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This study investigates the effects of 11B4C co-sputtering on the structural and optical properties of Fe/Si stacked multilayers, with a focus on neutron supermirror applications. X-ray and neutron reflectivity techniques reveal that 11B4C incorporation improves interface sharpness, reduces roughness, and enhances reflectivity for all multilayer periods. Neutron reflectivity measurements show reduced spin-flip intensities, while wafer-curvature measurements indicate a 50% reduction in internal stress, allowing for higher mechanical stability of the multilayers. These improvements are attributed to the amorphization of Fe layers, which also suppress the formation of structural and magnetic domains responsible for stress and spin-flip scattering. In contrast, the pure Fe/Si sample exhibits a persistent half-order Bragg peak, indicating residual antiferromagnetic coupling. The results demonstrate that 11B4C enhances neutron optics by reducing spin-flip effects, increasing reflectivity and polarization, and alleviating stress, enabling the use of polarizers at reduced external fields compared to pure Fe/Si multilayers. These findings establish 11B4C as a transformative material for advancing neutron supermirror technology, paving the way for more efficient, stable, and high-performance polarizers in next-generation neutron optics.

In this paper, we present an independent proof of the Cauchy identities for staircase matrices, originally discovered in arXiv:2411.03117, using the combinatorics of the Bruhat poset and the bubble-sort procedure. Additionally, we derive new insights into certain coefficients appearing in one of these identities. The first part of the paper focuses on combinatorial aspects. It is self-contained, of independent interest, and introduces a generalization of parabolic Bruhat graphs for monotone functions on an arborescent poset. The second part examines the intersections of Demazure modules within a given integrable representation. Finally, we propose a generalization of the classical Howe duality for staircase matrices in terms of the corresponding distributive lattice of Demazure submodules. Computing the associated character yields the desired Cauchy identities for staircase matrices., Comment: First draft, some figures and examples at the end of the paper

Interferometry is a fundamental technique in physics, enabling precise measurements through the interference of waves. High-harmonic generation (HHG) in solids has emerged as a powerful method for probing ultrafast electronic dynamics within crystalline structures. In this study, we employed extreme ultraviolet (XUV) high-harmonic interferometry with phase-locked XUV pulse pairs to investigate excitation-induced bandgap dynamics in solids. Our experiments on amorphous SiO2 and crystalline MgO, complemented by analytical modeling and semiconductor Bloch equation simulations, reveal a correlation between transient bandgap modifications and variations in the phase of harmonic emission. These findings suggest a potential pathway for sub-cycle, all-optical control of band structure modifications, advancing prospects for petahertz-scale electronic applications and attosecond diagnostics of carrier dynamics.

We present JWST NIRSpec integral field spectroscopy observations of the z=5.89 quasar NDWFS J1425+3254 from 0.6-5.3 microns, covering the rest-frame ultraviolet and optical at spectral resolution R~100. The quasar has a black hole mass of $M_{\rm{BH}}=(1.4\substack{+3.1\\-1.0})\times10^9 M_\odot$ and an Eddington ratio $L_{\rm{Bol}}/L_{\rm{Edd}}=0.3\substack{+0.6\\-0.2}$, as implied from the broad Balmer H$\alpha$ and H$\beta$ lines. We find that the quasar host has significant ongoing obscured star formation, as well as a quasar-driven outflow with velocity $6050\substack{+460\\-630}$ km/s, possibly one of the most extreme outflows in the early Universe. The data also reveals that two companion galaxies are merging with the quasar host. The north-eastern companion galaxy is relatively old and very massive, with luminosity-weighted stellar age $65\substack{+9\\-4}$ Myr, stellar mass $(3.6\substack{+0.6\\-0.3})\times10^{11} M_\odot$, and SFR $< (16.1\pm1.9) M_\odot$/yr. A bridge of gas connects this companion galaxy and the host, confirming their ongoing interaction. A second merger is occurring between the quasar host and a much younger companion galaxy to the south, with stellar age $6.7\pm1.8$ Myr, stellar mass $(1.9\pm0.4)\times10^{10} M_\odot$, and SFR $< (93\substack{+17\\-16}) M_\odot$/yr. There is also another galaxy in the field that is likely in the foreground at z=1.135, that could be gravitationally lensing the quasar with magnification $1<\mu<2$, and so <0.75 mag. Overall, the system is a "train-wreck" merger of three galaxies, with star formation and extreme quasar activity that were likely triggered by these ongoing interactions., Comment: Submitted to A&A

Context: Developing compilers and static analysis tools ("language tools") is a difficult and time-consuming task. We have previously presented *property probes*, a technique to help the language tool developer build understanding of their tool. A probe presents a live view into the internals of the compiler, enabling the developer to see all the intermediate steps of a compilation or analysis rather than just the final output. This technique has been realized in a tool called CodeProber. Inquiry: CodeProber has been in active use in both research and education for over two years, but its practical use has not been well studied. CodeProber combines liveness, AST exploration and presenting program analysis results on top of source code. While there are other tools that specifically target language tool developers, we are not aware of any that has the same design as CodeProber, much less any such tool with an extensive user study. We therefore claim there is a lack of knowledge how property probes (and by extension CodeProber) are used in practice. Approach: We present the results from a mixed-method study of use of CodeProber in an educational setting, with the goal to discover if and how property probes help, and how they compare to more traditional techniques such as test cases and print debugging. In the study, we analyzed data from 11 in-person interviews with students using CodeProber as part of a course on program analysis. We also analyzed CodeProber event logs from 24 students in the same course, and 51 anonymized survey responses across two courses where CodeProber was used. Knowledge: Our findings show that the students find CodeProber to be useful, and they make continuous use of it during the course labs. We further find that the students in our study seem to partially or fully use CodeProber instead of other development tools and techniques, e.g. breakpoint/step-debugging, test cases and print debugging. Grounding: Our claims are supported by three different data sources: 11 in-person interviews, log analysis from 24 students, and surveys with 51 responses. Importance: We hope our findings inspire others to consider live exploration to help language tool developers build understanding of their tool.

