Virtual reality for the analysis and visualization of scientific numerical models

The complexity of the data generated by (magneto)-hydrodynamic (HD/MHD) simulations requires advanced tools for their analysis and visualization. The dramatic improvements in virtual reality (VR) technologies have inspired us to seek the long-term goal of creating VR tools for scientific model analysis and visualization that would allow researchers to study and perform data analysis on their models within an immersive environment. Here, we report the results obtained at INAF-Osservatorio Astronomico di Palermo in the development of these tools, which would allow for the exploration of 3D models interactively, resulting in highly detailed analysis that cannot be performed with traditional data visualization and analysis platforms. Additionally, these VR-based tools offer the ability to produce high-impact VR content for efficient audience engagement and awareness.Comment: 9 pages, 5 figures, proceedings of the conference "Virtual and augmented reality for public outreach". Accepted for publication on Mem. SAI

Formation of X-ray emitting stationary shocks in magnetized protostellar jets

X-ray observations of protostellar jets show evidence of strong shocks heating the plasma up to temperatures of a few million degrees. In some cases, the shocked features appear to be stationary. They are interpreted as shock diamonds. We aim at investigating the physics that guides the formation of X-ray emitting stationary shocks in protostellar jets, the role of the magnetic field in determining the location, stability, and detectability in X-rays of these shocks, and the physical properties of the shocked plasma. We performed a set of 2.5-dimensional magnetohydrodynamic numerical simulations modelling supersonic jets ramming into a magnetized medium and explored different configurations of the magnetic field. The model takes into account the most relevant physical effects, namely thermal conduction and radiative losses. We compared the model results with observations, via the emission measure and the X-ray luminosity synthesized from the simulations. Our model explains the formation of X-ray emitting stationary shocks in a natural way. The magnetic field collimates the plasma at the base of the jet and forms there a magnetic nozzle. After an initial transient, the nozzle leads to the formation of a shock diamond at its exit which is stationary over the time covered by the simulations (~ 40 - 60 yr; comparable with time scales of the observations). The shock generates a point-like X-ray source located close to the base of the jet with luminosity comparable with that inferred from X-ray observations of protostellar jets. For the range of parameters explored, the evolution of the post-shock plasma is dominated by the radiative cooling, whereas the thermal conduction slightly affects the structure of the shock.Comment: Accepted for publication in Astronomy and Astrophysic

Modeling the remnants of core-collapse supernovae from luminous blue variable stars

Context. Luminous blue variable stars (LBVs) are massive evolved stars that suffer sporadic and violent mass-loss events. They have been proposed as the progenitors of some core-collapse supernovae (SNe), but this idea is still debated because of a lack of strong evidence. As supernova remnants (SNRs) can carry in their morphology the fingerprints of the progenitor stars as well as of the inhomogeneous circumstellar medium (CSM) sculpted by the progenitors, the study of SNRs from LBVs could help to place core-collapse SNe in context with the evolution of massive stars. Aims. We investigate the physical, chemical, and morphological properties of the remnants of SNe originating from LBVs in order to search for signatures in the ejecta distribution and morphology of the remnants that could reveal the nature of the progenitors. Methods. As a template of LBVs, we considered the LBV candidate Gal 026.47+0.02. We selected a grid of models that describe the evolution of a massive star with properties consistent with those of Gal 026.47+0.02 and its final fate as a core-collapse SN. We developed a three-dimensional hydrodynamic model that follows the post-explosion evolution of the ejecta from the breakout of the shock wave at the stellar surface to the interaction of the SNR with a CSM characterized by two dense nested toroidal shells, parametrized in agreement with multi-wavelength observations of Gal 026.47+0.02. Results. Our models show a strong interaction of the blast wave with the CSM which determines an important slowdown of the expansion of the ejecta in the equatorial plane where the two shells lay, determining a high degree of asymmetry in the remnant. After ≈10 000 yr of evolution, the ejecta show an elongated shape forming a broad jet-like structure caused by the interaction with the shells and oriented along the axis of the toroidal shells. Models with high explosion energy show Fe-rich internal ejecta distributions surrounded by an elongated Si-rich structure with a more diffuse O-rich ejecta all around. Models with low explosion energy instead show a more homogeneous distribution of chemical elements with a very low presence of Fe-group elements. Conclusions. The geometry and density distribution of the CSM where a LBV star goes SN are fundamental in determining the properties of the resulting SNR. For all the LBV-like progenitors explored here, we found that the remnants show a common morphology, namely elongated ejecta with an internal jet-like structure, which reflects the inhomogeneous and dense pre-SN CSM surrounding the star

Rubin LSST observing strategies to maximize volume and uniformity coverage of Star Forming Regions in the Galactic Plane

