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This work presents Mamba Imitation Learning (MaIL), a novel imitation learning (IL) architecture that provides an alternative to state-of-the-art (SoTA) Transformer-based policies. MaIL leverages Mamba, a state-space model designed to selectively focus on key features of the data. While Transformers are highly effective in data-rich environments due to their dense attention mechanisms, they can struggle with smaller datasets, often leading to overfitting or suboptimal representation learning. In contrast, Mamba's architecture enhances representation learning efficiency by focusing on key features and reducing model complexity. This approach mitigates overfitting and enhances generalization, even when working with limited data. Extensive evaluations on the LIBERO benchmark demonstrate that MaIL consistently outperforms Transformers on all LIBERO tasks with limited data and matches their performance when the full dataset is available. Additionally, MaIL's effectiveness is validated through its superior performance in three real robot experiments. Our code is available at https://github.com/ALRhub/MaIL.

Column chromatography is a laboratory and industrial technique used to separate different substances mixed in a solution. Mathematically, it can be modelled using non-linear partial differential equations whose main ingredients are the adsorption isotherms, which are non-linear functions modelling the affinity between the different substances in the solution and the solid stationary phase filling the column. The goal of this work is twofold. Firstly, we aim to extend the techniques of Donat, Guerrero and Mulet (Appl. Numer. Math. 123 (2018) 22-42) to other adsorption isotherms. In particular, we propose a family of generalized Langmuir-type isotherms and prove that the correspondence between the concentrations of solutes in the liquid phase (the primitive variables) and the conserved variables is well defined and admits a global smooth inverse that can be computed numerically. Secondly, to establish the well-posedness of the mathematical model, we study the eigenstructure of the Jacobian of the mentioned correspondence and use this characteristic information to get oscillation-free sharp interfaces on the numerical approximate solutions. To do so, we determine the structure of the Jacobian matrix of the system and use it to deduce its eigenstructure. We combine the use of characteristic-based numerical fluxes with a second-order implicit-explicit scheme proposed in the cited reference and perform some numerical experiments with T\'oth's adsorption isotherms to demonstrate that the characteristic-based schemes produce accurate numerical solutions with no oscillations, even when steep gradients appear in the solutions.

We increase the dynamical range of a scanning tunneling microscope (STM) by actively subtracting dominant current-harmonics generated by nonlinearities in the current-voltage characteristics that could saturate the current preamplifier at low junction impedances or high gains. The strict phase relationship between a cosinusoidal excitation voltage and the current-harmonics allows excellent cancellation using the displacement-current of a driven compensating capacitor placed at the input of the preamplifier. Removal of DC currents has no effect on, and removal of the first harmonic only leads to a rigid shift in conductivity that can be numerically reversed by adding the known removal current. Our method requires no permanent change of the hardware but only two phase synchronized voltage sources and a multi-frequency lock-in amplifier to enable high dynamic range spectroscopy and imaging.

Imitation learning with human data has demonstrated remarkable success in teaching robots in a wide range of skills. However, the inherent diversity in human behavior leads to the emergence of multi-modal data distributions, thereby presenting a formidable challenge for existing imitation learning algorithms. Quantifying a model's capacity to capture and replicate this diversity effectively is still an open problem. In this work, we introduce simulation benchmark environments and the corresponding Datasets with Diverse human Demonstrations for Imitation Learning (D3IL), designed explicitly to evaluate a model's ability to learn multi-modal behavior. Our environments are designed to involve multiple sub-tasks that need to be solved, consider manipulation of multiple objects which increases the diversity of the behavior and can only be solved by policies that rely on closed loop sensory feedback. Other available datasets are missing at least one of these challenging properties. To address the challenge of diversity quantification, we introduce tractable metrics that provide valuable insights into a model's ability to acquire and reproduce diverse behaviors. These metrics offer a practical means to assess the robustness and versatility of imitation learning algorithms. Furthermore, we conduct a thorough evaluation of state-of-the-art methods on the proposed task suite. This evaluation serves as a benchmark for assessing their capability to learn diverse behaviors. Our findings shed light on the effectiveness of these methods in tackling the intricate problem of capturing and generalizing multi-modal human behaviors, offering a valuable reference for the design of future imitation learning algorithms.

