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Exploring the formation and evolution of second-generation circumbinary discs around evolved binary stars, such as post-Asymptotic Giant Branch (post-AGB) and post-Red Giant Branch (post-RGB) binaries, provides valuable insights into the complex binary interaction process that concludes the red-giant phase of evolution in these systems. Additionally, it offers a novel opportunity to investigate the formation of second-generation planets within dusty discs surrounding evolved stars. We present a pilot multi-wavelength polarimetric imaging study of the post-AGB binary system IRAS 08544-4431 using the European Southern Observatory-Very Large Telescope/SPHERE instrument. This study is focused on optical V- and I'-band ZIMPOL data to complement near-infrared H-band IRDIS data presented previously. The study aims to investigate the dust scattering properties and surface morphology of the post-AGB circumbinary disc as a function of wavelength. We successfully resolved the extended disc structure of IRAS\,08544-4431, revealing a complex disc morphology, high polarimetric disc brightness (up to ~1.5%), and significant forward scattering at optical wavelengths. Additionally, we found that the disc shows a grey polarimetric colour in both optical and near-infrared. The findings highlight similarities between post-AGB circumbinary discs and protoplanetary discs, suggesting submicron-size porous aggregates as the dominant surface dust composition, and indicating potential warping within the disc. However, further expansion of the multi-wavelength analysis to a larger sample of post-AGB binary systems, as well as high-resolution observations of dust continuum and gas emission, is necessary to fully explore the underlying structure of post-AGB circumbinary discs and associated physical mechanisms., Comment: 15 pages, 15 figures

Time-resolved X-ray absorption spectroscopy (tr-XAS) has been shown to be a versatile measurement technique for investigating non-equilibrium dynamics. Novel X-ray free electron laser (XFEL) facilities like the European XFEL offer increased repetition rates for stroboscopic XAS experiments through a burst operation mode, which enables measurements with up to 4.5 MHz. These higher repetition rates lead to higher data acquisition rates but can also introduce long-lived excitations that persist and thus build up during each burst. Here, we report on such long-lived effects in Ni and NiO thin film samples that were measured at the European XFEL. We disentangle the long-lived excitations from the initial pump-induced change and perform a detailed modelling-based analysis of how they modify transient X-ray spectra. As a result, we link the long-lived effects in Ni to a local temperature increase, as well as the effects in NiO to excited charge carrier trapping through polaron formation. In addition, we present possible correction methods, as well as discuss ways in which the effects of these long-lived excitations could be minimized for future time-resolved X-ray absorption spectroscopy measurements.

In this work, we introduce a novel approach for predicting thermodynamic properties of binary mixtures, which we call the similarity-based method (SBM). The method is based on quantifying the pairwise similarity of components, which we achieve by comparing quantum-chemical descriptors of the components, namely $\sigma$-profiles. The basic idea behind the approach is that mixtures with similar pairs of components will have similar thermodynamic properties. The SBM is trained on a matrix that contains some data for a given property for different binary mixtures; the missing entries are then predicted by the SBM. As an example, we consider the prediction of isothermal activity coefficients at infinite dilution ($\gamma^\infty_{ij}$) and show that the SBM outperforms the well-established physical methods modified UNIFAC (Dortmund) and COSMO-SAC-dsp. In this case, the matrix is only sparsely occupied, and it is shown that the SBM works also if only a limited number of data for similar mixtures is available. The SBM idea can be transferred to any mixture property and is a powerful tool for generating essential data for many applications.

The ITk is a new silicon tracker for the ATLAS experiment designed to increase detector resolution, readout capacity, and radiation hardness, in preparation for the larger number of simultaneous proton-proton interactions at the High Luminosity LHC. This paper presents the first direct measurement of the material budget of an ATLAS ITk pixel module, performed at a testbeam at the CERN Proton Synchrotron via the multiple scattering of low energy positrons within the module volume. Using a four plane telescope of thin monolithic pixel detectors from the MALTA collaboration, scattering datasets were recorded at a beam energy of $1.2\,\text{GeV}$. Kink angle distributions were extracted from tracks derived with and without information from the ITk pixel module, and were fit to extract the RMS scattering angle, which was converted to a fractional radiation length $x/X_0$. The average $x/X_0$ across the module was measured as $[0.89 \pm 0.01 \text{ (resolution)} \pm 0.01 \text{ (subtraction)} \pm 0.08 \text{ (beam momentum band)}]\%$, which agrees within uncertainties with an estimate of $0.88\%$ derived from material component expectations., Comment: 12 pages, 12 figures

The main purpose of this paper is to present the generalization of the inequalities between the modulus of the polar derivative and the polynomial itself, depending on consideration of the zeros inside and outside of a closed disk and the extremal coefficient position of the underlying polynomial., Comment: 8 pages

The separation of physical forces acting on the tip of a magnetic force microscope (MFM) is essential for correct magnetic imaging. Electrostatic forces can be modulated by varying the tip-sample potential and minimized to map the local Kelvin potential. However, distinguishing magnetic forces from van der Waals forces typically requires two measurements with opposite tip magnetizations under otherwise identical measurement conditions. Here, we present an inverted magnetic force microscope where the sample is mounted on a flat cantilever for force sensing, and the magnetic tip is attached to a miniaturized electromagnet that periodically flips the tip magnetization. This setup enables the extraction of magnetic tip-sample interactions from the sidebands occurring at the switching rate in the cantilever oscillation spectrum. Our method achieves the separation of magnetic signals from other force contributions in a single-scan mode. Future iterations of this setup may incorporate membrane, trampoline, or string resonators with ultra-high quality factors, potentially improving measurement sensitivity by up to three orders of magnitude compared to the state-of-the-art MFM systems using cantilevers., Comment: 7 pages, 4 figures in Main and 3 pages, 3 figures in supplement

