| 1. |
- Cosentino, Giuliana, 1990, et al.
(author)
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Deuterium fractionation across the infrared-dark cloud G034.77-00.55 interacting with the supernova remnant W44
- 2023
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In: Astronomy and Astrophysics. - 0004-6361 .- 1432-0746. ; 675
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Journal article (peer-reviewed)abstract
- Supernova remnants (SNRs) may regulate star formation in galaxies. For example, SNR-driven shocks may form new molecular gas or compress pre-existing clouds and trigger the formation of new stars. Aims. To test this scenario, we measured the deuteration of N2H+, DNfrac 2H+- a well-studied tracer of pre-stellar cores - across the infrared-dark cloud (IRDC) G034.77-00.55, which is known to be experiencing a shock interaction with the SNR W44. Methods. We use N2H+ and N2D+ J = 1-0 single pointing observations obtained with the 30m antenna at the Instituto de Radioastronomia Millimetrica to infer DN2H+ frac towards five positions across the cloud, namely a massive core, different regions across the shock front, a dense clump, and ambient gas. Results. We find DN2H+ frac in the range 0.03-0.1, which is several orders of magnitude larger than the cosmic D/H ratio (∼10-5). The DN2H+ frac across the shock front is enhanced by more than a factor of 2 (DNfrac 2H+∼ 0.05-0.07) with respect to the ambient gas (=0.03) and similar to that measured generally in pre-stellar cores. Indeed, in the massive core and dense clump regions of this IRDC we measure DN2H+ frac ∼ 0.1.
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| 2. |
- Cevallos Soto, Arturo, 1993, et al.
(author)
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Inside-out planet formation - VII. Astrochemical models of protoplanetary discs and implications for planetary compositions
- 2022
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In: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 517:2, s. 2285-2308
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Journal article (peer-reviewed)abstract
- Inside-out planet formation (IOPF) proposes that the abundant systems of close-in Super-Earths and Mini-Neptunes form in situ at the pressure maximum associated with the dead zone inner boundary (DZIB). We present a model of physical and chemical evolution of protoplanetary disc midplanes that follows gas advection, radial drift of pebbles, and gas-grain chemistry to predict abundances from similar to 300 au down to the DZIB near 0.2 au. We consider typical disc properties relevant for IOPF, i.e. accretion rates 10(-9) < (m) over dot/(M-circle dot, yr(-1)) < 10(-8) and viscosity parameter alpha = 10(-)(4), and evolve for fiducial duration of 10(5) yr. For outer, cool disc regions, we find that C and up to 90 per cent of 0 nuclei start locked in CO and O-2 ice, which keeps abundances of CO2 and H2O one order of magnitude lower. Radial drift of icy pebbles is influential, with gas-phase abundances of volatiles enhanced up to two orders of magnitude at icelines, while the outer disc becomes depleted of dust. Discs with decreasing accretion rates gradually cool, which draws in icelines closer to the star. At less than or similar to 1 au, advective models yield water-rich gas with C/O ratios less than or similar to 0.1, which may be inherited by atmospheres of planets forming here via IOPF. For planetary interiors built by pebble accretion, IOPF predicts volatile-poor compositions. However, advectively enhanced volatile mass fractions of similar to 10 per cent can occur at the water iceline.
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| 3. |
- Entekhabi, N., et al.