Scientific and technological advances in numerical modelling have improved the quality of climate predictions over recent decades, but predictive skill remains limited in many aspects. Extreme events such as heat and cold waves, droughts, heavy rain and storms are particularly challenging to predict accurately due to their rarity and non-linear chaotic nature, and because of model limitations. However, recent studies have shown that predictive skill of extremes can be increased when using more sophisticated approaches, indicating that there might be systemic predictability that is not being leveraged. Recently, numerous studies have been devoted to the exploitation of Artificial Intelligence (AI) to study the predictability and make predictions of weather and climate. AI techniques have shown great potential to improve the prediction of extreme events and uncover their links to large-scale and local drivers. Machine and deep learning, causal discovery, explainable AI, are only some of the approaches that have been tested to both improve our understanding of the processes underlying predictability and enhance prediction skill of extreme events. Results are promising, especially for hybrid predictions that combine the AI, which can reveal and exploit unknown spatio-temporal connections from data, and climate models, that provide the theoretical foundation and interpretability of the physical world. On the other hand, challenges are multiple in many aspects, from data curation to model uncertainty and generalizability, to the reproducibility of methods and workflows. A few best practices are identified to increase trust in these novel techniques, and future perspectives are envisaged for further scientific development., Comment: 20 pages, 4 figures, 2 tables

This paper presents a comprehensive analysis of four triply eclipsing triple star systems, namely TIC 88206187, TIC 14839347, TIC 298714297, and TIC 66893949. The four systems with third-body eclipses were found in the TESS lightcurves from among a sample of ~400 matches between known eclipsing binaries and the Gaia DR3 Non-Single Star (NSS; Gaia Collaboration 2022; Pourbaix et al. 2022) solution database. We combined photometric lightcurves, eclipse timing variations, archival spectral energy distributions, and theoretical evolution tracks in a robust photodynamical analysis to determine the orbital and system parameters. The triples have outer periods of 52.9, 85.5, 117, and 471 days, respectively. All dozen stars have masses $\lesssim$ 2.6 M$_\odot$. The systems are quite flat with mutual inclination angles between the inner and outer orbital planes that are all $\lesssim 4^\circ$. The outer mass ratios range from 0.39--0.76, consistent with our earlier collection of compact triply eclipsing triples. TIC 88206187 exhibits a fractional radius of the outer tertiary component $(r_B \equiv R_B/a_{\rm out})$ exceeding 0.1 (only the third such system known), and we consider its future evolution. Finally, we compare our photodynamical analysis results and the orbital parameters given in the Gaia DR3 NSS solutions, indicating decent agreement, but with the photodynamical results being more accurate., Comment: 16 pages, 8 figures. Accepted for publication in MNRAS

Materials with complex inner structure can be challenging to characterize in an effective way. First, it is difficult to determine the representative volume for such a heterogeneous material. Second, the effective material parameters significantly depend on the structure, and thus on the interface properties. In the present paper, we focus on composite metal foams, and we attempt to determine the effective thermal parameters. We use the heat pulse experiment to study its transient thermal response. We observed deviation from Fourier's law, and thus we propose an evaluation procedure for such experimental data using the Guyer--Krumhansl heat equation. Furthermore, we studied the effective parameters, the specific heat, mass density, thermal conductivity and thermal diffusivity, and we propose a method for deducing a more reliable thermal diffusivity and thermal conductivity based on the transient temperature history.

The nearby spiral galaxy NGC 3147 hosted three Type Ia supernovae (SNe Ia) in the past decades, which have been subjects of intense follow-up observations. Simultaneous analysis of their data provides a unique opportunity for testing the different light curve fitting methods and distance estimations. The detailed optical follow-up of SN 2021hpr allows us to revise the previous distance estimations to NGC 3147, and compare the widely used light curve fitting algorithms to each other. After the combination of the available and newly published data of SN 2021hpr, its physical properties can be also estimated with higher accuracy. We present and analyse new BVgriz and Swift photometry of SN 2021hpr to constrain its general physical properties. Together with its siblings, SNe 1997bq and 2008fv, we cross-compare the individual distance estimates of these three SNe given by the SALT code, and also check their consistency with the results from the MLCS2k2 method. The early spectral series of SN 2021hpr are also fit with the radiative spectral code TARDIS in order to verify the explosion properties and constrain the chemical distribution of the outer ejecta. After combining the distance estimates for the three SNe, the mean distance to their host galaxy, NGC 3127, is 42.5 $\pm$ 1.0 Mpc, which matches with the distance inferred by the most up-to-date LC fitters, SALT3 and BayeSN. We confirm that SN~2021hpr is a Branch-normal Type Ia SN that ejected $\sim 1.12 \pm 0.28$ M$_\odot$ from its progenitor white dwarf, and synthesized $\sim 0.44 \pm 0.14$ M$_\odot$ of radioactive $^{56}$Ni., Comment: 16 pages, 17 figures, 11 tables; accepted for publication in A&A