We study electromagnetic (EM) response of the excitonic insulator phase of time-reversal invariant Weyl semimetals (WSMs). Because of the chiral anomaly and the chiral magnetic effect in the parent WSM, the phase of the exciton condensate couples to the EM fields as a massive dynamical axion. Although the translational symmetry of the WSM is broken in the excitonic insulator state, the axion field is not related to the phase of the sliding exciton density wave. The axion mass is generated by the inter-band matrix elements of electron-electron interactions, and is much smaller than the gap in the single-particle spectrum. Due to the small axion mass, in the presence of a magnetic field, the axion coupling to EM fields produces giant anisotropic polarizability and birefringence. The photon-axion hybridization produces a polariton resonance near the axion gap., Comment: 6 pages, 1 figure

We report the spectroscopic confirmation of the background source of the most distant Einstein ring known to date, the COSMOS-Web ring. This system consists of a complete Einstein ring at $z=5.1$, lensed by a massive early-type galaxy at $z\sim2$. The redshift $z=5.1043\pm0.0004$ is unambiguously identified with our NOEMA and Keck/MOSFIRE spectroscopy, where the NOEMA observations reveal the CO(4-3) and CO(5-4) lines at $>8\,\sigma$, and the MOSFIRE data detect [O\textsc{ii}] at $\sim 6\,\sigma$. Using multi-wavelength photometry spanning near-infrared to radio bands, we find that the lensed galaxy is a dust-obscured starburst ($M_{\star} \sim 1.8\times10^{10}\,{\rm M_{\odot}}$, ${\rm SFR_{IR}\sim 60\,{\rm M_{\odot}} ~yr^{-1}}$) with high star-formation efficiency (gas depletion time $\tau_{\rm dep}<100~$Myr) as indicated by the [C\textsc{i}](1-0) non-detection. The redshift confirmation revalidates that the total lens mass budget within the Einstein radius is fully accounted for by the stellar and dark matter components, without the need of modifying the initial mass function or dark matter distribution profile. This work paves the way for detailed studies and future follow-ups of this unique lensing system, providing an ideal laboratory for studying mass distribution at $z\sim2$ and physical conditions of star formation at $z\sim5$.

A piecewise affine map is one of the simplest mathematical objects exhibiting complex dynamics. The reachability problem of piecewise affine maps is given as follows: Given two vectors $\mathbf{s}, \mathbf{t} \in \mathbb{Q}^d$ and a piecewise affine map $f$, is there $n\in \mathbb{N}$ such that $f^{n}(\mathbf{s}) = \mathbf{t}$? Koiran, Cosnard, and Garzon show that the reachability problem of piecewise affine maps is undecidable even in dimension 2. Most of the recent progress has been focused on decision procedures for one-dimensional piecewise affine maps, where the reachability problem has been shown to be decidable for some subclasses. However, the general undecidability discouraged research into positive results in arbitrary dimension. In this work, we consider a rich subclass of piecewise affine maps defined by Bellman operators of Markov decision processes (MDPs). We then investigate the restriction of the piecewise affine reachability problem to that with Bellman operators and, in particular, its decidability in any dimension. As one of our primary contributions, we establish the decidability of reachability for two-dimensional Bellman operators, in contrast to the negative result known for general piecewise affine maps., Comment: 17 pages, 4 figures

Pulse-modulated feedback is utilized in drug dosing to mimic sustained over a longer period of time manual discrete dose administration, the latter is in contrast with continuous drug infusion. The intermittent mode of dosing calls for a hybrid (continuous-discrete) modeling of the closed-loop system, where the pharmacokinetics and pharmacodynamics of the drug are captured by differential equations whereas the control law is described by difference equations. Hybrid dynamics are highly nonlinear which complicates formal design of pulse-modulated feedback. This paper demonstrates complex nonlinear dynamical phenomena arising in a simple control system of dosing a neuromuscular blockade agent in anesthesia. Along with the nominal periodic regimen, undesirable nonlinear behaviors, i.e. periodic solutions of high multiplicity, multistability, as well as deterministic chaos, are shown to exist. It is concluded that design of feedback drug dosing algorithms based on a hybrid paradigm has to be informed by a thorough bifurcation analysis in order to secure patient safety.

Research in AI for Science often focuses on using AI technologies to augment components of the scientific process, or in some cases, the entire scientific method; how about AI for scientific publications? Peer-reviewed journals are foundational repositories of specialized knowledge, written in discipline-specific language that differs from general Internet content used to train most large language models (LLMs) and vision-language models (VLMs). We hypothesized that by combining a family of scientific journals with generative AI models, we could invent novel tools for scientific communication, education, and clinical care. We converted 23,000 articles from Neurosurgery Publications into a multimodal database - NeuroPubs - of 134 million words and 78,000 image-caption pairs to develop six datasets for building AI models. We showed that the content of NeuroPubs uniquely represents neurosurgery-specific clinical contexts compared with broader datasets and PubMed. For publishing, we employed generalist VLMs to automatically generate graphical abstracts from articles. Editorial board members rated 70% of these as ready for publication without further edits. For education, we generated 89,587 test questions in the style of the ABNS written board exam, which trainee and faculty neurosurgeons found indistinguishable from genuine examples 54% of the time. We used these questions alongside a curriculum learning process to track knowledge acquisition while training our 34 billion-parameter VLM (CNS-Obsidian). In a blinded, randomized controlled trial, we demonstrated the non-inferiority of CNS-Obsidian to GPT-4o (p = 0.1154) as a diagnostic copilot for a neurosurgical service. Our findings lay a novel foundation for AI with Science and establish a framework to elevate scientific communication using state-of-the-art generative artificial intelligence while maintaining rigorous quality standards.

