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Layered delafossite-type compounds and related transition metal dichalcogenides, characterized by their triangular net structures, serve as prototypical systems for exploring the intricate interplay between crystal structure and magnetic behavior. Herein, we report on the discovery of the compound K$_{1-x}$CrSe$_2$ ($x \approx$ 0.13), an incommensurately modulated phase. Single crystals of this compound were grown for the first time using a K/Se self-flux. We find a monoclinic crystal structure with incommensurate modulation, that can be rationalized by a 3+1 dimensional model. This modulation compensates for the under-stoichiometry of K cations, creating pronounced undulations in the CrSe$_2$ layers. Our anisotropic magnetization measurements reveal that K$_{1-x}$CrSe$_2$ undergoes a transition to a long-range magnetically ordered state below $T_{\mathrm N}$ = 133 K, a temperature 1.6 to 3.3 times higher than in earlier reported KCrSe$_2$ compounds. Our findings open new avenues for tuning the magnetic properties of these layered materials through structural modulation.

Established techniques for characterizing a layer on a substrate system via surface acoustic wave (SAW) dispersion measurement are often slow due to the need for scanning excitation or detection positions. We present a method for determining discrete points on the SAW mode at equidistant wavenumbers that requires only a single measurement, overcoming these speed limitations. A pulsed laser, shaped into an array of equidistant lines, generates elastic waves on the sample surface. A vibrometer detects the resulting surface displacement next to the line array. The periodic excitation arrangement results in constructive interference of the SAW at wavelengths corresponding to integer fractions of the line spacing. This leads to distinct peaks in the response spectrum, whose higher orders we term spatial harmonics of the SAW. The known line spacing determines the wavelengths, allowing the peak frequencies to be mapped to discrete points on the SAW dispersion curve, effectively sampling the SAW at specific equidistant wavenumbers. By solving an inverse problem, a model can be fit to the experimental data to obtain properties of the layered system. We demonstrate this technique on copper-clad epoxy laminate and roll-cladded aluminum alloy plates and compare our results with dispersion relation scans and micrography. Additionally, we analyze the method's sensitivity to elastic parameters and layer thickness. This approach offers a viable alternative to established SAW scanning methods, particularly in scenarios where the trade-off of lower wavenumber sampling density is acceptable to achieve exceptionally fast measurements while avoiding moving parts., Comment: submitted to Applied Physics Letters

The deployment of IoT (Internet of Things) sensor-based machine learning models in industrial systems for anomaly classification tasks poses significant challenges due to distribution shifts, as the training data acquired in controlled laboratory settings may significantly differ from real-time data in production environments. Furthermore, many real-world applications cannot provide a substantial number of labeled examples for each anomalous class in every new environment. It is therefore crucial to develop adaptable machine learning models that can be effectively transferred from one environment to another, enabling rapid adaptation using normal operational data. We extended this problem setting to an arbitrary classification task and formulated the one-class domain adaptation (OC-DA) problem setting. We took a meta-learning approach to tackle the challenge of OC-DA, and proposed a task sampling strategy to adapt any bi-level meta-learning algorithm to OC-DA. We modified the well-established model-agnostic meta-learning (MAML) algorithm and introduced the OC-DA MAML algorithm. We provided a theoretical analysis showing that OC-DA MAML optimizes for meta-parameters that enable rapid one-class adaptation across domains. The OC-DA MAML algorithm is evaluated on the Rainbow-MNIST meta-learning benchmark and on a real-world dataset of vibration-based sensor readings. The results show that OC-DA MAML significantly improves the performance on the target domains and outperforms MAML using the standard task sampling strategy.

This paper presents a comprehensive analysis of the energy consumption characteristics of a Silicon (Si)-based Reconfigurable IoT (RIoT) node developed in the initial phase of the SUPERIOT project, focusing on key operating states, including Bluetooth Low Energy (BLE) communication, Narrow-Band Visible Light Communication (NBVLC), sensing, and E-ink display. Extensive measurements were conducted to establish a detailed energy profile, which serves as a benchmark for evaluating the effectiveness of subsequent optimizations and future node iterations. To minimize the energy consumption, multiple optimizations were implemented at both the software and hardware levels, achieving a reduction of over 60% in total energy usage through software modifications alone. Further improvements were realized by optimizing the E-ink display driving waveform and implementing a very low-power mode for non-communication activities. Based on the measured data, three measurement-based energy consumption models were developed to characterize the energy behavior of the node under: (i) normal, unoptimized operation, (ii) low-power, software-optimized operation, and (iii) very low-power, hardware-optimized operation. These models, validated with new measurement data, achieved an accuracy exceeding 97%, confirming their reliability for predicting energy consumption in diverse configurations., Comment: 14 pages, 13 figures, 11 tables

