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It is well known that if $A\subseteq\R^n$ is an analytic set of Hausdorff dimension $a$, then $\dim_H(\pi_VA)=\min\{a,k\}$ for a.e. $V\in G(n,k)$, where $\pi_V$ is the orthogonal projection of $A$ onto $V$. In this paper we study how large the exceptional set \begin{center} $\{V\in G(n,k) \mid \dim_H(\pi_V A) < s\}$ \end{center} can be for a given $s\le\min\{a,k\}.$ We improve previously known estimates on the dimension of the exceptional set, and we show that our estimates are sharp for $k=1$ and for $k=n-1$.

In explanations, explainers have mental representations of explainees' developing knowledge and shifting interests regarding the explanandum. These mental representations are dynamic in nature and develop over time, thereby enabling explainers to react to explainees' needs by adapting and customizing the explanation. XAI should be able to react to explainees' needs in a similar manner. Therefore, a component that incorporates aspects of explainers' mental representations of explainees is required. In this study, we took first steps by investigating explainers' mental representations in everyday explanations of technological artifacts. According to the dual nature theory, technological artifacts require explanations with two distinct perspectives, namely observable and measurable features addressing "Architecture" or interpretable aspects addressing "Relevance". We conducted extended semi structured pre-, post- and video recall-interviews with explainers (N=9) in the context of an explanation. The transcribed interviews were analyzed utilizing qualitative content analysis. The explainers' answers regarding the explainees' knowledge and interests with regard to the technological artifact emphasized the vagueness of early assumptions of explainers toward strong beliefs in the course of explanations. The assumed knowledge of explainees in the beginning is centered around Architecture and develops toward knowledge with regard to both Architecture and Relevance. In contrast, explainers assumed higher interests in Relevance in the beginning to interests regarding both Architecture and Relevance in the further course of explanations. Further, explainers often finished the explanation despite their perception that explainees still had gaps in knowledge. These findings are transferred into practical implications relevant for user models for adaptive explainable systems.

Spatially-resolved emission line kinematics are invaluable to investigating fundamental galaxy properties and have become increasingly accessible for galaxies at $z\gtrsim0.5$ through sensitive near-infrared imaging spectroscopy and millimeter interferometry. Kinematic modeling is at the core of the analysis and interpretation of such data sets, which at high-z present challenges due to lower signal-to-noise ratio (S/N) and resolution compared to data of local galaxies. We present and test the 3D fitting functionality of DysmalPy, examining how well it recovers intrinsic disk rotation velocity and velocity dispersion, using a large suite of axisymmetric models, covering a range of galaxy properties and observational parameters typical of $z\sim1$-$3$ star-forming galaxies. We also compare DysmalPy's recovery performance to that of two other commonly used codes, GalPak3D and 3DBarolo, which we use in turn to create additional sets of models to benchmark DysmalPy. Over the ranges of S/N, resolution, mass, and velocity dispersion explored, the rotation velocity is accurately recovered by all tools. The velocity dispersion is recovered well at high S/N, but the impact of methodology differences is more apparent. In particular, template differences for parametric tools and S/N sensitivity for the non-parametric tool can lead to differences up to a factor of 2. Our tests highlight and the importance of deep, high-resolution data and the need for careful consideration of: (1) the choice of priors (parametric approaches), (2) the masking (all approaches) and, more generally, evaluating the suitability of each approach to the specific data at hand. This paper accompanies the public release of DysmalPy., Comment: 38 pages, 21 figures, accepted for publication in ApJ

Game-theoretic characterizations of process equivalences traditionally form a central topic in concurrency; for example, most equivalences on the classical linear-time / branching-time spectrum come with such characterizations. Recent work on so-called graded semantics has led to a generic behavioural equivalence game that covers the mentioned games on the linear-time~/ branching-time spectrum and moreover applies in coalgebraic generality, and thus instantiates also to equivalence games on systems with non-relational branching type (probabilistic, weighted, game-based etc.). In the present work, we generalize this approach to cover other types of process comparison beyond equivalence, such as behavioural preorders or pseudometrics. At the most general level, we abstract such notions of behavoiural conformance in terms of topological categories, and later specialize to conformances presented as relational structures to obtain a concrete syntax. We obtain a sound and complete generic game for behavioural conformances in this sense. We present a number of instantiations, obtaining game characterizations of, e.g., trace inclusion, probabilistic trace distance, bisimulation topologies, and simulation distances on metric labelled transition systems.

Deep learning is an emerging field revolutionizing various industries, including natural language processing, computer vision, and many more. These domains typically require an extensive amount of data for optimal performance, potentially utilizing huge centralized data repositories. However, such centralization could raise privacy issues concerning the storage of sensitive data. To address this issue, federated learning was developed. It is a newly distributed learning technique that enables to collaboratively train a deep learning model on decentralized devices, referred to as clients, without compromising their data privacy. Traditional federated learning methods often suffer from severe performance degradation when the data distribution among clients differs significantly. This becomes especially problematic in the case of label distribution skew, where the distribution of labels varies across clients. To address this, a novel method called FedEntOpt is proposed. FedEntOpt is designed to mitigate performance issues caused by label distribution skew by maximizing the entropy of the global label distribution of the selected client subset in each federated learning round. This ensures that the aggregated model parameters from the clients were exhibited to data from all available labels, which improves the accuracy of the global model. Extensive experiments on several benchmark datasets show that the proposed method outperforms several state-of-the-art algorithms by up to 6% in classification accuracy, demonstrating robust and superior performance, particularly under low participation rates. In addition, it offers the flexibility to be combined with them, enhancing their performance by over 40%.

