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Touch is a crucial sensing modality that provides rich information about object properties and interactions with the physical environment. Humans and robots both benefit from using touch to perceive and interact with the surrounding environment (Johansson and Flanagan, 2009; Li et al., 2020; Calandra et al., 2017). However, no existing systems provide rich, multi-modal digital touch-sensing capabilities through a hemispherical compliant embodiment. Here, we describe several conceptual and technological innovations to improve the digitization of touch. These advances are embodied in an artificial finger-shaped sensor with advanced sensing capabilities. Significantly, this fingertip contains high-resolution sensors (~8.3 million taxels) that respond to omnidirectional touch, capture multi-modal signals, and use on-device artificial intelligence to process the data in real time. Evaluations show that the artificial fingertip can resolve spatial features as small as 7 um, sense normal and shear forces with a resolution of 1.01 mN and 1.27 mN, respectively, perceive vibrations up to 10 kHz, sense heat, and even sense odor. Furthermore, it embeds an on-device AI neural network accelerator that acts as a peripheral nervous system on a robot and mimics the reflex arc found in humans. These results demonstrate the possibility of digitizing touch with superhuman performance. The implications are profound, and we anticipate potential applications in robotics (industrial, medical, agricultural, and consumer-level), virtual reality and telepresence, prosthetics, and e-commerce. Toward digitizing touch at scale, we open-source a modular platform to facilitate future research on the nature of touch., Comment: 28 pages

The merger of a black hole (BH) and a neutron star (NS) in most cases is expected to leave no material around the remnant BH; therefore, such events are often considered as sources of gravitational waves without electromagnetic counterparts. However, a bright counterpart can emerge if the NS is strongly magnetized, as its external magnetosphere can experience radiative shocks and magnetic reconnection during/after the merger. We use magnetohydrodynamic simulations in the dynamical spacetime of a merging BH-NS binary to investigate its magnetospheric dynamics. We find that the magnetosphere develops compressive waves that steepen into shocks. After swallowing the NS, the BH acquires a magnetosphere that quickly evolves into a split monopole configuration and then undergoes an exponential decay (balding), enabled by magnetic reconnection and also assisted by the ring-down of the remnant BH. This spinning BH drags the split monopole into rotation, forming a transient pulsar-like state. It emits a striped wind if the swallowed magnetic dipole moment is inclined to the spin axis. We predict two types of transients from this scenario: (1) a fast radio burst emitted by the shocks as they expand to large radii and (2) an X/gamma-ray burst emitted by the $e^\pm$ outflow heated by magnetic dissipation., Comment: 18 pages, 12 figures, submitted to ApJL

Merging supermassive black hole (SMBH) binaries will likely be surrounded by a circumbinary accretion disk. Close to merger, gravitational radiation-driven inspiral will happen on timescales faster than the effective viscous time at the disk cavity wall, leading to a decoupling of the inner binary dynamics from the surrounding gaseous environment. Here we perform the first simulation of this decoupling process from a magnetically arrested circumbinary accretion disk. In this regime, the central cavity is filled with very strong vertical magnetic flux, regulating accretion onto the binary. Our simulations identify three main stages of this process: (1) Large-scale magnetic flux loss prior to decoupling. (2) Rayleigh-Taylor-driven accretion streams onto the binary during and after decoupling, which can power magnetic tower-like outflows, resembling dual jets. (3) Post merger, the cavity wall becomes unstable and the magnetic flux trapped inside the cavity will get ejected in large coherent outbreak episodes with implications for potential multi-messenger transients to merging SMBH binaries., Comment: 9 pages, 4 figures