With the rising prevalence of cardiovascular and respiratory disorders and an aging global population, healthcare systems face increasing pressure to adopt efficient, non-contact vital sign monitoring (NCVSM) solutions. This study introduces a robust framework for multi-person localization and vital signs monitoring, using multiple-input-multiple-output frequency-modulated continuous wave radar, addressing challenges in real-world, cluttered environments. Two key contributions are presented. First, a custom hardware phantom was developed to simulate multi-person NCVSM scenarios, utilizing recorded thoracic impedance signals to replicate realistic cardiopulmonary dynamics. The phantom's design facilitates repeatable and rapid validation of radar systems and algorithms under diverse conditions to accelerate deployment in human monitoring. Second, aided by the phantom, we designed a robust algorithm for multi-person localization utilizing joint sparsity and cardiopulmonary properties, alongside harmonics-resilient dictionary-based vital signs estimation, to mitigate interfering respiration harmonics. Additionally, an adaptive signal refinement procedure is introduced to enhance the accuracy of continuous NCVSM by leveraging the continuity of the estimates. Performance was validated and compared to existing techniques through 12 phantom trials and 12 human trials, including both single- and multi-person scenarios, demonstrating superior localization and NCVSM performance. For example, in multi-person human trials, our method achieved average respiration rate estimation accuracies of 94.14%, 98.12%, and 98.69% within error thresholds of 2, 3, and 4 breaths per minute, respectively, and heart rate accuracies of 87.10%, 94.12%, and 95.54% within the same thresholds. These results highlight the potential of this framework for reliable multi-person NCVSM in healthcare and IoT applications.

Plasma turbulence in the edge of magnetic confinement devices is customarily treated as full-$f$ due to large fluctuations. For computational efficiency, field-aligned coordinates are employed, separating the magnetic field into equilibrium $B_0$ and delta-f perturbations which are handled by the magnetic flutter operators. Evolving the full-$f$ pressure with delta-$f$ magnetic perturbations can cause inconsistency since the latter contain background components such as the Shafranov shift, which are actually parts of the equilibrium magnetic field. Such background components ($B_s$) contained in the magnetic perturbations undermine the field-aligned numerics when treated as flutter: errors arise if $B_s/B_0\ll l_\perp/h_\parallel$ is not satisfied, with the perpendicular turbulence scale $l_\perp$ and the parallel grid distance $h_\parallel$. We find that the commonly used removal of $B_s$ by subtracting the toroidal average of magnetic perturbations intervenes in the Alfv\'en dynamics, causing spurious $E\times B$ transport. Instead, we propose an improved method to dynamically filter out the evolving background from the turbulent magnetic fluctuations in the time domain. The filter is verified in both low and high confinement tokamak conditions, confirming its capability to preserve the turbulence fidelity, provided sufficient filter width.

SPARC4 is a new astronomical instrument developed entirely by Brazilian institutions, currently installed on the 1.6-m Perkin-Elmer telescope of the Pico dos Dias Observatory. It allows the user to perform photometric or polarimetric observations simultaneously in the four SDSS bands (g, r, i, and z). In this paper, we describe the control system developed for SPARC4. This system is composed of S4ACS, S4ICS, and S4GUI softwares and associated hardware. S4ACS is responsible for controlling the four EMCCD scientific cameras (one for each instrument band). S4ICS controls the sensors and motors responsible for the moving parts of SPARC4. Finally, S4GUI is the interface used to perform observations, which includes the choice of instrument configuration and image acquisition parameters. S4GUI communicates with the instrument subsystems and with some observatory facilities, needed during the observations. Bench tests were performed for the determination of the overheads added by SPARC4 control system in the acquisition of photometric and polarimetric series of images. In the photometric mode, SPARC4 allows the acquisition of a series of 1400 full-frame images, with a deadtime of 4.5 ms between images. Besides, several image series can be concatenated with a deadtime of 450 ms plus the readout time of the last image. For the polarimetric mode, measurements can be obtained with a deadtime of 1.41 s plus the image readout time between subsequent waveplate positions. For both photometric and polarimetric modes, the user can choose among operating modes with image readout times between 5.9 ms and 1.24 s, which ultimately defines the instrument temporal performance., Comment: 20 pages, 14 figures, peer-reviewed paper