In the era of Extremely Large Telescopes, the current generation of 8-10m facilities are likely to remain competitive at ground-UV wavelengths for the foreseeable future. The Cassegrain U-Band Efficient Spectrograph (CUBES) has been designed to provide high instrumental efficiency ( $>$ 37\%) observations in the near UV (305-400 nm requirement, 300-420 nm goal) at a spectral resolving power of R $>$ 20, 000 (with a lower-resolution, sky-limited mode of R $\sim$ 7, 000). With the design focusing on maximizing the instrument throughput (ensuring a Signal to Noise Ratio -SNR- $\sim$ 20 per spectral resolution element at 313 nm for U $\sim$ 17.5 mag objects in 1h of observations), it will offer new possibilities in many fields of astrophysics: i) access to key lines of stellar spectra (e.g. lighter elements, in particular Beryllium), extragalactic studies (e.g. circumgalactic medium of distant galaxies, cosmic UV background) and follow-up of explosive transients. We present the CUBES instrument design, currently in Phase-C and approaching the final design review, summarizing the hardware architecture and interfaces between the different subsystems as well as the relevant technical requirements. We describe the optical, mechanical, electrical design of the different subsystems (from the telescope adapter and support structure, through the main opto-mechanical path, including calibration unit, detector devices and cryostat control, main control electronics), detailing peculiar instrument functions like the Active Flexure Compensation (AFC). Furthermore, we outline the AITV concept and the main instrument operations giving an overview of its software ecosystem. Installation at the VLT is planned for 2028-2029 and first science operations in late 2029.

Until now, it has been difficult for volumetric super-resolution to utilize the recent advances in transformer-based models seen in 2D super-resolution. The memory required for self-attention in 3D volumes limits the receptive field. Therefore, long-range interactions are not used in 3D to the extent done in 2D and the strength of transformers is not realized. We propose a multi-scale transformer-based model based on hierarchical attention blocks combined with carrier tokens at multiple scales to overcome this. Here information from larger regions at coarse resolution is sequentially carried on to finer-resolution regions to predict the super-resolved image. Using transformer layers at each resolution, our coarse-to-fine modeling limits the number of tokens at each scale and enables attention over larger regions than what has previously been possible. We experimentally compare our method, MTVNet, against state-of-the-art volumetric super-resolution models on five 3D datasets demonstrating the advantage of an increased receptive field. This advantage is especially pronounced for images that are larger than what is seen in popularly used 3D datasets. Our code is available at https://github.com/AugustHoeg/MTVNet, Comment: 14 pages, 8 Figures with supplementary material

This letter presents the measurement of the energy-dependent neutrino-nucleon cross section in tungsten and the differential flux of muon neutrinos and anti-neutrinos. The analysis is performed using proton-proton collision data at a center-of-mass energy of $13.6 \, {\rm TeV}$ and corresponding to an integrated luminosity of $(65.6 \pm 1.4) \, \mathrm{fb^{-1}}$. Using the active electronic components of the FASER detector, $338.1 \pm 21.0$ charged current muon neutrino interaction events are identified, with backgrounds from other processes subtracted. We unfold the neutrino events into a fiducial volume corresponding to the sensitive regions of the FASER detector and interpret the results in two ways: We use the expected neutrino flux to measure the cross section, and we use the predicted cross section to measure the neutrino flux. Both results are presented in six bins of neutrino energy, achieving the first differential measurement in the TeV range. The observed distributions align with Standard Model predictions. Using this differential data, we extract the contributions of neutrinos from pion and kaon decays.

We report our experiences for the development of a neighborhood algorithm implemented via tree-codes to optimize the performance of a discrete element method (DEM) for convex polytopes. Our implementation of the two-dimensional tree code needs $N\log N$, as does the sort and sweep approach. For our choice of boundary conditions (a rotating drum) and system sizes (up to several thousand particles), the performance of the tree-code is slightly better, but the algorithm is considerably more complicated than the sort and sweep approach., Comment: Preprint. Under Review for the CCP2023 Proceedings

We show that a nonchiral atom can act as an antenna to induce a photoelectron circular dichroism in a nearby chiral molecule in a three-step process: The donor atom (antenna) is initially resonantly excited by circularly polarized radiation. It then transfers its excess energy to the acceptor molecule by means of resonant interatomic Coulombic decay. The latter finally absorbs the energy and emits an electron which exhibits the aforementioned circular dichroism in its angular distribution. We study the process on the basis of the retarded dipole--dipole interaction and report an asymptotic analytic expression for the distance-dependent chiral asymmetry of the photoelectron as induced by resonant interatomic Coulombic decay for random line-of-sight and acceptor orientations. In the nonretarded limit, the predicted chiral asymmetry is reversed as compared to that of a direct photoelectron circular dichroism of the molecule.