Molybdenum (Mo) due to its optimal structural, physical, and acoustic properties find application as electrode material in aluminum scandium nitride (AlScN) and aluminum nitride (AlN) based bulk acoustic wave (BAW) resonators. Epitaxial Mo thin films exhibiting low resistivity can improve the performance of the BAW resonator by enhancing both the electromechanical coupling coefficient and quality factor. In this study, we systematically vary the growth temperature of Mo grown on fiber-textured and epitaxial wurtzite-aluminum nitride (AlN) to study the changes in structural and electrical properties of the Mo films. Results show that Mo grown at 700{\deg}C on epitaxial AlN exhibit low surface roughness, large average grain diameter, low resistivity, and high crystal quality. XRD pole figure and phi-scan reveal that irrespective of the growth temperature, Mo is fiber textured on fiber-textured AlN, and has three rotational domains on epitaxial AlN. The study shows that the resistivity of Mo reduces with increasing growth temperature, which we relate to increasing average grain diameter. Additionally, we show that fiber-textured Mo has more high angle grain boundaries resulting in consistently higher resistivity than its epitaxial equivalent., Comment: 13 pages, 7 figures, 1 supplementary file

Red quasars, often associated with potent [OIII] outflows on both galactic and circumgalactic scales, may play a pivotal role in galactic evolution and black hole feedback. In this work, we explore the [FeII] emission in one such quasar at redshift z = 0.4352, F2M J110648.32+480712.3, using the integral field unit (IFU) mode of the Near Infrared Spectrograph (NIRSpec) aboard the James Webb Space Telescope (JWST). Our observations reveal clumpy [FeII] gas located to the south of the quasar. By comparing the kinematics of [FeII] and [OIII], we find that the clumpy [FeII] gas in the southeast and southwest aligns with the outflow, exhibiting similar median velocities up to v_50 ~ 1200 km/s and high velocity widths W_80 > 1000 km/s. In contrast, the [FeII] gas to the south shows kinematics inconsistent with the outflow, with W_80 ~ 500 km/s, significantly smaller than the [OIII] at the same location, suggesting that the [FeII] may be confined within the host galaxy. Utilizing standard emission-line diagnostic ratios, we map the ionization sources of the gas. According to the MAPPINGS III shock models for [FeII]/Pabeta, the regions to the southwest and southeast of the quasar are primarily photoionized. Conversely, the [FeII] emission to the south is likely excited by shocks generated by the back-pressure of the outflow on the galaxy disk, a direct signature of the impact of the quasar on its host.

Aluminum scandium nitride (Al$_{1-x}$Sc$_x$N) is a promising material for ferroelectric devices due to its large remanent polarization, scalability, and compatibility with semiconductor technology. By doping AlN with Sc, the bonds in the polar AlN structure are weakened, which enables ferroelectric switching below the dielectric breakdown field. However, one disadvantage of Sc doping is that it increases the material's tendency towards oxidation. In the present study, the oxidation process of tungsten-capped and uncapped Al$_{0.83}$Sc$_{0.17}$N thin films is investigated by hard X-ray photoelectron spectroscopy (HAXPES). The samples had been exposed to air for either two weeks or 6 months. HAXPES spectra indicate the replacement of nitrogen by oxygen, and the tendency of oxygen to favor oxidation with Sc rather than Al. The appearance of an N$_2$ spectral feature thus can be directly related to the oxidation process. We present an oxidation model that mimics these spectroscopic results of the element-specific oxidation processes within Al$_{1-x}$Sc$_x$N. Finally, in operando HAXPES data of uncapped and capped AlScN-capacitor stacks are interpreted using the proposed model.

Refrigeration limits are of fundamental and practical importance. We here show that quantum systems can be cooled below existing incoherent cooling bounds by employing coherent virtual qubits, even if the amount of coherence is incompletely known. Virtual subsystems, that do not necessarily correspond to a natural eigensubspace of a system, are a key conceptual tool in quantum information science and quantum thermodynamics. We derive universal coherent cooling limits and introduce specific protocols to reach them. As an illustration, we propose a generalized algorithmic cooling protocol that outperforms its current incoherent counterpart. Our results provide a general framework to investigate the performance of coherent refrigeration processes., Comment: 6+8 pages, 3+6 figures

Stereotypical bias encoded in language models (LMs) poses a threat to safe language technology, yet our understanding of how bias manifests in the parameters of LMs remains incomplete. We introduce local contrastive editing that enables the localization and editing of a subset of weights in a target model in relation to a reference model. We deploy this approach to identify and modify subsets of weights that are associated with gender stereotypes in LMs. Through a series of experiments, we demonstrate that local contrastive editing can precisely localize and control a small subset (< 0.5%) of weights that encode gender bias. Our work (i) advances our understanding of how stereotypical biases can manifest in the parameter space of LMs and (ii) opens up new avenues for developing parameter-efficient strategies for controlling model properties in a contrastive manner., Comment: Accepted at EMNLP 2024

While behavioural equivalences among systems of the same type, such as Park/Milner bisimilarity of labelled transition systems, are an established notion, a systematic treatment of relationships between systems of different type is currently missing. We provide such a treatment in the framework of universal coalgebra, in which the type of a system (nondeterministic, probabilistic, weighted, game-based etc.) is abstracted as a set functor: We introduce relational connectors among set functors, which induce notions of heterogeneous (bi)simulation among coalgebras of the respective types. We give a number of constructions on relational connectors. In particular, we identify composition and converse operations on relational connectors; we construct corresponding identity relational connectors, showing that the latter generalize the standard Barr extension of weak-pullback-preserving functors; and we introduce a Kantorovich construction in which relational connectors are induced from relations between modalities. For Kantorovich relational connectors, one has a notion of dual-purpose modal logic interpreted over both system types, and we prove a corresponding Hennessy-Milner-type theorem stating that generalized (bi)similarity coincides with theory inclusion on finitely-branching systems. We apply these results to a number of example scenarios involving labelled transition systems with different label alphabets, probabilistic systems, and input/output conformances.

Generic notions of bisimulation for various types of systems (nondeterministic, probabilistic, weighted etc.) rely on identity-preserving (normal) lax extensions of the functor encapsulating the system type, in the paradigm of universal coalgebra. It is known that preservation of weak pullbacks is a sufficient condition for a functor to admit a normal lax extension (the Barr extension, which in fact is then even strict); in the converse direction, nothing is currently known about necessary (weak) pullback preservation conditions for the existence of normal lax extensions. In the present work, we narrow this gap by showing on the one hand that functors admitting a normal lax extension preserve 1/4-iso pullbacks, i.e. pullbacks in which at least one of the projections is an isomorphism. On the other hand, we give sufficient conditions, showing that a functor admits a normal lax extension if it weakly preserves either 1/4-iso pullbacks and 4/4-epi pullbacks (i.e. pullbacks in which all morphisms are epic) or inverse images. We apply these criteria to concrete examples, in particular to functors modelling neighbourhood systems and weighted systems.