We study a class of UV-complete, strongly coupled, confining three-dimensional field theories, that exhibit a novel stabilisation mechanism for the mass of the lightest scalar composite state, relying on the existence of a critical point. The theories admit a holographic dual description in terms of regular backgrounds in eleven-dimensional supergravity. Their phase diagram includes a line of first-order phase transitions ending at the critical point, where the transition becomes of second order. We calculate the mass spectrum of bound states of the field theory, by considering fluctuations around the background solutions, and find that, near the critical point, a hierarchy of scales develops, such that one state becomes parametrically light. We identify this state as the dilaton, the pseudo-Nambu-Goldstone boson associated with the spontaneous breaking of approximate scale invariance. This stabilisation mechanism might be exploited to address hierarchy problems in particle and astroparticle physics., Comment: 5 pages + appendices, 6 figures

An increasing number of datasets sharing similar domains for semantic segmentation have been published over the past few years. But despite the growing amount of overall data, it is still difficult to train bigger and better models due to inconsistency in taxonomy and/or labeling policies of different datasets. To this end, we propose a knowledge distillation approach that also serves as a label space unification method for semantic segmentation. In short, a teacher model is trained on a source dataset with a given taxonomy, then used to pseudo-label additional data for which ground truth labels of a related label space exist. By mapping the related taxonomies to the source taxonomy, we create constraints within which the model can predict pseudo-labels. Using the improved pseudo-labels we train student models that consistently outperform their teachers in two challenging domains, namely urban and off-road driving. Our ground truth-corrected pseudo-labels span over 12 and 7 public datasets with 388.230 and 18.558 images for the urban and off-road domains, respectively, creating the largest compound datasets for autonomous driving to date.

Auroral streamers are important meso-scale processes of dynamic magnetosphere-ionosphere coupling, typically studied using imagers sensitive to energetic (>1 keV) electron precipitation, such as all-sky imagers (ASIs). This paper reports streamer-like red-line auroras, representing low-energy (<1 keV) precipitation, observed poleward of a black aurora and an auroral torch. These red-line auroras were associated with a magnetospheric electron injection and braking ion flows. Observations were made using the THEMIS spacecraft and ground-based imagers, including the ASI, REGO, and meridian scanning photometer (MSP) at Fort Smith. We identify plasma sheet electron pitch-angle scattering by time-domain structures (TDSs) and electron cyclotron harmonics (ECH) waves as the driver of these red-line auroras, because of (1) a strong correlation (~0.9) between observed red-line intensities and precipitating fluxes; (2) consistent red-line intensities from auroral transport code forward modeling, and (3) consistent precipitation characteristic energies from MSP optical inference and quasi-linear estimates., Comment: 18 pages, 3 figures, to be submitted to Geophysical Research Letters

The culture of the Post-Soviet states is complex, shaped by a turbulent history that continues to influence current events. In this study, we investigate the Post-Soviet cultural food knowledge of foundation models by constructing BORSch, a multimodal dataset encompassing 1147 and 823 dishes in the Russian and Ukrainian languages, centered around the Post-Soviet region. We demonstrate that leading models struggle to correctly identify the origins of dishes from Post-Soviet nations in both text-only and multimodal Question Answering (QA), instead over-predicting countries linked to the language the question is asked in. Through analysis of pretraining data, we show that these results can be explained by misleading dish-origin co-occurrences, along with linguistic phenomena such as Russian-Ukrainian code mixing. Finally, to move beyond QA-based assessments, we test models' abilities to produce accurate visual descriptions of dishes. The weak correlation between this task and QA suggests that QA alone may be insufficient as an evaluation of cultural understanding. To foster further research, we will make BORSch publicly available at https://github.com/alavrouk/BORSch.

The increasing complexity and dynamic nature of 5G open radio access networks (O-RAN) pose significant challenges to maintaining low latency, high throughput, and resource efficiency. While existing methods leverage machine learning for latency prediction and resource management, they often lack real-world scalability and hardware validation. This paper addresses these limitations by presenting an artificial intelligence-driven latency forecasting system integrated into a functional O-RAN prototype. The system uses a bidirectional long short-term memory model to predict latency in real time within a scalable, open-source framework built with FlexRIC. Experimental results demonstrate the model's efficacy, achieving a loss metric below 0.04, thus validating its applicability in dynamic 5G environments.

We report on a search for weakly interacting massive particle (WIMP) dark matter (DM) via elastic DM-xenon-nucleus interactions in the XENONnT experiment. We combine datasets from the first and second science campaigns resulting in a total exposure of $3.1\;\text{tonne}\times\text{year}$. In a blind analysis of nuclear recoil events with energies above $3.8\,\mathrm{keV_{NR}}$, we find no significant excess above background. We set new upper limits on the spin-independent WIMP-nucleon scattering cross-section for WIMP masses above $10\,\mathrm{GeV}/c^2$ with a minimum of $1.7\,\times\,10^{-47}\,\mathrm{cm^2}$ at $90\,\%$ confidence level for a WIMP mass of $30\,\mathrm{GeV}/c^2$. We achieve a best median sensitivity of $1.4\,\times\,10^{-47}\,\mathrm{cm^2}$ for a $41\,\mathrm{GeV}/c^2$ WIMP. Compared to the result from the first XENONnT science dataset, we improve our sensitivity by a factor of up to 1.8., Comment: Limits are included in the submission file