In the search for accurate approximate solutions of the many-body Schr\"odinger equation, reduced density matrices play an important role, as they allow to formulate approximate methods with polynomial scaling in the number of particles. However, these methods frequently encounter the issue of $N$-representability, whereby in self-consistent applications of the methods, the reduced density matrices become unphysical. A number of algorithms have been proposed in the past to restore a given set of $N$-representability conditions once the reduced density matrices become defective. However, these purification algorithms have either ignored symmetries of the Hamiltonian related to conserved quantities, or have not incorporated them in an efficient way, thereby modifying the reduced density matrix to a greater extent than is necessary. In this paper, we present an algorithm capable of efficiently performing all of the following tasks in the least invasive manner: restoring a given set of $N$-representability conditions, maintaining contraction consistency between successive orders of reduced density matrices, and preserving all conserved quantities. We demonstrate the superiority of the present purification algorithm over previous ones in the context of the time-dependent two-particle reduced density matrix method applied to the quench dynamics of the Fermi-Hubbard model., Comment: 13 pages, 4 figures

Loop quantum gravity in its Hamiltonian form relies on a connection formulation of the gravitational phase space with three key properties: 1.) a compact gauge group, 2.) real variables, and 3.) canonical Poisson brackets. In conjunction, these properties allow to construct a well defined kinematical quantization of the holonomy flux-algebra on top of which the remaining constraints can be implemented. While this idea has traditionally been mainly used for Einstein gravity, any gravitational theory with the above properties can be accommodated. In this paper, we are going to review three strands of work building on this observation, namely the study of higher-dimensional loop quantum gravity, supersymmetric extensions of loop quantum gravity, as well as the quantization of modified gravitational theories., Comment: 35 pages, 1 figures, version to appear in "Handbook of Quantum Gravity", Cosimo Bambi, Leonardo Modesto, Ilya Shapiro (editors), Springer (2023)

We present HIP 8522, a young solar twin with the lowest detected lithium, potentially a field blue straggler or the result of episodic early accretion. Its stellar parameters ($T_{\rm eff} = 5729 \pm 7$ K, $\log g = 4.532 \pm 0.016$ dex, $\rm{[Fe/H]} = 0.005 \pm 0.010$ dex, $v_{t} = 1.08 \pm 0.02$ km s$^{-1}$) and chemical composition were determined via spectroscopic equilibrium using high resolution spectra ($R = 60~000-165~000$). The age of HIP 8522 was estimated to be an upper limit of $<$1 Gyr through isochrone fitting and was further confirmed using chemical clocks. Spectral synthesis of the lithium line at $\sim$6707.8 \AA\ yielded an upper lithium abundance limit of $A(\rm{Li}) <$ 0.8 dex. This value is unusually low for solar twins of similar age, which typically have $A(\rm{Li})$ values ranging from 2.0 to 3.3 dex, suggesting that $\sim$2 dex of lithium is missing. We investigate various scenarios, such as planet engulfment, sub-stellar mergers, and extra mixing. However, two distinct hypotheses provide plausible explanations for the significant depletion of lithium: one suggests that HIP 8522 is a field blue straggler formed by the merger of a close binary, while the other proposes that HIP 8522 experienced early episodic accretion. The young solar twin HIP 8522 presents an exceptional opportunity to rigorously test stellar evolution models and gain crucial insights into the internal mixing mechanisms responsible for the significant destruction of lithium.

We report on continuous high-harmonic generation at 1 kHz repetition rate from a liquid-sheet plasma mirror driven by relativistic-intensity near-single-cycle light transients. Through precise control of both the surface plasma density gradient and the driving light waveform, we can produce highly stable and reproducible extreme ultraviolet spectral quasi-continua, corresponding to the generation of stable kHz-trains of isolated attosecond pulses in the time domain. This confirms the exciting potential of liquid sheet targets as one of the building blocks of future high-power attosecond lasers.

