cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Measurability of precession and eccentricity for heavy binary-black-hole mergers
Creators: name: Xu, Yumeng
name: Hamilton, Eleanor
Publisher: name: arXiv
Year: 2022
Subjects: subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: Gravitational wave detections offer insights into the astrophysical populations of black holes in the universe and their formation processes. Detections of binaries consisting of black holes lying outside the bulk distribution of the astrophysical population are particularly intriguing. In this study, we perform an injection analysis within the intermediate-mass black hole range, utilizing the NR surrogate model NRSur7dq4 and a selection of NR waveforms from the SXS and RIT catalogues. Our investigation focuses on the detectability of precession and its potential degeneracy with eccentricity, especially for short signals with only a few cycles in band. While total mass, mass ratio, and $χ_\mathrm{eff}$ are generally well recovered, the recovery of $χ_\mathrm{p}$ is largely limited, and noise significantly impacts the recovery of some parameters for short signals. We also find that eccentricity lower than 0.2 is insufficient to mimic precession in parameter estimation when assuming a quasi-circular signal. Our results suggest that a certain degree of precession is necessary to produce evidence of high precession in parameter estimation, but it remains challenging to conclusively determine which effect is responsible for the high precession observed in events like GW190521. We emphasize the importance of caution when interpreting properties of a binary from short signals and highlight the potential benefits of future third generation detectors and eccentric waveform models for more exhaustive exploration of parameter space.
description: 16 pages, 13 figures
Influence of Collective Network Dynamics on Stimulus Separation
Creators: name: Schutzeichel, Lars
name: Bauer, Jan
name: Bouss, Peter
name: Dahmen, David
name: Musall, Simon
name: Helias, Moritz
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Temperature dependence of spin-model parameters in antiferromagnets
Creators: name: Rózsa, Levente
name: Atxitia, Unai
Publisher: name: arXiv
Year: 2022
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: The temperature dependence of mesoscopic spin-model parameters is derived in two-sublattice antiferromagnetically aligned systems based on Green's function theory. It is found that transversal spin correlations decrease the anisotropy terms while increasing the Heisenberg and Dzyaloshinsky--Moriya exchange interactions and the latter's contribution to the anisotropy. The obtained temperature dependences show quantitative agreement with the results for ferromagnets, and they also agree well with numerical atomistic simulations which treat the spin correlations without approximations. Possible applications of the results in multiscale modelling are discussed.
description: 13 pages, 7 figures
Deep-learning electronic-structure calculation of magnetic superstructures
Creators: name: Li, He
name: Tang, Zechen
name: Gong, Xiaoxun
name: Zou, Nianlong
name: Duan, Wenhui
name: Xu, Yong
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computational Physics (physics.comp-ph)
subject: Materials Science (cond-mat.mtrl-sci)
subject: FOS: Physical sciences