Quasar feedback may play a key role in the evolution of massive galaxies. The dust-reddened quasar, F2M110648.35$+$480712 at $z = 0.4352$ is one of the few cases at its redshift that exhibits powerful quasar feedback through bipolar outflows. Our new observation with the integral field unit mode of Near-infrared Spectrograph onboard JWST opens a new window to examine this spectacular outflow through Pa$\alpha$ emission line with $\sim$3$\times$ better spatial resolution than previous work. The morphology and kinematics of the Pa$\alpha$ nebula confirm the existence of a bipolar outflow extending on a scale of $\sim$17$\times$14 kpc and with a velocity reaching $\sim$1100 km s$^{-1}$. The higher spatial resolution of our new observation leads to more reliable measurements of outflow kinematics. Considering only the spatially resolved outflow and assuming an electron density of 100 cm$^{-2}$, the mass, momentum and kinetic energy outflow rates are $\sim$50-210 M$_{\odot}$ yr$^{-1}$, $\sim$0.3-1.7$\times$10$^{36}$ dynes ($\sim$14-78\% of the quasar photon momentum flux) and $\sim$0.16-1.27$\times$10$^{44}$ erg s$^{-1}$ ($\sim$0.02-0.20\% of the quasar bolometric luminosity), respectively. The local instantaneous outflow rates generally decrease radially. We infer that the quasar is powerful enough to drive the outflow, while stellar processes cannot be overlooked as a contributing energy source. The mass outflow rate is $\sim$0.4-1.5 times the star formation rate, and the ratio of kinetic energy outflow rate to the quasar bolometric luminosity is comparable to the minimum value required for negative quasar feedback in simulations. This outflow may help regulate the star formation activity within the system to some extent., Comment: 14 pages, 6 figures, 1 table, ApJ in review

Owing to their similarities with giant exoplanets, brown dwarf companions of stars provide insights into the fundamental processes of planet formation and evolution. From their orbits, several brown dwarf companions are found to be more massive than theoretical predictions given their luminosities and the ages of their host stars (e.g. Brandt et al. 2021, Cheetham et al. 2018, Li et al. 2023). Either the theory is incomplete or these objects are not single entities. For example, they could be two brown dwarfs each with a lower mass and intrinsic luminosity (Brandt et al. 2021, Howe et al. 2024). The most problematic example is Gliese 229 B (Nakajima et al. 1995, Oppenheimer et al. 1995), which is at least 2-6 times less luminous than model predictions given its dynamical mass of $71.4\pm0.6$ Jupiter masses ($M_{\rm Jup}$) (Brandt et al. 2021). We observed Gliese 229 B with the GRAVITY interferometer and, separately, the CRIRES+ spectrograph at the Very Large Telescope. Both sets of observations independently resolve Gliese 229 B into two components, Gliese 229 Ba and Bb, settling the conflict between theory and observations. The two objects have a flux ratio of $0.47\pm0.03$ at a wavelength of 2 $\mu$m and masses of $38.1\pm1.0$ and $34.4\pm1.5$ $M_{\rm Jup}$, respectively. They orbit each other every 12.1 days with a semimajor axis of 0.042 astronomical units (AU). The discovery of Gliese 229 BaBb, each only a few times more massive than the most massive planets, and separated by 16 times the Earth-moon distance, raises new questions about the formation and prevalence of tight binary brown dwarfs around stars., Comment: Published in Nature. The Version of Record of this article is located at https://www.nature.com/articles/s41586-024-08064-x

The first FASER search for a light, long-lived particle decaying into a pair of photons is reported. The search uses LHC proton-proton collision data at $\sqrt{s}=13.6~\text{TeV}$ collected in 2022 and 2023, corresponding to an integrated luminosity of $57.7\text{fb}^{-1}$. A model with axion-like particles (ALPs) dominantly coupled to weak gauge bosons is the primary target. Signal events are characterised by high-energy deposits in the electromagnetic calorimeter and no signal in the veto scintillators. One event is observed, compared to a background expectation of $0.44 \pm 0.39$ events, which is entirely dominated by neutrino interactions. World-leading constraints on ALPs are obtained for masses up to $300~\text{MeV}$ and couplings to the Standard Model W gauge boson, $g_{aWW}$, around $10^{-4}$ GeV$^{-1}$, testing a previously unexplored region of parameter space. Other new particle models that lead to the same experimental signature, including ALPs coupled to gluons or photons, U(1)$_B$ gauge bosons, up-philic scalars, and a Type-I two-Higgs doublet model, are also considered for interpretation, and new constraints on previously viable parameter space are presented in this paper., Comment: 37 pages, 22 figures

We prove that if the Morrison cone conjecture holds for a smooth Calabi-Yau threefold $Y$, it holds for any smooth Calabi-Yau threefold deformation-equivalent to $Y$. We use this result to prove a new case of the Morrison cone conjecture., Comment: Comments welcome!

500-nm-thick $\mathrm{In}_{x}\mathrm{Ga}_{1-x}\mathrm{N}$ layers with $x=$ 0.05-0.14 are grown using plasma-assisted molecular beam epitaxy, and their properties are assessed by a comprehensive analysis involving x-ray diffraction, secondary ion mass spectrometry, and cathodoluminescence as well as photoluminescence spectroscopy. We demonstrate low degrees of strain relaxation (10% for $x=0.12$), low threading dislocation densities ($\mathrm{1\times10^{9}\,cm^{-2}}$ for $x=0.12$), uniform composition both in the growth and lateral direction, and a narrow emission band. The unique sum of excellent materials properties make these layers an attractive basis for the top-down fabrication of ternary nanowires.

Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both single- and multi-modal models. As the GenAI ecosystem matures, the need for extensible and model-agnostic risk identification frameworks is growing. To meet this need, we introduce the Python Risk Identification Toolkit (PyRIT), an open-source framework designed to enhance red teaming efforts in GenAI systems. PyRIT is a model- and platform-agnostic tool that enables red teamers to probe for and identify novel harms, risks, and jailbreaks in multimodal generative AI models. Its composable architecture facilitates the reuse of core building blocks and allows for extensibility to future models and modalities. This paper details the challenges specific to red teaming generative AI systems, the development and features of PyRIT, and its practical applications in real-world scenarios.

This note proves that the nonparametric maximum likelihood estimator of a univariate log-concave probability density satisfies some consistency properties in the tail regions.

This study investigates the impact of Generative Artificial Intelligence (GenAI) on the dynam-ics and performance of innovation teams during the idea generation phase of the innovation process. Utilizing a custom AI-augmented ideation tool, the study applies the Knowledge Spill-over Theory of Entrepreneurship to understand the effects of AI on knowledge spillover, gen-eration and application. Through a framed field experiment with participants divided into exper-imental and control groups, findings indicate that AI-augmented teams generated higher quali-ty ideas in less time. GenAI application led to improved efficiency, knowledge exchange, in-creased satisfaction and engagement as well as enhanced idea diversity. These results high-light the transformative role of the field of AI within the innovation management domain and shows that GenAI has a positive impact on important elements of the Knowledge Spillover Theory of Entrepeneurship, emphasizing its potential impact on innovation, entrepreneurship, and economic growth. Future research should further explore the dynamic interaction be-tween GenAI and creative processes., Comment: 24 pages, 5 figures, Author Contributions: Michael Gindert: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration, Funding acquisition Marvin Lutz M\"uller: Validation, Investigation, Resources, Writing - Review & Editing, Supervision

Optical fiber amplifiers are key elements in present optical networks. Failures of these components result in high financial loss of income of the network operator as the communication traffic over an affected link is interrupted. Applying Remaining useful lifetime (RUL) prediction in the context of Predictive Maintenance (PdM) to optical fiber amplifiers to predict upcoming system failures at an early stage, so that network outages can be minimized through planning of targeted maintenance actions, ensures reliability and safety. Optical fiber amplifier are complex systems, that work under various operating conditions, which makes correct forecasting a difficult task. Increased monitoring capabilities of systems results in datasets that facilitate the application of data-driven RUL prediction methods. Deep learning models in particular have shown good performance, but generalization based on comparatively small datasets for RUL prediction is difficult. In this paper, we propose Sparse Low-ranked self-Attention Transformer (SLAT) as a novel RUL prediction method. SLAT is based on an encoder-decoder architecture, wherein two parallel working encoders extract features for sensors and time steps. By utilizing the self-attention mechanism, long-term dependencies can be learned from long sequences. The implementation of sparsity in the attention matrix and a low-rank parametrization reduce overfitting and increase generalization. Experimental application to optical fiber amplifiers exemplified on EDFA, as well as a reference dataset from turbofan engines, shows that SLAT outperforms the state-of-the-art methods., Comment: 9 pages, 7 figures, submitted to IEEE Transactions on Machine Learning in Communications and Networking (TMLCN)

We resolve the multiple images of the binary-lens microlensing event ASASSN-22av using the GRAVITY instrument of the Very Large Telescope Interferometer (VLTI). The light curves show weak binary perturbations, complicating the analysis, but the joint modeling with the VLTI data breaks several degeneracies, arriving at a strongly favored solution. Thanks to precise measurements of angular Einstein radius \theta_E = 0.724 +/- 0.002 mas and microlens parallax, we determine that the lens system consists of two M dwarfs with masses of M_1 = 0.258 +/- 0.008 M_sun and M_2 = 0.130 +/- 0.007 M_sun, a projected separation of r_\perp = 6.83 +/- 0.31 AU and a distance of D_L = 2.29 +/- 0.08 kpc. The successful VLTI observations of ASASSN-22av open up a new path for studying intermediate-separation (i.e., a few AUs) stellar-mass binaries, including those containing dark compact objects such as neutron stars and stellar-mass black holes., Comment: Accepted by ApJ. See the ancillary file for animation associated with Fig. 8

Studying the orbital motion of stars around Sagittarius A* in the Galactic Center provides a unique opportunity to probe the gravitational potential near the supermassive black hole at the heart of our Galaxy. Interferometric data obtained with the GRAVITY instrument at the Very Large Telescope Interferometer (VLTI) since 2016 has allowed us to achieve unprecedented precision in tracking the orbits of these stars. GRAVITY data have been key to detecting the in-plane, prograde Schwarzschild precession of the orbit of the star S2, as predicted by General Relativity. By combining astrometric and spectroscopic data from multiple stars, including S2, S29, S38, and S55 - for which we have data around their time of pericenter passage with GRAVITY - we can now strengthen the significance of this detection to an approximately $10 \sigma$ confidence level. The prograde precession of S2's orbit provides valuable insights into the potential presence of an extended mass distribution surrounding Sagittarius A*, which could consist of a dynamically relaxed stellar cusp comprised of old stars and stellar remnants, along with a possible dark matter spike. Our analysis, based on two plausible density profiles - a power-law and a Plummer profile - constrains the enclosed mass within the orbit of S2 to be consistent with zero, establishing an upper limit of approximately $1200 \, M_\odot$ with a $1 \sigma$ confidence level. This significantly improves our constraints on the mass distribution in the Galactic Center. Our upper limit is very close to the expected value from numerical simulations for a stellar cusp in the Galactic Center, leaving little room for a significant enhancement of dark matter density near Sagittarius A*., Comment: Submitted to A&A on September 17, 2024