Magnetite, a naturally abundant mineral, frequently interacts with water in both natural settings and various technical applications, making the study of its surface chemistry highly relevant. In this work, we investigate the hydrogen bonding dynamics and the presence of hydroxyl species at the magnetite-water interface using a combination of neural network potential-based molecular dynamics simulations and sum frequency generation vibrational spectroscopy. Our simulations, which involved large water systems, allowed us to identify distinct interfacial species, such as dissociated hydrogen and hydroxide ions formed by water dissociation. Notably, water molecules near the interface exhibited a preference for dipole orientation towards the surface, with bulk-like water behavior only re-emerging beyond 60 {\AA} from the surface. The vibrational spectroscopy results aligned well with the simulations, confirming the presence of a hydrogen bond network in the surface ad-layers. The analysis revealed that surface-adsorbed hydroxyl groups orient their hydrogen atoms towards the water bulk. In contrast, hydrogen-bonded water molecules align with their hydrogen atoms pointing towards the magnetite surface.

The layered cobaltate CaCoO$_2$ exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO$_2$ using X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Our results reveal a significant inter-plane hybridization between the Ca $4s-$ and Co $3d-$orbitals, leading to an inversion of the textbook orbital occupation of a square planar geometry. Further, our RIXS data reveal a strong low energy mode, with anomalous intensity modulations as a function of momentum transfer close to a quasi-static response suggestive of electronic and/or orbital ordering. These findings indicate that the newly discovered herringbone structure exhibited in CaCoO$_2$ may serve as a promising laboratory for the design of materials having strong electronic, orbital and lattice correlations.

Designing mechanically efficient geometry for architectural structures like shells, towers, and bridges is an expensive iterative process. Existing techniques for solving such inverse mechanical problems rely on traditional direct optimization methods, which are slow and computationally expensive, limiting iteration speed and design exploration. Neural networks would seem to offer a solution, via data-driven amortized optimization for specific design tasks, but they often require extensive fine-tuning and cannot ensure that important design criteria, such as mechanical integrity, are met. In this work, we combine neural networks with a differentiable mechanics simulator to develop a model that accelerates the solution of shape approximation problems for architectural structures modeled as bar systems. As a result, our model offers explicit guarantees to satisfy mechanical constraints while generating designs that match target geometries. We validate our model in two tasks, the design of masonry shells and cable-net towers. Our model achieves better accuracy and generalization than fully neural alternatives, and comparable accuracy to direct optimization but in real time, enabling fast and sound design exploration. We further demonstrate the real-world potential of our trained model by deploying it in 3D modeling software and by fabricating a physical prototype. Our work opens up new opportunities for accelerated physical design enhanced by neural networks for the built environment.

Biobanks are indispensable resources for medical research collecting biological material and associated data and making them available for research projects and medical studies. For that, the biobank data has to meet certain criteria which can be formulated as adherence to the FAIR (findable, accessible, interoperable and reusable) principles. We developed a tool, CollectionLocator, which aims at increasing the FAIR compliance of biobank data by supporting researchers in identifying which biobank and which collection are likely to contain cases (material and data) satisfying the requirements of a defined research project when the detailed sample data is not available due to privacy restrictions. The CollectionLocator is based on an ontology-based metadata model to address the enormous heterogeneities and ensure the privacy of the donors of the biological samples and the data. Furthermore, the CollectionLocator represents the data and metadata quality of the collections such that the quality requirements of the requester can be matched with the quality of the available data. The concept of CollectionLocator is evaluated with a proof-of-concept implementation.

We report the discovery and characterization of a small planet, TOI-1408 c, on a 2.2-day orbit located interior to a previously known hot Jupiter, TOI-1408 b ($P=4.42$ d, $M=1.86\pm0.02\,M_\mathrm{Jup}$, $R=2.4\pm0.5\,R_\mathrm{Jup}$) that exhibits grazing transits. The two planets are near 2:1 period commensurability, resulting in significant transit timing variations (TTVs) for both planets and transit duration variations (TDVs) for the inner planet. The TTV amplitude for TOI-1408 c is 15% of the planet's orbital period, marking the largest TTV amplitude relative to the orbital period measured to date. Photodynamical modeling of ground-based radial velocity (RV) observations and transit light curves obtained with the Transiting Exoplanet Survey Satellite (TESS) and ground-based facilities leads to an inner planet radius of $2.22\pm0.06\,R_\oplus$ and mass of $7.6\pm0.2\,M_\oplus$ that locates the planet into the Sub-Neptune regime. The proximity to the 2:1 period commensurability leads to the libration of the resonant argument of the inner planet. The RV measurements support the existence of a third body with an orbital period of several thousand days. This discovery places the system among the rare systems featuring a hot Jupiter accompanied by an inner low-mass planet., Comment: Accepted to ApJL, 17 pages, 6 figures, 4 tables

