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Related papers: An adiabatic approximation for grain alignment the…

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Conventional grain growth is rate-limited by the mobility of grain boundary. To describe similar phenomena limited by the mobility of other grain junctions, we have developed a general theory allowing for size-dependent mobility and its…

Materials Science · Physics 2017-08-16 Yanhao Dong , I-Wei Chen

Dust grains emit intrinsic polarized emission if they are elongated and aligned in the same direction. The direction of the grain alignment is determined by external forces, such as magnetic fields, radiation, and gas flow against the dust…

Earth and Planetary Astrophysics · Physics 2019-04-03 Akimasa Kataoka , Satoshi Okuzumi , Ryo Tazaki

We report a new and complete model of the beta Pictoris disk, which succeeds in accounting for both the surface brightness distribution, warp characteristics, the outer ``butterfly'' asymmetry as observed by HST/STIS in scattered light, as…

Astrophysics · Physics 2009-11-06 J. C. Augereau , R. P. Nelson , A. M. Lagrange , J. C. B. Papaloizou , D. Mouillet

The Planck mission detected a positive correlation between the intensity ($T$) and $B$-mode polarization of the Galactic thermal dust emission. The $TB$ correlation is a parity-odd signal, whose statistical mean vanishes in models with…

Astrophysics of Galaxies · Physics 2022-08-18 Zhiqi Huang

We present evolutionary calculations for the size and aromatization degree distributions of interstellar dust grains, driven by their destruction by radiation, collisions with gas particles, and shattering due to grain-grain collisions.…

Solar and Stellar Astrophysics · Physics 2016-12-07 M. S. Murga , S. A. Khoperskov , D. S. Wiebe

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner's generalized Dirichlet distribution (R.H. Lochner, A Generalized…

Mathematical Physics · Physics 2013-10-02 J. Bakosi , J. R. Ristorcelli

A detailed study of interstellar polarization efficiency toward molecular clouds is used to attempt discrimination between grain alignment mechanisms in dense regions of the ISM. Background field stars are used to probe polarization…

Astrophysics · Physics 2008-11-26 D. C. B. Whittet , J. H. Hough , A. Lazarian , Thiem Hoang

Observations of interstellar extinction and polarization indicate that the interstellar medium consists of aligned non-spherical dust grains which show variation in the interstellar extinction curve for wavelengths ranging from NIR to UV.…

Astrophysics · Physics 2009-09-15 Ranjan Gupta , Tadashi Mukai , D. B. Vaidya , Asoke K. Sen , Yasuhiko Okada

While most chemical reactions in the interstellar medium take place in the gas phase, those occurring on the surfaces of dust grains play an essential role. Chemical models based on rate equations including both gas phase and grain surface…

Astrophysics · Physics 2009-11-07 Azi Lipshtat , Ofer Biham

In neuroscience, the distribution of a decision time is modelled by means of a one-dimensional Fokker--Planck equation with time-dependent boundaries and space-time-dependent drift. Efficient approximation of the solution to this equation…

Numerical Analysis · Mathematics 2023-02-08 Udo Boehm , Sonja Cox , Gregor Gantner , Rob Stevenson

Interstellar abundance determinations from fits to X-ray absorption edges often rely on the incorrect assumption that scattering is insignificant and can be ignored. We show instead that scattering contributes significantly to the…

High Energy Astrophysical Phenomena · Physics 2016-02-05 John A. Hoffman , Bruce T. Draine

Dust is the usual minor component of the interstellar medium. Its dynamic role in the contraction of the diffuse gas into molecular clouds is commonly assumed to be negligible because of the small mass fraction, $f \simeq 0.01$. However, as…

Astrophysics of Galaxies · Physics 2020-11-11 V. V. Zhuravlev

We derive a version of the adiabatic theorem that is especially suited for applications in adiabatic quantum computation, where it is reasonable to assume that the adiabatic interpolation between the initial and final Hamiltonians is…

Quantum Physics · Physics 2009-10-21 D. A. Lidar , A. T. Rezakhani , A. Hamma

Shattering of dust grains in the interstellar medium is a viable mechanism of small grain production in galaxies. We examine the robustness or uncertainty in the theoretical predictions of shattering. We identify $P_1$ (the critical…

Astrophysics of Galaxies · Physics 2015-06-15 Hiroyuki Hirashita , Hiroshi Kobayashi

Dynamic shear banding under adiabatic conditions in a mesoscale polycrystalline aggregate is studied using a model of mesoscale dislocation mechanics and experiments. The model involves a length scale related to hardening induced by…

We present high resolution ($1024^3$) simulations of super-/hyper-sonic isothermal hydrodynamic turbulence inside an interstellar molecular cloud (resolving scales of typically 20 -- 100 AU), including a multi-disperse population of dust…

Astrophysics of Galaxies · Physics 2018-12-19 Lars Mattsson , Akshay Bhatnagar , Fred A. Gent , Beatriz Villarroel

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N coupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded…

Mathematical Physics · Physics 2013-03-05 J. Bakosi , J. R. Ristorcelli

We show that the growth rate of dust grains in cold molecular clouds is enhanced by the high degree of compressibility of a turbulent, dilute gas. By means of high resolution (10243) numerical simulations, we confirm the theory that the…

Astrophysics of Galaxies · Physics 2020-11-18 Xiang-Yu Li , Lars Mattsson

Grain growth by accretion of gas-phase metals is a common assumption in models of dust evolution, but in dense gas, where the timescale is short enough for accretion to be effective, material is accreted in the form of ice mantles rather…

Astrophysics of Galaxies · Physics 2021-01-20 F. D. Priestley , I. De Looze , M. J. Barlow

Neural networks are popular state-of-the-art models for many different tasks.They are often trained via back-propagation to find a value of the weights that correctly predicts the observed data. Although back-propagation has shown good…

Machine Learning · Statistics 2020-12-29 Simón Rodríguez Santana , Daniel Hernández-Lobato