3C 454.3 is a flat spectrum radio quasar (FSRQ) known for its high variability across the electromagnetic spectrum, showing structural and flux variability in its pc-scale jet, and correlated variability among frequency bands. This study aims to identify the structure, dynamics, and radiative processes common to the innermost regions of the blazar 3C 454.3. We investigate whether any jet component can be associated with $\gamma-$ray emission and variability. We analyze the relationship between the variable $\gamma-$ray emission and pc-scale jet properties in 3C 454.3 by combining $\gamma-$ray data spanning twelve years with contemporaneous VLBA multi-epoch images at 15 and 43 GHz. Spearman rank correlation tests are conducted to determine if the flux variability of any jet component is associated with $\gamma-$ray variability. Core emission at 43 and 15 GHz strongly correlates with $\gamma-$ray emission. The 43 GHz core (Q0) contributes around 37$\%$ of the observed $\gamma-$ray variability, while the 15 GHz core (K0) accounts for 30$\%$. A quasi-stationary component at 43 GHz, at a projected distance of 4.6 pc, correlates with the $\gamma-$ray flux, accounting for 20$\%$ of its emission between 2016 and 2021. We found a mobile component (Q3 between 2010.18 and 2011.16) at 43 GHz with a projected distance between 0.8 and 2.3 pc and apparent velocity of $\beta_{app} = 9.9 \pm 1.1$ c, accounting for approximately 28% of the $\gamma-$ray emission. The observed simultaneous variability in emission regions beyond the central parsec strongly suggests synchrotron self-Compton (SSC) as the primary mechanism for $\gamma-$ray production in these regions. Our findings demonstrate the existence of multiple $\gamma-$ray emission regions within the blazar jet but also suggest that some of these regions are non-stationary over time., Comment: A&A accepted, 9 pages, 6 figures

Tag-Pag is an application designed to simplify the categorization of web pages, a task increasingly common for researchers who scrape web pages to analyze individuals' browsing patterns or train machine learning classifiers. Unlike existing tools that focus on annotating sections of text, Tag-Pag systematizes page-level annotations, allowing users to determine whether an entire document relates to one or multiple predefined topics. Tag-Pag offers an intuitive interface to configure the input web pages and annotation labels. It integrates libraries to extract content from the HTML and URL indicators to aid the annotation process. It provides direct access to both scraped and live versions of the web page. Our tool is designed to expedite the annotation process with features like quick navigation, label assignment, and export functionality, making it a versatile and efficient tool for various research applications. Tag-Pag is available at https://github.com/Pantonius/TagPag.

This paper provides an overview of the applications of sheaf theory in deep learning, data science, and computer science in general. The primary text of this work serves as a friendly introduction to applied and computational sheaf theory accessible to those with modest mathematical familiarity. We describe intuitions and motivations underlying sheaf theory shared by both theoretical researchers and practitioners, bridging classical mathematical theory and its more recent implementations within signal processing and deep learning. We observe that most notions commonly considered specific to cellular sheaves translate to sheaves on arbitrary posets, providing an interesting avenue for further generalization of these methods in applications, and we present a new algorithm to compute sheaf cohomology on arbitrary finite posets in response. By integrating classical theory with recent applications, this work reveals certain blind spots in current machine learning practices. We conclude with a list of problems related to sheaf-theoretic applications that we find mathematically insightful and practically instructive to solve. To ensure the exposition of sheaf theory is self-contained, a rigorous mathematical introduction is provided in appendices which moves from an introduction of diagrams and sheaves to the definition of derived functors, higher order cohomology, sheaf Laplacians, sheaf diffusion, and interconnections of these subjects therein., Comment: 117 pages, 8 figures

We introduce methods to quantify how Large Language Models (LLMs) encode and store contextual information, revealing that tokens often seen as minor (e.g., determiners, punctuation) carry surprisingly high context. Notably, removing these tokens -- especially stopwords, articles, and commas -- consistently degrades performance on MMLU and BABILong-4k, even if removing only irrelevant tokens. Our analysis also shows a strong correlation between contextualization and linearity, where linearity measures how closely the transformation from one layer's embeddings to the next can be approximated by a single linear mapping. These findings underscore the hidden importance of filler tokens in maintaining context. For further exploration, we present LLM-Microscope, an open-source toolkit that assesses token-level nonlinearity, evaluates contextual memory, visualizes intermediate layer contributions (via an adapted Logit Lens), and measures the intrinsic dimensionality of representations. This toolkit illuminates how seemingly trivial tokens can be critical for long-range understanding., Comment: accepted to NAACL 2025

Frustrated magnetism in face-centred cubic (fcc) magnetic sublattices remains underexplored but holds considerable potential for exotic magnetic behaviour. Here we report on the crystal structure, magnetic and thermodynamic properties of the $A$-site-vacant double hydroxide perovskite MnSn(OH)$_6$. Despite dominant antiferromagnetic interactions among Mn$^{2+}$ moments, evidenced by a negative Curie-Weiss temperature, the lack of a sharp thermodynamic transition down to 350$\,$mK implies the absence of long-range magnetic order. However, a broad hump in the specific heat at 1.6$\,$K suggests short-range correlations. Neutron diffraction at low temperatures confirms the presence of three-dimensional (3D) antiferromagnetic correlations, manifested as diffuse magnetic scattering with a correlation length $\xi = 24.66\,${\AA} and magnetic propagation vectors $\mathbf{k}=(\frac{1}{2}\,\frac{1}{2}\,\frac{1}{2})$ and $(0\,0.625\,0)$ at 20$\,$mK., Comment: 9.5 pages, 5 figures. CIF files included as arXiv ancillary files

Approaching phase boundaries in many-body systems can give rise to intriguing signatures in their excitation spectra. Here, we explore the excitation spectrum of a Bose-Einstein condensate strongly coupled to an optical cavity and pumped by an optical standing wave, which simulates the famous Dicke-Hepp-Lieb phase transition of the open Dicke model with dissipation arising due to photon leakage from the cavity. For weak dissipation, the excitation spectrum displays two strongly polaritonic modes. Close to the phase boundary, we observe an intriguing regime where the lower-energetic of these modes, instead of showing the expected roton-type mode softening, is found to approach and persist at zero energy, well before the critical pump strength for the Dicke-Hepp-Lieb transition boundary is reached. Hence, a peculiar situation arises, where an excitation is possible at zero energy cost, but nevertheless no instability of the system is created.