Supermassive binary black holes in galactic centers are potential multimessenger sources in gravitational waves and electromagnetic radiation. To find such objects, isolating unique electromagnetic signatures of their accretion flow is key. With the aid of three-dimensional general-relativistic magnetohydrodynamic (GRMHD) simulations that utilize an approximate, semi-analytic, super-imposed spacetime metric, we identify two such signatures for merging binaries. Both involve magnetic reconnection and are analogous to plasma processes observed in the solar corona. The first, like colliding flux tubes that can cause solar flares, involves colliding jets that form an extended reconnection layer, dissipating magnetic energy and causing the two jets to merge. The second, akin to coronal mass ejection events, involves the accretion of magnetic field lines onto both black holes; these magnetic fields then twist, inflate, and form a trailing current sheet, ultimately reconnecting and driving a hot outflow. We provide estimates for the associated electromagnetic emission for both processes, showing that they likely accelerate electrons to high energies and are promising candidates for continuous, stochastic, and/or quasi-periodic higher energy electromagnetic emission. We also show that the accretion flows around each black hole can display features associated with the magnetically arrested state. However, simulations with black hole spins misaligned with the orbital plane and simulations with larger Bondi radii saturate at lower values of horizon-penetrating magnetic flux than standard magnetically arrested disks, leading to weaker, intermittent jets due to feedback from the weak jets or equatorial flux tubes ejected by reconnecting field lines near the horizon., Comment: 21 pages, 8 Figures, Submitted to ApJL. Animations available at https://www.youtube.com/playlist?list=PL3pLmTeUPcqThCLYhkSrkEBOUutrnSJWq

A significant interest has emerged recently in assessing whether collimated and ultra-relativistic outflows can be produced by a long-lived remnant from a binary neutron-star (BNS) merger, with different approaches leading to different outcomes. To clarify some of the aspect of this process, we report the results of long-term (\ie $\sim~110\,{\rm ms}$) state-of-the-art general-relativistic magnetohydrodynamics simulations of the inspiral and merger of a BNS system of magnetized stars. We find that after $\sim~50\,{\rm ms}$ from the merger, an $\alpha$-$\Omega$~dynamo driven by the magnetorotational instability (MRI) sets-in in the densest regions of the disk and leads to the breakout of the magnetic-field lines from the accretion disk around the remnant. The breakout, which can be associated with the violation of the Parker-stability criterion, is responsible for the generation of a collimated, magnetically-driven outflow with only mildly relativistic velocities that is responsible for a violent eruption of electromagnetic energy. We provide evidence that this outflow is partly collimated via a Blandford-Payne mechanism driven by the open field lines anchored in the inner disk regions. Finally, by including or not the radiative transport via neutrinos, we determine the role they play in the launching of the collimated wind. In this way, we conclude that the mechanism of magnetic-field breakout we observe is robust and takes place even without neutrinos. Contrary to previous expectations, the inclusion of neutrinos absorption and emission leads to a smaller baryon pollution in polar regions, and hence accelerates the occurrence of the breakout, yielding a larger electromagnetic luminosity. Given the mildly relativistic nature of these disk-driven breakout outflows, it is difficult to consider them responsible for the jet phenomenology observed in short gamma-ray bursts.

Black hole - neutron star $(BH/NS)$ binaries are of interest in many ways: they are intrinsically multi-messenger systems, highly transient, radiate gravitational waves detectable by LIGO, and may produce $\gamma$-ray bursts. Although it has long been assumed that their late-stage orbital evolution is driven entirely by gravitational wave emission, we show here that in certain circumstances, mass transfer from the neutron star onto the black hole can both alter the binary's orbital evolution and significantly reduce the neutron star's mass when the fraction of its mass transferred per orbit is $\gtrsim 10^{-2}$, the neutron star's mass diminishes by order-unity, leading to mergers in which the neutron star mass is exceptionally small. The mass transfer creates a gas disk around the black hole ${\it before}$ merger that can be comparable in mass to the debris remaining after merger, i.e. $\sim 0.1 M_\odot$. These processes are most important when the initial neutron star/black hole mass ratio $q$ is in the range $\approx 0.2 - 0.8$, the orbital semimajor axis is $40 \lesssim a_0/r_g \lesssim 300 $ ($r_g \equiv GM_{\rm B}/c^2$), and the eccentricity is large, $e_0 \gtrsim 0.8$. Systems of this sort may be generated through the dynamical evolution of a triple system, as well as by other means., Comment: Accepted for Publication in ApJ

