Search

The development of quantitative methods for characterizing molecular chirality can provide an important tool for studying chirality induced phenomena in molecular systems. Significant progress has been made in recent years toward understanding the chirality of molecular normal vibrational modes, mostly focusing on vibrations of helical molecular structures. In the present study, we examine the applicability two methodologies previously used for helical structures for the quantification of the chirality of molecular normal modes across a range of small, not necessarily helical, molecules. The first approach involves the application of the Continuous Chirality Measure (CCM) to each normal mode by associating the mode with a structure formed by imposing the corresponding motion about a common origin. The second approach assigns to each normal mode a pseudoscalar defined as the product of atomic linear and angular momentum summed over all atoms. In particular, using the CCM also as a measure of the chirality of the underlying molecular structure, we establish the existence of correlation between the chirality of molecular normal modes and that of the underlying molecular structure. Furthermore, we find that normal modes associated with different frequency ranges of the molecular vibrational spectrum exhibit distinct handedness behavior.

Robotic search and rescue, exploration, and inspection require trajectory planning across a variety of domains. A popular approach to trajectory planning for these types of missions is ergodic search, which biases a trajectory to spend time in parts of the exploration domain that are believed to contain more information. Most prior work on ergodic search has been limited to searching simple surfaces, like a 2D Euclidean plane or a sphere, as they rely on projecting functions defined on the exploration domain onto analytically obtained Fourier basis functions. In this paper, we extend ergodic search to any surface that can be approximated by a triangle mesh. The basis functions are approximated through finite element methods on a triangle mesh of the domain. We formally prove that this approximation converges to the continuous case as the mesh approximation converges to the true domain. We demonstrate that on domains where analytical basis functions are available (plane, sphere), the proposed method obtains equivalent results, and while on other domains (torus, bunny, wind turbine), the approach is versatile enough to still search effectively. Lastly, we also compare with an existing ergodic search technique that can handle complex domains and show that our method results in a higher quality exploration., Comment: 6 content pages, 1 references page, 6 figures, International Conference on Robotics and Automation 2025

In this work, we consider the problem of multi-agent informative path planning (IPP) for robots whose sensor visibility continuously changes as a consequence of a time-varying natural phenomenon. We leverage ergodic trajectory optimization (ETO), which generates paths such that the amount of time an agent spends in an area is proportional to the expected information in that area. We focus specifically on the problem of multi-agent drone search of a wildfire, where we use the time-varying environmental process of smoke diffusion to construct a sensor visibility model. This sensor visibility model is used to repeatedly calculate an expected information distribution (EID) to be used in the ETO algorithm. Our experiments show that our exploration method achieves improved information gathering over both baseline search methods and naive ergodic search formulations., Comment: Accepted to ICRA 2025

The level and uncertainty of the particle induced background in CCD detectors plays a crucial role for future X-ray instruments, such as the Wide Field Imager (WFI) onboard Athena. To mitigate the background systematic uncertainties, which will limit the Athena science goals, we aim to understand the relationship between the energetic charged particles interacting in the detector and satellite, and the instrumental science background to an unprecedented level. These particles produce easily identified "cosmic-ray tracks" along with less easily identified signals produced by secondary particles, e.g., X-rays generated by particle interactions with the instrument and indistinguishable from genuine sky X-rays. We utilize the Small Window Mode of the PN camera onboard XMM-Newton to understand the time, spatial and energy dependence of the various background components, particularly the particle induced background. While the distribution of particle events follows expected detector readout patterns, we find a particle track length distribution inconsistent with the simple, isotropic model. We also find that the detector mode-specific readout results in a shifted Cu fluorescent line. We illustrate that on long timescales the variability of the particle background correlates well with the solar cycle. This 20-year lightcurve, can be reproduced by a particle detector onboard Chandra, the HRC anti-coincidence shield. We conclude that the self-anti-coincidence method of removing X-ray-like events near detected particle tracks in the same frame can be optimized with the inclusion of additional information, such as the energy of the X-ray. The results presented here are relevant for any future pixelated X-ray imaging detector, and could allow the WFI to probe to truly faint X-ray surface brightness., Comment: 35 pages, 16 figures. Accepted for publication in JATIS

Recently, Seligman et. al. (2024) identified a population of near-Earth objects (NEOs) that exhibit statistically significant non-gravitational accelerations with no coma, and labeled them dark comets. Here, we show that one of these objects, 2005 VL1, was at closest approach to Earth in November 1965 when the Venera 2 spacecraft was launched to explore Venus. The observed H magnitude of 2005 VL1 is consistent with a high reflectance from the full surface of Venera 2 including its Solar panels. As known for Venera 2, 2005 VL1 arrived within a short distance from Venus in February 1966, a highly improbable coincidence (< 1%) for the orbital phase of a near-Earth object that does not target a close approach to Venus. Indeed, 2005 VL1's orbital parameters are very similar to the reported values for Venera 2. Given the area-to-mass ratio of Venera 2, we show that 2005 VL1's non-gravitational acceleration and negligible transverse acceleration match the values expected from Solar radiation pressure., Comment: 3 pages, 1 figure, submitted for publication in PNAS