A complete map of the youngest stellar populations of the Milky Way in the era of all-sky surveys, is one of the most challenging goals in modern astrophysics. The characterisation of the youngest stellar component is crucial not only for a global overview of the Milky Way structure, of the Galactic thin disk, and its spiral arms, but also for local studies. In fact, the identification of the star forming regions (SFRs) and the comparison with the environment in which they form are also fundamental to put them in the context of the surrounding giant molecular clouds and to understand still unknown physical mechanisms related to the star and planet formation processes. In 10 yrs of observations, Vera C. Rubin Legacy Survey of Space and Time (Rubin-LSST) will achieve an exquisite photometric depth that will allow us to significantly extend the volume within which we will be able to discover new SFRs and to enlarge the domain of a detailed knowledge of our own Galaxy. We describe here a metrics that estimates the total number of young stars with ages t < 10 Myr and masses >0.3M$_\odot$ that will be detected with the Rubin LSST observations in the gri bands at a 5 {\sigma} magnitude significance. We examine the results of our metrics adopting the most recent simulated Rubin-LSST survey strategies in order to evaluate the impact that different observing strategies might have on our science case.Comment: 11 pages, 5 figures, 1 table; accepted for publication in The Astrophysical Journal Supplement Serie

Young stellar objects, accretion disks, and their variability with Rubin Observatory LSST

Vera C. Rubin Observatory, through the Legacy Survey of Space and Time (LSST), will allow us to derive a panchromatic view of variability in young stellar objects (YSOs) across all relevant timescales. Indeed, both short-term variability (on timescales of hours to days) and long-term variability (months to years), predominantly driven by the dynamics of accretion processes in disk-hosting YSOs, can be explored by taking advantage of the multi-band filters option available in Rubin LSST, in particular the $u,g,r,i$ filters that enable us to discriminate between photospheric stellar properties and accretion signatures. The homogeneity and depth of sky coverage that will be achieved with LSST will provide us with a unique opportunity to characterize the time evolution of disk accretion as a function of age and varying environmental conditions (e.g. field crowdedness, massive neighbors, metallicity), by targeting different star-forming regions. In this contribution to the Rubin LSST Survey Strategy Focus Issue, we discuss how implementing a dense observing cadence to explore short-term variability in YSOs represents a key complementary effort to the Wide-Fast-Deep observing mode that will be used to survey the sky over the full duration of the main survey ($\approx$10 years). The combination of these two modes will be vital to investigate the connection between the inner disk dynamics and longer-term eruptive variability behaviors, such as those observed on EXor objects.Comment: 11 pages, 4 figures, 1 table; accepted for publication in The Astrophysical Journal Supplement Serie

Negative and positive feedback from a supernova remnant with SHREC: a detailed study of the shocked gas in IC443

Interstellar matter and star formatio

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho

From Data to Software to Science with the Rubin Observatory LSST

editorial reviewedThe Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science

Modeling the mixed-morphology supernova remnant IC 443: Origins of its complex morphology and X-ray emission

Context. The morphology and the distribution of material observed in supernova remnants (SNRs) reflect the interaction of the supernova (SN) blast wave with the ambient environment, the physical processes associated with the SN explosion, and the internal structure of the progenitor star. IC 443 is a mixed-morphology (MM) SNR located in a quite complex environment: it interacts with a molecular cloud in the northwestern and southeastern areas and with an atomic cloud in the northeast. Aims. In this work, we aim to investigate the origin of the complex morphology and multi-thermal X-ray emission observed in SNR IC 443 through the study of the effect of the inhomogeneous ambient medium in shaping its observed structure and an exploration of the main parameters characterizing the remnant. Methods. We developed a 3D hydrodynamic (HD) model for IC 443, which describes the interaction of the SNR with the environment, parametrized in agreement with the results of the multi-wavelength data analysis. We performed an ample exploration of the parameter space describing the initial blast wave and the environment, including the mass of the ejecta, the energy and position of the explosion, as well as the density, structure, and geometry of the surrounding clouds. From the simulations, we synthesized the X-ray emission maps and spectra and compared them with actual X-ray data collected by XMM-Newton. Results. Our model explains the origin of the complex X-ray morphology of SNR IC 443 in a natural way, with the ability to reproduce, for the first time, most of the observed features, including the centrally-peaked X-ray morphology (characteristic of MM SNRs) when considering the origin of the explosion at the position where the pulsar wind nebula CXOU J061705.3+222127 was at the time of the explosion. In the model that best reproduces the observations, the mass of the ejecta and the energy of the explosion are ~7 M⊙ and ~1 × 1051 erg, respectively. From the exploration of the parameter space, we find that the density of the clouds is n &gt; 300 cm-3 and that the age of SNR IC 443 is ~8000 yr. Conclusions. The observed inhomogeneous ambient medium is the main property responsible for the complex structure and the X-ray morphology of SNR IC 443, resulting in a very asymmetric distribution of the ejecta due to the off-centered location of the explosion inside the cavity formed by the clouds. It can be argued that the centrally peaked morphology (typical of MM SNRs) is a natural consequence of the interaction with the complex environment. A combination of high resolution X-ray observations and accurate 3D HD modeling is needed to confirm whether this scenario is applicable to other MM SNRs