(author)
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Astrochemical modelling of infrared dark clouds
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 662
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Journal article (peer-reviewed)abstract
- Context. Infrared dark clouds (IRDCs) are cold, dense regions of the interstellar medium (ISM) that are likely to represent the initial conditions for massive star and star cluster formation. It is thus important to study the physical and chemical conditions of IRDCs to provide constraints and inputs for theoretical models of these processes. Aims. We aim to determine the astrochemical conditions, especially the cosmic ray ionisation rate (CRIR) and chemical age, in different regions of the massive IRDC G28.37+00.07 by comparing observed abundances of multiple molecules and molecular ions with the predictions of astrochemical models. Methods. We have computed a series of single-zone, time-dependent, astrochemical models with a gas-grain network that systematically explores the parameter space of the density, temperature, CRIR, and visual extinction. We have also investigated the effects of choices of CO ice binding energy and temperatures achieved in the transient heating of grains when struck by cosmic rays. We selected ten positions across the IRDC that are known to have a variety of star formation activity. We utilised mid-infrared extinction maps and sub-millimetre (sub-mm) emission maps to measure the mass surface densities of these regions needed for abundance and volume density estimates. The sub-mm emission maps were also used to measure temperatures. We then used Instituto de Radioas-tromía Milimétrica (IRAM) 30 m observations of various tracers, especially C18O(1-0), H13CO+(1-0), HC18O+(1-0), and N2H+(1-0), to estimate column densities and thus abundances. Finally, we investigated the range of astrochemical conditions that are consistent with the observed abundances. Results. The typical physical conditions of the IRDC regions are nH ∼ 3 ×-104 to 105 cm-3 and T ∼ 10 to 15 K. Strong emission of H13CO+(1-0) and N2H+(1-0) is detected towards all the positions and these species are used to define relatively narrow velocity ranges of the IRDC regions, which are used for estimates of CO abundances, via C18O(1-0). We would like to note that CO depletion factors are estimated to be in the range fD ∼ 3 to 10. Using estimates of the abundances of CO, HCO+, and N2H+, we find consistency with astrochemical models that have relatively low CRIRs of ζ ∼ 10-18 to ∼10-17 s-1, with no evidence for systematic variation with the level of star formation activity. Astrochemical ages, which are defined with a reference to an initial condition of all H in H2, all C in CO, and all other species in atomic form, are found to be <1 Myr. We also explore the effects of using other detected species, that is HCN, HNC, HNCO, CH3OH, and H2CO, to constrain the models. These generally lead to implied conditions with higher levels of CRIRs and older chemical ages. Considering the observed fD versus nH relation of the ten positions, which we find to have relatively little scatter, we discuss potential ways in which the astrochemical models can match such a relation as a quasi-equilibrium limit valid at ages of at least a few free-fall times, that is 3;0.3 Myr, including the effect of CO envelope contamination, small variations in temperature history near 15 K, CO-ice binding energy uncertainties, and CR-induced desorption. We find general consistency with the data of ∼0.5 Myr-old models that have ζ ∼ 2-5-10-18 s-1 and CO abundances set by a balance of freeze-out with CR-induced desorption. Conclusions. We have constrained the astrochemical conditions in ten regions in a massive IRDC, finding evidence for relatively low values of CRIR compared to diffuse ISM levels. We have not seen clear evidence for variation in the CRIR with the level of star formation activity. We favour models that involve relatively low CRIRs (≲ 10-17 s-1) and relatively old chemical ages (≳ 3;0.3 Myr, i.e. 3;3tff). We discuss potential sources of systematic uncertainties in these results and the overall implications for IRDC evolutionary history and astrochemical models.
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| 4. |
- Hsu, Chia-Jung, 1991
(author)
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Chemodynamical Simulations of Star-Forming Molecular Clouds
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Stars are known to form from dense, dusty clumps and cores of molecular clouds. However, there is no consensus on a theory that can predict the rate of star formation, its clustering, and the conditions needed for massive stars to be born. A major challenge is how to observe and characterise the gas that is the fuel for star formation. One way is to take advantage of line emission from molecular species, a great variety of which have now been detected in the interstellar medium. However, interpreting the messages from these molecules necessitates an understanding and modeling of astrochemistry. In addition to this diagnostic power, astrochemistry is also expected to impact the physical evolution of the gas by influencing heating and cooling rates and controlling the degree of ionization, which mediates coupling to magnetic fields. To make progress in modeling the physical and chemical evolution of molecular clouds, we develop methods for chemodynamical simulations and carry out several studies combining magnetohydrodynamics (MHD) and astrochemistry. Our first investigation concerns the evolution of chemical abundances in massive pre-stellar cores, which are the initial conditions in some theories of massive star formation. A gas-phase chemical reaction network is applied to MHD simulations, with a focus on predicting the level of deuteration of key diagnostic species that are widely used in observational searches for such cores. We show how the abundances and kinematics of N2D+ and N2H+ can help disentangle the chemodynamical history of massive cores. Next we examine the formation of populations of cores from colliding and non-colliding giant molecular clouds (GMCs). We begin by carrying out high resolution MHD simulations to examine how core properties, especially the core mass function (CMF), are influenced by the dynamics of the GMCs. Synthetic observations of the simulated clouds are derived to enable a more direct comparison with observed CMFs. We then use a gas-grain chemical network to follow the evolution of key gas- and ice-phase species in these GMCs. One application is a study of the influence of the cosmic ray ionization rate on the abundances of CO, HCO+ and N2H+ in the colliding and non-colliding clouds and how observations of these species can help measure this key environmental property. Associated with the release of our astrochemical modeling tool, Naunet, we also discuss the computational performance of chemodynamical simulations and summarize methods to further improve their efficiency.
