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Reliable predictions of the etch rate profile are desirable in semiconductor manufacturing to prevent etch rate target misses and yield rate excursions. Conventional methods for analyzing etch rate require extensive metrology, which adds considerable costs to manufacturing. We demonstrate a data-driven method to predict the etch rate profiles of a capacitively-coupled plasma RIE etcher from the tool's sensor data. The model employs a hybrid autoencoder-multiquadric interpolation-based approach, with the autoencoder being used to encode the features of the wafers' etch rate profiles into a latent space representation. The tool's sensor data is then used to construct interpolation maps for the latent space variables using multiquadric radial basis functions, which are then used to generate synthetic wafer etch rate profiles using the decoder. The accuracy of the model is determined using experimental data, and the errors are analyzed in interpolation and extrapolation., Comment: 6 pages, 9 figures

Binary neutron star mergers are among the most energetic events in our Universe, with magnetic fields significantly impacting their dynamics, particularly after the merger. While numerical-relativity simulations that correctly describe the physics are essential to model their rich phenomenology, the inclusion of magnetic fields is crucial for realistic simulations. For this reason, we have extended the BAM code to enable general relativistic magneto-hydrodynamic (GRMHD) simulations employing a hyperbolic `divergence cleaning' scheme. We present a large set of standard GRMHD tests and compare the BAM code to other GRMHD codes, SPRITZ, GRaM-X, and SACRA$_{\rm KK22}$, which employ different schemes for the evolution of the magnetic fields. Overall, we find that the BAM code shows a good performance in simple special-relativistic tests. In addition, we find good agreement and consistent results when comparing GRMHD simulation results between BAM and SACRA$_{\rm KK22}$., Comment: 21 pages, 21 figures

Accurate modeling of the multi-messenger signatures connected to binary neutron star mergers requires proper knowledge on the final remnant's fate and the conditions under which black holes (BHs) can form in such mergers. In this article, we use a suite of 84 numerical-relativity simulations in 28 different physical setups to explore the impact of the individual stars' spin on the merger outcome and on the early postmerger dynamics. We find that for setups close to the prompt-collapse threshold, the stars' intrinsic spin significantly changes the lifespan of the remnant before collapse and that the mass of the debris disk surrounding the BH is also altered. To enable a better understanding of BH formation, we check if there is at least a theoretical chance of observing densities that are above the maximum density allowed in a stable isolated neutron star, and we investigate the importance of different pressure contributions on the evolution of the postmerger remnant and BH formation.

GW170817 and its associated electromagnetic counterpart AT2017gfo continue to be a treasure trove as observations and modeling continue. Recent precision astrometry of AT2017gfo with the Hubble Space Telescope combined with previous constraints from Very Long Baseline Interferometry (VLBI) constraints narrowed down the inclination angle to 19-25 deg (90\% confidence). This paper explores how the inclusion of precise inclination information can reveal new insights about the ejecta properties, in particular, about the composition of the dynamical ejecta of AT2017gfo. Our analysis relies on updated kilonova modeling, which includes state-of-the-art heating rates, thermalization efficiencies, and opacities and is parameterized by $\bar{Y}_{\rm e,dyn}$, the average electron fraction of the dynamical ejecta component. Using this model, we incorporate the latest inclination angle constraint of AT2017gfo into a light curve fitting framework to derive updated parameter estimates. Our results suggest that the viewing angle of the observer is pointed towards the lanthanide-poor ($Y_{\rm e,dyn}\gtrsim0.25$), squeezed polar dynamical ejecta component, which can explain the early blue emission observed in the light curve of AT2017gfo. In contrast to a recent claim of spherical ejecta powering AT2017gfo, our study indicates that the composition of the dynamical ejecta has a strong angular dependence, with a lanthanide-rich ($Y_{\rm e,dyn}\lesssim0.25$), tidal component distributed around the merger plane with a half-opening angle of $35^\circ$. The inclination angle constraint reduces $\bar{Y}_{\rm e,dyn}$ from $0.24$ to $0.22$, with values $0.17\lesssim Y_{\rm e, dyn} \lesssim0.41$ enabling the robust production of $r$-process elements up to the $3^{\rm rd}$ peak in the tidal dynamical ejecta., Comment: 8 pages, 6 figures