Interferometric observations of gravitational microlensing events offer an opportunity for precise, efficient, and direct mass and distance measurements of lensing objects, especially those of isolated neutron stars and black holes. However, such observations were previously possible for only a handful of extremely bright events. The recent development of a dual-field interferometer, GRAVITY Wide, has made it possible to reach out to significantly fainter objects, and increase the pool of microlensing events amenable to interferometric observations by two orders of magnitude. Here, we present the first successful observation of a microlensing event with GRAVITY Wide and the resolution of microlensed images in the event OGLE-2023-BLG-0061/KMT-2023-BLG-0496. We measure the angular Einstein radius of the lens with a sub-percent precision, $\theta_{\rm E} = 1.280 \pm 0.009$ mas. Combined with the microlensing parallax detected from the event light curve, the mass and distance to the lens are found to be $0.472 \pm 0.012 M_{\odot}$ and $1.81 \pm 0.05$ kpc, respectively. We present the procedure for the selection of targets for interferometric observations, and discuss possible systematic effects affecting GRAVITY Wide data. This detection demonstrates the capabilities of the new instrument and it opens up completely new possibilities for the follow-up of microlensing events, and future routine discoveries of isolated neutron stars and black holes., Comment: submitted to AAS Journals

In this paper we show that the random degree constrained process (a time-evolving random graph model with degree constraints) has a local weak limit, provided that the underlying host graphs are high degree almost regular. We, moreover, identify the limit object as a multi-type branching process, by combining coupling arguments with the analysis of a certain recursive tree process. Using a spectral characterization, we also give an asymptotic expansion of the critical time when the giant component emerges in the so-called random $d$-process, resolving a problem of Warnke and Wormald for large $d$., Comment: 53 pages, 3 figures

Using a combination of HST, JWST, and ALMA data, we perform spatially resolved spectral energy distributions (SED) fitting of fourteen 4

This paper is devoted to the study of analytic equivalence relations which are Borel graphable, i.e. which can be realized as the connectedness relation of a Borel graph. Our main focus is the question of which analytic equivalence relations are Borel graphable. First, we study an equivalence relation arising from the theory of countable admissible ordinals and show that it is Borel graphable if and only if there is a non-constructible real. As a corollary of the proof, we construct an analytic equivalence relation which is (provably in ZFC) not Borel graphable and an effectively analytic equivalence relation which is Borel graphable but not effectively Borel graphable. Next, we study analytic equivalence relations given by the isomorphism relation for some class of countable structures. We show that all such equivalence relations are Borel graphable, which implies that for every Borel action of $S_\infty$, the associated orbit equivalence relation is Borel graphable. This leads us to study the class of Polish groups whose Borel actions always give rise to Borel graphable orbit equivalence relations; we refer to such groups as graphic groups. We show that besides $S_\infty$, the class of graphic groups includes all connected Polish groups and is closed under countable products. We finish by studying structural properties of the class of Borel graphable analytic equivalence relations and by considering two variations on Borel graphability: a generalization with hypegraphs instead of graphs and an analogue of Borel graphability in the setting of computably enumerable equivalence relations., Comment: 60 pages, updated to add references

We present the Wavefront Sensor units of the Gravity Plus Adaptive Optics (GPAO) system, which will equip all 8m class telescopes of the VLTI and is an instrumental part of the GRAVITY+ project. It includes two modules for each Wavefront Sensor unit: a Natural Guide Star sensor with high-order 40x40 Shack-Hartmann and a Laser Guide Star 30x30 sensor. The state-of-the-art AO correction will considerably improve the performance for interferometry, in particular high-contrast observations for NGS observations and all-sky coverage with LGS, which will be implemented for the first time on VLTI instruments. In the following, we give an overview of the Wavefront Sensor units system after completion of their integration and characterization., Comment: Optical and Infrared Interferometry and Imaging IX

Social network users are commonly connected to hundreds or even thousands of other users. However, these ties are not all of equal strength; for example, we often are connected to good friends or family members as well as acquaintances. Inferring the tie strengths is an essential task in social network analysis. Common approaches classify the ties into strong and weak edges based on the network topology using the strong triadic closure (STC). The STC states that if for three nodes, $\textit{A}$, $\textit{B}$, and $\textit{C}$, there are strong ties between $\textit{A}$ and $\textit{B}$, as well as $\textit{A}$ and $\textit{C}$, there has to be a (weak or strong) tie between $\textit{B}$ and $\textit{C}$. Moreover, a variant of the STC called STC+ allows adding new weak edges to obtain improved solutions. Recently, the focus of social network analysis has been shifting from single-layer to multilayer networks due to their ability to represent complex systems with multiple types of interactions or relationships in multiple social network platforms like Facebook, LinkedIn, or X (formerly Twitter). However, straightforwardly applying the STC separately to each layer of multilayer networks usually leads to inconsistent labelings between layers. Avoiding such inconsistencies is essential as they contradict the idea that tie strengths represent underlying, consistent truths about the relationships between users. Therefore, we adapt the definitions of the STC and STC+ for multilayer networks and provide ILP formulations to solve the problems exactly. Solving the ILPs is computationally costly; hence, we additionally provide an efficient 2-approximation for the STC and a 6-approximation for the STC+ minimization variants. The experiments show that, unlike standard approaches, our new highly efficient algorithms lead to consistent strong/weak labelings of the multilayer network edges.

The laws of thermodynamics strongly restrict the performance of thermal machines. Standard thermodynamics, initially developed for uncorrelated macroscopic systems, does not hold for microscopic systems correlated with their environments. We here derive exact generalized laws of quantum thermodynamics for arbitrary, time-periodic, open systems that account for all possible correlations between all involved parties. We demonstrate the existence of two basic modes of engine operation: the usual thermal case, where heat is converted into work, and a novel athermal regime, where work is extracted from entropic resources, such as system-bath correlations. In the latter regime, the efficiency of a quantum engine is not bounded by the usual Carnot formula. Our results provide a unified formalism to determine the efficiency of correlated microscopic thermal devices.