Alkaline vents (AV) are hypothesized to have been a setting for the emergence of life, by creating strong gradients across inorganic membranes within chimney structures. In the past, 3-dimensional chimney structures were formed under laboratory conditions, however, no in situ visualisation or testing of the gradients was possible. We develop a quasi-2-dimensional microfluidic model of alkaline vents that allows spatio-temporal visualisation of mineral precipitation in low volume experiments. Upon injection of an alkaline fluid into an acidic, iron-rich solution, we observe a diverse set of precipitation morphologies, mainly controlled by flow-rate and ion-concentration. Using microscope imaging and pH dependent dyes, we show that finger-like precipitates can facilitate formation and maintenance of microscale pH gradients and accumulation of dispersed particles in confined geometries. Our findings establish a model to investigate the potential of gradients across a semi-permeable boundary for early compartmentalisation, accumulation and chemical reactions at the origins of life., Comment: 13 pages, 4 figures

With the planning of new ambitious gravitational wave (GW) observatories, fully controlled laboratory experiments on dynamic gravitation become more and more important. Such new experiments can provide new insights in potential dynamic effects such as gravitational shielding or energy flow and might contribute to bringing light into the mystery still surrounding gravity. Here we present a laboratory-based transmitter-detector experiment using two rotating bars as transmitter and a 42 Hz, high-Q bending beam resonator as detector. Using a highly precise phase control to synchronize the rotating bars, a dynamic gravitational field emerges that excites the bending motion with amplitudes up to 100 nm/s or 370 pm, which is a factor of 500 above the thermal noise. The two-transmitter design enables the investigation of different setup configurations. The detector movement is measured optically, using three commercial interferometers. Acoustical, mechanical, and electrical isolation, a temperature-stable environment, and lock-in detection are central elements of the setup. The moving load response of the detector is numerically calculated based on Newton's law of gravitation via discrete volume integration, showing excellent agreement between measurement and theory both in amplitude and phase. The near field gravitational energy transfer is 10$^{25}$ times higher than what is expected from GW analysis.

Aims. We introduce a novel way to identify new compact hierarchical triple stars by exploiting the huge potential of Gaia DR3 and also its future data releases. We aim to increase the current number of compact hierarchical triples significantly. Methods. We utilize several eclipsing binary catalogs from different sky surveys totaling more than 1 million targets for which we search for Gaia DR3 Non-single Star orbital solutions with periods substantially longer than the eclipsing periods of the binaries. Those solutions in most cases should belong to outer orbits of tertiary stars in those systems. We also try to validate some of our best-suited candidates using TESS eclipse timing variations. Results. We find 403 objects with suitable Gaia orbital solutions of which 27 are already known triple systems. This makes 376 newly identified hierarchical triple system candidates in our sample. We analyze the cumulative probability distribution of the outer orbit eccentricities and find that it is very similar to the ones found by earlier studies based on the observations of the Kepler and OGLE missions. We found measurable non-linear eclipse timing variations or third-body eclipses in the TESS data for 192 objects which we also consider to be confirmed candidates. Out of these, we construct analytical light-travel time effect models for the eclipse timing variations of 22 objects with well-sampled TESS observations. We compare the outer orbital parameters from our solutions with the ones from the Gaia solutions and find that the most reliable orbital parameter is the orbital period, while the values of the other parameters should be used with caution., Comment: 18 pages, 9 figures, 6 tables, Accepted for publication in Astronomy & Astrophysics