Context: Compared to Class 0 protostars, the higher densities and lower temperatures of the disk midplanes of Class I young stellar objects (YSOs) limit the detectability of complex organic molecules (COMs). The elevated luminosities of eruptive YSOs increase disk temperatures sublimating frozen molecules and easing their detection. Aims: Our aim is to investigate the chemical composition of four FUor-like Class I YSOs: L1551 IRS 5, Haro 5a IRS, V346 Nor, and OO Ser, and to compare their abundances of COMs with other YSOs in the literature. Methods: We search for COMs line emission in ALMA Band 6 observations. We use the CASSIS software to determine their column densities (N) and excitation temperatures (T_ex) assuming local thermodynamical equilibrium. Results: We detect 249 transitions from 12 COMs. In L1551 IRS 5 we identified CH3OH, 13CH3OH, CH318OH, CH2DOH, CH3CHO, CH3OCH3, CH3OCHO, CH3COCH3, C2H5OH, C2H5CN, 13CH3CN, and CH3C15)N. Haro 5a IRS and OO Ser have emission from CH3OH, CH3CHO, CH3OCH3, and CH3OCHO. CH3COCH3 is also detected in OO Ser. In V346 Nor we found CH3OH, CH2DOH, CH3CHO, CH3OCH3, CH3OCHO, and C2H5CN. The emission of COMs is compact in all targets. The analysis indicates their temperatures are above 100K. The abundance ratios of COMs derived for these eruptive YSOs, as well as for other protostars in the literature, span several orders of magnitude without any clear differentiation between the eruptive and quiescent YSOs. The column density of the main isotopologue of CH3OH should not be used as a reference, as most of the lines are optically thick. Conclusions: The hot and compact emission of COMs indicates that the four FUor-like targets are hot corino-like. Spectral studies of such objects can be useful to investigate the complex organic chemistry at later evolutionary stages than the usual Class 0 stage., Comment: Accepted to A&A. 19 pages, 7 figures, 10 tables. 15 pages with 6 appendices uploaded to zenodo

We present a sample of 146 high-redshift ($z>7.5$) galaxies from the CANUCS/Technicolor surveys, showcasing photometry in every wide- and medium-band NIRCam filter in addition to ancillary HST data sampling $0.4-5 \mu m$ (22 JWST bands out of 29 bands total). Additionally, 48 ($33\%$) galaxies in our sample meet criteria to be classified as extreme emission line galaxies, 15 ($10\%$) of which are completely missed by typical dropout selections due to faint UV emission. By fitting the SEDs covering the rest-frame UV to optical at $z > 7.5$, we investigate the dust obscuration properties, giving an unbiased view of dust buildup in high-redshift galaxies free from spectroscopic follow-up selection effects. Dust attenuation correlates with stellar mass, but more strongly with star formation rate. We find typical galaxies at $z>7.5$ have $\sim 25 \%$ of their star formation obscured. However, since galaxies with higher star formation rates suffer more attenuation, $\sim 50 \%$ of the total star formation rate density at $7.5 15$, implying that epoch as when dust first forms in bright galaxies., Comment: 16 pages, 8 figures. Submitted to ApJ

The Bellman equation and its continuous-time counterpart, the Hamilton-Jacobi-Bellman (HJB) equation, serve as necessary conditions for optimality in reinforcement learning and optimal control. While the value function is known to be the unique solution to the Bellman equation in tabular settings, we demonstrate that this uniqueness fails to hold in continuous state spaces. Specifically, for linear dynamical systems, we prove the Bellman equation admits at least $\binom{2n}{n}$ solutions, where $n$ is the state dimension. Crucially, only one of these solutions yields both an optimal policy and a stable closed-loop system. We then demonstrate a common failure mode in value-based methods: convergence to unstable solutions due to the exponential imbalance between admissible and inadmissible solutions. Finally, we introduce a positive-definite neural architecture that guarantees convergence to the stable solution by construction to address this issue.

High-resolution colon segmentation is crucial for clinical and research applications, such as digital twins and personalized medicine. However, the leading open-source abdominal segmentation tool, TotalSegmentator, struggles with accuracy for the colon, which has a complex and variable shape, requiring time-intensive labeling. Here, we present the first fully automatic high-resolution colon segmentation method. To develop it, we first created a high resolution colon dataset using a pipeline that combines region growing with interactive machine learning to efficiently and accurately label the colon on CT colonography (CTC) images. Based on the generated dataset consisting of 435 labeled CTC images we trained an nnU-Net model for fully automatic colon segmentation. Our fully automatic model achieved an average symmetric surface distance of 0.2 mm (vs. 4.0 mm from TotalSegmentator) and a 95th percentile Hausdorff distance of 1.0 mm (vs. 18 mm from TotalSegmentator). Our segmentation accuracy substantially surpasses TotalSegmentator. We share our trained model and pipeline code, providing the first and only open-source tool for high-resolution colon segmentation. Additionally, we created a large-scale dataset of publicly available high-resolution colon labels.

We introduce the Granite Embedding models, a family of encoder-based embedding models designed for retrieval tasks, spanning dense-retrieval and sparse retrieval architectures, with both English and Multilingual capabilities. This report provides the technical details of training these highly effective 12 layer embedding models, along with their efficient 6 layer distilled counterparts. Extensive evaluations show that the models, developed with techniques like retrieval oriented pretraining, contrastive finetuning, knowledge distillation, and model merging significantly outperform publicly available models of similar sizes on both internal IBM retrieval and search tasks, and have equivalent performance on widely used information retrieval benchmarks, while being trained on high-quality data suitable for enterprise use. We publicly release all our Granite Embedding models under the Apache 2.0 license, allowing both research and commercial use at https://huggingface.co/collections/ibm-granite.