Treatment of cancer has rapidly evolved over time in quite dramatic ways, for example from chemotherapies, targeted therapies to immunotherapies and chimeric antigen receptor T-cells. Nonetheless, the basic design of early phase I trials in oncology still follows pre-dominantly a dose-escalation design. These trials monitor safety over the first treatment cycle in order to escalate the dose of the investigated drug. However, over time studying additional factors such as drug combinations and/or variation in the timing of dosing became important as well. Existing designs were continuously enhanced and expanded to account for increased trial complexity. With toxicities occurring at later stages beyond the first cycle and the need to treat patients over multiple cycles, the focus on the first treatment cycle only is becoming a limitation in nowadays multi-cycle treatment therapies. Here we introduce a multi-cycle time-to-event model (TITE-CLRM: Time-Interval-To-Event Complementary-Loglog Regression Model) allowing guidance of dose-escalation trials studying multi-cycle therapies. The challenge lies in balancing the need to monitor safety of longer treatment periods with the need to continuously enroll patients safely. The proposed multi-cycle time to event model is formulated as an extension to established concepts like the escalation with over dose control principle. The model is motivated from a current drug development project and evaluated in a simulation study., Comment: 18 pages, 8 figures, 1 table, 4 supplementary figures

In invasive breast cancer, cell clusters of varying sizes and shapes are embedded in the fibrous extracellular matrix (ECM). Although the prevailing view attributes this structure to increasing disorder resulting from loss of function and dedifferentiation, our findings reveal that it arises through a process of active self-organization driven by cancer cell motility. Simulations and histological analyses of tumours from over 2,000 breast cancer patients reveal that motile, aligned cancer cells within clusters move as active nematic aggregates through the surrounding highly aligned ECM fibres, which form a confining, passive nematic phase. Cellular motion leads to cluster splitting and coalescence. The degree of cluster activity, combined with heterogeneity in cell motility, is reflected in specific scaling behaviours for cluster shape, size distribution, and the distance between cluster boundaries and nematic defects in ECM alignment. Increased activity estimates correlate with tumour progression and are associated with a poorer prognosis for patients.

Stellar-mass black holes descend from high-mass stars, most of which had stellar binary companions. However, the number of those binary systems that survive the binary evolution and black hole formation is uncertain by multiple orders of magnitude. The survival rate is particularly uncertain for massive stars with low-mass companions, which are thought to be the progenitors of most black hole X-ray binaries. We present a search for close black hole companions (separations less than 20 solar radii) to AFGK-type stars in TESS, i.e. the non-accreting counterparts to and progenitors of low-mass X-ray binaries. Such black holes can be detected by the tidally induced ellipsoidal deformation of the visible star, and the ensuing photometric light-curve variations. From an initial sample of 4.7 million TESS stars, we have selected 457 candidates for such variations. However, spectroscopic followup of 251 of them shows that none are consistent with a close black hole companion. On the basis of this non-detection, we determine (2 $\sigma$ confidence) that fewer than one in $10^5$ Solar-type stars in the Solar neighbourhood host a short-period black hole companion. This upper limit is in tension with a number of ``optimistic'' population models in the literature that predict short-period black hole companions around one in $10^{4-5}$ stars. Our limits are still consistent with other models that predict only a few in $10^{7-8}$., Comment: 14 pages, 12 figures. Submitted to A&A. Comments welcome. Long forms of Tables 3 and 4 are included as FITS files in the Arxiv zip folder

Microdosimetry and nanodosimetry study the track structure of charged particles, i.e., the stochastics of radiation interaction on the microscopic scale. The (different) concepts developed in micro- and nanodosimetry are matched to the experimental approaches in the two fields. This work reviews the concepts of an event used in the two fields and explores a common denominator between the two methodologies to characterize particle track structure at the nanometric level. An approach to harmonize the concepts of microdosimetry and nanodosimetry for nanometric sites and linking them to macroscopic fluence is theoretically formulated and tested on proton tracks with energies between 1 MeV and 100 MeV. Unification of microdosimetry and nanodosimetry for the same target seems to require three elements: (1) the definition of an event as relating to a beam volume within which interactions of the primary particle can result in energy deposits or ionizations in the site, (2) the definition of a nanodosimetric analogue to a microdosimetric event, and (3) the redefinition of the microdosimetric concept of an event to include only events in which an ionization occurs in the site. The range of impact parameters of particle tracks that contributes to energy imparted in a site appears not to depend on whether any energy deposits or only energy deposits by ionizations are considered. Since there is no longer a one-to-one correspondence between tracks passing a site and the occurrence of an event, it is proposed to use the fluence for which on average one event occurs as a substitute for single events., Comment: 14 pages, 8 Figs. plus 11 Suppl. Figs., submitted To Radiation Physics and Chemistry

Push notifications are brief messages that users frequently encounter in their daily lives. However, the volume of notifications can lead to information overload, making it challenging for users to engage effectively. This study investigates how notification behavior and color influence user interaction and perception. To explore this, we developed an app prototype that tracks user interactions with notifications, categorizing them as accepted, dismissed, or ignored. After each interaction, users were asked to complete a survey regarding their perception of the notifications. The study focused on how different notification colors might affect the likelihood of acceptance and perceived importance. The results reveal that certain colors were more likely to be accepted and were perceived as more important compared to others, suggesting that both color and behavior play significant roles in shaping user engagement with notifications., Comment: 9 pages, 5 tables, 4 figures, 11 references