In this paper, we study a Ramsey-type problem for equations of the form $ax+by=p(z)$. We show that if certain technical assumptions hold, then any 2-colouring of the positive integers admits infinitely many monochromatic solutions to the equation $ax+by=p(z)$. This entails the $2$-Ramseyness of several notable cases such as the equation $ax+y=z^n$ for arbitrary $a\in\mathbb{Z}^{+}$ and $n\ge 2$, and also of $ax+by=a_Dz^D+\dots+a_1z\in\mathbb{Z}[z]$ such that $\text{gcd}(a,b)=1$, $D\ge 2$, $a,b,a_D>0$ and $a_1\neq0$., Comment: 16 pages

The on-surface synthesis of nano-graphenes has led the charge in prototyping structures with perspectives beyond silicon-based technology. Following reports of open-shell systems in graphene-nanoribbons (GNR), a flurry of research activities is directed at investigating their magnetic properties with a keen eye for spintronic applications. Although the synthesis of nano-graphenes is usually straightforward on gold, it is difficult to use it for electronic decoupling and spin-polarized measurements. Using a binary alloy Cu3Au(111), we show how to combine the efficient gold-like nano-graphene formation with spin polarization and electronic decoupling known from copper. We prepare copper oxide layers, demonstrate thermally and tip-assisted synthesis of GNR and grow thermally stable magnetic Co islands. We functionalize the tip of a scanning tunneling microscope with carbon-monoxide, nickelocene, or attach Co clusters for high-resolution imaging, magnetic sensing, or spin-polarized measurements. This versatile platform will be a valuable tool in the advanced study of magnetic nano-graphenes.

General purpose optimization techniques can be used to solve many problems in engineering computations, although their cost is often prohibitive when the number of degrees of freedom is very large. We describe a multilevel approach to speed up the computation of the solution of a large-scale optimization problem by a given optimization technique. By embedding the problem within Harten's Multiresolution Framework (MRF), we set up a procedure that leads to the desired solution, after the computation of a finite sequence of sub-optimal solutions, which solve auxiliary optimization problems involving a smaller number of variables. For convex optimization problems having smooth solutions, we prove that the distance between the optimal solution and each sub-optimal approximation is related to the accuracy of the interpolation technique used within the MRF and analyze its relation with the performance of the proposed algorithm. Several numerical experiments confirm that our technique provides a computationally efficient strategy that allows the end user to treat both the optimizer and the objective function as black boxes throughout the optimization process., Comment: 24 pages + 7 appendix pages. 7 + 7 figures

Time-dependent femtosecond pump-probe spectroscopic ellipsometry studies on zincblende gallium-nitride (zb-GaN) are performed and analyzed between 2.9-3.7eV. An ultra-fast change of the absorption onset (3.23eV for zb-GaN) is observed by investigating the imaginary part of the dielectric function. The 266nm (4.66eV) pump pulses induce a large free-carrier concentration up to $4\times 10^{20}$cm$^{-3}$, influencing the transition energy between conduction and valence bands due to many-body effects, like band filling and band gap renormalization, up to $\approx$500meV. Additionally, the absorption of the pump-beam creates a free-carrier profile within the 605nm zb-GaN layer. This leads to varying optical properties from sample surface to substrate, which are taken into account by grading analysis for an accurate description of the experimental data. A temporal resolution of 100fs allows in-depth investigations of occurring ultra-fast relaxation and recombination processes. We provide a quantitative description of the free-carrier concentration and absorption onset at the sample surface as a function of relaxation, recombination, and diffusion yielding a characteristic relaxation time of 0.19ps and a recombination time of 26.1ps.

We demonstrate a straightforward approach to integrating a magnetic field into a low-temperature scanning tunneling microscope (STM) by adhering an NdFeB permanent magnet to a magnetizable sample plate. To render our magnet concept compatible with high-temperature sample cleaning procedures, we make the irreversible demagnetization of the magnet a central part of our preparation cycle. After sacrificing the magnet by heating it above its Curie temperature, we use a transfer tool to attach a new magnet in-situ prior to transferring the sample into the STM. We characterize the magnetic field created by the magnet using the Abrikosov vortex lattice of superconducting NbSe2. Excellent agreement between the distance dependent magnetic fields from experiments and simulations allows us to predict the magnitude and orientation of magnetic flux at any location with respect to the magnet and the sample plate. Our concept is an accessible solution for field-dependent surface science studies that require fields in the range of up to 400 mT and otherwise detrimental heating procedures., Comment: 6 pages, 5 figures