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement (AMR) framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic (SR), and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers we describe (1) a new solver for the Einstein equations based on the Z4c formalism and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging ARM processors. AthenaK shows excellent performance and weak scaling, achieving over one billion cell updates per second for hydrodynamics in three-dimensions on a single NVIDIA Grace Hopper processor and with a typical parallel efficiency of 80% on 65536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics., Comment: Submitted to ApJS

The dynamics of a black hole traveling through a plasma -- a general relativistic extension of the classic Bondi-Hoyle-Lyttleton (BHL) accretion problem -- can be related to a variety of astrophysical contexts, including the aftermath of binary black hole mergers in gaseous environments. We perform three-dimensional general relativistic magnetohydrodynamics simulations of BHL accretion onto a rotating black hole for an incoming flow with a toroidal (inclined) magnetization with respect to the spin axis of the black hole. Irrespective of inclination but dependent on the wind speed, we find that the accretion flow onto the black hole can become magnetically arrested, launching an intermittent (and sometimes striped) jet. The upstream ram pressure of the wind bends the jet, and confines the angular extent into which the magnetic flux tubes ejected from quasi-periodic eruptions are released. Recoil from magnetic flux eruptions drives strong oscillations in the accretion plane, resulting in jet nutation at the outer radii and occasionally ripping off the inner part of the accretion disk. In addition to dynamical friction, the black hole experiences a perpendicular drag force analogous to the Magnus effect. Qualitative effects of the incoming magnetic field orientation, the strength of the magnetization, and the incoming wind speed are investigated as well., Comment: 25 pages, 15 figures

The merger of two neutron stars probes dense matter in a hot, neutrino-trapped regime. In this work, we investigate how fully accounting for pions, muons, and muon-type neutrinos in the trapped regime may affect the outcome of the merger. By performing fully general-relativistic hydrodynamics simulations of merging neutron stars with equations of state to which we systematically add those different particle species, we aim to provide a detailed assessment of the impact of muons and pions on the merger and post-merger phase. In particular, we investigate the merger thermodynamics, mass ejection and gravitational wave emission. Our findings are consistent with previous expectations, that the inclusion of such microphysical degrees of freedom and finite temperature corrections leads to frequency shifts on the order of 100-200 Hz in the post-merger gravitational wave signal, relative to a fiducial cold nucleonic equation of state model., Comment: 25 pages, 14 figures, submitted to PRD

In real case applications within the virtual prototyping process, it is not always possible to reduce the complexity of the physical models and to obtain numerical models which can be solved quickly. Usually, every single numerical simulation takes hours or even days. Although the progresses in numerical methods and high performance computing, in such cases, it is not possible to explore various model configurations, hence efficient surrogate models are required. Generally the available meta-model techniques show several advantages and disadvantages depending on the investigated problem. In this paper we present an automatic approach for the selection of the optimal suitable meta-model for the actual problem. Together with an automatic reduction of the variable space using advanced filter techniques an efficient approximation is enabled also for high dimensional problems., Comment: presented at 7th Optimization and Stochastic Days, Weimar, Germany, 21-22 October, 2010

Within the calibration of material models, often the numerical results of a simulation model $y$ are compared with the experimental measurements $y^*$. Usually, the differences between measurements and simulation are minimized using least squares approaches including global and local optimization techniques. In this paper, the resulting scatter or uncertainty of the identified material parameters p are investigated by assuming the measurement curves as non-deterministic. Based on classical probabilistic approaches as the Markov estimator or the Bayesian updating procedure, the scatter of the identified parameters can be estimated as a multi-variate probability density function. Both procedures require a sufficient accurate knowledge or estimate of the scatter of the measurement points, often modeled by a Gaussian covariance matrix. In this paper, we present a different idea by assuming the scatter of the measurements not as correlated random numbers but just as individual intervals with known minimum and maximum values. The corresponding possible minimum and maximum values for each input parameter can be obtained for this assumption using a constrained optimization approach. However, the identification of the whole possible parameter domain for the given measurement bounds is not straight forward. Therefore, we introduce an efficient line-search method, where not only the bounds itself but also the shape of the feasible parameter domain can be identified. This enables the quantification of the interaction and the uniqueness of the input parameters. As a numerical example, we identify the fracture parameters of plain concrete with respect to a wedge splitting test, where five unknown material parameters could be identified., Comment: presented at the NAFEMS DACH conference, Bamberg, Germany, 10-12 June 2024