The emission and escape of Lyman-$\alpha$ photons from star-forming galaxies is determined through complex interactions between the emitted photons and a galaxy's interstellar and circumgalactic gas, causing Lyman-$\alpha$ emitters (LAEs) to commonly appear not as point sources but in spatially extended halos with complex spectral profiles. We develop a 3D spatial-spectral model of Lyman-$\alpha$ halos (LAHs) to replicate LAH observations in integral field spectroscopic studies, such as those made with VLT/MUSE. The profile of this model is a function of 6 key halo properties: the halo- and compact-source exponential scale lengths ($r_{sH}$ and $r_{sC}$), the halo flux fraction ($f_H$), the compact component ellipticity ($q$), the spectral line width ($\sigma$), and the spectral line skewness parameter ($\gamma$). Placing a series of model LAHs into datacubes reflecting observing conditions in the MUSE UDF-Mosaic survey, we test their detection recoverability and determine that $\sigma$, $r_{sH}$, and $f_H$ are expected to have the most significant effect on the detectability of the overall LAH at a given central wavelength and intrinsic line luminosity. We develop a general selection function model spanning a grid of these halo parameters, and with a sample of 145 UDF-Mosaic LAHs with measured halo properties, we derive completeness-corrected, intrinsic distributions of the values of $\sigma$, $r_{sH}$, and $f_H$ for $3

We report the discovery of a rare Mg II $\lambda$$\lambda$ 2796, 2803 doublet emission halo around a star forming galaxy with $\log (M_\star$/M$_\odot) = 10.3 \pm 0.3$ at $z=0.737$ in deep (9.94 h) VLT/MUSE data from the MUSE-HUDF mosaic. While the central region prominently displays an absorption-dominated Mg II doublet, characterized by discernible P-Cyg features, our examination reveals a remarkably extended Mg II emission, spanning approximately $\sim30$ kpc from the central galaxy. We introduce a simple outflow radiative transfer modeling scheme based on the Sobolev approximation, and we employ a Bayesian Monte Carlo Markov Chain (MCMC) fitting to find the best-fitting parameters that match our data. The model reproduces several key features of the observed Mg II halo and allows us to constrain the kinematics and geometry of the outflowing gas. Our data are consistent with a biconical wind whose velocity increases with radius, pointing nearly towards the observer, with an opening angle of $59\pm4^{\circ}$ In general, we find that our outflow model performs better in the inner regions of the galactic wind ($\lesssim 10$ kpc $\approx 6$ half-light radii), reaching a velocity of $\sim120$ km s$^{-1}$ at 10 kpc from the central galaxy. However, discrepancies between the data and the model in the outer regions suggest the possible influence of additional mechanisms, such as inflows, satellite interactions, or turbulence, which might significantly shape the circumgalactic medium (CGM) of galaxies at larger impact parameters. This analysis underscores the complexity of galactic outflows and encourages further exploration of the processes governing the dynamics of galactic winds through spatially resolved studies of the CGM., Comment: 22 pages + appendix, 18 figures, accepted for publication in A&A

Magnetic 2D materials enable novel tuning options of magnetism. As an example, the van der Waals material FePS3, a zigzag-type intralayer antiferromagnet, exhibits very strong magnetoelastic coupling due to the different bond lengths along different ferromagnetic and antiferromagnetic coupling directions enabling elastic tuning of magnetic properties. The likely cause of the length change is the intricate competition between direct exchange of the Fe atoms and superexchange via the S and P atoms. To elucidate this interplay, we study the band structure of exfoliated FePS3 by mu m scale ARPES (Angular Resolved Photoelectron Spectroscopy), both, above and, for the first time, below the Neel temperature TN. We find three characteristic changes across TN. They involve S 3p-type bands, Fe 3d-type bands and P 3p-type bands, respectively, as attributed by comparison with density functional theory calculations (DFT+U). This highlights the involvement of all the atoms in the magnetic phase transition providing independent evidence for the intricate exchange paths.

Lanthanide atoms show long magnetic lifetimes because of their strongly localized 4f electrons, but electrical control of their spins has been difficult because of their closed valence shell configurations. We achieved electron spin resonance of individual lanthanide atoms using a scanning tunneling microscope to probe the atoms bound to a protective insulating film. These atoms were prepared in the monovalent state with an unpaired 6s electron, enabling tunnel current to access their 4f electrons. Europium spectra display a rich array of transitions among the 54 combined electron and nuclear spin states. In contrast, samarium's ground state is a Kramers doublet with an extraordinarily large g-factor of nearly 5. These results demonstrate that all-electronic sensing and control of individual lanthanide spins is possible for quantum devices and spin-based electronics by using their rarely-observed monovalent cation state., Comment: 63 pages, 5 main text figures, 15 supplementary information figures

We report the fabrication and characterization of photonic waveguides from sputtered aluminum nitride (AlN). The AlN films were deposited on 6" silicon substrates with a 3 $\mu$m buried silicon oxide layer using reactive DC magnetron sputtering at a temperature of 700{\deg}C. The resulting uncladded polycrystalline waveguides exhibit propagation losses of 0.137 $\pm$ 0.005 dB/cm at wavelengths of 1310 nm and 0.154 $\pm$ 0.008 dB/cm at a wavelength of 1550 nm in the TE polarization. These results are the best reported for sputtered AlN waveguides in the C-band and the first report in the O-band. These performances are comparable to those of the best-reported AlN waveguides, which are epitaxially grown by metal-organic chemical vapor deposition (MOCVD) on sapphire substrates. Our findings highlight the potential of sputtered AlN for photonic platforms working in the telecom spectrum., Comment: 12 pages