Quasiparticle interference imaging (QPI) offers insight into the band structure of quantum materials from the Fourier transform of local density of states (LDOS) maps. Their acquisition with a scanning tunneling microscope is traditionally tedious due to the large number of required measurements that may take several days to complete. The recent demonstration of sparse sampling for QPI imaging showed how the effective measurement time could be fundamentally reduced by only sampling a small and random subset of the total LDOS. However, the amount of required sub-sampling to faithfully recover the QPI image remained a recurring question. Here we introduce an adaptive sparse sampling (ASS) approach in which we gradually accumulate sparsely sampled LDOS measurements until a desired quality level is achieved via compressive sensing recovery. The iteratively measured random subset of the LDOS can be interleaved with regular topographic images that are used for image registry and drift correction. These reference topographies also allow to resume interrupted measurements to further improve the QPI quality. Our ASS approach is a convenient extension to quasiparticle interference imaging that should remove further hesitation in the implementation of sparse sampling mapping schemes., Comment: 10 pages, 5 figures

Naturals and synthetic perovskites are widely used functional materials thanks to their particular physical properties, such as superconductivity, ferroelectricity and photo-activity. Many of these properties are related to static or dynamic motion of octahedral units; Yet a full understanding of the relationships between perovskite crystal structure, chemical bonding and physical properties is currently missing. Several studies indicate the existence of dynamic disorder generated by anharmonic motion of octahedral units e.g. in halide perovskite structures. In this work, we derive all possible space groups for simple perovskites $\rm ABX_3$ with dynamical octahedral tilting. The derived space groups extend the well established space group tables for static tiltings by [Glazer, A. Acta Cryst. B 1972, 28, 3384-3392; Aleksandrov, K. Ferroelectrics 1976, 24, 801-805; Howard, C.J., Stokes, H.T. Acta Cryst. B 1998, 54, 782-789]. We demonstrate ubiquity of dynamical tilting by analysing the structural data for perovskites reported in recent scientific publications and discuss the signature of dynamic tilting in the corresponding structures. Finally, we discuss the possible influence of dynamic disorder on the physical properties of halide perovskites.

Recent spectacular results of gravitational waves obtained by the LIGO system, with frequencies in the 100 Hz regime, make corresponding laboratory experiments with full control over cause and effect of great importance. Dynamic measurements of gravitation in the laboratory have to date been scarce, due to difficulties in assessing non-gravitational crosstalk and the intrinsically weak nature of gravitational forces. In fact, fully controlled quantitative experiments have so far been limited to frequencies in the mHz regime. New experiments in gravity might also yield new physics, thereby opening avenues towards a theory that explains all of physics within one coherent framework. Here we introduce a new, fully-characterized experiment at three orders of magnitude higher frequencies. It allows experimenters to quantitatively determine the dynamic gravitational interaction between two parallel beams vibrating at 42 Hz in bending motion. The large amplitude vibration of the transmitter beam produces gravitationally-induced motion with amplitudes up to 1E-11 m of the resonant detector beam. The reliable measurement with sub-pm displacement resolution is made possible by a set-up which combines acoustical, mechanical and electrical isolation, a temperature-stable environment, heterodyne laser interferometry and lock-in detection. The interaction is quantitatively modelled based on Newton's theory. Our initial results agree with the theory to within about three percent in amplitude. Based on a power balance analysis, we determined the near-field gravitational energy flow from the transmitter to the detector to be 2.5 E-20 J/s, and to decay with distance as d-4. We expect our experiment to make significant progress in directions where current experimental evidence for dynamic gravitation is limited, such as the dynamic determination of G, inverse-square law, and gravitational shielding.

Quantum well (QW) heterostructures have been extensively used for the realization of a wide range of optical and electronic devices. Exploiting their potential for further improvement and development requires a fundamental understanding of their electronic structure. So far, the most commonly used experimental techniques for this purpose have been all-optical spectroscopy methods that, however, are generally averaged in momentum space. Additional information can be gained by angle-resolved photoelectron spectroscopy (ARPES), which measures the electronic structure with momentum resolution. Here we report on the use of extremely low energy ARPES (photon energy $\sim$ 7 eV) to increase its depth sensitivity and access buried QW states, located at 3 nm and 6 nm below the surface of cubic-GaN/AlN and GaAs/AlGaAs heterostructures, respectively. We find that the QW states in cubic-GaN/AlN can indeed be observed, but not their energy dispersion because of the high surface roughness. The GaAs/AlGaAs QW states, on the other hand, are buried too deep to be detected by extremely low energy ARPES. Since the sample surface is much flatter, the ARPES spectra of the GaAs/AlGaAs show distinct features in momentum space, which can be reconducted to the band structure of the topmost surface layer of the QW structure. Our results provide important information about the samples' properties required to perform extremely low energy ARPES experiments on electronic states buried in semiconductor heterostructures.