Business users dedicate significant amounts of time to repetitive tasks within enterprise digital platforms, highlighting a critical need for automation. Despite advancements in low-code tools for UI automation, their complexity remains a significant barrier to adoption among non-technical business users. However, recent advancements in large language models (LLMs) have created new opportunities to overcome this barrier by offering more powerful, yet simpler and more human-centric programming environments. This paper presents IDA (Intelligent Digital Apprentice), a novel no-code Web UI automation tool designed specifically to empower business users with no technical background. IDA incorporates human-centric design principles, including guided programming by demonstration, semantic programming model, and teacher-student learning metaphor which is tailored to the skill set of business users. By leveraging LLMs, IDA overcomes some of the key technical barriers that have traditionally limited the possibility of no-code solutions. We have developed a prototype of IDA and conducted a user study involving real world business users and enterprise applications. The promising results indicate that users could effectively utilize IDA to create automation. The qualitative feedback indicates that IDA is perceived as user-friendly and trustworthy. This study contributes to unlocking the potential of AI assistants to enhance the productivity of business users through no-code user interface automation.

Modelling and characterizing emergent behaviour within a swarm can pose significant challenges in terms of 'assurance'. Assurance tasks encompass adherence to standards, certification processes, and the execution of verification and validation (V&V) methods, such as model checking. In this study, we propose a holistic, multi-level modelling approach for formally verifying and validating autonomous robotic swarms, which are defined at the macroscopic formal modelling, low-fidelity simulation, high-fidelity simulation, and real-robot levels. Our formal macroscopic models, used for verification, are characterized by data derived from actual simulations, ensuring both accuracy and traceability across different system models. Furthermore, our work combines formal verification with experimental validation involving real robots. In this way, our corroborative approach for V&V seeks to enhance confidence in the evidence, in contrast to employing these methods separately. We explore our approach through a case study focused on a swarm of robots operating within a public cloakroom., Comment: 15 pages, 11 figures

The Quantum Approximate Optimization Algorithm (QAOA) is a prominent quantum algorithm designed to find approximate solutions to combinatorial optimization problems, which are challenging for classical computers. In the current era, where quantum hardware is constrained by noise and limited qubit availability, simulating the QAOA remains essential for research. However, existing state-of-the-art simulation frameworks suffer from long execution times or lack comprehensive functionality, usability, and versatility, often requiring users to implement essential features themselves. Additionally, these frameworks are primarily restricted to Python, limiting their use in safer and faster languages like Rust, which offer, e.g., advanced parallelization capabilities. In this paper, we develop a GPU accelerated QAOA simulation framework utilizing the NVIDIA CUDA toolkit. This framework offers a complete interface for QAOA simulations, enabling the calculation of (exact) expectation values, direct access to the statevector, fast sampling, and high-performance optimization methods using an advanced state-of-the-art gradient calculation technique. The framework is designed for use in Python and Rust, providing flexibility for integration into a wide range of applications, including those requiring fast algorithm implementations leveraging QAOA at its core. The new framework's performance is rigorously benchmarked on the MaxCut problem and compared against the current state-of-the-art general-purpose quantum circuit simulation frameworks Qiskit and Pennylane as well as the specialized QAOA simulation tool QOKit. Our evaluation shows that our approach outperforms the existing state-of-the-art solutions in terms of runtime up to multiple orders of magnitude. Our implementation is publicly available at https://github.com/JFLXB/cuaoa and Zenodo., Comment: 6 pages, 3 figures