We demonstrate that the diffusion coefficient, $D$, for ultrasound propagating in a multiple scattering medium, such as a dense granular suspension, can be measured using a time reversal experiment. This requires an unprecedented experimental setup in which a piezoelectric transducer, acting as a Time-Reversal Mirror (TRM), is embedded within the granular suspension at a depth much larger than the scattering mean free path, while an array of transducers is placed in the far field of the scattering sample. A single element of the array emits a short pulse and the TRM records the resulting ultrasonic field, which consists of a ballistic coherent wave followed by a coda wave. When the entire coda wave is time-reversed and re-emitted from the TRM, it is observed to refocus on the original source, with a focal spot size that decreases with the inverse depth of the TRM, characteristic of a diffusive regime. Time-reversal of short windows selected at different times $t$ in the coda wave reveals a focal spot size that decreases as the inverse square root of time, i.e., $1 / \sqrt{Dt}$. By fitting the predictions of a microscopic diffusion theory to our experimental data, we are able to accurately measure the diffusion coefficient in the granular suspension. Remarkably, this method does not require ensemble averaging due to stability of time-reversal against statistical fluctuations.

Nuclear physics seeks to describe both bound and unbound states within a unified predictive framework. While coordinate-space Quantum Monte Carlo (QMC) methods have successfully computed bound states for systems with $A \leq 12$, their application to unbound states remains limited. In this work, we extend the QMC approach to enable a broader range of unbound-state calculations. Our method infers long-range amplitudes in the wave function from integrals over the short-range interaction region. By evaluating these integrals using Green's Function Monte Carlo wave functions with the Argonne $v_{18}$ potential, we accurately reproduce existing results for neutron-alpha scattering. This approach provides a systematic pathway for studying more complex nuclear systems, including coupled-channel scattering and the effects of three-nucleon forces. It serves as a powerful tool for advancing $\textit{ab initio}$ calculations in nuclear reactions, paving the way for a unified framework that consistently describes both bound and scattering states within a single theoretical approach., Comment: 38 pages, 9 figures

Breathing pyrochlores are a unique class of materials characterized by a three-dimensional lattice of corner-sharing tetrahedra. However, unlike conventional pyrochlores where all tetrahedra are identical in size, the breathing pyrochlore lattice is composed of alternating large and small tetrahedra. Experimental realizations of the breathing pyrochlore lattice are rare but they do occur in $A$-site ordered spinels, as in the prototype materials LiGaCr$_4$O$_8$ and LiInCr$_4$O$_8$. In this work, we demonstrate that Cr cannot be straightforwardly substituted with other magnetic transition metals while retaining the breathing pyrochlore structure. To explain this observation, we perform density functional theory (DFT) calculations to investigate the formation and stability of LiGaCr$_4$O$_8$ and LiInCr$_4$O$_8$, focusing on the energy scales associated with $A$ and $B$-site orderings as well as the magnetic exchange interactions of Cr ions. We identify the strong octahedral site preference of Cr$^{3+}$ as a key factor in protecting the structural integrity of the pyrochlore sublattice, which in turn enables the breathing distortion to proceed. We also demonstrate that the charge order between the $A$ (Li) and $A'$ sites (Ga or In) is maintained at all temperatures up to decomposition. Furthermore, while the magnetic exchange interactions constitute a relatively small energy scale and therefore do not play a fundamental role in the structural stability of LiGaCr$_4$O$_8$ and LiInCr$_4$O$_8$, magnetism may play a critical role in setting the magnitude of the tetrahedral distortion. Ultimately, we conclude that the scarcity of breathing pyrochlores is a consequence of the stringent requirement on site ordering for their formation., Comment: Accepted in Phys. Rev. Materials

DX Cha (HD 104237) is a spectroscopic binary consisting of a Herbig A7.5Ve-A8Ve primary star and a K3-type companion. Here we report on new $3.55$ micrometer interferometric observations of this source with the Multi Aperture Mid-Infrared Spectroscopic Experiment (MATISSE) at the Very Large Telescope Interferometer (VLTI). To model the four MATISSE observations obtained between 2020 and 2023, we constructed a time-dependent interferometric model of the system, using the oimodeler software. The model consists of an asymmetric ring and two point sources on a Keplerian orbit. Our best-fit model consists of a circumbinary ring with a diameter of $0.86$ au ($8.1$ mas), featuring a strong azimuthal asymmetry. We found that the position angle of the asymmetry changes tens of degrees between the MATISSE epochs. The ring is relatively narrow, with a full width at half maximum (FWHM) of $\sim$$0.13$ au ($1.23$ mas). The presence of circumstellar dust emission so close to the binary is unexpected, as previous hydrodynamic simulations predicted an inner disk cavity with a diameter of $\sim$$4$ au ($\sim$$37.5$ mas). Thus, we argue that the narrow envelope of material we detected is probably not a gravitationally stable circumbinary ring, but may be part of tidal accretion streamers channeling material from the inner edge of the disk toward the stars., Comment: Accepted for publication in ApJ, 11 pages, 5 figures, 5 tables

We prove well posedness and stability in $\mathbf{L}^1$ for a class of mixed hyperbolic-parabolic non linear and non local equations in a bounded domain with no flow along the boundary. While the treatment of boundary conditions for the hyperbolic equation is standard, the extension to $\mathbf{L}^1$ of classical results about parabolic equations with Neumann conditions is here achieved.