description: Ab initio study of magnetic superstructures (e.g., magnetic skyrmion) is indispensable to the research of novel materials but bottlenecked by its formidable computational cost. For solving the bottleneck problem, we develop a deep equivariant neural network method (named xDeepH) to represent density functional theory Hamiltonian $H_\text{DFT}$ as a function of atomic and magnetic structures and apply neural networks for efficient electronic structure calculation. Intelligence of neural networks is optimized by incorporating a priori knowledge about the important locality and symmetry properties into the method. Particularly, we design a neural-network architecture fully preserving all equivalent requirements on $H_\text{DFT}$ by the Euclidean and time-reversal symmetries ($E(3) \times \{I, T\}$), which is essential to improve method performance. High accuracy (sub-meV error) and good transferability of xDeepH are shown by systematic experiments on nanotube, spin-spiral, and Moiré magnets, and the capability of studying magnetic skyrmion is also demonstrated. The method could find promising applications in magnetic materials research and inspire development of deep-learning ab initio methods.
Increase in dimensionality and sparsification of neural activity over development across diverse cortical areas
Creators: name: Butti, Lorenzo
name: Powel, Nathaniel
name: Hein, Bettina
name: Kong, Deyue
name: Elpelt, Jonas
name: Mulholland, Haleigh
name: Smith, Gordon
name: Kaschube, Matthias
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling
Creators: name: Saberi, Amin
name: Wischnewski, Kevin
name: Jung, Kyesam
name: Lotter, Leon
name: Schaare, H. L.
name: Banaschweski, Tobias
name: Barker, Gareth
name: Bokde, Arun
name: Desrivières, Sylvane
name: Flor, Herta
name: Grigis, Antoine
name: Garavan, Hugh
name: Gowland, Penny
name: Heinz, Andreas
name: Brühl, Rüdiger
name: Martinot, Jean-Luc
name: Paillère Martinot, Marie-Laure
name: Artiges, Eric
name: Nees, Frauke
name: Papadopoulos Orfanos, Dimitri
name: Lemaitre, Herve
name: Poustka, Luise
name: Hohmann, Sarah
name: Holz, Nathalie
name: Baeuchl, Christian
name: Smolka, Michael
name: Vaidya, Nilakshi
name: Walter, Henrik
name: Whelan, Robert
name: Schumann, Gunther
name: Paus, Tomas
name: Dukart, Juergen
name: Bernhardt, Boris
name: Popovych, Oleksandr
name: Eickhoff, Simon
name: Valk, Sofie
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Adiabatic two-photon quantum gate operations using a long-range photonic bus
Creators: name: Hope, Anthony P.
name: Nguyen, Thach G.
name: Mitchell, Arnan
name: Greentree, Andrew D.
Publisher: name: arXiv
Year: 2013
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Adiabatic techniques have much potential to realise practical and robust optical waveguide devices. Traditionally photonic elements are limited to coupling schemes that rely on proximity to nearest neighbour elements. We combine adiabatic passage with a continuum based long-range optical bus to break free from such topological restraints and thereby outline a new approach to photonic quantum gate design. We explicitly show designs for adiabatic quantum gates that produce a Hadamard, 50:50 and 1/3:2/3 beam splitter, and non-deterministic CNOT gate based on planar thin, shallow ridge waveguides. Our calculations are performed under conditions of one and two-photon inputs.
description: 16 pages, 7 figures
Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives
Creators: name: Li, H.
name: Johra, H.
name: Pereira, F. de Andrade
name: Hong, T.
name: Dreau, J. Le
name: Maturo, A.
name: Wei, M.
name: Liu, Y.
name: Saberi-Derakhtenjani, A.
name: Nagy, Z.
name: Marszal-Pomianowska, A.
name: Finn, D.
name: Miyata, S.
name: Kaspar, K.
name: Nweye, K.
name: Neill, Z. O
name: Pallonetto, F.
name: Dong, B.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Systems and Control (eess.SY)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different energy grids with the energy demand of buildings. This is especially important when considering the intermittent nature of ever-growing renewable energy production, as well as the increasing dynamics of electricity demand in buildings. This paper provides a holistic review of (1) data-driven energy flexibility key performance indicators (KPIs) for buildings in the operational phase and (2) open datasets that can be used for testing energy flexibility KPIs. The review identifies a total of 81 data-driven KPIs from 91 recent publications. These KPIs were categorized and analyzed according to their type, complexity, scope, key stakeholders, data requirement, baseline requirement, resolution, and popularity. Moreover, 330 building datasets were collected and evaluated. Of those, 16 were deemed adequate to feature building performing demand response or building-to-grid (B2G) services. The DSM strategy, building scope, grid type, control strategy, needed data features, and usability of these selected 16 datasets were analyzed. This review reveals future opportunities to address limitations in the existing literature: (1) developing new data-driven methodologies to specifically evaluate different energy flexibility strategies and B2G services of existing buildings; (2) developing baseline-free KPIs that could be calculated from easily accessible building sensors and meter data; (3) devoting non-engineering efforts to promote building energy flexibility, such as designing utility programs, standardizing energy flexibility quantification and verification processes; and (4) curating datasets with proper description for energy flexibility assessments.
description: 30 pages, 14 figures, 4 tables
Realistic and verifiable coherent control of excitonic states in a light harvesting complex
Creators: name: Hoyer, Stephan
name: Caruso, Filippo
name: Montangero, Simone
name: Sarovar, Mohan
name: Calarco, Tommaso
name: Plenio, Martin B.
name: Whaley, K. Birgitta
Publisher: name: arXiv
Year: 2013
Subjects: subject: Quantum Physics (quant-ph)
subject: Chemical Physics (physics.chem-ph)
subject: FOS: Physical sciences