Spectroscopic mapping refers to the massive recording of spectra whilst varying an additional degree of freedom, such as: magnetic field, location, temperature, or charge carrier concentration. As this involves two serial tasks, spectroscopic mapping can become excruciatingly slow. We demonstrate exponentially faster mapping through our combination of sparse sampling and parallel spectroscopy. We exemplify our concept using quasiparticle interference imaging of Au(111) and Bi2Sr2CaCu2O8 (Bi2212), as two well-known model systems. Our method is accessible, straightforward to implement with existing scanning tunneling microscopes, and can be easily extended to enhance gate or field-mapping spectroscopy. In view of a possible four orders of magnitude speed advantage, it is setting the stage to fundamentally promote the discovery of novel quantum materials.

We present simplified formulae for the analytic integration of the Newton potential of polynomials over boxes in two- and three-dimensional space. These are implemented in an easy-to-use C++ library that allows computations in arbitrary precision arithmetic which is also documented here. We describe how these results can be combined with fast multipole methods for general, non-polynomial data., Comment: The software is available from the first author's website: http://www.acom.rwth-aachen.de/5people/kirchhart/start#software

Germanium telluride (GeTe), a phase-change material, is known to exhibit four different structural phases: three at room temperature (one amorphous and two crystalline, $\alpha$ and $\gamma$) and one at high temperature (crystalline $\beta$). Because transitions between the amorphous and crystalline phases lead to significant changes in material properties (e.g., refractive index and resistivity), GeTe has been investigated as a phase-change material for photonics, thermoelectrics, ferroelectrics, and spintronics. Consequently, the temperature-dependent phase transitions in GeTe have been studied for bulk and thin-film GeTe, both fabricated by sputtering. Colloidal synthesis of nanoparticles offers a more flexible fabrication approach for amorphous and crystalline GeTe. These nanoparticles are known to exhibit size-dependent properties, such as an increased crystallization temperature for the amorphous-to-$\alpha$ transition in sub-10\,nm GeTe particles. The $\alpha$-to-$\beta$ phase transition is also expected to vary with size, but this effect has not yet been investigated for GeTe. Here, we report time-resolved X-ray diffraction of GeTe nanoparticles with different diameters and from different synthetic protocols. We observe a non-volatile amorphous-to-$\alpha$ transition between 210$^{\circ}$C and 240$^{\circ}$C and a volatile $\alpha$-to-$\beta$ transition between 370$^{\circ}$C and 420$^{\circ}$C. The latter transition was reversible and repeatable. While the transition temperatures are shifted relative to the values known for bulk GeTe, the nanoparticle-based samples still exhibit the same structural phases reported for sputtered GeTe. Thus, colloidal GeTe maintains the same general phase behavior as bulk GeTe while allowing for more flexible and accessible fabrication. Therefore, nanoparticle-based GeTe films show great potential for applications, such as in active photonics.

We consider a real-valued function $f$ defined on the set of infinite branches $X$ of a countably branching pruned tree $T$. The function $f$ is said to be a \textit{limsup function} if there is a function $u \colon T \to \mathbb{R}$ such that $f(x) = \limsup_{t \to \infty} u(x_{0},\dots,x_{t})$ for each $x \in X$. We study a game characterization of limsup functions, as well as a novel game characterization of functions of Baire class 1.