The recently launched James Webb Space Telescope (JWST) is opening new observing windows on the distant universe. Among JWST's instruments, the Mid Infrared Instrument (MIRI) offers the unique capability of imaging observations at wavelengths $\lambda > 5\mu$m. This enables unique access to the rest frame near infra-red (NIR, $\lambda \ge 1$\mum) emission from galaxies at redshifts $z>4$ and the visual ($\lambda \gtrsim 5000$\AA) rest frame for $z>9$. We here report on the guaranteed time observations (GTO) from the MIRI European Consortium, of the Hubble Ultra Deep Field (HUDF), forming the MIRI Deep Imaging Survey (MIDIS), consisting of an on source integration time of $\sim41$ hours in the MIRI/F560W (5.6 $\mu$m) filter. To our knowledge, this constitutes the longest single filter exposure obtained with JWST of an extragalactic field as yet., Comment: submitted to A&A on July 30, 2024

Using the parametric representation of a chaotic many-body quantum system derived earlier, we calculate explicitly the large-time dependence and asymptotic value of the out-of-time correlator (OTOC) of that system. The dependence on time $t$ is determined by $\Delta t / \hbar$. Here $\Delta$ is the energy correlation width within which the Bohigas-Giannoni-Schmit conjecture applies. We conjecture that $\Delta$ is universally related to the leading Ljapunov coefficient of the corresponding classical system by $\Delta = \hbar \lambda_{\max}$. Then the large-time behavior of OTOC is given by the dimensionless parameter $\lambda_{\max} t$.

In the last decade, the free energy principle (FEP) and active inference (AIF) have achieved many successes connecting conceptual models of learning and cognition to mathematical models of perception and action. This effort is driven by a multidisciplinary interest in understanding aspects of self-organizing complex adaptive systems, including elements of agency. Various reinforcement learning (RL) models performing active inference have been proposed and trained on standard RL tasks using deep neural networks. Recent work has focused on improving such agents' performance in complex environments by incorporating the latest machine learning techniques. In this paper, we take an alternative approach. Within the constraints imposed by the FEP and AIF, we attempt to model agents in an interpretable way without deep neural networks by introducing Free Energy Projective Simulation (FEPS). Using internal rewards only, FEPS agents build a representation of their partially observable environments with which they interact. Following AIF, the policy to achieve a given task is derived from this world model by minimizing the expected free energy. Leveraging the interpretability of the model, techniques are introduced to deal with long-term goals and reduce prediction errors caused by erroneous hidden state estimation. We test the FEPS model on two RL environments inspired from behavioral biology: a timed response task and a navigation task in a partially observable grid. Our results show that FEPS agents fully resolve the ambiguity of both environments by appropriately contextualizing their observations based on prediction accuracy only. In addition, they infer optimal policies flexibly for any target observation in the environment., Comment: 26 pages (including 5 pages appendix), 6 figures

Mathematical diffraction theory has been developed since about 1995. Hof's initial approach relied on tempered distributions in euclidean space. Nowadays often the Fourier theory by Argabright and Gil de Lamadrid is used, which applies to appropriate measures on locally compact abelian groups. We review diffraction theory using Wiener amalgams as test function spaces. For translation bounded measures, this unifies and simplifies the former two approaches. We treat weighted versions of Meyer's model sets as examples., Comment: 46 pages

We study the data-parallel language BUTF, inspired by the Futhark language for array programming. We give a translation of BUTF into a version of the pi-calculus with broadcasting and labeled names. The translation is both complete and sound. Moreover, we propose a cost model by annotating translated BUTF processes. This is used for a complexity analysis of the translation., Comment: In Proceedings EXPRESS/SOS 2024, arXiv:2411.13318

Simultaneous localization and mapping (SLAM) techniques can be used to navigate the visually impaired, but the development of robust SLAM solutions for crowded spaces is limited by the lack of realistic datasets. To address this, we introduce InCrowd-VI, a novel visual-inertial dataset specifically designed for human navigation in indoor pedestrian-rich environments. Recorded using Meta Aria Project glasses, it captures realistic scenarios without environmental control. InCrowd-VI features 58 sequences totaling a 5 km trajectory length and 1.5 hours of recording time, including RGB, stereo images, and IMU measurements. The dataset captures important challenges such as pedestrian occlusions, varying crowd densities, complex layouts, and lighting changes. Ground-truth trajectories, accurate to approximately 2 cm, are provided in the dataset, originating from the Meta Aria project machine perception SLAM service. In addition, a semi-dense 3D point cloud of scenes is provided for each sequence. The evaluation of state-of-the-art visual odometry (VO) and SLAM algorithms on InCrowd-VI revealed severe performance limitations in these realistic scenarios, demonstrating the need and value of the new dataset to advance SLAM research for visually impaired navigation in complex indoor environments., Comment: 18 pages, 7 figures, 5 tabels

A natural open problem in Ramsey theory is to determine those $3$-graphs $H$ for which the off-diagonal Ramsey number $r(H, K_n^{(3)})$ grows polynomially with $n$. We make substantial progress on this question by showing that if $H$ is tightly connected or has at most two tight components, then $r(H, K_n^{(3)})$ grows polynomially if and only if $H$ is not contained in an iterated blowup of an edge., Comment: 12 pages

