Institut für Physik und Astronomie
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Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross disciplinary collaboration together with close communication between scientists and policy makers.
We present a catalogue of 362 million stellar parameters, distances, and extinctions derived from Gaia's Early Data Release (EDR3) cross-matched with the photometric catalogues of Pan-STARRS1, SkyMapper, 2MASS, and All WISE. The higher precision of the Gaia EDR3 data, combined with the broad wavelength coverage of the additional photometric surveys and the new stellar-density priors of the StarHorse code, allows us to substantially improve the accuracy and precision over previous photo-astrometric stellar-parameter estimates. At magnitude G = 14 (17), our typical precisions amount to 3% (15%) in distance, 0.13 mag (0.15 mag) in V-band extinction, and 140 K (180 K) in effective temperature. Our results are validated by comparisons with open clusters, as well as with asteroseismic and spectroscopic measurements, indicating systematic errors smaller than the nominal uncertainties for the vast majority of objects. We also provide distance- and extinction-corrected colour-magnitude diagrams, extinction maps, and extensive stellar density maps that reveal detailed substructures in the Milky Way and beyond. The new density maps now probe a much greater volume, extending to regions beyond the Galactic bar and to Local Group galaxies, with a larger total number density. We publish our results through an ADQL query interface (gaia . aip . de) as well as via tables containing approximations of the full posterior distributions. Our multi-wavelength approach and the deep magnitude limit render our results useful also beyond the next Gaia release, DR3.
The study of exoplanets and especially their atmospheres can reveal key insights on their evolution by identifying specific atmospheric species. For such atmospheric investigations, high-resolution transmission spectroscopy has shown great success, especially for Jupiter-type planets. Towards the atmospheric characterization of smaller planets, the super-Earth exoplanet 55 Cnc e is one of the most promising terrestrial exoplanets studied to date. Here, we present a high-resolution spectroscopic transit observation of this planet, acquired with the PEPSI instrument at the Large Binocular Telescope. Assuming the presence of Earth-like crust species on the surface of 55 Cnc e, from which a possible silicate-vapor atmosphere could have originated, we search in its transmission spectrum for absorption of various atomic and ionized species such as Fe , Fe (+), Ca , Ca (+), Mg, and K , among others. Not finding absorption for any of the investigated species, we are able to set absorption limits with a median value of 1.9 x R-P. In conclusion, we do not find evidence of a widely extended silicate envelope on this super-Earth reaching several planetary radii.
Forests play a key role in a bio-based economy by providing renewable materials, mitigating climate change, and accommodating biodiversity. However, forests experience massive increases in stresses in their ecological and socioeconomic environments, threatening forest ecosystem services supply. Alleviating those stresses is hampered by conflicting and disconnected governance arrangements, competing interests and claims, and rapid changes in technology and social demands. Identifying which stresses threaten forest ecosystem services supply and which factors hamper their alleviation requires stakeholders' perceptions. Stakeholder-oriented stress tests for the supply of forest ecosystem services are therefore necessary but are not yet available. This perspective presents a roadmap to develop a stress test tailored to multiple stakeholders' needs and demands across spatial scales. We provide the Cascade and Resilience Rosetta, with accompanying performance- and resilience indicators, as tools to facilitate development of the stress test. The application of the stress test will facilitate the transition toward a bio-based economy in which healthy and diverse forests provide sustainable and resilient ecosystem services.
Recent observations have revealed remarkable insights into the gas reservoir in the circumgalactic medium (CGM) of galaxy haloes. In this paper, we characterise the gas in the vicinity of Milky Way and Andromeda analogues in the hestia (High resolution Environmental Simulations of The Immediate Area) suite of constrained Local Group (LG) simulations. The hestia suite comprise of a set of three high-resolution arepo-based simulations of the LG, run using the Auriga galaxy formation model. For this paper, we focus only on the z = 0 simulation datasets and generate mock skymaps along with a power spectrum analysis to show that the distributions of ions tracing low-temperature gas (H i and Si iii) are more clumpy in comparison to warmer gas tracers (O vi, O vii and O viii). We compare to the spectroscopic CGM observations of M31 and low-redshift galaxies. hestia under-produces the column densities of the M31 observations, but the simulations are consistent with the observations of low-redshift galaxies. A possible explanation for these findings is that the spectroscopic observations of M31 are contaminated by gas residing in the CGM of the Milky Way.