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| 5. |
- Hsu, Chia-Jung, 1991
(author)
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Chemodynamics in Star-Forming Molecular Clouds
- 2021
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Licentiate thesis (other academic/artistic)abstract
- Stars are fundamental building blocks of galaxies. However, the answers to many basic questions about their formation remain elusive. There is no consensus on a theory that can predict the rate of star formation, its clustering properties, and the conditions needed for massive stars to be born. Although stars are known to form from dense regions of molecular clouds, measuring the physical properties in such regions is an outstanding challenge. Astrochemistry is the crucial set of processes that control the chemical evolution of the universe. It is important for controlling physical evolution, e.g., by setting heating and cooling rates and ionization fractions, but also for allowing predictions to be made for the emission from key diagnostic species to probe interstellar processes, such as star formation. To reconstruct the three-dimensional structures of galaxies and their interstellar media, chemodynamics, which is the combination of hydrodynamics and chemistry, is necessary. In this thesis, chemodynamical simulations are applied to star-forming regions to follow their combined physical and chemical evolution and make predictions for observations. In particular a gas phase deuterium fractionation network is applied to massive prestellar core simulations. Various chemical model parameters are investigated to understand whether fast collapse of a turbulent, magnetised prestellar core can achieve the high levels of deuteration that are commonly observed in such systems. The structure, kinematics and dynamics of the core, as traced by the rotational transitions of the key diagnostic species of $\rm N_2D^+$, are investigated. Another astrochemical network, including gas-grain processes, is constructed for simulations of larger-scale, generally lower density molecular clouds and applied to a simulation of giant molecular cloud collisions. We also discuss the computational performance of our chemodynamical simulations and summarize some methods to improve their efficiency.
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| 6. |
- Hsu, Chia-Jung, 1991, et al.
(author)
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Deuterium Chemodynamics of Massive Pre-Stellar Cores
- 2021
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In: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 502:1, s. 1104-1127
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Journal article (peer-reviewed)abstract
- High levels of deuterium fractionation of $\rm N_2H^+$ (i.e., $\rm D_{frac}^{N_2H^+} = 0.1$) are often observed in pre-stellar cores (PSCs) and detection of $\rm N_2D^+$ is a promising method to identify elusive massive PSCs. However, the physical and chemical conditions required to reach such high levels of deuteration are still uncertain, as is the diagnostic utility of $\rm N_2H^+$ and $\rm N_2D^+$ observations of PSCs. We perform 3D magnetohydrodynamics simulations of a massive, turbulent, magnetised PSC, coupled with a sophisticated deuteration astrochemical network. Although the core has some magnetic/turbulent support, it collapses under gravity in about one freefall time, which marks the end of the simulations. Our fiducial model achieves relatively low $\rm D_{frac}^{N_2H^+} \sim0.002$ during this time. We then investigate effects of initial ortho-para ratio of $\rm H_2$ ($\rm OPR^{H_2}$), temperature, cosmic ray (CR) ionization rate, CO and N-species depletion factors and prior PSC chemical evolution. We find that high CR ionization rates and high depletion factors allow the simulated $\rm D_{frac}^{N_2H^+}$ and absolute abundances to match observational values within one freefall time. For $\rm OPR^{H_2}$, while a lower initial value helps the growth of $\rm D_{frac}^{N_2H^+}$, the spatial structure of deuteration is too widespread compared to observed systems. For an example model with elevated CR ionization rates and significant heavy element depletion, we then study the kinematic and dynamic properties of the core as traced by its $\rm N_2D^+$ emission. The core, undergoing quite rapid collapse, exhibits disturbed kinematics in its average velocity map. Still, because of magnetic support, the core often appears kinematically sub-virial based on its $\rm N_2D^+$ velocity dispersion.