Closed quantum systems follow a unitary time evolution that can be simulated on quantum computers. By incorporating non-unitary effects via, e.g., measurements on ancilla qubits, these algorithms can be extended to open-system dynamics, such as Markovian processes described by the Lindblad master equation. In this paper, we analyze the convergence criteria and speed of a Markovian, purely dissipative quantum random walk on an unstructured classical search space. Notably, we show that certain jump operators make the quantum process replicate a classical one, while others yield differences between open quantum (OQRW) and classical random walks. We also clarify a previously observed quadratic speedup, demonstrating that OQRWs are no more efficient than classical search. Finally, we analyze a dissipative discrete-time ground-state preparation algorithm with a lower implementation cost. This allows us to interpolate between the dissipative and the unitary domain and thereby illustrate the important role of coherence for the quadratic speedup., Comment: 20 pages, 4 figures, submitted to PRA

With high equilibrium temperatures and tidally locked rotation, ultra-hot Jupiters (UHJs) are unique laboratories within which to probe extreme atmospheric physics and chemistry. In this paper, we present high-resolution dayside spectroscopy of the UHJ WASP-189b obtained with the new Gemini High-resolution Optical SpecTrograph (GHOST) at the Gemini South Observatory. The observations, which cover three hours of post-eclipse orbital phases, were obtained during the instrument's System Verification run. We detect the planet's atmosphere via the Doppler cross-correlation technique, and recover a detection of neutral iron in the planet's dayside atmosphere at a significance of 7.5$\sigma$ in the red-arm of the data, verifying the presence of a thermal inversion. We also investigate the presence of other species in the atmosphere and discuss the implications of model injection/recovery tests. These results represent the first atmospheric characterization of an exoplanet with GHOST's high-resolution mode, and demonstrate the potential of this new instrument in detecting and studying ultra-hot exoplanet atmospheres., Comment: 21 pages, 12 figures, 3 tables. Accepted for publication in The Astronomical Journal

In this paper, combining the Rashevsky-Chow-Sussmann (orbit) theorem with the Ambrose-Singer theorem, we introduce the notion of controllable principal connections on principal $G$-bundles. Using this concept, under a mild assumption of compactness, we estimate the Gromov-Hausdorff distance between principal $G$-bundles and certain reductive homogeneous $G$-spaces. In addition, we prove that every reduction of the structure group $G$ to a closed connected subgroup gives rise to a sequence of Riemannian metrics on the total space for which the underlying sequence of metric spaces converges, in the Gromov-Housdorff topology, to a normal reductive homogeneous $G$-space. This last finding allows one to detect the presence of certain reductive homogeneous $G$-spaces in the Gromov-Housdorff closure of the moduli space of Riemannian metrics of the total space of the bundle through topological invariants provided by obstruction theory., Comment: 13 pages, Comments are welcome

Determining the local coordination of the active site is a pre-requisite for the reliable modeling of single-atom catalysts (SACs). Obtaining such information is difficult on powder-based systems, so much emphasis is placed on density functional theory-based computations based on idealized low-index surfaces of the support. In this work, we investigate how Pt atoms bind to the (1-102) facet of Fe2O3, a common support material in SAC. Using a combination of scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), and an extensive computational evolutionary search, we find that Pt atoms significantly reconfigure the support lattice to facilitate a pseudo-linear coordination to surface oxygen atoms. Despite breaking three surface Fe-O bonds, this geometry is favored by 0.84 eV over the best configuration involving an unperturbed support. We suggest that the linear O-Pt-O configuration is common in reactive Pt-based SAC systems because it balances thermal stability with the ability to adsorb reactants from the gas phase, and that extensive structural searches are likely necessary to determine realistic active site geometry in single-atom catalysis.

In this paper, we provide a detailed and systematic study of weak (singular) Hermite-Einstein structures on homogeneous holomorphic vector bundles over rational homogeneous varieties. We use standard tools from spectral geometry, Harmonic analysis, and Cartan's highest weight theory to provide a sufficient condition in terms of Fourier series and intersection numbers under which an $L^{2}$-function can be realized as mean curvature of a singular Hermitian structure on an irreducible homogeneous holomorphic vector bundle. We prove that the condition provided is necessary and sufficient for functions that belong to certain interpolation spaces. In the particular case of line bundles over irreducible Hermitian symmetric spaces of compact type, we describe explicitly in terms of representation theory the solutions of the underlying geometric PDE. Also, we establish a sufficient condition in terms of Fourier coefficients and intersection numbers for solvability and convergence of the weak Hermite-Einstein flow on irreducible homogeneous holomorphic vector bundles. As an application of our methods, we describe the first explicit examples in the literature of solutions to several geometric flows, including Donaldson's heat flow, Yang-Mills heat flow, and the gradient flow of Donaldson's Lagrangian, on line bundles over irreducible Hermitian symmetric spaces of compact type. Additionally, we show that every polynomial central charge function gives rise to a weak Donaldson's Lagrangian $\mathcal{M}$. In the particular case of irreducible homogeneous holomorphic vector bundles, we prove that the gradient flow of $\mathcal{M}$ converges to a Hermitian structure which is, up to a gauge transformation, a $Z$-critical Hermitian structure in the large volume limit., Comment: 66 pages, 3 figures, Comments are welcome