description: We explore the feasibility of coherent control of excitonic dynamics in light harvesting complexes, analyzing the limits imposed by the open nature of these quantum systems. We establish feasible targets for phase and phase/amplitude control of the electronically excited state populations in the Fenna-Mathews-Olson (FMO) complex and analyze the robustness of this control with respect to orientational and energetic disorder, as well as decoherence arising from coupling to the protein environment. We further present two possible routes to verification of the control target, with simulations for the FMO complex showing that steering of the excited state is experimentally verifiable either by extending excitonic coherence or by producing novel states in a pump-probe setup. Our results provide a first step toward coherent control of these complex biological quantum systems in an ultrafast spectroscopy setup.
description: 12 pages, 8 figures
Predicting Bearings' Degradation Stages for Predictive Maintenance in the Pharmaceutical Industry
Creators: name: Juodelyte, Dovile
name: Cheplygina, Veronika
name: Graversen, Therese
name: Bonnet, Philippe
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (stat.ML)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: In the pharmaceutical industry, the maintenance of production machines must be audited by the regulator. In this context, the problem of predictive maintenance is not when to maintain a machine, but what parts to maintain at a given point in time. The focus shifts from the entire machine to its component parts and prediction becomes a classification problem. In this paper, we focus on rolling-elements bearings and we propose a framework for predicting their degradation stages automatically. Our main contribution is a k-means bearing lifetime segmentation method based on high-frequency bearing vibration signal embedded in a latent low-dimensional subspace using an AutoEncoder. Given high-frequency vibration data, our framework generates a labeled dataset that is used to train a supervised model for bearing degradation stage detection. Our experimental results, based on the FEMTO Bearing dataset, show that our framework is scalable and that it provides reliable and actionable predictions for a range of different bearings.
description: Submitted to the KDD Applied Data Science track
Unraveling perceptual biases: Insights from spiking recurrent neural networks
Creators: name: Serrano-Fernandez, Luis
name: Beiran, Manuel
name: Parga, Nestor
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Symmetry Resolved Entanglement Entropy in Hyperbolic de Sitter Space
Creators: name: Gaur, Himanshu
name: Yajnik, Urjit A.
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: In this paper, we study the relation between entanglement and global internal symmetries on de Sitter space. We consider two symmetric causally disconnected regions in the hyperbolic chart on de Sitter space. Since entanglement measures characterises correlations, the study of entanglement between the two causally disconnected regions gives information about the long range correlations in de Sitter space. When a theory possesses an additive global internal symmetry, the entanglement measures for a state with fixed global charge may be decomposed into local charge sectors in either subsystem and thus providing a finer resolution of entanglement. Here we will consider two theories: free complex scalar field, and free Dirac field on de Sitter space. Both theories possess global internal $U(1)$ symmetry. We study the symmetry resolved entanglement entropy for both theories in the Bunch-Davies vacuum state. We find that the symmetry resolved entanglement entropy has equipartition into local charge sectors upto the terms that scale as $V_{H_3}^0$ in the limit of large $V_{H_3}$, where $V_{H_3}$ is the volume of either region. This equipartition however is only broken by the terms of order $O(1/V_{H_3})$. Consequently, we have equipartition of symmetry resolved entanglement entropy in the limit of infinite volume.
description: v2, 15 pages, 3 figures; Typos corrected; Figure 2, and Figure 3 modified; Discussions and new references added; Results unchanged; Accepted for publication in PRD
A remark on the $\mathfrak{M}_H(G)$-conjecture and Akashi series
Creators: name: Lim, Meng Fai
Publisher: name: arXiv
Year: 2013
Subjects: subject: Number Theory (math.NT)
subject: FOS: Mathematics
subject: 11R23, 11R34, 11G05, 11F80

description: In this article, we give a criterion for the dual Selmer group of an elliptic curve which has either good ordinary reduction or multiplicative reduction at every prime above $p$ to satisfy the $\M_H(G)$-conjecture. As a by-product of our calculations, we are able to define the Akashi series of the dual Selmer groups assuming the conjectures of Mazur and Schneider. Previously, the Akashi series are defined under the stronger assumption that the dual Selmer group satisfies the $\M_H(G)$-conjecture. We then establish a criterion for the vanishing of the dual Selmer groups using the Akashi series. We will apply this criterion to prove some results on the characteristic elements of the dual Selmer groups. Our methods in this paper are inspired by the work of Coates-Schneider-Sujatha and can be extended to the Greenberg Selmer groups attached to other ordinary representations, for instance, those coming from an $p$-ordinary modular form.
description: 26 pages; final version
Origin and function of gamma oscillatory complexity in hippocampal networks
Creators: name: Di Volo, Matteo
name: Douchamps, Vincent
name: Torcini, Alessandro
name: Battaglia, Demian
name: Goutagny, Romain
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Approximate next-to-next-to-leading order corrections to hadronic jet production
Creators: name: de Florian, Daniel
name: Hinderer, Patriz
name: Mukherjee, Asmita
name: Ringer, Felix
name: Vogelsang, Werner
Publisher: name: arXiv
Year: 2013
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: We determine dominant next-to-next-to-leading order QCD corrections to single-inclusive jet production at the LHC and Tevatron, using the established threshold resummation framework. In contrast to previous literature on this topic, our study incorporates all of the following features: (1) It properly accounts for the way a jet is defined in experiment and treated in available full next-to-leading order calculations, (2) It includes the three leading classes of logarithmic terms in the perturbative expansion, and (3) It is adapted to the full kinematics in jet transverse momentum and rapidity relevant for experiments. A recent full next-to-next-to-leading order calculation in the purely gluonic channel allows us to assess the region where our approximate corrections provide an accurate description. We expect our results to be important on the way to precision jet phenomenology at the LHC and as benchmark for further full next-to-next-to-leading order calculations.
description: 4 pages, 3 figures, improved version
Distribution of toric periods of modular forms on definite quaternion algebras
Creators: name: Suzuki, Miyu
name: Wakatsuki, Satoshi
name: Yokoyama, Shun'ichi
Publisher: name: arXiv
Year: 2022
Subjects: subject: Number Theory (math.NT)
subject: FOS: Mathematics
subject: 11F67