In this paper, a Monte Carlo based approach for the quantification of the importance of the scattering input parameters with respect to the failure probability is presented. Using the basic idea of the alpha-factors of the First Order Reliability Method, this approach was developed to analyze correlated input variables as well as arbitrary marginal parameter distributions. Based on an efficient transformation scheme using the importance sampling principle, only a single analysis run by a plain or variance-reduced Monte Carlo method is required to give a sufficient estimate of the introduced parameter sensitivities. Several application examples are presented and discussed in the paper., Comment: presented at the 14th International Conference on Applications of Statistics and Probability in Civil Engineering, Dublin, Ireland, 9-13 July, 2023

In this study the common least-squares minimization approach is compared to the Bayesian updating procedure. In the content of material parameter identification the posterior parameter density function is obtained from its prior and the likelihood function of the measurements. By using Markov Chain Monte Carlo methods, such as the Metropolis-Hastings algorithm \cite{Hastings1970}, the global density function including local peaks can be computed. Thus this procedure enables an accurate evaluation of the global parameter quality. However, the computational effort is remarkable larger compared to the minimization approach. Thus several methodologies for an efficient approximation of the likelihood function are discussed in the present study., Comment: presented at 15th working conference IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems, Munich, April 7-10, 2010

In this paper we propose an extension of the classical Sobol' estimator for the estimation of variance based sensitivity indices. The approach assumes a linear correlation model between the input variables which is used to decompose the contribution of an input variable into a correlated and an uncorrelated part. This method provides sampling matrices following the original joint probability distribution which are used directly to compute the model output without any assumptions or approximations of the model response function., Comment: presented at 5th International Conference on Reliable Engineering Computing (REC), Brno, Czech Republic, 13-15 June, 2012

In this paper the accuracy and robustness of quality measures for the assessment of machine learning models are investigated. The prediction quality of a machine learning model is evaluated model-independent based on a cross-validation approach, where the approximation error is estimated for unknown data. The presented measures quantify the amount of explained variation in the model prediction. The reliability of these measures is assessed by means of several numerical examples, where an additional data set for the verification of the estimated prediction error is available. Furthermore, the confidence bounds of the presented quality measures are estimated and local quality measures are derived from the prediction residuals obtained by the cross-validation approach., Comment: accepted for publication in Engineering Modelling, Analysis & Simulation (EMAS)

Antennas are more prevalent than ever enabling 5G connectivity for wide ranging applications like cellular communication, IoT, autonomous vehicles, etc. Optimizing an antenna design can be challenging and employing traditional optimization techniques oftentimes require evaluating ~100s of design variations, which is time prohibitive to tight design deadlines. Instead, the common optimization approach relies on engineering expertise and solving only a handful design variations to manually determine a design with good-enough performance. Here, we present a novel approach for antenna optimization, which utilizes analytical derivatives calculated by Ansys HFSS to dramatically reduce the number of necessary simulation runs. In the presented approach a local updating scheme, which converges quickly to the next local optimum, is extended to a global search strategy intended to detect several local and global optima. This global search procedure uses a consistent interpolation model to approximate the simulation model outputs and its derivatives depending on the design parameters values. The presented approach is implemented in an optimization workflow, which automatically interacts with the HFSS simulation model. Since this optimizer relies on the analytical derivatives calculated by HFSS, it is applicable to any design optimization where geometry or material properties are varied, and the device response is described by SYZ-parameters or far-field quantities. The usability of this new optimizer is therefore wide ranging from antenna design to signal integrity applications., Comment: presented at the NAFEMS DACH Conference, Bamberg, Germany, 4-6 October, 2022

