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Design fictions allow us to prototype the future. They enable us to interrogate emerging or non-existent technologies and examine their implications. We present three design fictions that probe the potential consequences of operationalizing a mutual theory of mind (MToM) between human users and one (or more) AI agents. We use these fictions to explore many aspects of MToM, including how models of the other party are shaped through interaction, how discrepancies between these models lead to breakdowns, and how models of a human's knowledge and skills enable AI agents to act in their stead. We examine these aspects through two lenses: a utopian lens in which MToM enhances human-human interactions and leads to synergistic human-AI collaborations, and a dystopian lens in which a faulty or misaligned MToM leads to problematic outcomes. Our work provides an aspirational vision for human-centered MToM research while simultaneously warning of the consequences when implemented incorrectly., Comment: 11 pages. Published in Proceedings of Workshop on Theory of Mind in Human-AI Interaction at CHI 2024

The PICOSEC Micromegas (MM) detector is a precise timing gaseous detector based on a MM detector operating in a two-stage amplification mode and a Cherenkov radiator. Prototypes equipped with cesium iodide (CsI) photocathodes have shown promising time resolutions as precise as 24 picoseconds (ps) for Minimum Ionizing Particles. However, due to the high hygroscopicity and susceptibility to ion bombardment of the CsI photocathodes, alternative photocathode materials are needed to improve the robustness of PICOSEC MM. Diamond-like Carbon (DLC) film have been introduced as a novel robust photocathode material, which have shown promising results. A batch of DLC photocathodes with different thicknesses were produced and evaluated using ultraviolet light. The quantum efficiency measurements indicate that the optimized thickness of the DLC photocathode is approximately 3 nm. Furthermore, DLC photocathodes show good resistance to ion bombardment in aging test compared to the CsI photocathode. Finally, a PICOSEC MM prototype equipped with DLC photocathodes was tested in muon beams. A time resolution of around 42 ps with a detection efficiency of 97% for 150 GeV/c muons were obtained. These results indicate the great potential of DLC as a photocathode for the PICOSEC MM detector.

High resolution (0."037-0."13 [10-35 pc]) e-MERLIN ($\lambda6-18$ cm) and (0."024 [6.5 pc]) ALMA ($\lambda 1.1$ mm) observations have been used to image OH (hydroxyl) and H$_2$CO (formaldehyde) megamaser emission, and HCN 3->2 emission towards the nuclear (<100 pc) region of the luminous infrared galaxy Zw049.057. Zw049.057 hosts a compact obscured nucleus (CON), thus representing a class of galaxies that are often associated with inflow and outflow motions. Formaldehyde megamaser emission is detected towards the nuclear region, <30 pc (<0."1), and traces a structure along the disk major axis. OH megamaser (OHM) emission is detected along the minor axis of the disk, ~30 pc (0."1) from the nucleus, where it exhibits a velocity gradient with extrema of -20 km/s south-east (SE) of the disk and -110 km/s north-west (NW) of the disk. HCN 3->2 emission reveals extended emission, along the disk minor axis out to ~60 pc (0."2). Analysis of the minor axis HCN emission reveals high-velocity features, extending out to 600 km/s, redshifted on the SE side and blueshifted on the NW side. We propose that the high-velocity HCN emission traces a fast >250 km/s and collimated outflow, that is enveloped by a wide-angle and slow ~50 km/s outflow that is traced by the OHM emission. Analysis of the outflow kinematics suggests that the slow wide-angle outflow will not reach escape velocity and instead will fall back to the galaxy disk, evolving as a so-called fountain flow, while the fast collimated outflow traced by HCN emission will likely escape the nuclear region. We suggest that the absence of OHM emission in the nuclear region is due to high densities there. Even though OHMs associated with outflows are an exception to conventional OHM emission, we expect them to be common in CON sources that host both OHM and H$_2$CO megamasers., Comment: 13 pages, 3 figures. Accepted to A&A

This paper presents design guidelines and experimental verification of a single-channel PICOSEC Micromegas (MM) detector with an improved time resolution. The design encompasses the detector board, vessel, auxiliary mechanical parts, and electrical connectivity for high voltage (HV) and signals, focusing on improving stability, reducing noise, and ensuring signal integrity to optimize timing performance. A notable feature is the simple and fast reassembly procedure, facilitating quick replacement of detector internal components that allows for an efficient measurement strategy involving different detector components. The paper also examines the influence of parasitics on the output signal integrity. To validate the design, a prototype assembly and three interchangeable detector boards with varying readout pad diameters were manufactured. The detectors were initially tested in the laboratory environment. Finally, the timing performance of detectors with different pad sizes was verified using a Minimum Ionizing Particle (MIP) beam test. Notably, a record time resolution for a PICOSEC Micromegas detector technology with a CsI photocathode of 12.5$\pm$0.8 ps was achieved with a 10 mm diameter readout pad size detector.