description: Let $D$ be a definite quaternion algebra over $\mathbb{Q}$ and $\mathcal{O}$ an Eichler order in $D$ of square-free level. We study distribution of the toric periods of algebraic modular forms of level $\mathcal{O}$. We focus on two problems: non-vanishing and sign changes. Firstly, under certain conditions on $\mathcal{O}$, we prove the non-vanishing of the toric periods for positive proportion of imaginary quadratic fields. This improves the known lower bounds toward Goldfeld's conjecture in some cases and provides evidence for similar non-vanishing conjectures for central values of twisted automorphic $L$-functions. Secondly, we show that the sequence of toric periods has infinitely many sign changes. This proves the sign changes of the Fourier coefficients $\{a(n)\}_n$ of weight 3/2 modular forms, where $n$ ranges over fundamental discriminants. In the final section, we present numerical experiments in some cases and formulate several conjectures based on them.
description: 35 pages, 2 figures available at http://wakatsuki.w3.kanazawa-u.ac.jp/Figures.html, minor revision based on the referees' comments
Improving the performance of algorithms to find communities in networks
Creators: name: Darst, Richard K.
name: Nussinov, Zohar
name: Fortunato, Santo
Publisher: name: arXiv
Year: 2013
Subjects: subject: Physics and Society (physics.soc-ph)
subject: Social and Information Networks (cs.SI)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Many algorithms to detect communities in networks typically work without any information on the cluster structure to be found, as one has no a priori knowledge of it, in general. Not surprisingly, knowing some features of the unknown partition could help its identification, yielding an improvement of the performance of the method. Here we show that, if the number of clusters were known beforehand, standard methods, like modularity optimization, would considerably gain in accuracy, mitigating the severe resolution bias that undermines the reliability of the results of the original unconstrained version. The number of clusters can be inferred from the spectra of the recently introduced non-backtracking and flow matrices, even in benchmark graphs with realistic community structure. The limit of such two-step procedure is the overhead of the computation of the spectra.
description: 9 pages, 6 figures. Published version
title: Die Dienststellen des Landesdenkmalamtes
Creators: name: Redaktion, Die
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 28, Nr. 1 (1999), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Locating the source of forced oscillations in transmission power grids
Creators: name: Delabays, Robin
name: Lokhov, Andrey Y.
name: Tyloo, Melvyn
name: Vuffray, Marc
Publisher: name: arXiv
Year: 2022
Subjects: subject: Adaptation and Self-Organizing Systems (nlin.AO)
subject: Optimization and Control (math.OC)
subject: FOS: Physical sciences
subject: FOS: Mathematics

description: Forced oscillation event in power grids refers to a state where malfunctioning or abnormally operating equipment causes persisting periodic disturbances in the system. While power grids are designed to damp most of perturbations during standard operations, some of them can excite normal modes of the system and cause significant energy transfers across the system, creating large oscillations thousands of miles away from the source. Localization of the source of such disturbances remains an outstanding challenge due to a limited knowledge of the system parameters outside of the zone of responsibility of system operators. Here, we propose a new method for locating the source of forced oscillations which addresses this challenge by performing a simultaneous dynamic model identification using a principled maximum likelihood approach. We illustrate the validity of the algorithm on a variety of examples where forcing leads to resonance conditions in the system dynamics. Our results establish that an accurate knowledge of system parameters is not required for a successful inference of the source and frequency of a forced oscillation. We anticipate that our method will find a broader application in general dynamical systems that can be well-described by their linearized dynamics over short periods of time.
description: Main text: 9 pages, 4 figures. Supplementary material: 10 pages, 9 figures
title: Hinter Gittern ohne Ausblick. Das Gefängnis in Laupheim (Kr. Biberach)
Creators: name: Kraume-Probst, Sabine
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 31, Nr. 1 (2002), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
title: Das wieder gewonnene Stifterepitaph der Schmiedelfelder Schlosskapelle. Ein Puzzle mit vielen Unbekannten
Creators: name: Günther, Silke
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 31, Nr. 4 (2002), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
The first confirmation of V-type asteroids among the Mars crosser population
Creators: name: Ribeiro, A. O.
name: Roig, F.
name: Cañada-Assandri, M.
name: Carvano, J. M. F.
name: Jasmin, F. L.
name: Alvarez-Candal, A.
name: Gil-Hutton, R.
Publisher: name: arXiv
Year: 2013
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: FOS: Physical sciences