Motivated by the vast gap between photometric and spectroscopic data volumes, there is great potential in using 5D kinematic information to identify and study substructures of the Milky Way. We identify substructures in the Galactic halo using 46,575 RR Lyrae stars (RRLs) from Gaia DR3 with the photometric metallicities and distances newly estimated by Li et al. (2023). Assuming a Gaussian prior distribution of radial velocity, we calculate the orbital distribution characterized by the integrals of motion for each RRL based on its 3D positions, proper motions and corresponding errors, and then apply the friends-of-friends algorithm to identify groups moving along similar orbits. We have identified several known substructures, including Sagittarius (Sgr) Stream, Hercules-Aquila Cloud (HAC), Virgo Overdensity (VOD), Gaia-Enceladus-Sausage (GES), Orphan-Chenab stream, Cetus-Palca, Helmi Streams, Sequoia, Wukong and Large Magellanic Cloud (LMC) leading arm, along with 18 unknown groups. Our findings indicate that HAC and VOD have kinematic and chemical properties remarkably similar to GES, with most HAC and VOD members exhibiting eccentricity as high as GES, suggesting that they may share a common origin with GES. The ability to identify the low mass and spatially dispersed substructures further demonstrates the potential of our method, which breaks the limit of spectroscopic survey and is competent to probe the substructures in the whole Galaxy. Finally, we have also identified 18 unknown groups with good spatial clustering and proper motion consistency, suggesting more excavation of Milky Way substructures in the future with only 5D data., Comment: 23 pages, 19 figures, 4 tables, accepted for publication in ApJ, version before language edition

We construct canonical measures, referred to as Hilbert measures, on orbit spaces of classical coregular representations of the orthogonal groups $\operatorname{O}_m$. We observe that the measures have singularities along non-principal strata of the orbit space if and only if the number of copies of the defining representation of $\operatorname{O}_m$ is equal to $m$., Comment: 12 pages

Understanding and predicting the structure and evolution of coronal mass ejections (CMEs) in the heliosphere remains one of the most sought-after goals in heliophysics and space weather research. A powerful tool for improving current knowledge and capabilities consists of multi-spacecraft observations of the same event, which take place when two or more spacecraft fortuitously find themselves in the path of a single CME. Multi-probe events can not only supply useful data to evaluate the large-scale of CMEs from 1D in-situ trajectories, but also provide additional constraints and validation opportunities for CME propagation models. In this work, we analyse and simulate the coronal and heliospheric evolution of a slow, streamer-blowout CME that erupted on 23 September 2021 and was encountered in situ by four spacecraft approximately equally distributed in heliocentric distance between 0.4 and 1 au. We employ the Open Solar Physics Rapid Ensemble Information (OSPREI) modelling suite in ensemble mode to predict the CME arrival and structure in a hindcast fashion and to compute the "best-fit" solutions at the different spacecraft individually and together. We find that the spread in the predicted quantities increases with heliocentric distance, suggesting that there may be a maximum (angular and radial) separation between an inner and an outer probe beyond which estimates of the in-situ magnetic field orientation (parameterised by flux rope model geometry) increasingly diverge. We discuss the importance of these exceptional observations and the results of our investigation in the context of advancing our understanding of CME structure and evolution as well as improving space weather forecasts., Comment: 20 pages, 12 figures, 3 tables; accepted for publication in MNRAS

A retrieval data structure stores a static function f : S -> {0,1}^r . For all x in S, it returns the r-bit value f(x), while for other inputs it may return an arbitrary result. The structure cannot answer membership queries, so it does not have to encode S. The information theoretic space lower bound for arbitrary inputs is r|S| bits. Retrieval data structures have widespread applications. They can be used as an approximate membership filter for S by storing fingerprints of the keys in S, where they are faster and more space efficient than Bloom filters. They can also be used as a basic building block of succinct data structures like perfect hash functions. Bumped Ribbon Retrieval (BuRR) [Dillinger et al., SEA'22] is a recently developed retrieval data structure that is fast to construct with a space overhead of less than 1%. The idea is to solve a nearly diagonal system of linear equations to determine a matrix that, multiplied with the hash of each key, gives the desired output values. During solving, BuRR might bump lines of the equation system to another layer of the same data structure. While the paper describes a simple parallel construction based on bumping the keys on thread boundaries, it does not give an implementation. In this brief announcement, we now fill this gap. Our parallel implementation is transparent to the queries. It achieves a speedup of 14 on 32 cores for 8-bit filters. The additional space overhead is 105 bytes per thread, or 105 slots. This matches 0.0007% of the total space consumption when constructing with 1 billion input keys. A large portion of the construction time is spent on parallel sorting.

The advancement of novel combinatorial CRISPR screening technologies enables the identification of synergistic gene combinations on a large scale. This is crucial for developing novel and effective combination therapies, but the combinatorial space makes exhaustive experimentation infeasible. We introduce NAIAD, an active learning framework that efficiently discovers optimal gene pairs capable of driving cells toward desired cellular phenotypes. NAIAD leverages single-gene perturbation effects and adaptive gene embeddings that scale with the training data size, mitigating overfitting in small-sample learning while capturing complex gene interactions as more data is collected. Evaluated on four CRISPR combinatorial perturbation datasets totaling over 350,000 genetic interactions, NAIAD, trained on small datasets, outperforms existing models by up to 40\% relative to the second-best. NAIAD's recommendation system prioritizes gene pairs with the maximum predicted effects, resulting in the highest marginal gain in each AI-experiment round and accelerating discovery with fewer CRISPR experimental iterations. Our NAIAD framework (https://github.com/NeptuneBio/NAIAD) improves the identification of novel, effective gene combinations, enabling more efficient CRISPR library design and offering promising applications in genomics research and therapeutic development.