In real case applications within the virtual prototyping process, it is not always possible to reduce the complexity of the physical models and to obtain numerical models which can be solved quickly. Usually, every single numerical simulation takes hours or even days. Although the progresses in numerical methods and high performance computing, in such cases, it is not possible to explore various model configurations, hence efficient surrogate models are required. Generally the available meta-model techniques show several advantages and disadvantages depending on the investigated problem. In this paper we present an automatic approach for the selection of the optimal suitable meta-model for the actual problem. Together with an automatic reduction of the variable space using advanced filter techniques an efficient approximation is enabled also for high dimensional problems. This filter techniques enable a reduction of the high dimensional variable space to a much smaller subspace where meta-model-based sensitivity analyses are carried out to assess the influence of important variables and to identify the optimal subspace with corresponding surrogate model which enables the most accurate probabilistic analysis. For this purpose we investigate variance-based and moment-free sensitivity measures in combination with advanced meta-models as moving least squares and kriging., Comment: presented at 8th Optimization and Stochastic Days, Weimar, Germany, 24-25 November, 2011

Binary systems with comparable masses and a surrounding accretion disk can accrete gas through spiral accretion streams penetrating the central cavity formed by tidal interactions. Using three-dimensional Newtonian magnetohydrodynamics simulations, we investigate the possibility of a magnetically arrested accretion flow through the cavity. Rather than solely continuously feeding the binary through spiral accretion streams, the accretion is regulated by the strong magnetic field inside the cavity. Transport of mass and angular momentum onto the binary then proceeds largely periodically in magnetic flux eruption episodes. The ejected flux tubes carry angular momentum outwards and away from the binary, inject hot plasma into the disk and can launch flares. This likely intermittent scenario could have potential implications for the emission signatures of supermassive black hole binaries, and shed light onto the role magnetic fields play in the binary's orbital evolution., Comment: 13 pages, 6 figures, accepted version to appear in ApJL

Neutron stars have solid crusts threaded by strong magnetic fields. Perturbations in the crust can excite non-radial oscillations, which can in turn launch Alfven waves into the magnetosphere. In the case of a compact binary close to merger involving at least one neutron star, this can happen through tidal interactions causing resonant excitations that shatter the neutron star crust. We present the first numerical study that elucidates the dynamics of Alfven waves launched in a compact binary magnetosphere. We seed a magnetic field perturbation on the neutron star crust, which we then evolve in fully general-relativistic force-free electrodynamics using a GPU-based implementation. We show that Alfven waves steepen nonlinearly before reaching the orbital light cylinder, form flares, and dissipate energy in a transient current sheet. Our results predict radio and X-ray precursor emission from this process., Comment: 16 pages, 6 figures, version accepted by ApJL, changed title to match published version

We present a discontinuous Galerkin-finite difference hybrid scheme that allows high-order shock capturing with the discontinuous Galerkin method for general relativistic magnetohydrodynamics in dynamical spacetimes. We present several optimizations and stability improvements to our algorithm that allow the hybrid method to successfully simulate single, rotating, and binary neutron stars. The hybrid method achieves the efficiency of discontinuous Galerkin methods throughout almost the entire spacetime during the inspiral phase, while being able to robustly capture shocks and resolve the stellar surfaces. We also use Cauchy-Characteristic evolution to compute the first gravitational waveforms at future null infinity from binary neutron star mergers. The simulations presented here are the first successful binary neutron star inspiral and merger simulations using discontinuous Galerkin methods., Comment: 31 pages, 8 figures, minor wording updates

Black holes threaded by massive vector fields can be subject to a superradiant instability, growing a cloud of massive vector particles around it. In this work, we consider what happens if such a dark matter candidate field mimicking a dark photon interacts with an accretion flow onto the black hole. By including a kinetic mixing term with the standard model photon, we extend the commonly used equations of general-relativistic magnetohydrodynamics to a dark photon constituent. The coupling to the dark photon then appears as an effective dynamo term together with a dark Lorentz force acting on the accreting matter. We numerically study the interactions between the superradiant dark photon cloud and the inner accretion flow by solving the coupled system in full numerical relativity. By parameterically varying the mixing parameter between dark and standard model sector, we provide a first investigation of how the accretion flow could be modified. Depending on the coupling strength, our solutions exhibit increased wind launching, as well as oscillation modes in the disk.