Gas Electron Multipliers (GEMs) are used in many particle physics experiments, employing their 'standard' configuration with amplification holes of 140 um pitch in a hexagonal pattern. However, the collection of the charge cloud from the primary ionisation electrons from the drift region of the detector into the GEM holes affects the position information from the initial interacting particle. In this paper, the results from studies with a triple-GEM detector with an X-Y-strip readout anode are presented. It is demonstrated that GEMs with a finer hole pitch of here 90 um improve the detector's spatial resolution. Within these studies, also the impact of the front-end electronics on the spatial resolution was investigated, which is briefly discussed in the paper.

Type Ia supernova (SN Ia) cosmology relies on the estimation of lightcurve parameters to derive precision distances that leads to the estimation of cosmological parameters. The empirical SALT2 lightcurve modeling that relies on only two parameters, a stretch x1, and a color c, has been used by the community for almost two decades. In this paper we study the ability of the SALT2 model to fit the nearly 3000 cosmology-grade SN Ia lightcurves from the second release of the Zwicky Transient Facility (ZTF) cosmology science working group. While the ZTF data was not used to train SALT2, the algorithm is modeling the ZTF SN Ia optical lightcurves remarkably well, except for lightcurve points prior to -10 d from maximum, where the training critically lacks statistics. We find that the lightcurve fitting is robust against the considered choice of phase-range, but we show the [-10; +40] d range to be optimal in terms of statistics and accuracy. We do not detect any significant features in the lightcurve fit residuals that could be connected to the host environment. Potential systematic population differences related to the SN Ia host properties might thus not be accountable for by the addition of extra lightcurve parameters. However, a small but significant inconsistency between residuals of blue- and red-SN Ia strongly suggests the existence of a phase-dependent color term, with potential implications for the use of SNe Ia in precision cosmology. We thus encourage modellers to explore this avenue and we emphasize the importance that SN Ia cosmology must include a SALT2 retraining to accurately model the lightcurves and avoid biasing the derivation of cosmological parameters., Comment: 10 pages, 9 figures. Submitted to Astronomy and Astrophysics

Understanding the impact of the astrophysical environment on Type Ia supernova (SN Ia) properties is crucial to minimize systematic uncertainties in cosmological analyses based on this probe. We investigate the dependence of the SN Ia SALT2.4 light-curve stretch on the distance from their nearest galaxy cluster to study a potential effect of the intracluster medium (ICM) environment on SN Ia intrinsic properties. We use the largest SN Ia sample to date and cross-match it with existing X-ray, Sunyaev-Zel'dovich, and optical cluster catalogs in order to study the dependence between stretch and distance to the nearest detected cluster from each SN Ia. We model the underlying stretch distribution with a Gaussian mixture with relative amplitudes that depend on redshift and cluster-centric distance. We find a significant improvement of the fit quality of the stretch distribution if we include the distance-dependant term in the model with a variation of the Akaike information criterion $\rm{\Delta AIC} = -10.2$. Because of the known correlation between galaxy age and distance from cluster center, this supports previous evidence that the age of the stellar population is the underlying driver of the bimodial shape of the SN Ia stretch distribution. We further compute the evolution of the fraction of quenched galaxies as a function of distance with respect to cluster center from our best-fit model of the SNe Ia stretch distribution and compare it to previous results obtained from $H\alpha$ line measurements, optical broadband photometry, and simulations. We find our estimate to be compatible with these results. The results of this work indicate that SNe Ia searches at high redshift targeted towards clusters to maximize detection probability should be considered with caution as the stretch distribution of the detected sample would be strongly biased towards the old sub-population of SNe Ia., Comment: Accepted in Astronomy & Astrophysics