Understanding water behaviour on 2D materials is crucial for sensing, microfluidics, and tribology. While water/graphene interactions are well studied, water on hexagonal boron nitride (h-BN) remains largely unexplored. Despite structural similarity to graphene, h-BN's slightly polar B-N bonds impart a large band gap, high thermal conductivity, and chemical stability, making it promising for electronics, lubricants, and coatings. Moreover, existing water studies often focus on multilayer water dynamics, overlooking single-molecular details. We bridge this gap by studying single-molecular water friction and diffusion on h-BN, comparing it with graphene using helium spin-echo experiments and ab initio calculations. Our findings show that water diffusion on h-BN/Ni follows a complex rotational-translational dynamic, unlike graphene. While conventional views treat water motion as discrete jumps between equivalent adsorption sites, we demonstrate that on h-BN, water molecules rotate freely around their centre of mass. Although the binding energies of water on h-BN and graphene are similar, the activation energy for water dynamics on h-BN is 2.5 times lower than on graphene, implying a much lower barrier for molecular mobility. The fundamentally different diffusion characteristics which classical models cannot capture, underscores the need to rethink how we model water on polar 2D materials. Moreover, our analysis reveals that the metal substrate strongly influences water friction, with h-BN/Ni showing a markedly lower friction than graphene/Ni, in stark contrast to the free-standing materials. These findings challenge assumptions about 2D material-water interactions, highlighting the crucial role of substrate effects in chemistry and material science and offer insights for designing next-generation microfluidic devices that require precise water mobility control.

The rise of generative image models leads to privacy concerns when it comes to the huge datasets used to train such models. This paper investigates the possibility of inferring if a set of face images was used for fine-tuning a Latent Diffusion Model (LDM). A Membership Inference Attack (MIA) method is presented for this task. Using generated auxiliary data for the training of the attack model leads to significantly better performance, and so does the use of watermarks. The guidance scale used for inference was found to have a significant influence. If a LDM is fine-tuned for long enough, the text prompt used for inference has no significant influence. The proposed MIA is found to be viable in a realistic black-box setup against LDMs fine-tuned on face-images., Comment: In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2025) - Volume 2: VISAPP, pages 439-446

The Athena mission entered a redefinition phase in July 2022, driven by the imperative to reduce the mission cost at completion for the European Space Agency below an acceptable target, while maintaining the flagship nature of its science return. This notably called for a complete redesign of the X-ray Integral Field Unit (X-IFU) cryogenic architecture towards a simpler active cooling chain. Passive cooling via successive radiative panels at spacecraft level is now used to provide a 50 K thermal environment to an X-IFU owned cryostat. 4.5 K cooling is achieved via a single remote active cryocooler unit, while a multi-stage Adiabatic Demagnetization Refrigerator ensures heat lift down to the 50 mK required by the detectors. Amidst these changes, the core concept of the readout chain remains robust, employing Transition Edge Sensor microcalorimeters and a SQUID-based Time-Division Multiplexing scheme. Noteworthy is the introduction of a slower pixel. This enables an increase in the multiplexing factor (from 34 to 48) without compromising the instrument energy resolution, hence keeping significant system margins to the new 4 eV resolution requirement. This allows reducing the number of channels by more than a factor two, and thus the resource demands on the system, while keeping a 4' field of view (compared to 5' before). In this article, we will give an overview of this new architecture, before detailing its anticipated performances. Finally, we will present the new X-IFU schedule, with its short term focus on demonstration activities towards a mission adoption in early 2027., Comment: 44 pages, 14 figures, accepted for publication in Experimental Astronomy

(Abridged) JWST observations have measured the ice composition toward two highly-extinguished field stars in the Chamaeleon I cloud. The observed extinction excess on the long-wavelength side of the H2O ice band at 3 micron has been attributed to a mixture of CH3OH with ammonia hydrates, which suggests that CH3OH ice could have formed in a water-rich environment with little CO depletion. Laboratory experiments and quantum chemical calculations suggest that CH3OH could form via the grain surface reactions CH3+OH and/or C+H2O in water-rich ices. However, no dedicated chemical modelling has been carried out thus far to test their efficiency and dependence on the astrochemical code employed. We model the ice chemistry in the Chamaeleon I cloud using a set of astrochemical codes (MAGICKAL, MONACO, Nautilus, UCLCHEM, and KMC simulations) to test the effects of the different code architectures and of the assumed ice chemistry. Our models show that the JWST ice observations are better reproduced for gas densities >1e5 cm-3 and collapse times >1e5 yr. CH3OH ice forms predominantly (>99%) via CO hydrogenation. The contribution of reactions CH3+OH and C+H2O, is negligible. The CO2 ice may form either via CO+OH or CO+O depending on the code. However, KMC simulations reveal that both mechanisms are efficient despite the low rate constant of the CO+O surface reaction. CH4 is largely underproduced for all codes except for UCLCHEM, for which a higher amount of atomic C is available during the initial translucent cloud phase. Large differences in the ice abundances are found at Tdust<12 K between diffusive and non-diffusive chemistry codes. This is due to the fact that non-diffusive chemistry takes over diffusive chemistry at such low Tdust. This could explain the rather constant ice chemical composition found in Chamaeleon I and other dense cores despite the different visual extinctions probed., Comment: Accepted in A&A

We construct a nonnegative function $g$ and a set $\Lambda = \{\lambda_1 < \lambda_2 < \dots\}$ of positive real numbers such that the system $\{g(x-\lambda_n)\}_{n=1}^\infty$ is complete simultaneously in all $L^p(\mathbb{R})$ spaces, $1 < p < \infty$, and $\Lambda$ satisfies one of the following two additional conditions: either $\Lambda$ is very sparse, namely, the ratios $\lambda_{n+1}/\lambda_n$ tend to $1$ arbitrarily slowly; or the differences $\lambda_{n+1} - \lambda_n$ attain only two different values, so $\Lambda$ has finite local complexity. Both constructions are, in a sense, extreme: it is well known that $\Lambda$ cannot be Hadamard lacunary and cannot be contained in any arithmetic progression.