We introduce Granite Vision, a lightweight large language model with vision capabilities, specifically designed to excel in enterprise use cases, particularly in visual document understanding. Our model is trained on a comprehensive instruction-following dataset, including document-related tasks, such as content extraction from tables, charts, diagrams, sketches, and infographics, as well as general image tasks. The architecture of Granite Vision is centered around visual modality alignment with a decoder-only, 2 billion parameter Granite large language model. Additionally, we introduce a dedicated safety classification approach in test-time that leverages a sparse set of attention vectors to identify potential harmful inputs. Despite its lightweight architecture, Granite Vision achieves strong results in standard benchmarks related to visual document understanding, as well as on the LiveXiv benchmark, which is designed to avoid test set contamination by using a constantly updated corpus of recently published Arxiv papers. We are releasing the model under the Apache-2 license, allowing for both research and commercial use, while offering complete visibility into the training data and other relevant details. See https://huggingface.co/ibm-granite/ for model weights.

We report the discovery and multiwavelength followup of LEDA 1313424 ("Bullseye"), a collisional ring galaxy (CRG) with nine readily-identified rings -- the most so far reported for a CRG. These data shed new light on the rapid, multi-ring phase of CRG evolution. Using Hubble Space Telescope (HST) imaging, we identify and measure nine ring structures, several of which are "piled up" near the center of the galaxy, while others extend to tens of kpc scales. We also identify faint patches of emission at large radii ($\sim$70 kpc) in the HST imaging, and confirm the association of this emission with the galaxy via spectroscopy. Deep ground based imaging using the Dragonfly Telephoto Array finds evidence that this patch of emission is part of an older, fading ring from the collision. We find that the locations of the detected rings are an excellent match to predictions from analytic theory, if the galaxy was a 10-ring system whose outermost ring has faded away. We identify the likely impacting galaxy via Keck/KCWI spectroscopy, finding evidence for gas extending between it and the Bullseye. The overall size of this galaxy rivals that of known Giant Low Surface Brightness Galaxies (GLSBs) such as Malin I, lending credence to the hypothesis that CRGs can evolve into GLSBs as their rings expand and fade. Analysis of the HI content in this galaxy from ALFALFA finds significantly elevated neutral hydrogen with respect to the galaxy's stellar mass, another feature in alignment with GLSB systems., Comment: Published in ApJL

I show that a dedicated space telescope with a meter-size aperture can detect numerous interstellar objects, 10-m in diameter, that pass within ~20 degrees from the Sun. Separating the emitted thermal radiation from the reflection of sunlight would allow to measure the surface temperature, area and albedo of these objects. Spectroscopic observations of any evaporated material at the expected temperature of ~600K would provide important clues about the nature and birth sites of interstellar objects., Comment: 5 pages, submitted for publication in ApJL

Face parsing is a fundamental task in computer vision, enabling applications such as identity verification, facial editing, and controllable image synthesis. However, existing face parsing models often lack fairness and robustness, leading to biased segmentation across demographic groups and errors under occlusions, noise, and domain shifts. These limitations affect downstream face synthesis, where segmentation biases can degrade generative model outputs. We propose a multi-objective learning framework that optimizes accuracy, fairness, and robustness in face parsing. Our approach introduces a homotopy-based loss function that dynamically adjusts the importance of these objectives during training. To evaluate its impact, we compare multi-objective and single-objective U-Net models in a GAN-based face synthesis pipeline (Pix2PixHD). Our results show that fairness-aware and robust segmentation improves photorealism and consistency in face generation. Additionally, we conduct preliminary experiments using ControlNet, a structured conditioning model for diffusion-based synthesis, to explore how segmentation quality influences guided image generation. Our findings demonstrate that multi-objective face parsing improves demographic consistency and robustness, leading to higher-quality GAN-based synthesis.

Traditional methods for closing gastrointestinal (GI) surgery incisions, like suturing and stapling, present significant challenges, including potentially life-threatening leaks. These techniques, especially in robot-assisted minimally invasive surgery (RAMIS), require advanced manual skills. While their repetitive and time-consuming nature makes them suitable candidates for automation, the automation process is complicated by the need for extensive contact with the tissue. Addressing this, we demonstrate a semi-autonomous contactless surgical procedure using our novel Robot-assisted Laser Tissue Soldering (RLTS) system on a live porcine bowel. Towards this in-vivo demonstration, we optimized soldering protocols and system parameters in ex-vivo experiments on porcine bowels and a porcine cadaver. To assess the RLTS system performance, we compared the pressure at which the anastomosis leaked between our robotic soldering and manual suturing. With the best setup, we advanced to an in-vivo Heineke Mikulicz closure on small bowel incision in live pigs and evaluated their healing for two weeks. All pigs successfully completing the procedure (N=5) survived without leaks and the histology indicated mucosal regeneration and fibrous tissue adhesion. This marks the first in-vivo semi-automated contactless incision closure, paving the way for automating GI surgery incision closure which has the potential to become an alternative to traditional methods.