Dynamo processes are ubiquitous in astrophysical systems. In relativistic astrophysical systems, such as accretion disks around black holes or neutron stars, they may critically affect the launching of winds and jets that can power electromagnetic emission. Dynamo processes are governed by several microscopic parameters, one of them being magnetic helicity. As a conserved quantity in nonresistive plasmas, magnetic helicity is transported across the system. One important implication of helicity conservation is, that in the absence of helicity fluxes some mean-field dynamos can be quenched, potentially affecting the large-scale evolution of the magnetic field. One of the major challenges in computing magnetic helicity is the need to fix a meaningful electromagnetic gauge. We here present a fully covariant formulation of magnetic helicity transport in general-relativistic plasmas based on the concept of relative helicity by Berger & Field and Finn & Antonsen. This formulation is separately invariant under gauge-transformation of the Maxwell and Einstein equations. As an application of this new formalism we present the first analysis of magnetic helicity transport in the merger of two neutron stars. We demonstrate the presence of global helicity fluxes into the outer layers of the stellar merger remnant, which may impact subsequent large-scale dynamo amplification in these regions., Comment: 14 pages, 4 figures

Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming process, preventing its further spread can be aided by creating machine-based forecasts. Machine learning and Explainable AI are crucial in classification as they not only provide accurate predictions but also offer insights into how the model arrives at its decisions, aiding in the understanding and trustworthiness of the classification results. In this study, we evaluate and compare the classification accuracy, precision, recall, and F-1 scores of five different machine learning methods using a primary dataset (500 patients from Dhaka Medical College Hospital). Five different supervised machine learning techniques, including decision tree, random forest, logistic regression, naive bayes, and XGBoost, have been used to achieve optimal results on our dataset. Additionally, this study applied SHAP analysis to the XGBoost model to interpret the model's predictions and understand the impact of each feature on the model's output. We compared the accuracy with which several algorithms classified the data, as well as contrasted with other literature in this field. After final evaluation, this study found that XGBoost achieved the best model accuracy, which is 97%., Comment: Accepted for the Scientific Reports (Nature) journal. 32 pages, 12 figures

General Effect Modelling (GEM) is an umbrella over different methods that utilise effects in the analyses of data with multiple design variables and multivariate responses. To demonstrate the methodology, we here use GEM in gene expression data where we use GEM to combine data from different cohorts and apply multivariate analysis of the effects of the targeted disease across the cohorts. Omics data are by nature multivariate, yet univariate analysis is the dominating approach used for such data. A major challenge in omics data is that the number of features such as genes, proteins and metabolites are often very large, whereas the number of samples is limited. Furthermore, omics research aims to obtain results that are generically valid across different backgrounds. The present publication applies GEM to address these aspects. First, we emphasise the benefit of multivariate analysis for multivariate data. Then we illustrate the use of GEM to combine data from two different cohorts for multivariate analysis across the cohorts, and we highlight that multivariate analysis can detect information that is lost by univariate validation., Comment: 12 pages

In this work we provide a new, well-controlled expansion of the equation of state of dense matter from zero to finite temperatures ($T$), while covering a wide range of charge fractions ($Y_Q$), from pure neutron to isospin symmetric nuclear matter. Our expansion can be used to describe neutron star mergers and core-collapse supernova explosions using as a starting point neutron star observations, while maintaining agreement with laboratory data, in a model independent way. We suggest new thermodynamic quantities of interest that can be calculated from theoretical models or directly inferred by experimental data that can help constrain the finite $T$ equation of state. With our new method, we can quantify the uncertainty in our finite $T$ and $Y_Q$ expansions in a well-controlled manner without making assumptions about the underlying degrees of freedom. We can reproduce results from a microscopic equation of state up to $T=100$ MeV for baryon chemical potential $\mu_B\gtrsim 1100$ MeV ($\sim1-2 \ n_{\rm sat}$) within $5\%$ error, with even better results for larger $\mu_B$ and/or lower $T$. We investigate the sources of numerical and theoretical uncertainty and discuss future directions of study., Comment: 33 pages, 12 figures