We investigated the temporal and spectral features of $\gamma$ Cassiopeiae's X-ray emission within the context of the white dwarf accretion hypothesis. We find that the variabilities present in the X-ray data show two different signals, one primarily due to absorption and the other due to flickering like in non-magnetic cataclysmic variables. We then use this two-component insight to investigate previously un-reported simultaneous XMM and NuSTAR data. The model fitting results find white dwarf properties consistent with optical studies alongside a significant secondary, thermal source. We propose a secondary shock between the Be decretion disk and white dwarf accretion disk as the source. Finally, we analyzed a unique, low-count rate event of the XMM light curve as potential evidence for the white dwarf encountering Be decretion disk structures., Comment: Accepted for publication in ApJ

We present NeuralMag, a flexible and high-performance open-source Python library for micromagnetic simulations. NeuralMag leverages modern machine learning frameworks, such as PyTorch and JAX, to perform efficient tensor operations on various parallel hardware, including CPUs, GPUs, and TPUs. The library implements a novel nodal finite-difference discretization scheme that provides improved accuracy over traditional finite-difference methods without increasing computational complexity. NeuralMag is particularly well-suited for solving inverse problems, especially those with time-dependent objectives, thanks to its automatic differentiation capabilities. Performance benchmarks show that NeuralMag is competitive with state-of-the-art simulation codes while offering enhanced flexibility through its Python interface and integration with high-level computational backends.

This paper describes the Grid Optimization (GO) Competition Challenge 3, focusing on the problem motivation, formulation, solvers submitted by competition entrants, and analysis of the solutions produced. Funded by DOE/ARPA-E and led by a collaboration of national labs and academia members, the GO Competition addresses challenging problems in power systems planning and operations to drive research in advanced solution methods essential for a rapidly evolving electric power sector. Challenge 3 targets a multi-period unit commitment problem, incorporating AC power modeling and topology switching to reflect the dynamic grid management techniques required for future power systems. The competition results offer significant benefits to both researchers and industry practitioners. For researchers, it fosters innovation, encouraging the development of new algorithms to address the complexities of modern power systems. For industry practitioners, the competition drives the creation of more efficient and reliable computational tools, directly improving grid management practices. This collaboration bridges the gap between theory and practical implementation, advancing the field in meaningful ways. This paper documents the problem formulation, solver approaches, and the effectiveness of the solutions developed., Comment: Accepted for publication, Energy Systems S.I. : Power System Analytics under Uncertainty: In Memory of Peter W Sauer and Robert J Thomas

Two-dimensional (2D) carrier systems exhibit various significant physical phenomena for electronics and spintronics, where one of the most promising traits is efficient spin-to-charge conversion stemming from their Rashba-type spin-orbit interaction. Meanwhile, a nuisance in quests of promising materials for spintronics application is that vast majority of the investigated platforms consists of rare and/or toxic elements, such as Pt and Te, which hinders progress of spin conversion physics in view of element strategy and green technology. Here, we show the emergence of giant spin-orbit torque driven by 2D hole gas at the surface of hydrogen-terminated diamond, where the constituent substances are ubiquitous elements, carbon and hydrogen. The index of its spin torque efficiency at room temperature is several times greater than that of rare metal, Pt, the benchmark system/element for spin-to-charge conversion. Our finding opens a new pathway for more sustainable spintronics and spin-orbitronics applications, with efficient spin-orbit torque employing ubiquitous non-toxic elements., Comment: 19pages, 4figures

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment., Comment: 25 pages, 11 figures, submitted to ApJ

Photoelectron diffraction (PED) is a powerful and essential experimental technique for resolving the structure of surfaces with sub-angstrom resolution. In the high energy regime, researchers in angle-resolved photoemission spectroscopy (ARPES) observe modulating patterns attributed to X-ray-PED (XPD) effects. This is accompanied by other challenges such as low cross-sections, significant photon momentum transfer, and non-negligible phonon scattering. Overall, XPD is not only an advantageous approach but also exhibits unexpected effects. To disentangle these diffraction influences, we present a PED implementation for the SPRKKR package that utilizes multiple scattering theory and a one-step model in the photoemission process. Unlike real-space implementations of the multiple scattering XPD formalism, we propose a k-space implementation based on the layer KKR method. The main advantage of this method is its ability to address a very broad kinetic energy range (20-8000 eV) without convergence problems related to angular momentum and cluster size. Furthermore, the so-called alloy analogy model can be used to simulate XPD at finite temperatures as well as XPD effects observed in soft and hard X-ray ARPES. For practical applications, we have calculated the circular dichroism in angular distributions (CDAD) associated with core-level photoemission of 2p from Si(100) and 3p from Ge(100). Photoelectrons are excited by hard X-rays (6000 eV) with right and left circularly polarized radiation (RCP and LCP, respectively).

In future power systems, the detailed structure and dynamics may not always be fully known. This is due to an increasing number of distributed energy resources, such as photovoltaic generators, battery storage systems, heat pumps and electric vehicles, as well as a shift towards active distribution grids. Obtaining physically-based models for simulation and control synthesis can therefore become challenging. Differential equations, where the right-hand side is represented by a neural network, i.e., neural ordinary differential equations (NODEs), have a great potential to serve as a data-driven black-box model to overcome this challenge. This paper explores their use in identifying the dynamics of droop-controlled grid-forming units based on inputs and state measurements. In numerical studies, various NODE structures used with different numerical solvers are trained and evaluated. Moreover, they are compared to the sparse identification of nonlinear dynamics (SINDy) method. The results demonstrate that even though SINDy yields more accurate models, NODEs achieve good prediction performance without prior knowledge about the system's nonlinearities which SINDy requires to work best.