description: The Mars crossing region constitutes a path to deliver asteroids from the Inner Main Belt to the Earth crossing space. While both the Inner Main Belt and the population of Earth crossing asteroids contains a significant fraction of asteroids belonging to the V taxonomic class, only two of such V-type asteroids has been detected in the Mars crossing region up to now. In this work, we searched for asteroids belonging to the V class among the population of Mars crossing asteroids, in order to support alternative paths to the delivery of this bodies into the Earth crossing region. We selected 18 candidate V-type asteroids in the Mars crossing region using observations contained in the Sloan Digital Sky Survey Moving Objects Catalog. Then, we observed 4 of these candidates to take their visible spectra using the Southern Astrophysical Research Telescope (SOAR). We also performed the numerical simulation of the orbital evolution of the observed asteroids. We confirmed that 3 of the observed asteroids belong to the V class, and one of these may follow a path that drives it to an Earth collision in some tens of million years.
Predictive safety filter using system level synthesis
Creators: name: Leeman, Antoine P.
name: Köhler, Johannes
name: Benanni, Samir
name: Zeilinger, Melanie N.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Systems and Control (eess.SY)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: Safety filters provide modular techniques to augment potentially unsafe control inputs (e.g. from learning-based controllers or humans) with safety guarantees in the form of constraint satisfaction. In this paper, we present an improved model predictive safety filter (MPSF) formulation, which incorporates system level synthesis techniques in the design. The resulting SL-MPSF scheme ensures safety for linear systems subject to bounded disturbances in an enlarged safe set. It requires less severe and frequent modifications of potentially unsafe control inputs compared to existing MPSF formulations to certify safety. In addition, we propose an explicit variant of the SL-MPSF formulation, which maintains scalability, and reduces the required online computational effort - the main drawback of the MPSF. The benefits of the proposed system level safety filter formulations compared to state-of-the-art MPSF formulations are demonstrated using a numerical example.
description: https://gitlab.ethz.ch/ics/SLS_safety_filter/
Derivation of a statistical model for classical systems obeying fractional exclusion principle
Creators: name: Roy, Projesh Kumar
Publisher: name: arXiv
Year: 2022
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: FOS: Physical sciences

description: The violation of the Pauli principle has been surmised in several models of the Fractional Exclusion Statistics and successfully applied to several quantum systems. In this paper, a classical alternative of the exclusion statistics is studied using the maximum entropy methods. The difference between the Bose-Einstein statistics and the Maxwell-Boltzmann statistics is understood in terms of a separable quantity, namely the degree of indistinguishability. Starting from the usual Maxwell-Boltzmann microstate counting formula, a special restriction related to the degree of indistinguishability is incorporated using Lagrange multipliers to derive the probability distribution function at equilibrium under NVE conditions. It is found that the resulting probability distribution function generates real positive values within the permissible range of parameters. For a dilute system, the probability distribution function is intermediate between the Fermi-Dirac and Bose-Einstein statistics and follows the exclusion principle. Properties of various variables of this novel statistical model are studied and possible application to classical thermodynamics is discussed.
description: 17 pages, 1 figure
title: Inhalt
Creators: name: Redaktion, Die
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 32, Nr. 1 (2003), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Inferring stochastic low-rank recurrent neural networks from neural data
Creators: name: Pals, Matthijs
name: Sağtekin, A E.
name: Pei, Felix
name: Gloeckler, Manuel
name: Macke, Jakob H.
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Semantic Embodiment: Decoding Action Words through Topographic Neuronal Representation with Brain-Constrained Network
Creators: name: Carrière, Maxime
name: Tomasello, Rosario
name: Pulvermüller, Friedemann
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Cluster-based reduced-order modelling of a mixing layer
Creators: name: Kaiser, Eurika
name: Noack, Bernd R.
name: Cordier, Laurent
name: Spohn, Andreas
name: Segond, Marc
name: Abel, Markus
name: Daviller, Guillaume
name: Östh, Jan
name: Krajnović, Siniša
name: Niven, Robert K.
Publisher: name: arXiv
Year: 2013
Subjects: subject: Fluid Dynamics (physics.flu-dyn)
subject: Chaotic Dynamics (nlin.CD)
subject: Data Analysis, Statistics and Probability (physics.data-an)
subject: FOS: Physical sciences

description: We propose a novel cluster-based reduced-order modelling (CROM) strategy of unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger's group (Burkardt et al. 2006) and and transition matrix models introduced in fluid dynamics in Eckhardt's group (Schneider et al. 2007). CROM constitutes a potential alternative to POD models and generalises the Ulam-Galerkin method classically used in dynamical systems to determine a finite-rank approximation of the Perron-Frobenius operator. The proposed strategy processes a time-resolved sequence of flow snapshots in two steps. First, the snapshot data are clustered into a small number of representative states, called centroids, in the state space. These centroids partition the state space in complementary non-overlapping regions (centroidal Voronoi cells). Departing from the standard algorithm, the probabilities of the clusters are determined, and the states are sorted by analysis of the transition matrix. Secondly, the transitions between the states are dynamically modelled using a Markov process. Physical mechanisms are then distilled by a refined analysis of the Markov process, e.g. using finite-time Lyapunov exponent and entropic methods. This CROM framework is applied to the Lorenz attractor (as illustrative example), to velocity fields of the spatially evolving incompressible mixing layer and the three-dimensional turbulent wake of a bluff body. For these examples, CROM is shown to identify non-trivial quasi-attractors and transition processes in an unsupervised manner. CROM has numerous potential applications for the systematic identification of physical mechanisms of complex dynamics, for comparison of flow evolution models, for the identification of precursors to desirable and undesirable events, and for flow control applications exploiting nonlinear actuation dynamics.
description: 48 pages, 30 figures. Revised version with additional material. Accepted for publication in Journal of Fluid Mechanics
Short-Distance Connections Enhance Neural Network Dynamics
Creators: name: Hussainyar, Mohmmad Sharif
name: Li, Dong
name: Hilgetag, Claus C.
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Connectome and task predict neural activity across the fly visual system
Creators: name: Lappalainen, Janne K.
name: Tschopp, Fabian D.
name: Prakhya, Sridhama
name: McGill, Mason
name: Nern, Aljoscha
name: Shinomiya, Kazunori
name: Takemura, Shin-Ya
name: Gruntman, Eyal
name: Macke, Jakob H.
name: Turaga, Srinivas C.
Publisher: name: G-Node
Year: 2024
Subjects: Computational Neuroscience
Networks and dynamical systems

