichment of the interstellar medium. Reliable determination of mass-loss rate is dependent upon unravelling details of massive star outflows, including…
We investigate how the removal of interstellar material by stellar feedback limits the efficiency of star formation in molecular clouds and how this determines the shape of the mass function of young star clusters. In particular, we derive…
High-dimensional images, known for their rich semantic information, are widely applied in remote sensing and other fields. The spatial information in these images reflects the object's texture features, while the spectral information…
Echoing recent calls to counter reliability and robustness concerns in machine learning via multiverse analysis, we present PRESTO, a principled framework for mapping the multiverse of machine-learning models that rely on latent…
We present the first systematic study of bipolar outflows using HC$_3$N as a tracer in a sample of 146 massive star-forming regions from ALMA-ATOMS survey. Protostellar outflows arise at the initial stage of star formation as a consequence…