To get distances, Type Ia Supernovae magnitudes are corrected for their correlation with lightcurve width and colour. Here we investigate how this standardisation is affected by the SN environment, with the aim to reduce scatter and improve standardisation. We first study the SN Ia stretch distribution, as well as its dependence on environment, as characterised by local and global (g-z) colour and stellar mass. We then look at the standardisation parameter $\alpha$, which accounts for the correlation between residuals and stretch, along with its environment dependence and linearity. We finally compute magnitude offsets between SNe in different astrophysical environments after colour and stretch standardisation, aka steps. This analysis is made possible due to the unprecedented statistics of the ZTF SN Ia DR2 volume-limited sample. The stretch distribution exhibits a bimodal behaviour, as previously found in literature. However, we find the distribution means to decrease with host stellar mass at a 9.0$\sigma$ significance. We demonstrate, at the 14.3$\sigma$ level, that the stretch-magnitude relation is non-linear, challenging the usual linear stretch-residuals relation. Fitting for a broken-$\alpha$ model, we indeed find two different slopes between stretch regimes ($x_1<-0.49\pm0.06$): $\alpha_{low}=0.28\pm0.01$ and $\alpha_{high}=0.09\pm0.01$, a $\Delta_{\alpha}=-0.19\pm0.01$ difference. As the relative proportion of SNe Ia in the high-/low-stretch modes evolves with redshift and environment, this implies that a linear $\alpha$ also evolves with redshift and environment. Concerning the environmental magnitude offset $\gamma$, we find it to be greater than 0.14 mag regardless of the considered environmental tracer used (local or global colour and stellar mass), all measured at the $\geq 6\sigma$ level, increased to $\sim0.18\pm0.01$ mag when accounting for the stretch-non linearity., Comment: 15 pages, 9 figures, submitted to Astronomy and Astrophysics

Exam documents are essential educational materials for exam preparation. However, they pose a significant academic barrier for blind and visually impaired students, as they are often created without accessibility considerations. Typically, these documents are incompatible with screen readers, contain excessive white space, and lack alternative text for visual elements. This situation frequently requires intervention by experienced sighted individuals to modify the format and content for accessibility. We propose ACCSAMS, a semi-automatic system designed to enhance the accessibility of exam documents. Our system offers three key contributions: (1) creating an accessible layout and removing unnecessary white space, (2) adding navigational structures, and (3) incorporating alternative text for visual elements that were previously missing. Additionally, we present the first multilingual manually annotated dataset, comprising 1,293 German and 900 English exam documents which could serve as a good training source for deep learning models., Comment: Accepted at ICCHP 2024

Visualizations, such as charts, are crucial for interpreting complex data. However, they are often provided as raster images, which are not compatible with assistive technologies for people with blindness and visual impairments, such as embossed papers or tactile displays. At the same time, creating accessible vector graphics requires a skilled sighted person and is time-intensive. In this work, we leverage advancements in the field of chart analysis to generate tactile charts in an end-to-end manner. Our three key contributions are as follows: (1) introducing the ChartFormer model trained to convert raster chart images into tactile-accessible SVGs, (2) training this model on the Chart2Tactile dataset, a synthetic chart dataset we created following accessibility standards, and (3) evaluating the effectiveness of our SVGs through a pilot user study with an refreshable two-dimensional tactile display. Our work is publicly available at https://github.com/nsothman/ChartFormer ., Comment: Accepted at ICCHP 2024. Codes will be available at https://github.com/nsothman/ChartFormer

Alternative Texts (Alt-Text) for chart images are essential for making graphics accessible to people with blindness and visual impairments. Traditionally, Alt-Text is manually written by authors but often encounters issues such as oversimplification or complication. Recent trends have seen the use of AI for Alt-Text generation. However, existing models are susceptible to producing inaccurate or misleading information. We address this challenge by retrieving high-quality alt-texts from similar chart images, serving as a reference for the user when creating alt-texts. Our three contributions are as follows: (1) we introduce a new benchmark comprising 5,000 real images with semantically labeled high-quality Alt-Texts, collected from Human Computer Interaction venues. (2) We developed a deep learning-based model to rank and retrieve similar chart images that share the same visual and textual semantics. (3) We designed a user interface (UI) to facilitate the alt-text creation process. Our preliminary interviews and investigations highlight the usability of our UI. For the dataset and further details, please refer to our project page: https://moured.github.io/alt4blind/., Comment: Accepted at ICCHP 2024. Codes will be available at https://moured.github.io/alt4blind/

We present LEMMING, a modular log-linear model that jointly models lemmatization and tagging and supports the integration of arbitrary global features. It is trainable on corpora annotated with gold standard tags and lemmata and does not rely on morphological dictionaries or analyzers. LEMMING sets the new state of the art in token-based statistical lemmatization on six languages; e.g., for Czech lemmatization, we reduce the error by 60%, from 4.05 to 1.58. We also give empirical evidence that jointly modeling morphological tags and lemmata is mutually beneficial., Comment: EMNLP 2015; Honorable Mention for Best Short Paper

We give a classification of finite groups of symplectic birational automorphisms on a manifold of K3^[3]-type with stable and stably saturated cohomological action. We describe the group of polarized automorphisms of a smooth double EPW-cube. Using this description, we exhibit examples of projective hyperkaehler manifolds of K3^[3]-type of maximal Picard rank with a symplectic action of a large group., Comment: 19 pages, 3 tables, 1 figure. Previous sections 3.1 and 3.2 on degenerations removed. New theorem 0.1 with focus on birational automorphisms. Appendix moved as a proper section. Comments welcome!