We consider periodic homogenization with localized defects of boundary value problems for semilinear ODE systems of the type $$ \Big((A(x/\varepsilon)+B(x/\varepsilon))u'(x)+c(x,u(x))\Big)'= d(x,u(x)) \mbox{ for } x \in (0,1),\; u(0)=u(1)=0. $$ For small $\varepsilon>0$ we show existence of weak solutions $u=u_\varepsilon$ as well as their local uniqueness for $\|u-u_0\|_\infty \approx 0$, where $u=u_0$ is a given solution to the homogenized problem $$ \Big(A_0u'+c(x,u(x))\Big)'= d(x,u(x)) \mbox{ for } x \in (0,1),\; u(0)=u(1)=0,\; A_0:=\left(\int_0^1A(y)^{-1}dy\right)^{-1} $$ such that the linearized problem $$ \Big(A_0u'+\partial_uc(x,u_0(x))u(x)\Big)'= \partial_ud(x,u_0(x))u(x) \mbox{ for } x \in (0,1),\; u(0)=u(1)=0 $$ does not have weak solutions $u\not=0$. Further, we prove that $\|u_\varepsilon-u_0\|_\infty\to 0$ and, if $c(\cdot,u)\in W^{1,\infty}((0,1);\mathbb{R}^n)$, that $\|u_\varepsilon-u_0\|_\infty=O(\varepsilon)$ for $\varepsilon \to 0$. We assume that $A \in L^\infty(\mathbb{R};\mathbb{M}_n)$ is 1-periodic, $B \in L^\infty(\mathbb{R};\mathbb{M}_n)\cap L^1(\mathbb{R};\mathbb{M}_n)$, $A(y)$ and $A(y)+B(y)$ are positive definite uniformly with respect to $y$, $c(x,\cdot),d(x,\cdot)\in C^1(\mathbb{R}^n;\mathbb{R}^n)$ and $c(\cdot,u),d(\cdot,u) \in L^\infty((0,1);\mathbb{R}^n)$. The main tool of the proofs is an abstract result of implicit function theorem type which has been tailored for applications to nonlinear singular perturbation and homogenization problems., Comment: arXiv admin note: substantial text overlap with arXiv:2309.15611

This article proposes a novel fuzzy clustering based anomaly detection method for pump current time series of EDFA systems. The proposed change detection framework (CDF) strategically combines the advantages of entropy analysis (EA) and principle component analysis (PCA) with fuzzy clustering procedures. In the framework, EA is applied for dynamic selection of features for reduction of the feature space and increase of computational performance. Furthermore, PCA is utilized to extract features from the raw feature space to enable generalization capability of the subsequent fuzzy clustering procedures. Three different fuzzy clustering methods, more precisely the fuzzy clustering algorithm, a probabilistic clustering algorithm and a possibilistic clustering algorithm are evaluated for performance and generalization. Hence, the proposed framework has the innovative feature to detect changes in pump current time series at an early stage for arbitrary points of operation, compared to state-of-the-art predefined alarms in commercially used EDFAs. Moreover, the approach is implemented and tested using experimental data. In addition, the proposed framework enables further approaches of applying decentralized predictive maintenance for optical fiber networks., Comment: 6 pages, 6 figures

Attosecond X-ray pulses are the key to studying electron dynamics at their natural time scale involving specific electronic states. They are promising to build the conceptual bridge between physical and chemical photo-reaction processes. Free-electron lasers have demonstrated their capability of generating intense attosecond X-ray pulses. However, harnessing them for time-resolving experiments and investigations of nonlinear X-ray absorption mechanisms remains a cutting-edge challenge. We have characterised X-ray pulses with durations of down to 700$\,$attoseconds and peak powers up to 200$\,$GW at $\sim$ 1$\,$keV photon energy via angular streaking at the SQS instrument of the European XFEL. As direct application, we present results of nonlinear X-ray-matter interaction via state-specific spectroscopy on a transient system. Using the derived spectral and temporal information of each pulse, we deliberately steer the probability for formation of double-core vacancies in neon gas atoms through excitation or ionisation of the second inner-shell electron after K-shell ionisation. Our results advance the field of attosecond science with highly intense and fully characterised X-ray pulses to the site-specific investigation of electronic motion in transient media.

Formal languages over infinite alphabets serve as abstractions of structures and processes carrying data. Automata models over infinite alphabets, such as classical register automata or, equivalently, nominal orbit-finite automata, tend to have computationally hard or even undecidable reasoning problems unless stringent restrictions are imposed on either the power of control or the number of registers. This has been shown to be ameliorated in automata models with name allocation such as regular nondeterministic nominal automata, which allow for deciding language inclusion in elementary complexity even with unboundedly many registers while retaining a reasonable level of expressiveness. In the present work, we demonstrate that elementary complexity survives under extending the power of control to alternation: We introduce regular alternating nominal automata (RANAs), and show that their non-emptiness and inclusion problems have elementary complexity even when the number of registers is unbounded. Moreover, we show that RANAs allow for nearly complete de-alternation, specifically de-alternation up to a single deadlocked universal state.

Analyzing large sets of visual media remains a challenging task, particularly in mixed-method studies dealing with problematic information and human subjects. Using AI tools in such analyses risks reifying and exacerbating biases, as well as untenable computational and cost limitations. As such, we turn to adopting geometric computer graphics and vision methods towards analyzing a large set of images from a problematic information campaign, in conjunction with human-in-the-loop qualitative analysis. We illustrate an effective case of this approach with the implementation of color quantization towards analyzing online hate image at the US-Mexico border, along with a historicist trace of the history of color quantization and skin tone scales, to inform our usage and reclamation of these methodologies from their racist origins. To that end, we scaffold motivations and the need for more researchers to consider the advantages and risks of reclaiming such methodologies in their own work, situated in our case study.

We investigate the spatial extent of the [CII] line emission in a sample of 34 galaxies at $z=4-6$ from the ALMA-CRISTAL Survey. By modeling the [CII] line emission in the visibility data directly, we derive the effective radius of [CII] line emission assuming exponential distribution. These measurements comprise not only isolated galaxies but also interacting systems, identified thanks to the high spatial resolution of the data. The [CII] line radius ranges from 0.5 to 3.5 kpc with an average value of 1.9 kpc. We compare the [CII] sizes with the sizes of UV and FIR continua, which were measured from the HST F160W and ALMA Band-7 continuum images, respectively. We confirm that the [CII] line emission is more spatially extended than the continuum emission, with average size ratios of $R_{e,[CII]}/R_{e,UV}=2.90$ and $R_{e,[CII]}/R_{e,FIR}=1.54$, although about half of the FIR-detected sample show comparable spatial extent between [CII] line and FIR continuum emission ($R_{e,[CII]}\approx R_{e, FIR}$). The residual visibility data of the best-fit model do not show evidence of flux excesses either individually or in stacking analysis. This indicates that the [CII] line emission in star-forming galaxies can be characterized by an extended exponential disk profile. Overall, our results suggest that the spatial extent of [CII] line emission can primarily be explained by photodissociation regions associated with star formation activity, while the contribution from diffuse neutral medium (atomic gas) and the effects of mergers may further expand the [CII] line distributions, causing their variations among our sample. We report the correlations between the [CII] line, dust, and Lya line properties, which may be in line with our scenario. Future 3D-analysis of Lya and Ha lines will shed light on the association of the extended [CII] line emission with atomic gas and outflows., Comment: Submitted to A&A, 21 pages, 14 figures, 4 tables