Poverty is a multidimensional concept often comprising a monetary outcome and other welfare dimensions such as education, subjective well-being or health, that are measured on an ordinal scale. In applied research, multidimensional poverty is ubiquitously assessed by studying each poverty dimension independently in univariate regression models or by combining several poverty dimensions into a scalar index. This inhibits a thorough analysis of the potentially varying interdependence between the poverty dimensions. We propose a multivariate copula generalized additive model for location, scale and shape (copula GAMLSS or distributional copula model) to tackle this challenge. By relating the copula parameter to covariates, we specifically examine if certain factors determine the dependence between poverty dimensions. Furthermore, specifying the full conditional bivariate distribution, allows us to derive several features such as poverty risks and dependence measures coherently from one model for different individuals. We demonstrate the approach by studying two important poverty dimensions: income and education. Since the level of education is measured on an ordinal scale while income is continuous, we extend the bivariate copula GAMLSS to the case of mixed ordered-continuous outcomes. The new model is integrated into the GJRM package in R and applied to data from Indonesia. Particular emphasis is given to the spatial variation of the income-education dependence and groups of individuals at risk of being simultaneously poor in both education and income dimensions.

We answer a question of Banakh, Jab\l{}o\'nska and Jab\l{}o\'nski by showing that for $d\ge 2$ there exists a compact set $K \subseteq \mathbb{R}^d$ such that the projection of $K$ onto each hyperplane is of non-empty interior, but $K+K$ is nowhere dense. The proof relies on a random construction. A natural approach in the proofs is to construct such a $K$ in the unit cube with full projections, that is, such that the projections of $K$ agree with that of the unit cube. We investigate the generalization of these problems for projections onto various dimensional subspaces as well as for $\ell$-fold sumsets. We obtain numerous positive and negative results, but also leave open many interesting cases. We also show that in most cases if we have a specific example of such a compact set then actually the generic (in the sense of Baire category) compact set in a suitably chosen space is also an example. Finally, utilizing a computer-aided construction, we show that the compact set in the plane with full projections and nowhere dense sumset can be self-similar., Comment: 26 pages, 3 figures. Small modifications, final version

The Minkowski sum and Minkowski product can be considered as the addition and multiplication of subsets of $\mathbb{R}$. If we consider a compact subset $K\subseteq[0,1]$ and a power series $f$ which is absolutely convergent on $[0,1]$, then we may use these operations and the natural topology of the space of compact sets to substitute the compact set $K$ into the power series $f$. Changhao Chen studied this kind of substitution in the special case of polynomials and showed that if we substitute the typical compact set $K\subseteq [0,1]$ into a polynomial, we get a set of Hausdorff dimension 0. We generalize this result and show that the situation is the same for power series where the coefficients converge to zero quickly. On the other hand we also show a large class of power series where the result of the substitution has Hausdorff dimension one.

Scanning tunneling microscopy (STM) is a notoriously slow technique; Data-recording is serial which renders complex measurement tasks, such as quasiparticle interference (QPI) mapping, impractical. However, QPI would provide insight into band-structure details of quantum materials which can be inaccessible to angle-resolved photoemission spectroscopy. Here we use compressed sensing (CS) to fundamentally speed-up QPI mapping. We reliably recover the QPI information from a fraction of the usual local density of state measurements. The requirement of CS is naturally fulfilled for QPI, since CS relies on sparsity in a vector domain, here given by few nonzero coefficients in Fourier space. We exemplify CS on a simulated Cu(111) surface using random sampling of constant and varying probability density. We further simplify the motion of the STM tip through an open traveling salesman's problem for greater efficiency. We expect that the implications of our CS approach will be transformative for the exploration of 2D quantum materials.

Advances in the field of seismic interferometry have provided a basic theoretical interpretation to the full spectrum of the microtremor horizontal-to-vertical spectral ratio [H/V(f)]. The interpretation has been applied to ambient seismic noise data recorded both at the surface and at depth. The new algorithm, based on the diffuse wavefield assumption, has been used in inversion schemes to estimate seismic wave velocity profiles that are useful input information for engineering and exploration seismology both for earthquake hazard estimation and to characterize surficial sediments. However, until now, the developed algorithms are only suitable for on land environments with no offshore consideration. Here, the microtremor H/V(z, f) modeling is extended for applications to marine sedimentary environments for a 1D layered medium. The layer propagator matrix formulation is used for the computation of the required Green's functions. Therefore, in the presence of a water layer on top, the propagator matrix for the uppermost layer is defined to account for the properties of the water column. As an application example we analyze eight simple canonical layered earth models. Frequencies ranging from 0.2 to 50 Hz are considered as they cover a broad wavelength interval and aid in practice to investigate subsurface structures in the depth range from a few meters to a few hundreds of meters. Results show a marginal variation of 8 percent at most for the fundamental frequency when a water layer is present. The water layer leads to variations in H/V peak amplitude of up to 50 percent atop the solid layers., Comment: peer reviewed article, 7 figures