Prethermalization phenomena in driven systems are generally understood via a local Floquet Hamiltonian obtained from a high-frequency expansion. Remarkably, recently it has been shown that a driven Kitaev spin liquid with fractionalized excitations can realize a quasi-stationary state that is not captured by this paradigm. Instead distinct types of fractionalized excitations are characterized by vastly different temperatures-a phenomenon dubbed "fractionalized prethermalization". In our work, we analyze fractionalized prethermalization in a driven one-dimensional Hubbard model at strong coupling which hosts spin-charge fractionalization. At intermediate frequencies quasi-steady states emerge which are characterized by a low spin and high charge temperature with lifetimes set by two competing processes: the lifetime of the quasiparticles determined by Fermi's Golden rule and the exponential lifetime of the Floquet prethermal plateau. We classify drives into three categories, each giving rise to distinct (fractional) prethermalization dynamics. Resorting to a time-dependent variant of the Schrieffer-Wolff transformation, we systematically analyze how these drive categories are linked to the underlying driven Hubbard model, thereby providing a general understanding of the emergent thermalization dynamics. We discuss routes towards an experimental realization of this phenomenon in quantum simulation platforms., Comment: 17 pages, 10 figures

Neutron reflectivity is a powerful technique for probing density profiles in films, with applications across Physics, Chemistry, and Biology. However, challenges arise when dealing with samples characterized by high roughness, unknown scattering length density (SLD) with low contrast, very thin layers, or complex multi-layered structures, that cannot be uniquely resolved due to the phase problem. Incorporating a magnetic reference layer (MRL) and using polarized neutron reflectivity improves sensitivity and modeling accuracy by providing complementary information. In this study, we introduce a quantitative way to compare MRL systems in a model-free way. We apply this approach to demonstrate that CoTi alloys offer a superior solution as an MRL compared to the commonly used Fe or Ni-based MRLs. The low nuclear and magnetic scattering length densities of CoTi significantly enhance sensitivity, making it particularly advantageous for soft matter research. Furthermore, the tunable Co vs Ti ratio allows for optimization of the SLDs to achieve maximum sensitivity, establishing CoTi as a highly effective choice for MRL applications. The applied simulation framework for optimizing MRL sensitivity to a specific materials system and research question is a generic approach that can be used prior to growing the MRL for a given experiment.

Magnetic hysteresis properties in Fe/Si multilayers have been studied as a function of the B4C content to control magnetization amplitude, coercivity, and hysteresis tilt, properties that are beneficial to tune for advancing applications in e.g. data storage, spintronics, and sensors. With an ion-assisted magnetron sputtering technique, 35 distinct thin film multilayer samples were prepared and their magnetic and structural properties were characterized by vibrating sample magnetometry, X-ray photoelectron spectroscopy, near edge X-ray absorption fine structure spectroscopy, and X-ray and neutron scattering methods. Key findings indicate that adding B4C lowers the coercivity and can decrease the saturation magnetization, demonstrating the tunability of magnetic responses based on composition. For samples with =30{\AA} periodicity, 10-15% of B4C addition produces antiferromagnetically (AF) coupled multilayers, and such AF coupling strength increases with the B4C content. Our findings reveal that B atoms do not chemically bind within the Fe atoms but instead occupy interstitial positions, disrupting medium- to long-range crystallinity thereby inducing the amorphization. Thereon, the observed effects on magnetic properties are directly attributed to this amorphization process caused by the presence of B4C. The demonstrated ability to finely adjust magnetic properties by varying the B4C content offers a promising approach to overcome challenges in magnetic device performance and efficiency.

The right tail asymptotic series consisting of attenuating exponential terms are derived for the densities of Galton-Watson processes with fractional probability generating functions. The frequencies in the exponential factors form fractal structures in the complex plane. We discuss conditions when the asymptotic series converges everywhere. The obtained right tail asymptotic is compared with the standard integral representation of the density and with the complete left tail asymptotic.

We propose a universal adversarial attack on multimodal Large Language Models (LLMs) that leverages a single optimized image to override alignment safeguards across diverse queries and even multiple models. By backpropagating through the vision encoder and language head, we craft a synthetic image that forces the model to respond with a targeted phrase (e.g., ''Sure, here it is'') or otherwise unsafe content-even for harmful prompts. In experiments on the SafeBench benchmark, our method achieves significantly higher attack success rates than existing baselines, including text-only universal prompts (e.g., up to 93% on certain models). We further demonstrate cross-model transferability by training on several multimodal LLMs simultaneously and testing on unseen architectures. Additionally, a multi-answer variant of our approach produces more natural-sounding (yet still malicious) responses. These findings underscore critical vulnerabilities in current multimodal alignment and call for more robust adversarial defenses. We will release code and datasets under the Apache-2.0 license. Warning: some content generated by Multimodal LLMs in this paper may be offensive to some readers., Comment: Added an affiliation

