As one of the most important elements in astronomy, iron abundance determinations need to be as accurate as possible. We investigate the accuracy of spectroscopic iron abundance analyses using arch ...

/pdf/non-lte-line-formation-of-fe-in-late-type-stars-iii-3d-non-4cdfn0e4sa.pdf

Non-LTE line formation of Fe in late-type stars – III. 3D non-LTE analysis of metal-poor stars

We derive a microscopic expression for a quantity μ that plays the role of chemical potential of active Brownian particles (ABPs) in a steady state in the absence of vortices. We show that μ consists of (i) an intrinsic chemical potential similar to passive systems, which depends on density and self-propulsion speed, but not on the external potential, (ii) the external potential, and (iii) a newly derived one-body swim potential due to the activity of the particles. Our simulations on ABPs show good agreement with our Fokker–Planck calculations, and confirm that is spatially constant for several inhomogeneous active fluids in their steady states in a planar geometry. Finally, we show that phase coexistence of ABPs with a planar interface satisfies not only mechanical but also diffusive equilibrium. The coexistence can be well-described by equating the bulk chemical potential and bulk pressure obtained from bulk simulations for systems with low activity but requires explicit evaluation of the interfacial contributions at high activity.

https://iopscience.iop.org/article/10.1088/1367-2630/aa9b4d/pdf

Chemical potential in active systems: predicting phase equilibrium from bulk equations of state?

In protoplanetary disks, CO$_2$ is solid ice beyond its snow line at $\sim 10 \rm AU$. Due to its high abundance, it contributes heavily to the collisional evolution in this region of the disk. For the first time, we carried out laboratory collision experiments with CO$_2$ ice particles and a CO$_2$-covered wall at a temperature of 80 K. Collision velocities varied between 0 - 2.5 m/s. Particle sizes were on the order of $\sim$ 100 $\mu$m. We find a threshold velocity between the sticking and the bouncing regime at 0.04 m/s. Particles with greater velocities but below 1 m/s bounce off the wall. For yet greater velocities, fragmentation occurs. We give analytical models for the coefficients of restitution and fragmentation strength consistent with the experimental data. Set in context, our data show that CO$_2$ ice and silicate dust resemble each other in the collisional behavior. Compared to water ice the sticking velocity is an order of magnitude smaller. One immediate consequence as example is that water ice particles mantled by CO$_2$ ice lose any "sticking advantage." In this case, preferential planetesimal growth attributed to the sticking properties of water ice will be limited to the region between the H$_2$O ice line and the CO$_2$ ice line.

Collisions of CO$_2$ Ice Grains in Planet Formation

We study data-driven representations for three-dimensional triangle meshes, which are one of the prevalent objects used to represent 3D geometry. Recent works have developed models that exploit the intrinsic geometry of manifolds and graphs, namely the Graph Neural Networks (GNNs) and its spectral variants, which learn from the local metric tensor via the Laplacian operator. Despite offering excellent sample complexity and built-in invariances, intrinsic geometry alone is invariant to isometric deformations, making it unsuitable for many applications. To overcome this limitation, we propose several upgrades to GNNs to leverage extrinsic differential geometry properties of three-dimensional surfaces, increasing its modeling power. In particular, we propose to exploit the Dirac operator, whose spectrum detects principal curvature directions - this is in stark contrast with the classical Laplace operator, which directly measures mean curvature. We coin the resulting models Surface Networks (SN). We prove that these models define shape representations that are stable to deformation and to discretization, and we demonstrate the efficiency and versatility of SNs on two challenging tasks: temporal prediction of mesh deformations under non-linear dynamics and generative models using a variational autoencoder framework with encoders/decoders given by SNs.

Surface Networks

. It is commonly accepted that the variations of Earth's orbit and obliquity control the timing of Pleistocene glacial–interglacial cycles. Evidence comes from power spectrum analysis of palaeoclimate records and from inspection of the timing of glacial and deglacial transitions. However, we do not know how tight this control is. Is it, for example, conceivable that random climatic fluctuations could cause a delay in deglaciation, bad enough to skip a full precession or obliquity cycle and subsequently modify the sequence of ice ages? To address this question, seven previously published conceptual models of ice ages are analysed by reference to the notion of generalised synchronisation. Insight is being gained by comparing the effects of the astronomical forcing with idealised forcings composed of only one or two periodic components. In general, the richness of the astronomical forcing allows for synchronisation over a wider range of parameters, compared to periodic forcing. Hence, glacial cycles may conceivably have remained paced by the astronomical forcing throughout the Pleistocene. However, all the models examined here show regimes of strong structural dependence on parameters. This means that small variations in parameters or random fluctuations may cause significant shifts in the succession of ice ages. Whether the actual system actually resides in such a regime depends on the amplitude of the effects associated with the astronomical forcing, which significantly differ across the different models studied here. The possibility of synchronisation on eccentricity is also discussed and it is shown that a high Rayleigh number on eccentricity, as recently found in observations, is no guarantee of reliable synchronisation.

/pdf/why-could-ice-ages-be-unpredictable-5euzpv7vm2.pdf

Why could ice ages be unpredictable

The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. S. 8

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The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. S. 8