description: Bernstein Conference 2024 abstract. https://bernstein-conference.de
Observing axions through photon ring dimming of black holes
Creators: name: Nomura, Kimihiro
name: Saito, Kaishu
name: Soda, Jiro
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: It is known that magnetic fields exist near black holes and photons can go around black holes due to strong gravity. Utilizing these facts, we can probe hypothetical pseudoscalar particles, so-called axions. In fact, photons can be converted into axions when they propagate in a magnetic field. The conversion of such photons into axions leads to a dimming of the photon ring around the black hole shadow. We show that photon ring dimming can occur efficiently for supermassive black holes. Remarkably, it turns out that the maximal dimming rate of the photon ring is 25%. In the case of M87*, the dimming of 10% will be observed in the X-ray and gamma-ray bands if the angular resolution of $10^{-5}$ arcsec is achieved. The frequency band and the magnitude of the dimming depend on the axion-photon coupling and axion mass. Hence, the distorted spectrum of the photon ring provides a novel tool for detecting axions.
description: 18 pages, 4 figures
title: Inhalt
Creators: name: Redaktion, Die
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 32, Nr. 2 (2003), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Kullback-Leibler Approximation for Probability Measures on Infinite Dimensional Spaces
Creators: name: Pinski, Frank
name: Simpson, Gideon
name: Stuart, Andrew
name: Weber, Hendrik
Publisher: name: arXiv
Year: 2013
Subjects: subject: Probability (math.PR)
subject: FOS: Mathematics

description: In a variety of applications it is important to extract information from a probability measure $μ$ on an infinite dimensional space. Examples include the Bayesian approach to inverse problems and possibly conditioned) continuous time Markov processes. It may then be of interest to find a measure $ν$, from within a simple class of measures, which approximates $μ$. This problem is studied in the case where the Kullback-Leibler divergence is employed to measure the quality of the approximation. A calculus of variations viewpoint is adopted and the particular case where $ν$ is chosen from the set of Gaussian measures is studied in detail. Basic existence and uniqueness theorems are established, together with properties of minimising sequences. Furthermore, parameterisation of the class of Gaussians through the mean and inverse covariance is introduced, the need for regularisation is explained, and a regularised minimisation is studied in detail. The calculus of variations framework resulting from this work provides the appropriate underpinning for computational algorithms.
description: 38 pages, 2 figures
A Dataset of Images of Public Streetlights with Operational Monitoring using Computer Vision Techniques
Creators: name: Mavromatis, Ioannis
name: Stanoev, Aleksandar
name: Carnelli, Pietro
name: Jin, Yichao
name: Sooriyabandara, Mahesh
name: Khan, Aftab
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: A dataset of street light images is presented. Our dataset consists of $\sim350\textrm{k}$ images, taken from 140 UMBRELLA nodes installed in the South Gloucestershire region in the UK. Each UMBRELLA node is installed on the pole of a lamppost and is equipped with a Raspberry Pi Camera Module v1 facing upwards towards the sky and lamppost light bulb. Each node collects an image at hourly intervals for 24h every day. The data collection spans for a period of six months. Each image taken is logged as a single entry in the dataset along with the Global Positioning System (GPS) coordinates of the lamppost. All entries in the dataset have been post-processed and labelled based on the operation of the lamppost, i.e., whether the lamppost is switched ON or OFF. The dataset can be used to train deep neural networks and generate pre-trained models providing feature representations for smart city CCTV applications, smart weather detection algorithms, or street infrastructure monitoring. The dataset can be found at \url{https://doi.org/10.5281/zenodo.6046758}.
description: Data in Brief Journal
Parametric models and information geometry on W*-algebras
Creators: name: Ciaglia, Florio M.
name: Di Nocera, Fabio
name: Jost, Jürgen
name: Schwachhöfer, Lorenz
Publisher: name: arXiv
Year: 2022
Subjects: subject: Mathematical Physics (math-ph)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We introduce the notion of smooth parametric model of normal positive linear functionals on possibly infinite-dimensional W*-algebras generalizing the notions of parametric models used in classical and quantum information geometry. We then use the Jordan product naturally available in this context in order to define a Riemannian metric tensor on parametric models satsfying suitable regularity conditions. This Riemannian metric tensor reduces to the Fisher-Rao metric tensor, or to the Fubini-Study metric tensor, or to the Bures-Helstrom metric tensor when suitable choices for the W*-algebra and the models are made.
description: 24 pages. Comments are welcome!
Supplementary document for Optimization of the Conversion Efficiency and Noise Figure of an Optical Frequency Converter based on a Dual-Pump Fiber Phase Sensitive Amplifier - 6107344.pdf
Creators: name: Chatterjee, Debanuj
name: Bouasria, Yousra
name: Goldfarb, Fabienne
name: HASSOUNI, Yassine
name: Bretenaker, Fabien
Publisher: name: Optica Publishing Group
Year: 2022
Subjects: Uncategorized