In the 1960s, the social scientist Stanley Milgram performed his famous "small-world" experiments where he found that people in the US who are far apart geographically are nevertheless connected by remarkably short chains of acquaintances. Since then, there has been considerable work to design networks that accurately model the phenomenon that Milgram observed. One well-known approach was Barab{\'a}si and Albert's preferential attachment model, which has small diameter yet lacks an algorithm that can efficiently find those short connections between nodes. Jon Kleinberg, in contrast, proposed a small-world graph formed from an $n \times n$ lattice that guarantees that greedy routing can navigate between any two nodes in $\mathcal{O}(\log^2 n)$ time with high probability. Further work by Goodrich and Ozel and by Gila, Goodrich, and Ozel present a hybrid technique that combines elements from these previous approaches to improve greedy routing time to $\mathcal{O}(\log n)$ hops. These are important theoretical results, but we believe that their reliance on the square lattice limits their application in the real world. In this work, we generalize the model of Gila, Ozel, and Goodrich to any class of what we call fixed-growth graphs of dimensionality $\alpha$, a subset of bounded-growth graphs introduced in several prior papers. We prove tight bounds for greedy routing and diameter in these graphs, both in expectation and with high probability. We then apply our model to the U.S. road network to show that by modeling the network as a fixed-growth graph rather than as a lattice, we are able to improve greedy routing performance over all 50 states. We also show empirically that the optimal clustering exponent for the U.S. road network is much better modeled by the dimensionality of the network $\alpha$ than by the network's size, as was conjectured in a previous work., Comment: v1 to appear in the 14th International Conference on Algorithms and Complexity (CIAC'25) in 2025, 26 pages, 5 figures

Two novel and direct quantum mechanical representations of the Black-Scholes model are constructed based on the (Wick-rotated) quantization of two specific mechanical systems. The quantum setup is achieved by means of the associated Laplace-Beltrami operator (one for each model), and not by merely applying the usual naive rule. Additionally, the clear identification of the geometric content of the underlying classical framework is exploited in order to arrive at a noncommutative quantum mechanics generalization of the Black-Scholes model. We also consider a system consisting of two degrees of freedom whose (Wick-rotated) quantization leads to a model which can be seen as related to the Merton-Garman family. This model is also generalized via noncommutative quantum mechanics.

The advent of AI tools, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 HCI researchers experienced in QDA. While our participants were open to AI support in their QDA workflows, they expressed concerns about data privacy, autonomy, and the quality of AI outputs. In response, we developed a framework that spans from minimal to high AI involvement, providing tangible scenarios for integrating AI into HCI researchers' QDA practices while addressing their needs and concerns. Aligned with real-life QDA workflows, we identify potentials for AI tools in areas such as data pre-processing, researcher onboarding, or mediation. Our framework aims to provoke further discussion on the development of AI-supported QDA and to help establish community standards for their responsible use.

Concept erasure has emerged as a promising technique for mitigating the risk of harmful content generation in diffusion models by selectively unlearning undesirable concepts. The common principle of previous works to remove a specific concept is to map it to a fixed generic concept, such as a neutral concept or just an empty text prompt. In this paper, we demonstrate that this fixed-target strategy is suboptimal, as it fails to account for the impact of erasing one concept on the others. To address this limitation, we model the concept space as a graph and empirically analyze the effects of erasing one concept on the remaining concepts. Our analysis uncovers intriguing geometric properties of the concept space, where the influence of erasing a concept is confined to a local region. Building on this insight, we propose the Adaptive Guided Erasure (AGE) method, which \emph{dynamically} selects optimal target concepts tailored to each undesirable concept, minimizing unintended side effects. Experimental results show that AGE significantly outperforms state-of-the-art erasure methods on preserving unrelated concepts while maintaining effective erasure performance. Our code is published at {https://github.com/tuananhbui89/Adaptive-Guided-Erasure}.

Sentinel-5P (S5P) satellite provides atmospheric measurements for air quality and climate monitoring. While the S5P satellite offers rich spectral resolution, it inherits physical limitations that restricts its spatial resolution. Super-resolution (SR) techniques can overcome these limitations and enhance the spatial resolution of S5P data. In this work, we introduce a novel SR model specifically designed for S5P data that have eight spectral bands with around 500 channels for each band. Our proposed S5-DSCR model relies on Depth Separable Convolution (DSC) architecture to effectively perform spatial SR by exploiting cross-channel correlations. Quantitative evaluation demonstrates that our model outperforms existing methods for the majority of the spectral bands. This work highlights the potential of leveraging DSC architecture to address the challenges of hyperspectral SR. Our model allows for capturing fine details necessary for precise analysis and paves the way for advancements in air quality monitoring as well as remote sensing applications.

We study a new type of 2D active material that exhibits macroscopic phases with two emergent broken symmetries: self-propelled achiral particles that form dense hexatic clusters, which spontaneously rotate. We experimentally realise active colloids that self-organise into both polar and hexatic crystallites, exhibiting exotic emergent phenomena. This is accompanied by a field theory of coupled order parameters formulated on symmetry principles, including non-reciprocity, to capture the non-equilibrium dynamics. We find that the presence of two interacting broken symmetry fields leads to the emergence of novel chiral phases built from (2D) achiral active colloids (here Quincke rollers). These phases are characterised by the presence of both clockwise and counterclockwise rotating clusters. We thus show that spontaneous rotation can emerge in non-equilibrium systems, even when the building blocks are achiral, due to non-reciprocally coupled broken symmetries. This interplay leads to self-organized stirring through counter-rotating vortices in confined colloidal systems, with cluster size controlled by external electric fields.