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| 7. |
- Hsu, Chia-Jung, 1991, et al.
(author)
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GMC collisions as triggers of star formation – VIII. The core mass function
- 2023
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In: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 522:1, s. 700-720
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Journal article (peer-reviewed)abstract
- Compression in giant molecular cloud (GMC) collisions is a promising mechanism to trigger the formation of massive star clusters and OB associations. We simulate colliding and non-colliding magnetized GMCs and examine the properties of pre-stellar cores, selected from projected mass surface density maps, including after synthetic ALMA observations. We then examine core properties, including mass, size, density, velocity, velocity dispersion, temperature, and magnetic field strength. After 4 Myr, ∼1000 cores have formed in the GMC collision, and the high-mass end of the core mass function (CMF) can be fit by a power-law dN/dlogM ∝ M-α with α ≃ 0.7, i.e. relatively top heavy compared to a Salpeter mass function. Depending on how cores are identified, a break in the power law can appear around a few ×10 M☉. The non-colliding GMCs form fewer cores with a CMF with α ≃ 0.8–1.2, i.e. closer to the Salpeter index. We compare the properties of these CMFs to those of several observed samples of cores. Considering other properties, cores formed from colliding clouds are typically warmer, have more disturbed internal kinematics, and are more likely to be gravitational unbound, than cores formed from non-colliding GMCs. The dynamical state of the protocluster of cores formed in the GMC–GMC collision is intrinsically subvirial but can appear to be supervirial if the total mass measurement is affected by observations that miss mass on large scales or at low densities.
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| 8. |
- Huang, Kuan Wei, et al.
(author)
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Strong Gravitational Lensing Parameter Estimation with Vision Transformer
- 2023
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer Nature Switzerland. - 1611-3349 .- 0302-9743. ; 13801 LNCS, s. 143-153
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Conference paper (peer-reviewed)abstract
- Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant (H0 ) tension. The commonly used Markov chain Monte Carlo (MCMC) method has been too time-consuming to achieve this goal, yet recent work has shown that convolution neural networks (CNNs) can be an alternative with seven orders of magnitude improvement in speed. With 31,200 simulated strongly lensed quasar images, we explore the usage of Vision Transformer (ViT) for simulated strong gravitational lensing for the first time. We show that ViT could reach competitive results compared with CNNs, and is specifically good at some lensing parameters, including the most important mass-related parameters such as the center of lens θ1 and θ2, the ellipticities e1 and e2, and the radial power-law slope γ′. With this promising preliminary result, we believe the ViT (or attention-based) network architecture can be an important tool for strong lensing science for the next generation of surveys. The open source of our code and data is in https://github.com/kuanweih/strong_lensing_vit_resnet.
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| 9. |
- Xu, Duo, et al.
(author)
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Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds
- 2023
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In: Astrophysical Journal. - 1538-4357 .- 0004-637X. ; 950:2
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Journal article (peer-reviewed)abstract
- We introduce the state-of-the-art deep-learning denoising diffusion probabilistic model as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps. We adopt magnetohydrodynamic simulations with different global magnetic field strengths and large-scale dynamics, i.e., noncolliding and colliding GMCs. We train a diffusion model on both mass surface density maps and their corresponding mass-weighted number density maps from different viewing angles for all the simulations. We compare the diffusion model performance with a more traditional empirical two-component and three-component power-law fitting method and with a more traditional neural network machine-learning approach. We conclude that the diffusion model achieves an order-of-magnitude improvement on the accuracy of predicting number density compared to that by other methods. We apply the diffusion method to some example astronomical column density maps of Taurus and the infrared dark clouds G28.37+0.07 and G35.39-0.33 to produce maps of their mean volume densities.
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