Related papers: Disk Wind Feedback from High-mass Protostars. V. A…
All molecular clouds are observed to be turbulent, but the origin, means of sustenance, and evolution of the turbulence remain debated. One possibility is that stellar feedback injects enough energy into the cloud to drive observed motions…
Very massive stars (VMS) dominate the light of young stellar populations and are sources of intense stellar feedback. Their evolution is mainly driven by strong wind mass loss, yet current evolution models make simplistic assumptions on…
Determining the initial stellar multiplicity is a challenging problem since protostars are faint and deeply embedded at early times; once formed, multiple protostellar systems may significantly dynamically evolve before they are optically…
Wind speed at sea surface is a key quantity for a variety of scientific applications and human activities. Due to the non-linearity of the phenomenon, a complete description of such variable is made infeasible on both the small scale and…
Outflowing motions, whether a wind launched from the disk, a jet launched from the protostar, or the entrained molecular outflow, appear to be an ubiquitous feature of star formation. These outwards motions have a number of root causes, and…
Magnetic fields influence the structure and evolution of protostellar systems, thus understanding their role is essential for probing the earliest stages of star formation. We present ALMA Band 3 and 6 polarized continuum observations at…
It has been proposed that the magnetic field, pervasive in the ISM, plays an important role in the process of massive star formation. To better understand its impact at the pre and protostellar stages, high-angular resolution observations…
Model reduction of high-dimensional dynamical systems alleviates computational burdens faced in various tasks from design optimization to model predictive control. One popular model reduction approach is based on projecting the governing…
Utilising JWST, ALMA and the VLA we present high angular resolution (0.06''- 0.42''), multi-wavelength (4 micron - 3cm) observations of the VLA 1623-2417 protostellar system to characterise the origin, morphology and, properties of the…
The evolution of protostellar outflow is investigated with resistive magneto-hydrodynamic nested-grid simulations that cover a wide range of spatial scales (\sim 1AU - 1pc). We follow cloud evolution from the pre-stellar core stage until…
Model-agnostic tools for interpreting machine-learning models struggle to summarize the joint effects of strongly dependent features in high-dimensional feature spaces, which play an important role in pattern recognition, for example in…
We investigated the formation of arc-like structures in the infalling envelope around protostars, motivated by the recent Atacama Large Millimeter/Submillimeter Array (ALMA) observations of the high-density molecular cloud core,…
We report results from twelve simulations of the collapse of a molecular cloud core to form one or more protostars, comprising three field strengths (mass-to-flux ratios, {\mu}, of 5, 10, and 20) and four field geometries (with values of…
Observations with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Jansky Very Large Array (JVLA) have revealed many dust rings in protoplanetary disks, often interpreted as dust traps at gas pressure bumps. Previous studies…
Protein structure prediction is pivotal for understanding the structure-function relationship of proteins, advancing biological research, and facilitating pharmaceutical development and experimental design. While deep learning methods and…
In order to obtain the information about flow field, traditional computational fluid dynamics methods need to solve the Navier-Stokes equations on the mesh with boundary conditions, which is a time-consuming task. In this work, a…
We present an overview and first results of the Stratospheric Observatory For Infrared Astronomy Massive (SOMA) Star Formation Survey, which is using the FORCAST instrument to image massive protostars from $\sim10$--$40\:\rm{\mu}\rm{m}$.…
We summarize some of the compelling new scientific opportunities for understanding stars and stellar systems that can be enabled by sub-mas angular resolution, UV/Optical spectral imaging observations, which can reveal the details of the…
Deep learning provides a versatile suite of methods for extracting structured information from complex datasets, enabling deeper understanding of underlying fluid dynamic phenomena. The field of turbulence modeling, in particular, benefits…
Accurate beam prediction is essential for maintaining reliable links and high spectral efficiency in dynamic low-altitude wireless networks. However, existing approaches often fail to capture the deep correlations across heterogeneous…