description: Supplemental Document
Aperiodic pseudorandom number generators based on infinite words
Creators: name: Balkova, Lubomira
name: Bucci, Michelangelo
name: De Luca, Alessandro
name: Hladky, Jiri
name: Puzynina, Svetlana
Publisher: name: arXiv
Year: 2013
Subjects: subject: Combinatorics (math.CO)
subject: Discrete Mathematics (cs.DM)
subject: Formal Languages and Automata Theory (cs.FL)
subject: FOS: Mathematics
subject: FOS: Computer and information sciences
subject: G.3; F.4.3; G.2.1; G.2.3
subject: 68R15

description: In this paper we study how certain families of aperiodic infinite words can be used to produce aperiodic pseudorandom number generators (PRNGs) with good statistical behavior. We introduce the \emph{well distributed occurrences} (WELLDOC) combinatorial property for infinite words, which guarantees absence of the lattice structure defect in related pseudorandom number generators. An infinite word $u$ on a $d$-ary alphabet has the WELLDOC property if, for each factor $w$ of $u$, positive integer $m$, and vector $\mathbf v\in\mathbb Z_{m}^{d}$, there is an occurrence of $w$ such that the Parikh vector of the prefix of $u$ preceding such occurrence is congruent to $\mathbf v$ modulo $m$. (The Parikh vector of a finite word $v$ over an alphabet $\mathcal A$ has its $i$-th component equal to the number of occurrences of the $i$-th letter of $\mathcal A$ in $v$.) We prove that Sturmian words, and more generally Arnoux-Rauzy words and some morphic images of them, have the WELLDOC property. Using the TestU01 and PractRand statistical tests, we moreover show that not only the lattice structure is absent, but also other important properties of PRNGs are improved when linear congruential generators are combined using infinite words having the WELLDOC property.
description: updated and extended version; 24 pages
title: Von Stuttgart nach Esslingen. Ein Baudenkmal wird für das Landesdenkmalamt umgenutzt
Creators: name: Roggenbuck-Azad, Ulrike
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 32, Nr. 2 (2003), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Distributions of Off-Diagonal Scattering Matrix Elements: Exact Results
Creators: name: Nock, André
name: Kumar, Santosh
name: Sommers, Hans-Jürgen
name: Guhr, Thomas
Publisher: name: arXiv
Year: 2013
Subjects: subject: Statistical Mechanics (cond-mat.stat-mech)
subject: Mathematical Physics (math-ph)
subject: Chaotic Dynamics (nlin.CD)
subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences
subject: 15B52, 60E05, 60E10, 81U35, 82B31

description: Scattering is a ubiquitous phenomenon which is observed in a variety of physical systems which span a wide range of length scales. The scattering matrix is the key quantity which provides a complete description of the scattering process. The universal features of scattering in chaotic systems is most generally modeled by the Heidelberg approach which introduces stochasticity to the scattering matrix at the level of the Hamiltonian describing the scattering center. The statistics of the scattering matrix is obtained by averaging over the ensemble of random Hamiltonians of appropriate symmetry. We derive exact results for the distributions of the real and imaginary parts of the off-diagonal scattering matrix elements applicable to orthogonally-invariant and unitarily-invariant Hamiltonians, thereby solving a long standing problem.
description: 29 pages, 5 figures, Published version
title: Die Mariä-Entschlafens-Kirche (Uspenskij- Kirche) in Wolotowo bei Nowgorod. Dokumentation – Kriegszerstörung – Wiederaufbau und Restaurierung
Creators: name: Jakobs, Dörthe
name: Reichwald, Helmut F.
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 32, Nr. 4 (2003), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Radial Transport of Large-Scale Magnetic Fields in Accretion Disks. I. Steady Solutions and an Upper Limit on the Vertical Field Strength
Creators: name: Okuzumi, Satoshi
name: Takeuchi, Taku
name: Muto, Takayuki
Publisher: name: arXiv
Year: 2013
Subjects: subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: Large-scale magnetic fields are key ingredients of magnetically driven disk accretion. We study how large-scale poloidal fields evolve in accretion disks, with the primary aim of quantifying the viability of magnetic accretion mechanisms in protoplanetary disks. We employ a kinematic mean-field model for poloidal field transport and focus on steady states where inward advection of a field balances with outward diffusion due to effective resistivities. We analytically derive the steady-state radial distribution of poloidal fields in highly conducting accretion disks. The analytic solution reveals an upper limit on the strength of large-scale vertical fields attainable in steady states. Any excess poloidal field will be diffused away within a finite time, and we demonstrate this with time-dependent numerical calculations of the mean-field equations. We apply this upper limit to large-scale vertical fields threading protoplanetary disks. We find that the maximum attainable strength is about 0.1 G at 1 AU, and about 1 mG at 10 AU from the central star. When combined with recent magnetic accretion models, the maximum field strength translates into the maximum steady-state accretion rate of $\sim 10^{-7} M_\odot {\rm yr}^{-1}$, in agreement with observations. We also find that the maximum field strength is ~ 1 kG at the surface of the central star provided that the disk extends down to the stellar surface. This implies that any excess stellar poloidal field of strength >~ kG can be transported to the surrounding disk. This might in part resolve the magnetic flux problem in star formation.
description: 16 pages, 9 figures, to appear in ApJ. v3: typos corrected, Figure 7 updated, some references added, a note added in proof
title: Adolf von Oechelhaeuser – ein Badener auf den Tagen für Denkmalpflege von 1900-1922
Creators: name: Schwarzkopf, Christoph
Publisher: name: University Library Heidelberg
Year: 2014