The neutrino sector of the seesaw-modified Standard Model is investigated under the anarchy principle. The anarchy principle leading to the seesaw ensemble is studied analytically with tools of random matrix theory. The probability density function is obtained., Comment: 16 pages. arXiv admin note: text overlap with arXiv:1609.08581 by other authors

The performance of millimeter-wave (mmWave) and sub-terahertz (sub-THz) communication systems is significantly impaired by sensitivity to sudden blockages. In this work, we employ machine learning (ML) and our physics-based simulation tool to warn about the upcoming blockage tens of 5G frames ahead for highway speeds, providing a sufficient time for a proactive response. Performance of this ML-aided early-warning-of-blockage (ML-EW) algorithm is analyzed for realistic outdoor mobile environments with diverse reflectors and antenna arrays placed at the base station (BS) and user equipment (UE) over a range of mmWave and sub-THz frequencies. ML accuracy of about 90% or higher is demonstrated for highway UE, blocker, and reflector speeds, multiple-input-multiple-output (MIMO) systems, and frequencies in mmWave/sub-THz range.

Altermagnets constitute a new class of magnetic materials that combine properties previously thought to be exclusive to either antiferromagnets or ferromagnets, and have unique properties of their own. In particular, a combination of symmetries connecting magnetic sublattices gives rise to a band spin splitting exhibiting unconventional d, g, or i-wave character. Their unique electronic properties have already led to new spin-dependent transport effects. Here, we consider their spin and charge dynamics on ultrafast timescales. We use a minimal tight binding model that captures the main features of the altermagnetic candidate material KRu$_4$O$_8$. In the framework of this model, we compute the spin-dependent electronic scattering dynamics after ultrashort-pulse excitation and show through these microscopic calculations how electron-electron and electron-phonon scattering processes redistribute optically excited carriers in a 2D slice of the Brillouin zone. We find that the optically excited spin polarization is long lived (~1ps) compared to the electron-electron momentum scattering lifetime of roughly 10fs. This contrasts remarkably with the much shorter spin lifetimes observed in typical ultrafast electronic spin dynamics in conventional ferromagnets and antiferromagnets, making these pulse-driven spin excitation experiments a key probe of altermagnetism.

In quantum computing, error mitigation is a method to improve the results of an error-prone quantum processor by post-processing them on a classical computer. In this work, we improve the General Error Mitigation (GEM) method for scalability. GEM relies on the use of a matrix to represent the device error, which requires the execution of $2^{n+1}$ calibration circuits on the quantum hardware, where $n$ is the number of qubits. With our improved method, the number of calibration runs is independent of the number of qubits and depends only on the number of non-zero states in the output distribution. We run 1853 randomly generated circuits with widths between 2-7 qubits and depths between 10-140 gates on IBMQ superconducting devices. The experiments show that the mitigation works comparably well to GEM, while requiring a fraction of the calibration runs. Finally, an experiment to mitigate errors in a 100 qubit circuit demonstrates the scalable features of our method.

Unauthorized sensing activities pose an increasing threat to individual privacy, particularly in the industrial, scientific, and medical (ISM) band where regulatory frameworks remain limited. This paper presents a novel signal process methodology to monitor and counter unauthorized sensing activities. Specifically, we model the pedestrian trajectories as a random process. Then, we leverage the Cram\'er-Rao bound (CRB) to evaluate sensing performance and model it as sampling error of such a random process. Through simulation, we verify the accuracy of monitoring unauthorized sensing activities in urban scenarios, and validate the effectiveness of corresponding mitigation strategies., Comment: Submitted to ICC 2025

We develop the notions of connections and curvature for general Lie-Rinehart algebras without using smoothness assumptions on the base space. We present situations when a connection exists. E.g., this is the case when the underlying module is finitely generated. We show how the group of module automorphism acts as gauge transformations on the space of connections. When the underlying module is projective we define a version of the Chern character reproducing results of Hideki Ozeki. We discuss various examples of flat connections and the associated Maurer-Cartan equations. We provide examples of Levi-Civita connections on singular varieties and singular differential spaces with non-zero Riemannian curvature. The main observation is that for quotient singularities, even though the metric degenerates along strata, the poles of the Christoffel symbols are removable., Comment: revised version, 30 pages, error in Section 11 corrected

Well-posedness and higher regularity of the heat equation with Robin boundary conditions in an unbounded two-dimensional wedge is established in an $L^{2}$-setting of monomially weighted spaces. A mathematical framework is developed which allows to obtain arbitrarily high regularity without a smallness assumption on the opening angle of the wedge. The challenging aspect is that the resolvent problem exhibits two breakings of the scaling invariance, one in the equation and one in the boundary condition.