The HAWC Observatory collected 6 years of extensive data, providing an ideal platform for long-term monitoring of blazars in the Very High Energy (VHE) band, without bias towards specific flux states. HAWC continuously monitors blazar activity at TeV energies, focusing on sources with a redshift of {z \lt 0.3}, based on the Third Fermi-LAT Catalog of High-Energy sources. We specifically focused our analysis on Mrk 421 and Mrk 501, as they are the brightest blazars observed by the HAWC Observatory. With a dataset of 2143 days, this work significantly extends the monitoring previously published, which was based on 511 days of observation. By utilizing HAWC data for the VHE {\gamma}-ray emission in the 300 GeV to 100 TeV energy range, in conjunction with Swift-XRT data for the 0.3 to 10 keV X-ray emission, we aim to explore potential correlations between these two bands. For Mrk 501, we found evidence of a long-term correlation. Additionally, we identified a period in the light curve where the flux was very low for more than two years. On the other hand, our analysis of Mrk 421 measured a strong linear correlation for quasi-simultaneous observations collected by HAWC and Swift-XRT. This result is consistent with a linear dependence and a multiple-zone synchrotron self-Compton model to explain the X-ray and the {\gamma}-ray emission. Finally, as suggested by previous findings, we confirm a harder-when-brighter behavior in the spectral evolution of the flux properties for Mrk 421. These findings contribute to the understanding of blazar emissions and their underlying mechanisms.

Studying accretion-driven episodic outbursts in YSOs is key to understanding the later stages of star and planet formation. FU Orionis-type objects form a YSO subclass, distinguished by rapid, multi-magnitude increases in brightness at optical and near-infrared wavelengths. These outbursts may significantly impact the chemistry and molecular composition around eruptive stars. However, no comprehensive millimeter-wavelength line survey exists for more evolved (Class II) sources, unlike optical and near-infrared coverage. We conducted the first wideband millimeter spectral line survey of V1057 Cyg, a low-mass eruptive FUor with the highest observed peak accretion rate in its class. Using the IRAM 30-m telescope, we surveyed the 72-263 GHz range and complemented this with targeted spectra at 219, 227, 291, and 344 GHz with the APEX 12-m telescope. We conducted radiative transfer and population diagram analyses to get first estimates of the excitation temperatures and column densities. Several molecular species trace large-scale structures, and the position-velocity diagram of $^{12}$CO suggest episodic outburst activity, with outflow dynamical timescales on the order of tens of thousands of years. We identified simple molecules (C-, N-, O-, and S-bearing), deuterated species, molecular ions, and complex organic molecules. With over 30 molecular species (including isotopologues) detected, V1057 Cyg demonstrates rich chemistry for its evolutionary state, compared to other younger (Class 0/I) FUors. V1057 Cyg is a good candidate for future interferometric studies to resolve emission structures, to possibly constrain molecular freeze-out, and detect water and complex organic molecules. Our results highlight the importance of millimeter line surveys in complementing optical/near-infrared studies, improving statistics on molecular inventories in eruptive stars and their environments., Comment: 45 pages, 20 figures, Accepted for publication in Astronomy & Astrophysics (A&A). This work is dedicated to the memory of Karl M. Menten

We present direct observational constraints on tachyons; particles with group velocity greater than $c$ in vacuum in a Lorentz invariant theory. Since tachyons may have no direct couplings to Standard Model particles, the most robust and model independent constraints come from gravitational effects, especially black holes. We compute the Hawking radiation of tachyons from black holes, finding it to be significantly enhanced in the presence of heavy tachyons. For a black hole of mass $M$ and tachyons of mass $m$ with $g$ degrees of freedom, the black hole lifetime is found to be $t_{bh} \approx 192 \pi \hbar M/(g c^2 m^2)$ (or doubled for fermions). This implies that the observation of black holes of a few solar masses, with lifetime of several billion years, rules out tachyons of mass $m > 3 \times 10^9$ GeV. This means there cannot exist any tachyons associated with unification scales or quantum gravity. So while there already exists theoretical reasons to be skeptical of tachyons, our work provides a complementary direct observational constraint., Comment: 7 pages in double column format, 2 figures

The FASER experiment was designed to study long-lived dark sector particles and neutrinos traveling in the forward direction at the LHC. Neutrinos are predominantly produced from meson decays, which also result in an intense energetic flux of muons in the forward direction regularly observed by FASER. So far, these muons are treated only as backgrounds to neutrino and new physics studies, and extensive effort is required to suppress them. In this study, we consider the opposite scenario and use muons produced in the forward direction to produce new muonphilic scalars, which can then be searched for at the FASER detector. To minimize the backgrounds for this search, we make use of an upgraded preshower component, which is expected to be installed at FASER before the end of Run 3, and is capable of spatially resolving two energetic photons. We find that FASER, and its upgrade, FASER2 can probe currently unconstrained regions of parameter space, including regions that can potentially explain the $(g-2)_{\mu}$ anomaly. This highlights the physics opportunities that the intense TeV muon beam at the LHC can bring., Comment: 13 pages, 5 figures, 1 appendix