Novel test selectors have demonstrated their effectiveness in accelerating the closure of functional coverage for various industrial digital designs in simulation-based verification. The primary advantages of these test selectors include performance that is not impacted by coverage holes, straightforward implementation, and relatively low computational expense. However, the detection of stimuli with novel temporal patterns remains largely unexplored. This paper introduces two novel test selectors designed to identify such stimuli. The experiments reveal that both test selectors can accelerate the functional coverage for a commercial bus bridge, compared to random test selection. Specifically, one selector achieves a 26.9\% reduction in the number of simulated tests required to reach 98.5\% coverage, outperforming the savings achieved by two previously published test selectors by factors of 13 and 2.68, respectively.

Planets orbiting binary systems are relatively unexplored compared to those around single stars. Detections of circumbinary planets and planetary systems offer a first detailed view into our understanding of circumbinary planet formation and dynamical evolution. The BEBOP (Binaries Escorted by Orbiting Planets) radial velocity survey plays a special role in this adventure as it focuses on eclipsing single-lined binaries with an FGK dwarf primary and M dwarf secondary allowing for the highest-radial velocity precision using the HARPS and SOPHIE spectrographs. We obtained 4512 high-resolution spectra for the 179 targets in the BEBOP survey which we used to derive the stellar atmospheric parameters using both equivalent widths and spectral synthesis. We furthermore derive stellar masses, radii, and ages for all targets. With this work, we present the first homogeneous catalogue of precise stellar parameters for these eclipsing single-lined binaries., Comment: accepted for publication in MNRAS

X-ray spectroscopy has been a key method to determine ground and excited state properties of quantum materials with atomic specificity. Now, new x-ray facilities are opening the door to the study of pump-probe x-ray spectroscopy - specifically time-resolved x-ray absorption (trXAS) and time-resolved resonant inelastic x-ray scattering (trRIXS). In this paper we will present simulations of each of these spectroscopies using a time-domain full atomic multiplet, charge transfer Hamiltonian, adapted to study the properties of a generalized cluster model including a central transition metal ion caged by ligand atoms in a planar geometry. The numerically evaluated trXAS and trRIXS cross-sections for representative electron configurations $3d^9$ and $3d^8$ demonstrate the insights that can be obtained from charge transfer pumping, and how this nonequilibrium process affects ground and excited state properties. The straightforward characterization of the excitations in these systems, based on our analysis of the simulations, can serve as a benchmark for future experiments, as access to these time-resolved spectroscopic techniques becomes more widely available.

We report on the discovery and validation of a transiting long-period mini-Neptune orbiting a bright (V = 9.0 mag) G dwarf (TOI 4633; R = 1.05 RSun, M = 1.10 MSun). The planet was identified in data from the Transiting Exoplanet Survey Satellite by citizen scientists taking part in the Planet Hunters TESS project. Modeling of the transit events yields an orbital period of 271.9445 +/- 0.0040 days and radius of 3.2 +/- 0.20 REarth. The Earth-like orbital period and an incident flux of 1.56 +/- 0.2 places it in the optimistic habitable zone around the star. Doppler spectroscopy of the system allowed us to place an upper mass limit on the transiting planet and revealed a non-transiting planet candidate in the system with a period of 34.15 +/- 0.15 days. Furthermore, the combination of archival data dating back to 1905 with new high angular resolution imaging revealed a stellar companion orbiting the primary star with an orbital period of around 230 years and an eccentricity of about 0.9. The long period of the transiting planet, combined with the high eccentricity and close approach of the companion star makes this a valuable system for testing the formation and stability of planets in binary systems., Comment: 24 pages, 16 figures, 4 tables