Related papers: Efficient Simulations of Interstellar Gas-Grain Ch…
Cells can utilize chemical communication to exchange information and coordinate their behavior in the presence of noise. Communication can reduce noise to shape a collective response, or amplify noise to generate distinct phenotypic…
Artificial neural networks are used to fit a potential energy surface. We demonstrate the benefits of using not only energies, but also their first and second derivatives as training data for the neural network. This ensures smooth and…
In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while…
Observational evidence seems to indicate that the depletion of interstellar carbon into dust shows rather wide variations and that carbon undergoes rather rapid recycling in the interstellar medium (ISM). Small hydrocarbon grains are…
The development of computational models for the numerical simulation of chemically reacting flows operating in the turbulent regime requires the solution of partial differential equations that represent the balance of mass, linear momentum,…
The probability distribution describing the state of a Stochastic Reaction Network evolves according to the Chemical Master Equation (CME). It is common to estimated its solution using Monte Carlo methods such as the Stochastic Simulation…
We present numerical simulations of the hydrodynamical interactions that produce circumstellar shells. These simulations include several scenarios, such as wind-wind interaction and wind-ISM collisions. In our calculations we have taken…
Accurate simulations of molecules require high-level electronic-structure theory in combination with rigorous methods for approximating the quantum dynamics. Machine-learning approaches can significantly reduce the computational expense of…
Computational models of interstellar gas-grain chemistry have historically adopted a single dust-grain size of 0.1 micron, assumed to be representative of the size distribution present in the interstellar medium. Here, we investigate the…
The aim of this paper is to provide a new set of branching ratios for interstellar and planetary chemical networks based on a semi empirical model. We applied, instead of zero order theory (i.e. only the most exoergic decaying channel is…
Context. Interstellar dust particles, which represent 1% of the total mass, are recognized to be very powerful interstellar catalysts in star-forming regions. The presence of dust can have a strong impact on the chemical composition of…
Methane is typically thought to be formed in the solid state on the surface of cold interstellar icy grain mantles via the successive atomic hydrogenation of a carbon atom. In the current work we investigate the potential role of molecular…
During the evolution of diffuse clouds to molecular clouds, gas-phase molecules freeze out on surfaces of small dust particles to form ices. On dust surfaces, water is the main constituent of the icy mantle in which a complex chemistry is…
Artificial neural networks (NNs) are one of the most frequently used machine learning approaches to construct interatomic potentials and enable efficient large-scale atomistic simulations with almost ab initio accuracy. However, the…
Chemical reaction networks (CRNs) provide a convenient language for modelling a broad variety of biological systems. These models are commonly studied with respect to the time series they generate in deterministic or stochastic simulations.…
We present MULTIGRAIN, an algorithm for simulating multiple phases of small dust grains embedded in a gas, building on our earlier work in simulating two-phase mixtures of gas and dust in SPH (Laibe & Price 2012a,b; Price & Laibe 2015). The…
We investigate the roles of stochastic grain heating in the formation of complex organic molecules (COMs) in cold cores, where COMs have been detected. Two different types of grain-size distributions are used in the chemical models. The…
The $\mathrm{H}_2$ formation on grains is known to be sensitive to dust temperature, which is also known to fluctuate for small grain sizes due to photon absorption. We aim at exploring the consequences of simultaneous fluctuations of the…
Aims. Interstellar dust grains, because of their catalytic properties, are crucial to the formation of H2, the most abundant molecule in the Universe. The formation of molecular hydrogen strongly depends on the ability of H atoms to stick…
Methane is one of the simplest stable molecules that is both abundant and widely distributed across space. It is thought to have partial origin from interstellar molecular clouds, which are near the beginning of the star formation cycle.…