Cosmic spherules have largely been classified into S-, I-, and G-types according to their compositions, and are identified to have chondritic or achondritic materials as precursors. A recent recovery expedition attempted to sample fragments of the CNEOS 2014-01-08 bolide retrieved roughly 850 magnetic particles, some of which have unknown origins. Among those identified were a new group of highly differentiated materials consisting of close to 160 specimens categorized as "D-type" particles. We studied the D-type particles with the goal of comparing their various morphological features to their chemical compositional groupings. Four morphological classifications are considered: "scoriaceous," "stubby," "blocky," and "vesicular." The specimens from the "scoriaceous" and "stubby" groups exhibit a spinel/magnetite rim in at least one instance, characteristic of atmospheric entry, and textures indicative of quenching such as dendritic microcrystalline structures, suggesting that a subset of specimens from these groups are candidates for materials of extraterrestrial origin. The particles exhibiting "blocky" and "vesicular" textures are likely to be terrestrial in origin, with no obvious quench features or signs of ablation. The D-type particles identified and characterized in this study have a spectrum of terrestrial and probable extraterrestrial origins., Comment: Chemical Geology

We consider the spatial classification problem for monitoring using data collected by a coordinated team of mobile robots. Such classification problems arise in several applications including search-and-rescue and precision agriculture. Specifically, we want to classify the regions of a search environment into interesting and uninteresting as quickly as possible using a team of mobile sensors and mobile charging stations. We develop a data-driven strategy that accommodates the noise in sensed data and the limited energy capacity of the sensors, and generates collision-free motion plans for the team. We propose a bi-level approach, where a high-level planner leverages a multi-armed bandit framework to determine the potential regions of interest for the drones to visit next based on the data collected online. Then, a low-level path planner based on integer programming coordinates the paths for the team to visit the target regions subject to the physical constraints. We characterize several theoretical properties of the proposed approach, including anytime guarantees and task completion time. We show the efficacy of our approach in simulation, and further validate these observations in physical experiments using mobile robots., Comment: 8 pages, 6 figures. See https://www.youtube.com/watch?v=gzulpOcVYzg for an overview of the approach along with videos of the hardware experiments

We consider an ensemble of $2\times 2$ normal matrices with complex entries representing operators in the quantum mechanics of 2 - level parity-time reversal (PT) symmetric systems. The randomness of the ensemble is endowed by obtaining probability distributions based on symmetry and statistical independence. The probability densities turn out to be power law with exponents that depend on the boundedness of the domain. For small spacings, $\sigma$, the probability density varies as $\sigma^{\nu}$, $\nu \geq 2$. The degree of level repulsion is a parameter of great interest as it makes a connection to quantum chaos; the lower bound of $\nu$ for our ensemble coincides with the Gaussian Unitary Ensemble. We believe that the systematic development presented here paves the way for further generalizations in the field of random matrix theory for PT-symmetric quantum systems.

We present a gradient-based meta-learning framework for rapid adaptation of neural state-space models (NSSMs) for black-box system identification. When applicable, we also incorporate domain-specific physical constraints to improve the accuracy of the NSSM. The major benefit of our approach is that instead of relying solely on data from a single target system, our framework utilizes data from a diverse set of source systems, enabling learning from limited target data, as well as with few online training iterations. Through benchmark examples, we demonstrate the potential of our approach, study the effect of fine-tuning subnetworks rather than full fine-tuning, and report real-world case studies to illustrate the practical application and generalizability of the approach to practical problems with physical-constraints. Specifically, we show that the meta-learned models result in improved downstream performance in model-based state estimation in indoor localization and energy systems., Comment: 30 pages

Resonant soft X-ray scattering (RSXS) is a powerful technique for probing both spatial and electronic structures within solid-state systems.We present a newly developed RSXS capability at beamline 13-3 of the Stanford Synchrotron Radiation Lightsource (SSRL), designed to enhance materials science research. This advanced setup achieves a base sample temperature as low as 9.8 K combined with extensive angular motions (azimuthal \phi and flipping \chi), enables comprehensive exploration of reciprocal space. Two types of detectors, an Au/GaAsP Schottky photodiode and a CCD detector with over 95% quantum efficiency, are integrated to effectively capture scattered photons. Extensive testing has confirmed the enhanced functionality of this RSXS setup, including its temperature and angular performance. The versatility and effectiveness of the system have been demonstrated through studies of various materials, including superlattice heterostructures and high-temperature superconductors., Comment: 22 pages, 7 figures

The Hamiltonian Monte Carlo (HMC) algorithm is a powerful Markov Chain Monte Carlo (MCMC) method that uses Hamiltonian dynamics to generate samples from a target distribution. To fully exploit its potential, we must understand how Hamiltonian dynamics work and why they can be used in a MCMC algorithm. This work elucidates the Monte Carlo Hamiltonian, providing comprehensive explanations of the underlying physical concepts. It is intended for readers with a solid foundation in mathematics who may lack familiarity with specific physical concepts, such as those related to Hamiltonian dynamics. Additionally, we provide Python code for the HMC algorithm, examples and comparisons with the Random Walk Metropolis-Hastings (RWMH) and t-walk algorithms to highlight HMC's strengths and weaknesses when applied to Bayesian Inference.