Neutrino interactions are essential for an accurate understanding of the binary neutron star merger process. In this article, we extend the code infrastructure of the well-established numerical-relativity code BAM that until recently neglected neutrino-driven interactions. In fact, while previous work allowed already the usage of nuclear-tabulated equations of state and employing a neutrino leakage scheme, we are moving forward by implementing a first-order multipolar radiation transport scheme (M1) for the advection of neutrinos. After testing our implementation on a set of standard scenarios, we apply it to the evolution of four low-mass binary systems, and we perform an analysis of ejecta properties. We also show that our new ejecta analysis infrastructure is able to provide numerical relativity-informed inputs for the codes $\texttt{POSSIS}$ and $\texttt{Skynet}$, for the computation of kilonova lightcurves and nucleosynthesis yields, respectively., Comment: 29 pages, 27 figures

Over the last few years, there has been an increasing interest in sub-solar mass black holes due to their potential to provide valuable information about cosmology or the black hole population. Motivated by this, we study observable phenomena connected to the merger of a sub-solar mass black hole with a neutron star. For this purpose, we perform new numerical-relativity simulations of a binary system composed of a black hole with mass $0.5M_\odot$ and a neutron star with mass $1.4 M_\odot$. We investigate the merger dynamics of this exotic system and provide information about the connected gravitational-wave and kilonova signals. Our study indicates that current gravitational-waveform models are unable to adequately describe such systems and that phenomenological relations connecting the binary parameters with the ejecta and remnant properties are not applicable to our system. Furthermore, we find a dependence of the kilonova signal on the azimuthal viewing angle due to the asymmetric mass ejection. This first-of-its-kind simulation opens the door for the study of sub-solar mass black hole - neutron star mergers and could serve as a testing ground for future model development., Comment: 16 pages, 14 figures, to be submitted to PRD, comments welcome

Accurate numerical-relativity simulations are essential to study the rich phenomenology of binary neutron star systems. In this work, we focus on the material that is dynamically ejected during the merger process and on the kilonova transient it produces. Typically, radiative transfer simulations of kilonova light curves from ejecta make the assumption of homologous expansion, but this condition might not always be met at the end of usually very short numerical-relativity simulations. In this article, we adjust the infrastructure of the BAM code to enable longer simulations of the dynamical ejecta with the aim of investigating when the condition of homologous expansion is satisfied. In fact, we observe that the deviations from a perfect homologous expansion are about 30% at roughly 100ms after the merger. To determine how these deviations might affect the calculation of kilonova light curves, we extract the ejecta data for different reference times and use them as input for radiative transfer simulations. Our results show that the light curves for extraction times later than 80ms after the merger deviate by less than 0.4mag and are mostly consistent with numerical noise. Accordingly, deviations from the homologous expansion for the dynamical ejecta component are negligible for the purpose of kilonova modelling.

Advective trapping occurs when solute enters low velocity zones in heterogeneous porous media. Classical local modeling approaches combine the impact of slow advection and diffusion into a hydrodynamic dispersion coefficient and many temporally non-local approaches lump these mechanisms into a single memory function. This joint treatment makes parameterization difficult and thus prediction of large scale transport a challenge. Here we investigate the mechanisms of advective trapping and their impact on transport in media composed of a high conductivity background and isolated low permeability inclusions. Breakthrough curves show that effective transport changes from a streamtube-like behavior to genuine random trapping as the degree of disorder of the inclusion arrangement increases. We upscale this behavior using a Lagrangian view point, in which idealized solute particles transition over a fixed distance at random advection times combined with Poissonian advective trapping events. We discuss the mathematical formulation of the upscaled model in the continuous time random walk and mobile-immobile mass transfer frameworks, and derive a model for large scale solute non-Fickian dispersion. These findings give new insight into transport in highly heterogeneous media.

We study modeling of two-phase flow in highly heterogeneous fractured and porous media. The flow behaviour is strongly influenced by mass transfer between a highly permeable (mobile) fracture domain and less permeable (immobile) matrix blocks. We quantify the effective two-phase flow behaviour using a multirate rate mass transfer (MRMT) approach. We discuss the range of applicability of the MRMT approach in terms of the pertinent viscous and capillary diffusion time scales. We scrutinize the linearization of capillary diffusion in the immobile regions, which allows for the formulation of MRMT in the form of a non-local single equation model. The global memory function, which encodes mass transfer between the mobile and the immobile regions, is at the center of this method. We propose two methods to estimate the global memory function for a fracture network with given fracture and matrix geometry. Both employ a scaling approach based on the known local memory function for a given immobile region. With the first method, the local memory function is calculated numerically, while the second one employs a parametric memory function in form of truncated power-law. The developed concepts are applied and tested for fracture networks of different complexity. We find that both physically based parameter estimation methods for the global memory function provide predictive MRMT approaches for the description of multiphase flow in highly heterogeneous porous media.