Simplicial complexes (SCs), a generalization of graph models for relational data that account for higher-order relations between data items, have become a popular abstraction for analyzing complex data using tools from topological data analysis or topological signal processing. However, the analysis of many real-world datasets leads to dense SCs with a large number of higher-order interactions. Unfortunately, analyzing such large SCs often has a prohibitive cost in terms of computation time and memory consumption. The sparsification of such complexes, i.e., the approximation of an original SC with a sparser simplicial complex with only a log-linear number of high-order simplices while maintaining a spectrum close to the original SC, is of broad interest. In this work, we develop a novel method for a probabilistic sparsifaction of SCs. At its core lies the efficient computation of sparsifying sampling probability through local densities of states as functional descriptors of the spectral information. To avoid pathological structures in the spectrum of the corresponding Hodge Laplacian operators, we suggest a "kernel-ignoring" decomposition for approximating the sampling probability; additionally, we exploit error estimates to show asymptotically prevailing algorithmic complexity of the developed method. The performance of the framework is demonstrated on the family of Vietoris--Rips filtered simplicial complexes., Comment: 10 pages, 7 figures

It is shown that the horizontal holonomy group of a K-contact sub-Riemannian manifold either coincides with the holonomy group of a Riemannian manifold, or it is a codimension-one normal subgroup of the later group. The question of existence of parallel horizontal spinors, examples, and consequences are discussed., Comment: 15 pages

This study explores the impact of boron carbide (B4C) addition on magnetic domains within Fe/Si multilayers through off-specular neutron scattering with polarization analysis. The incorporation of B4C induces amorphization in layers, disrupting magnetic domain structures. Analysis of the scattering patterns reveals that magnetic domains in pure Fe/Si multilayers exhibit no significant correlation between layers, resulting in a specific diffuse off-specular scattering signal, while the B4C incorporated Fe/Si multilayers revealed no diffuse off-specular scattering. We offer a qualitative interpretation of these scattering phenomena and accurately model the observed diffuse patterns using the distorted wave Born approximation. Low-energy {\mu}+SR measurements further reveal that local magnetic fields in Fe/Si and Fe/Si + B4C multilayers are more easily manipulated by external fields in B4C-containing layers, with enhanced field uniformity in the muon length-scale. Our findings provide insights into the role of B4C in altering magnetic domain arrangements within Fe/Si multilayers, contributing to advances in the design of magnetic materials and neutron polarization coatings.

This study investigates the effects of incorporating 11B4C interlayers into Fe/Si multilayers, with a focus on interface quality, reflectivity, polarization, and magnetic properties for polarized neutron optics. It is found that the introduction of 1 {\AA} and 2 {\AA} 11B4C interlayers significantly improves the interface sharpness, reducing interface width and preventing excessive Si diffusion into the Fe layers. X-ray reflectivity and polarized neutron reflectivity measurements show enhanced reflectivity and polarization, with a notable increase in polarization for 30 {\AA} period multilayers. The inclusion of interlayers also helps prevent the formation of iron-silicides, improving both the magnetic properties and neutron optical performance. However, the impact of interlayers is less pronounced in thicker-period multilayers (100 {\AA}), primarily due to the ratio between layer and interface widths. These results suggest that 11B4C interlayers offer a promising route for optimizing Fe/Si multilayer performance in polarized neutron mirrors.

CapyMOA is an open-source library designed for efficient machine learning on streaming data. It provides a structured framework for real-time learning and evaluation, featuring a flexible data representation. CapyMOA includes an extensible architecture that allows integration with external frameworks such as MOA and PyTorch, facilitating hybrid learning approaches that combine traditional online algorithms with deep learning techniques. By emphasizing adaptability, scalability, and usability, CapyMOA allows researchers and practitioners to tackle dynamic learning challenges across various domains.

All data modalities are not created equal, even when the signal they measure comes from the same source. In the case of the brain, two of the most important data modalities are the scalp electroencephalogram (EEG), and the intracranial electroencephalogram (iEEG). They are used by human experts, supported by deep learning (DL) models, to accomplish a variety of tasks, such as seizure detection and motor imagery classification. Although the differences between EEG and iEEG are well understood by human experts, the performance of DL models across these two modalities remains under-explored. To help characterize the importance of clean data on the performance of DL models, we propose BrainCodec, a high-fidelity EEG and iEEG neural compressor. We find that training BrainCodec on iEEG and then transferring to EEG yields higher reconstruction quality than training on EEG directly. In addition, we also find that training BrainCodec on both EEG and iEEG improves fidelity when reconstructing EEG. Our work indicates that data sources with higher SNR, such as iEEG, provide better performance across the board also in the medical time-series domain. BrainCodec also achieves up to a 64x compression on iEEG and EEG without a notable decrease in quality. BrainCodec markedly surpasses current state-of-the-art compression models both in final compression ratio and in reconstruction fidelity. We also evaluate the fidelity of the compressed signals objectively on a seizure detection and a motor imagery task performed by standard DL models. Here, we find that BrainCodec achieves a reconstruction fidelity high enough to ensure no performance degradation on the downstream tasks. Finally, we collect the subjective assessment of an expert neurologist, that confirms the high reconstruction quality of BrainCodec in a realistic scenario. The code is available at https://github.com/IBM/eeg-ieeg-brain-compressor., Comment: Published at ICLR 2025, see https://openreview.net/forum?id=b57IG6N20B. Code is available at https://github.com/IBM/eeg-ieeg-brain-compressor

Bent monolithic active pixel sensors are the basis for the planned fully cylindrical ultra low material budget tracking detector ITS3 of the ALICE experiment. This paper presents results from testbeam campaigns using high-energy particles to verify the performance of 50 um thick bent ALPIDE chips in terms of efficiency and spatial resolution. The sensors were bent to radii of 18, 24 and 30 mm, slightly smaller than the foreseen bending radii of the future ALICE ITS3 layers. An efficiency larger than $99.9\%$ and a spatial resolution of approximately 5 um, in line with the nominal operation of flat ALPIDE sensors, is obtained at nominal operating conditions. These values are found to be independent of the bending radius and thus constitute an additional milestone in the demonstration of the feasibility of the planned ITS3 detector. In addition, a special geometry in which the beam particles graze the chip and traverse it laterally over distances of up to 3 mm is investigated.