Mobilities and lifetimes of photogenerated charge carriers are core properties of photovoltaic materials and can both be characterized by contactless terahertz or microwave measurements. Here, the expertise from fifteen laboratories is combined to quantitatively model the current-voltage characteristics of a solar cell from such measurements. To this end, the impact of measurement conditions, alternate interpretations, and experimental inter-laboratory variations are discussed using a (Cs,FA,MA)Pb(I,Br)(3) halide perovskite thin-film as a case study. At 1 sun equivalent excitation, neither transport nor recombination is significantly affected by exciton formation or trapping. Terahertz, microwave, and photoluminescence transients for the neat material yield consistent effective lifetimes implying a resistance-free JV-curve with a potential power conversion efficiency of 24.6 %. For grainsizes above approximate to 20 nm, intra-grain charge transport is characterized by terahertz sum mobilities of approximate to 32 cm(2) V-1 s(-1). Drift-diffusion simulations indicate that these intra-grain mobilities can slightly reduce the fill factor of perovskite solar cells to 0.82, in accordance with the best-realized devices in the literature. Beyond perovskites, this work can guide a highly predictive characterization of any emerging semiconductor for photovoltaic or photoelectrochemical energy conversion. A best practice for the interpretation of terahertz and microwave measurements on photovoltaic materials is presented.
Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars(1-9) and from heavy-ion collisions of gold nuclei at relativistic energies(10,11) with microscopic nuclear theory calculations(12-17) to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission(5-8,18). Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.
Random logic networks
(2021)
We investigate dynamical properties of a quantum generalization of classical reversible Boolean networks. The state of each node is encoded as a single qubit, and classical Boolean logic operations are supplemented by controlled bit-flip and Hadamard operations. We consider synchronous updating schemes in which each qubit is updated at each step based on stored values of the qubits from the previous step. We investigate the periodic or quasiperiodic behavior of quantum networks, and we analyze the propagation of single site perturbations through the quantum networks with input degree one. A nonclassical mechanism for perturbation propagation leads to substantially different evolution of the Hamming distance between the original and perturbed states.
We apply the concepts of relative dimensions and mutual singularities to characterize the fractal properties of overlapping attractor and repeller in chaotic dynamical systems. We consider one analytically solvable example (a generalized baker's map); two other examples, the Anosov-Mobius and the Chirikov-Mobius maps, which possess fractal attractor and repeller on a two-dimensional torus, are explored numerically. We demonstrate that although for these maps the stable and unstable directions are not orthogonal to each other, the relative Renyi and Kullback-Leibler dimensions as well as the mutual singularity spectra for the attractor and repeller can be well approximated under orthogonality assumption of two fractals.
The fundamental sensitivity limit of atomic force microscopy is strongly correlated to the thermal noise of cantilever oscillation. A method to suppress this unwanted noise is to reduce the bandwidth of the measurement, but this approach is limited by the speed of the measurement and the width of the cantilever resonance, commonly defined through the quality factor Q. However, it has been shown that optomechanical resonances in interferometers might affect cantilever oscillations resulting in an effective quality factor Q(eff). When the laser power is sufficiently increased cantilever oscillations might even reach the regime of self-oscillation. In this self-oscillation state, the noise of the system is partially determined by the interaction with laser light far from equilibrium. Here, we show and discuss how tuning of laser power leads to nonlinear optomechanical effects that can dramatically increase the effective quality factor of the cantilever leading to out-of-equilibrium noise. We model the effects using a fourth order nonlinearity of the damping coefficient. Published under an exclusive license by AIP Publishing.