The three essential pillars of magnetic data storage devices are readability, writeability, and stability. However, these requirements compete as magnetic domain sizes reach the fundamental limit of single atoms and molecules. The proven magnetic bistability of individual holmium atoms on magnesium oxide appeared to operate within this magnetic trilemma, sacrificing writeability for unprecedented stability. Using the magnetic stray field created by the tip of a spin-polarized scanning tunneling microscope (SP-STM), we controllably move the Ho state into the quantum regime, allowing us to write its state via the quantum tunneling of magnetization (QTM). We find that the hyperfine interaction causes both the excellent magnetic bistability, even at zero applied magnetic field, and the avoided level crossings which we use to control the magnetic state via QTM. We explore how to use such a system to realize a high-fidelity single atom NOT gate (inverter). Our approach reveals the prospect of combining the best traits of the classical and quantum worlds for next generation data storage.

We present here the straightforward implementation of pump-probe methods into existing scanning tunneling microscopy (STM) systems. Our method uses the waveform-sequencing abilities of a standard arbitrary waveform generator (AWG) and a simple mechanical relay switch that either connects the regular STM control electronics or the AWG to the STM system. Our upgrade further enables pulsed-ESR excitation for advanced STM based spin-resonance experiments. We demonstrate the technical implementation, signal detection using a lock-in amplifier, and cross-correlation measurements of DC/DC and DC/RF pulses highlighting our ~5 ns time resolution, here limited by the speed of the available electronics. Our setup is highly versatile and can be extended to suit other needs of STM based investigations such as required in diverse mapping schemes or the coherent manipulation of qubits.

Here we present Translocatome, the first dedicated database of human translocating proteins. The core of the Translocatome database is the manually curated data set of 213 human translocating proteins listing the source of their experimental validation, several details of their translocation mechanism, their local compartmentalized interactome, as well as their involvement in signalling pathways and disease development. In addition, using the well-established and widely used gradient boosting machine learning tool, XGBoost, Translocatome provides translocation probability values for 13,066 human proteins identifying 1133 and 3268 high- and low-confidence translocating proteins, respectively. The database has user-friendly search options with a UniProt autocomplete quick search and advanced search for proteins filtered by their localization, UniProt identifiers, translocation likelihood or data complexity. Download options of search results, manually curated and predicted translocating protein sets are available on its website. The update of the database is helped by its manual curation framework and connection to the previously published ComPPI compartmentalized protein-protein interaction database. As shown by the application examples of merlin (NF2) and tumor protein 63 (TP63) Translocatome allows a better comprehension of protein translocation as a systems biology phenomenon and can be used as a discovery-tool in the protein translocation field. The database is available here: http://translocatome.linkgroup.hu

In this paper we define a family of nonlinear, stationary, interpolatory subdivision schemes with the capability of reproducing conic shapes including polynomials upto second order. Linear, non-stationary, subdivision schemes do also achieve this goal, but different conic sections require different refinement rules to guarantee exact reproduction. On the other hand, with our construction, exact reproduction of different conic shapes can be achieved using exactly the same nonlinear scheme. Convergence, stability, approximation and shape preservation properties of the new schemes are analyzed. In addition, the conditions to obtain $\mathcal{C}^1$ limit functions are also studied.

Following Darji, we say that a Borel subset $B$ of an abelian Polish group $G$ is Haar meager if there is a compact metric space $K$ and a continuous function $f : K \to G$ such that the preimage of the translate, $f^{-1}(B+g)$ is meager in $K$ for every $g \in G$. The set $B$ is called strongly Haar meager if there is a compact set $C \subseteq G$ such that $(B+g) \cap C$ is meager in $C$ for every $g \in G$. The main open problem in this area is Darji's question asking whether these two notions are the same. Even though there have been several partial results suggesting a positive answer, in this paper we construct a counterexample. More specifically, we construct a $G_\delta$ set in $\mathbb{Z}^\omega$ that is Haar meager but not strongly Haar meager. We also show that no $F_\sigma$ counterexample exists, hence our result is optimal.