The dust- and gas-rich protoplanetary disks around young stellar systems play a key role in star and planet formation. While considerable progress has recently been made in probing these disks on large scales of a few tens of astronomical units (au), the central au needs to be more investigated. We aim at unveiling the physical processes at play in the innermost regions of the strongly accreting T Tauri Star S CrA N by means of near-infrared interferometric observations. The K-band continuum emission is well reproduced with an azimuthally-modulated dusty ring. As the star alone cannot explain the size of this sublimation front, we propose that magnetospheric accretion is an important dust-heating mechanism leading to this continuum emission. The differential analysis of the Hydrogen Br$\gamma$ line is in agreement with radiative transfer models combining magnetospheric accretion and disk winds. Our observations support an origin of the Br$\gamma$ line from a combination of (variable) accretion-ejection processes in the inner disk region.

The thermal system of battery electric vehicles demands advanced control. Its thermal management needs to effectively control active components across varying operating conditions. While robust control function parametrization is required, current methodologies show significant drawbacks. They consume considerable time, human effort, and extensive real-world testing. Consequently, there is a need for innovative and intelligent solutions that are capable of autonomously parametrizing embedded controllers. Addressing this issue, our paper introduces a learning-based tuning approach. We propose a methodology that benefits from automated scenario generation for increased robustness across vehicle usage scenarios. Our deep reinforcement learning agent processes the tuning task context and incorporates an image-based interpretation of embedded parameter sets. We demonstrate its applicability to a valve controller parametrization task and verify it in real-world vehicle testing. The results highlight the competitive performance to baseline methods. This novel approach contributes to the shift towards virtual development of thermal management functions, with promising potential of large-scale parameter tuning in the automotive industry., Comment: 8 pages, 7 figures, 2 tables, 1 algorithm, 10 equations, conference

Though research into text-to-image generators (T2Is) such as Stable Diffusion has demonstrated their amplification of societal biases and potentials to cause harm, such research has primarily relied on computational methods instead of seeking information from real users who experience harm, which is a significant knowledge gap. In this paper, we conduct the largest human subjects study of Stable Diffusion, with a combination of crowdsourced data from 133 crowdworkers and 14 semi-structured interviews across diverse countries and genders. Through a mixed-methods approach of intra-set cosine similarity hierarchies (i.e., comparing multiple Stable Diffusion outputs for the same prompt with each other to examine which result is 'closest' to the prompt) and qualitative thematic analysis, we first demonstrate a large disconnect between user expectations for Stable Diffusion outputs with those generated, evidenced by a set of Stable Diffusion renditions of `a Person' providing images far away from such expectations. We then extend this finding of general dissatisfaction into highlighting representational harms caused by Stable Diffusion upon our subjects, especially those with traditionally marginalized identities, subjecting them to incorrect and often dehumanizing stereotypes about their identities. We provide recommendations for a harm-aware approach to (re)design future versions of Stable Diffusion and other T2Is., Comment: Upcoming Publication, AIES 2024

We study extensions of expressive decidable fragments of first-order logic with circumscription, in particular the two-variable fragment FO$^2$, its extension C$^2$ with counting quantifiers, and the guarded fragment GF. We prove that if only unary predicates are minimized (or fixed) during circumscription, then decidability of logical consequence is preserved. For FO$^2$ the complexity increases from $\textrm{coNexp}$ to $\textrm{coNExp}^\textrm{NP}$-complete, for GF it (remarkably!) increases from $\textrm{2Exp}$ to $\textrm{Tower}$-complete, and for C$^2$ the complexity remains open. We also consider querying circumscribed knowledge bases whose ontology is a GF sentence, showing that the problem is decidable for unions of conjunctive queries, $\textrm{Tower}$-complete in combined complexity, and elementary in data complexity. Already for atomic queries and ontologies that are sets of guarded existential rules, however, for every $k \geq 0$ there is an ontology and query that are $k$-$\textrm{Exp}$-hard in data complexity., Comment: 23 pages - Extended version of a paper accepted at KR 2024

The performance of equilibrium sensors is restricted by the laws of equilibrium thermodynamics. We here investigate the physical limits on nonequilibrium sensing in bipartite systems with nonreciprocal coupling. We show that one of the subsystems, acting as a Maxwell's demon, can significantly suppress the fluctuations of the other subsystem relative to its response to an external perturbation. Such negative violation of the fluctuation-dissipation relation can considerably improve the signal-to-noise ratio above its corresponding equilibrium value, allowing the subsystem to operate as an enhanced sensor. We find that the nonequilibrium signal-to-noise ratio of linear systems may be arbitrary large at low frequencies, even at a fixed overall amount of dissipation., Comment: 14 pages, 3 figures

Scaling up interferometry to 8m collectors should smooth-out the optical piston perturbations and allow a slow fringe tracker to obtain high precision correction on faint targets. In practice, the GRAVITY fringe tracker still observes high frequency OPD components that limit the exposure time, its precision and limiting magnitude. Perturbations seem to come from mechanical vibrations in the train of mirrors. As part of the GRAVITY+ efforts, accelerometers were added to all the mirrors of the coud\'e train to compensate in real-time the optical path using the main delay lines. We show their effectiveness on vibrations peaks between 40 and 200Hz and outline prospects for the upgrade of the deformable mirrors and the beam-compressor differential delay lines., Comment: 11 pages, 12 figures, Proc. SPIE Astronomical Telescopes + Instrumentation 2024 (Yokohama Japan), Optical and Infrared Interferometry and Imaging VI