A distinct power-law break is apparent m_AB approximately 21 in the deep Near-Infrared PEARLS-JWST galaxy counts. The break becomes more pronounced at longer wavelengths, with the counts slope flattening smoothly with apparent magnitude in the shortest band used at 0.9 microns, trending towards an increasingly broken slope by the longest wavelength passband of JWST NIRCam, 4.4 microns. This behaviour is remarkably well predicted by the GALFORM semi-analytical model of galaxy formation. We use the model to diagnose the origin of this behaviour. We find that the features that are responsible for the break are: 1) the inherent break in the luminosity function; 2) the change in the volume element with redshift and 3) the redshift-dependent nature of the k-correction. We study the contribution to these effects by early and late-type galaxies, using as a proxy for morphology the bulge-to-total stellar mass ratio. We find that the way in which ellipticals populate the bright end of the luminosity function while spirals dominate the faint end is preserved in the galaxy number counts, with a characteristic stellar mass at the break of approximately 10^10 M_sun. We also find that the shape of the number counts is mainly driven by galaxies with relatively low redshift (z < 2) for the PEARLS observational limit of m_AB < 28. We give a comprehensive description of why the galaxy number counts in the near-infrared PEARLS-JWST observation look the way they do and which population of galaxies is dominant at each apparent magnitude.

The XENONnT experiment has achieved an unprecedented reduction of the $^\text{222}$Rn activity concentration within its liquid xenon dual-phase time projection chamber to a level of (0.90$\,\pm\,$0.01$\,$stat.$\,\pm\,$0.07 sys.)$\,\mu$Bq/kg, equivalent to about 1200 $^\text{222}$Rn atoms per cubic meter of liquid xenon. This represents a 15-fold improvement over the $^\text{222}$Rn levels encountered during XENON1T's main science runs and is a factor five lower compared to other currently operational multi-tonne liquid xenon detectors engaged in dark matter searches. This breakthrough enables the pursuit of various rare event searches that lie beyond the confines of the standard model of particle physics, with world-leading sensitivity. The ultra-low $^\text{222}$Rn levels have diminished the radon-induced background rate in the detector to a point where it is for the first time lower than the solar neutrino-induced background, which is poised to become the primary irreducible background in liquid xenon-based detectors.

The gamma-ray emission from Flat Spectrum Radio Quasars (FSRQs), a sub-class of blazars, is believed to be generated through interactions of high-energy leptons and/or hadrons in the jet with the ambient photon fields, including those from the accretion disk, the broad line region (BLR), and the dusty torus. However, these same photon fields can also attenuate gamma-rays through internal photon-photon (gamma-gamma) absorption, imprinting characteristic spectral features. Investigating the internal absorption is crucial for unraveling the complex structure of FSRQs and constraining the poorly known location of the gamma-ray emission region. In this study, we select a sample of gamma-ray detected FSRQs with high redshift (z >= 3), to search for absorption features appearing at lower photon energies due to a substantial redshift. We extract the Fermi-LAT gamma-ray spectra of these sources and perform physical modeling using a detailed gamma-gamma opacity model, assuming that the BLR photon field dominates the absorption and focusing on the energy range ~25 GeV/(1+z), where the absorption feature due to Ly{\alpha} photons is expected. Our analysis reveals a hint of internal absorption for one source (the lowest redshift object in our sample, z~3) and provides constraints on the location of its gamma-ray emitting region along the jet. For the remaining, higher-redshift sources, the limited photon statistics prevent a reliable detection of internal opacity features., Comment: 10 pages, 3 figures. Accepted for publication in ApJ

This paper investigates measurement uncertainty in a Reverberation Chamber (RC) within the lower FR2 bands (24.25-29.5 GHz). The study focuses on the impact of several factors contributing to RC measurement uncertainty, including finite sample size, polarization imbalance, and spatial non-uniformity. A series of 24 measurements were conducted using a horn antenna, known for its directivity in mmWave frequencies, varying antenna parameters such as height, orientation, position on the turntable, and polarization within a predefined chamber volume. The measurement uncertainty was evaluated by a method based on the standardized 3GPP and CTIA approaches, incorporating uncorrelated measurements and analyzing Pearson correlation coefficients between measurement pairs. An analysis of variance (ANOVA) was performed on the frequency-averaged power transfer function to identify the significance and impact of each variable on measurement variability. Additionally, the K-factor was estimated for each measurement set as part of the RC characterization, using an alternative approach to account for the turntable stirring effect. The findings highlight which variables most significantly influence measurement uncertainty, where the antenna orientation emerges as the most significant factor for the mmWave directive antenna setup.

High-performance micro-kernels must fully exploit today's diverse and specialized hardware to deliver peak performance to DNNs. While higher-level optimizations for DNNs are offered by numerous compilers (e.g., MLIR, TVM, OpenXLA), performance-critical micro-kernels are left to specialized code generators or handwritten assembly. Even though widely-adopted compilers (e.g., LLVM, GCC) offer tuned backends, their CPU-focused input abstraction, unstructured IR, and general-purpose best-effort design inhibit tailored code generation for innovative hardware. We think it is time to widen the classical hourglass backend and embrace progressive lowering across a diverse set of structured abstractions to bring domain-specific code generation to compiler backends. We demonstrate this concept by implementing a custom backend for a RISC-V-based accelerator with hardware loops and streaming registers, leveraging knowledge about the hardware at levels of abstraction that match its custom ISA. We use incremental register allocation over structured IRs, while dropping classical spilling heuristics, and show up to 90% FPU utilization across key DNN kernels. By breaking the backend hourglass model, we reopen the path from domain-specific abstractions to specialized hardware.