description: Denkmalpflege in Baden-Württemberg – Nachrichtenblatt der Landesdenkmalpflege, Bd. 33, Nr. 1 (2004), Beginn und Erscheinungsfrequenz: Ausgaben pro Band: 4
Phanaeus funereus Balthasar 1939
Creators: name: Lizardo, Viridiana
name: Moctezuma, Víctor
name: Escobar-Sarria, Federico
Publisher: name: Zenodo
Year: 2022
Subjects: Biodiversity
Taxonomy
Animalia
Arthropoda
Insecta
Coleoptera
Scarabaeidae
Phanaeus
Phanaeus funereus

description: Phanaeus funereus Balthasar, 1939 Recorded Distribution: COLOMBIA: Chocó — Quibdó, ECUADOR: Esmeraldas — Eloy Alfaro, Guayas — General Antonio Elizalde, Los Rios — Mocache, Manabi — Chone, Pichincha — Quito. Altitude: from 28 to 2880 m a.s.l. Biomes: Tropical & Subtropical Dry Broadleaf Forests, Tropical & Subtropical Moist Broadleaf Forests. Ecorregions: NEOTROPIC: Ecuadorian dry forests, Chocó-Darién moist forests, Western Ecuador moist forests, Northwest Andean montane forests. Predicted distribution: This species distributes from -5.39° to 10.39° latitude in an area of 114,300 Km2. Its predicted distribution has a mean annual temperature of 22.95-25.28° C with a maximum difference of temperature of 10.61° C during the year and mean precipitation of 1126-2266 mm per year.
description: Published as part of Lizardo, Viridiana, Moctezuma, Víctor & Escobar-Sarria, Federico, 2022, Predicted and recorded distribution maps of the genus Phanaeus (Coleoptera: Scarabaeidae). Supplementary material of Distribution, Regionalization, and Diversity of the dung beetle genus Phanaeus MacLeay (Coleoptera: Scarabaeidae) using Species Distribution Models, pp. 1-77 in Zootaxa (suppl.) (suppl.) 5213 (5) on page 26, DOI: 10.5281/zenodo.7387492
Learning new physics efficiently with nonparametric methods
Creators: name: Letizia, Marco
name: Losapio, Gianvito
name: Rando, Marco
name: Grosso, Gaia
name: Wulzer, Andrea
name: Pierini, Maurizio
name: Zanetti, Marco
name: Rosasco, Lorenzo
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: Machine Learning (cs.LG)
subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any continuous function given enough data. Based on the original proposal by D'Agnolo and Wulzer (arXiv:1806.02350), the model evaluates the compatibility between experimental data and a reference model, by implementing a hypothesis testing procedure based on the likelihood ratio. Model-independence is enforced by avoiding any prior assumption about the presence or shape of new physics components in the measurements. We show that our approach has dramatic advantages compared to neural network implementations in terms of training times and computational resources, while maintaining comparable performances. In particular, we conduct our tests on higher dimensional datasets, a step forward with respect to previous studies.
description: 22 pages, 13 figures
Discrete symmetry transformations on non-abelian gauge fields
Creators: name: Lahiri, Amitabha
name: Pal, Palash B.
name: Shokova, Marina
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: All gauge bosons of a non-abelian gauge theory do not transform the same way under the discrete transformations of time-reversal and charge-conjugation. Moreover, the transformations rules depend on how the generators are chosen. We show how well-defined rules pertain only to specific choices of generators, and then show how unified rules can be constructed, using matrix forms of the gauge bosons, which are completely independent of the choice of generators.
description: 10 pages, no figure, LaTeX