The Ziegler-Rauk-Baerends multiplet sum method (MSM) assumes that density-functional theory (DFT) provides a good description of states dominated by a single determinant. It then uses symmetry to add static correlation to DFT. In our previous article (Article I) [J. Chem. Phys. 159, 244306 (2023)], we introduced diagrammatic MSM-DFT as a tool to aid in extending MSM-DFT to include the nondynamic correlation needed for making and breaking bonds even in the absence of symmetry. An attractive feature of this approach is that no functional-dependent parameters need to be introduced, though choices are needed in making correspondances between wave function theory (WFT) and MSM-DFT diagrams. The preliminary examples in Article I used the two-orbital two-electron model (TOTEM) less completely than could have been the case. Diagrammatic MSM-DFT is extended here to treat the full TOTEM and it is shown that the unsymmetric lithium hydride (LiH) molecule dissociates into neutral atoms when diagrammatic MSM-DFT techniques are used to introduce a proper description of the avoided crossing between ionic bonding and covalent bonding states.The method is tested for Hartree-Fock and for three functionals (LDA, PW91, and B3LYP). All the functionals yield similar results as should be expected for a properly-formulated parameter-free theory. Agreement with available estimates show that the magnitude of the coupling element introduced here is excellent. However more work will be needed to obtain quantitative agreement between our diagrammatic MSM-DFT ground-state potential energy curve and that found from high-quality ab initio calculations

Amidst the burgeoning landscape of database architectures, the surge in NoSQL databases has heralded a transformative era, liberating data storage from traditional relational constraints and ushering in unprecedented scalability. As organizations grapple with the escalating security threats posed by database breaches, a novel theoretical framework emerges at the nexus of chaos theory and topology: the Database in motion Chaos Encryption (DaChE) Algorithm. This paradigm-shifting approach challenges the static nature of data storage, advocating for dynamic data motion to fortify database security. By incorporating chaos theory, this innovative strategy not only enhances database defenses against evolving attack vectors but also redefines the boundaries of data protection, offering a paradigmatic shift in safeguarding critical information assets. Additionally, it enables parallel processing, facilitating on-the-fly processing and optimizing the performance of the proposed framework.

The Solar Ultraviolet Imaging Telescope (SUIT) is an instrument on the Aditya-L1 mission of the Indian Space Research Organization (ISRO) launched on September 02, 2023. SUIT continuously provides, near-simultaneous full-disk and region-of-interest images of the Sun, slicing through the photosphere and chromosphere and covering a field of view up to 1.5 solar radii. For this purpose, SUIT uses 11 filters tuned at different wavelengths in the 200{--}400~nm range, including the Mg~{\sc ii} h~and~k and Ca~{\sc ii}~H spectral lines. The observations made by SUIT help us understand the magnetic coupling of the lower and middle solar atmosphere. In addition, for the first time, it allows the measurements of spatially resolved solar broad-band radiation in the near and mid ultraviolet, which will help constrain the variability of the solar ultraviolet irradiance in a wavelength range that is central for the chemistry of the Earth's atmosphere. This paper discusses the details of the instrument and data products., Comment: 37 pages, Accepted for Publication in Solar Physics

The study of spectral graph determination is a fascinating area of research in spectral graph theory and algebraic combinatorics. This field focuses on examining the spectral characterization of various classes of graphs, developing methods to construct or distinguish cospectral nonisomorphic graphs, and analyzing the conditions under which a graph's spectrum uniquely determines its structure. This paper presents an overview of both classical and recent advancements in these topics, along with newly obtained proofs of some existing results, which offer additional insights., Comment: Final version. It is published (in a different style file) in Mathematics, vol. 13, no. 4, paper 549, pp. 1--44, February 2025. Please also follow this link https://www.mdpi.com/2227-7390/13/4/549

Nanoscale confinement of molecules in a fluid can result in enhanced viscosity, local fluidic order, or collective motion. Confinement also affects ion transport and/or the rate and equilibrium concentration in a chemical reaction, all of which makes it the subject of broad interest. Studying these effects, however, is notoriously difficult, mainly due to the lack of experimental methods with the required sensitivity and spatial or time resolution. Here we leverage shallow nitrogen-vacancy (NV) centers in diamond to probe the dynamics of room-temperature water molecules entrapped within ~6-nm-tall channels formed between the diamond crystal and a suspended hexagonal boron nitride (hBN) flake. NV-enabled nuclear magnetic resonance measurements of confined water protons reveal a much reduced H2O self-diffusivity, orders of magnitude lower than in bulk water. We posit the slow dynamics stem from the accumulation of photogenerated carriers at the interface and trapped fluid, a notion we support with the help of molecular dynamics modeling. Our results provide feedback for theories describing interfacial water, and lay out a route for investigating other fluids under confinement.

Assessing the extent of human edits on texts generated by Large Language Models (LLMs) is crucial to understanding the human-AI interactions and improving the quality of automated text generation systems. Existing edit distance metrics, such as Levenshtein, BLEU, ROUGE, and TER, often fail to accurately measure the effort required for post-editing, especially when edits involve substantial modifications, such as block operations. In this paper, we introduce a novel compression-based edit distance metric grounded in the Lempel-Ziv-77 algorithm, designed to quantify the amount of post-editing applied to LLM-generated texts. Our method leverages the properties of text compression to measure the informational difference between the original and edited texts. Through experiments on real-world human edits datasets, we demonstrate that our proposed metric is highly correlated with actual edit time and effort. We also show that LLMs exhibit an implicit understanding of editing speed, that aligns well with our metric. Furthermore, we compare our metric with existing ones, highlighting its advantages in capturing complex edits with linear computational efficiency. Our code and data are available at: https://github.com/NDV-tiime/CompressionDistance