We live in a world full of networks where our economy, our communication, and even our social life crucially depends on them. These networks typically emerge from the interaction of many entities, which is why researchers study agent-based models of network formation. While traditionally static networks with a fixed set of links were considered, a recent stream of works focuses on networks whose behavior may change over time. In particular, Bil\`o et al. (IJCAI 2023) recently introduced a game-theoretic network formation model that embeds temporal aspects in networks. More precisely, a network is formed by selfish agents corresponding to nodes in a given host network with edges having labels denoting their availability over time. Each agent strategically selects local, i.e., incident, edges to ensure temporal reachability towards everyone at low cost. In this work we set out to explore the impact of two novel conceptual features: agents are no longer restricted to creating incident edges, called the global setting, and agents might only want to ensure that they can reach a subset of the other nodes, called the terminal model. For both, we study the existence, structure, and quality of equilibrium networks. For the terminal model, we prove that many core properties crucially depend on the number of terminals. We also develop a novel tool that allows translating equilibrium constructions from the non-terminal model to the terminal model. For the global setting, we show the surprising result that equilibria in the global and the local model are incomparable and we establish a high lower bound on the Price of Anarchy of the global setting that matches the upper bound of the local model. This shows the counter-intuitive fact that allowing agents more flexibility in edge creation does not improve the quality of equilibrium networks.

As a promising technology, physical layer security (PLS) enhances security by leveraging the physical characteristics of communication channels. However, the conventional PLS approach leads to a considerable disparity in the effort legitimate users need to secure data compared to eavesdroppers. To address this issue, we propose a physical layer deception (PLD) framework, which applies random deceptive ciphering and orthogonal frequency-division multiplexing (OFDM) to defend against eavesdropping proactively. While ensuring the same level of confidentiality as traditional PLS methods, the PLD approach additionally introduces a deception mechanism, even when the eavesdropper possesses the same knowledge about the transmitter end as the legitimate receiver. Through thorough theoretical analyses and numerical simulations, we prove the superiority of our method over the conventional PLS approach., Comment: Submitted to ICC 2025 (appendices are excluded from the submitted version due to length limit)

In this paper we evaluate integrals of products of gamma functions of Ramanujan type in terms of bilateral hypergeometric series. In cases where the bilateral hypergeometric series are summable, then we evaluate these integral as beta integrals. In addition, we obtain integral representations for bilateral hypergeometric series.

Accurate property prediction is crucial for accelerating the discovery of new molecules. Although deep learning models have achieved remarkable success, their performance often relies on large amounts of labeled data that are expensive and time-consuming to obtain. Thus, there is a growing need for models that can perform well with limited experimentally-validated data. In this work, we introduce MoleVers, a versatile pretrained model designed for various types of molecular property prediction in the wild, i.e., where experimentally-validated molecular property labels are scarce. MoleVers adopts a two-stage pretraining strategy. In the first stage, the model learns molecular representations from large unlabeled datasets via masked atom prediction and dynamic denoising, a novel task enabled by a new branching encoder architecture. In the second stage, MoleVers is further pretrained using auxiliary labels obtained with inexpensive computational methods, enabling supervised learning without the need for costly experimental data. This two-stage framework allows MoleVers to learn representations that generalize effectively across various downstream datasets. We evaluate MoleVers on a new benchmark comprising 22 molecular datasets with diverse types of properties, the majority of which contain 50 or fewer training labels reflecting real-world conditions. MoleVers achieves state-of-the-art results on 20 out of the 22 datasets, and ranks second among the remaining two, highlighting its ability to bridge the gap between data-hungry models and real-world conditions where practically-useful labels are scarce.

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

This paper explores the integration of symmetries into the Koopman-operator framework for the analysis and efficient learning of equivariant dynamical systems using a group-convolutional approach. Approximating the Koopman operator by finite-dimensional surrogates, e.g., via extended dynamic mode decomposition (EDMD), is challenging for high-dimensional systems due to computational constraints. To tackle this problem with a particular focus on EDMD, we demonstrate -- under suitable equivarance assumptions on the system and the observables -- that the optimal EDMD matrix is equivariant. That is, its action on states can be described by group convolutions and the generalized Fourier transform. We show that this structural property has many advantages for equivariant systems, in particular, that it allows for data-efficient learning, fast predictions and fast eigenfunction approximations. We conduct numerical experiments on the Kuramoto--Sivashinsky equation, a nonlinear and chaotic partial differential equation, providing evidence of the effectiveness of this approach, and highlighting its potential for broader applications in dynamical systems analysis.

Open-weight large language model (LLM) zoos allow users to quickly integrate state-of-the-art models into systems. Despite increasing availability, selecting the most appropriate model for a given task still largely relies on public benchmark leaderboards and educated guesses. This can be unsatisfactory for both inference service providers and end users, where the providers usually prioritize cost efficiency, while the end users usually prioritize model output quality for their inference requests. In commercial settings, these two priorities are often brought together in Service Level Agreements (SLA). We present MESS+, an online stochastic optimization algorithm for energy-optimal model selection from a model zoo, which works on a per-inference-request basis. For a given SLA that requires high accuracy, we are up to 2.5x more energy efficient with MESS+ than with randomly selecting an LLM from the zoo while maintaining SLA quality constraints., Comment: Accepted at the 2024 Workshop on Adaptive Foundation Models in conjunction with NeurIPS 2024

Using a quantum gas setup consisting of a Bose-Einstein condensate strongly coupled to a high-finesse optical cavity by a transverse pump laser, we experimentally observe an instability of a dissipative continuous time crystal (CTC) towards a time crystalline state exhibiting two prominent oscillation frequencies. Applying a mean-field approximation model and a Floquet analysis, we theoretically confirm that this transition is a manifestation in a many-body system of a torus bifurcation between a limit cycle (LC) and a limit torus (LT). We theoretically illustrate the LC and LT attractors using the minimal model and experimentally reconstruct them using Takens' embedding theorem applied to the non-destructively measured intracavity photon dynamics.