Relativistic plasmas around compact objects can sometimes be approximated as being force-free. In this limit, the plasma inertia is negligible and the overall dynamics is governed by global electric currents. We present a novel numerical approach for simulating such force-free plasmas, which allows for high accuracy in smooth regions as well as capturing dissipation in current sheets. Using a high-order accurate discontinuous Galerkin method augmented with a conservative finite-difference method, we demonstrate efficient global simulations of black hole and neutron star magnetospheres. In addition to a series of challenging test problems, we show that our approach can-depending on the physical properties of the system and the numerical implementation-be up to 10x more efficient than conventional simulations, with a speedup of 2-3x for most problems we consider in practice., Comment: 22 pages, 13 figures

We perform the first magnetohydrodynamic simulation tracking the magnetosphere of a collapsing magnetar. The collapse is expected for massive rotating magnetars formed in merger events, and may occur many hours after the merger. Our simulation suggests a novel mechanism for a gamma-ray burst (GRB) which is uncollimated and forms a delayed high-energy counterpart of the merger gravitational waves. The simulation shows that the collapse launches an outgoing magnetospheric shock, and a hot magnetized outflow forms behind the shock. The outflow is baryon-free and uncollimated, and its power peaks on a millisecond timescale. Then, the outflow becomes modulated by the ring-down of the nascent black hole, imprinting its kilohertz quasi-normal modes on the GRB tail., Comment: 9 pages, 4 figures; accepted version; to appear in ApJL

Vision-based tactile sensors have recently become popular due to their combination of low cost, very high spatial resolution, and ease of integration using widely available miniature cameras. The associated field of view and focal length, however, are difficult to package in a human-sized finger. In this paper we employ optical fiber bundles to achieve a form factor that, at 15 mm diameter, is smaller than an average human fingertip. The electronics and camera are also located remotely, further reducing package size. The sensor achieves a spatial resolution of 0.22 mm and a minimum force resolution 5 mN for normal and shear contact forces. With these attributes, the DIGIT Pinki sensor is suitable for applications such as robotic and teleoperated digital palpation. We demonstrate its utility for palpation of the prostate gland and show that it can achieve clinically relevant discrimination of prostate stiffness for phantom and ex vivo tissue., Comment: This work has been submitted to the IEEE for possible publication. The CAD design files of DIGIT Pinki are available at https://github.com/facebookresearch/digit-design

We investigate the impact of a mean field model for the $\alpha\Omega$-dynamo potentially active in the post-merger phase of a binary neutron star coalescence. We do so by deriving equations for ideal general relativistic magnetohydrodynamics (GRMHD) with an additional $\alpha-$term, which closely resemble their Newtonian counterpart, but remain compatible with standard numerical relativity simulations. We propose a heuristic dynamo closure relation for the magnetorotational instability-driven turbulent dynamo in the outer layers of a differentially rotating magnetar remnant and its accretion disk. As a first demonstration, we apply this framework to the early stages of post-merger evolution ($\lesssim 50\, \rm ms$). We demonstrate that depending on the efficacy of the dynamo action, magnetically driven outflows can be present with their amount of baryon loading correlating with the magnetic field amplification. These outflows can also contain precursor flaring episodes before settling into a quasi-steady state. For the dynamo parameters explored in this work, we observe electromagnetic energy fluxes of up to $10^{50}\, \rm erg/s$, although larger amplification parameters will likely lead to stronger fluxes. Our results are consistent with the expectation that substantial dynamo amplification (either during or after the merger) may be necessary for neutron-star remnants to power short gamma-ray bursts or precursors thereof., Comment: 14 pages, 12 figures