Causal representation learning promises to extend causal models to hidden causal variables from raw entangled measurements. However, most progress has focused on proving identifiability results in different settings, and we are not aware of any successful real-world application. At the same time, the field of dynamical systems benefited from deep learning and scaled to countless applications but does not allow parameter identification. In this paper, we draw a clear connection between the two and their key assumptions, allowing us to apply identifiable methods developed in causal representation learning to dynamical systems. At the same time, we can leverage scalable differentiable solvers developed for differential equations to build models that are both identifiable and practical. Overall, we learn explicitly controllable models that isolate the trajectory-specific parameters for further downstream tasks such as out-of-distribution classification or treatment effect estimation. We experiment with a wind simulator with partially known factors of variation. We also apply the resulting model to real-world climate data and successfully answer downstream causal questions in line with existing literature on climate change., Comment: 21 pages, 8 figures, 6 tables

Spin-nematic and spin-smectic phases have been reported in magnetic materials, which break rotational symmetry while preserving translational symmetry along certain directions. However, until now the analogy to liquid crystals remained incomplete because no magnetic analog of cholesteric order was known. Here we show that the bilayer perovskite Sr$_3$Fe$_2$O$_7$, previously believed to adopt a simple single-$\mathbf{q}$ spin-helical order, hosts two distinct types of multi-$\mathbf{q}$ spin textures and the first "spin-cholesteric". Its ground state represents a novel multi-$\mathbf{q}$ spin texture with unequally intense spin modulations at the two ordering vectors. This is followed in temperature by the new "spin-cholesteric" phase with spontaneously broken chiral symmetry, in which the translational symmetry is broken only along one of the crystal directions while the weaker orthogonal modulation melts, giving rise to intense short-range dynamical fluctuations. Shortly before the transition to the paramagnetic state, vortex-crystal order spanned by two equivalent $\mathbf{q}$ vectors emerges. The "spin-cholesteric" phase completes the spin analogy with liquid crystals and renders Sr$_3$Fe$_2$O$_7$ a touchstone for studying transitions among multiple-$\mathbf{q}$ spin textures in a centrosymmetric host.

Sulphur-bearing species are detected in various environments within Galactic star-forming regions and are particularly abundant in the gas phase of outflows and shocks, and photo-dissociation regions. In this work, we aim to investigate the nature of the emission from the most common sulphur-bearing species observable at millimetre wavelengths towards the nuclear starburst of the galaxy NGC 253. We intend to understand which type of regions are probed by sulphur-bearing species and which process(es) dominate(s) the release of sulphur into the gas phase. We used the high-angular resolution (1.6" or 27 pc) observations from the ALCHEMI ALMA Large Program to image several sulphur-bearing species towards the central molecular zone (CMZ) of NGC 253. We performed local thermodynamic equilibrium (LTE) and non-LTE large velocity gradient (LVG) analyses to derive the physical conditions of the gas in which S-bearing species are emitted, and their abundance ratios across the CMZ. Finally, we compared our results with previous ALCHEMI studies and a few selected Galactic environments. We found that not all sulphur-bearing species trace the same type of gas: strong evidence indicates that H2S and part of the emission of OCS, H2CS, and SO, are tracing shocks whilst part of SO and CS emission rather trace the dense molecular gas. For some species, such as CCS and SO2, we could not firmly conclude on their origin of emission. The present analysis indicates that the emission from most sulphur-bearing species throughout the CMZ is likely dominated by shocks associated with ongoing star formation. In the inner part of the CMZ where the presence of super star clusters was previously indicated, we could not distinguish between shocks or thermal evaporation as the main process releasing the S-bearing species., Comment: 44 pages, 20 figures, Accepted for publication in A&A

Position calibration in the deep sea is typically done by means of acoustic multilateration using three or more acoustic emitters installed at known positions. Rather than using hydrophones as receivers that are exposed to the ambient pressure, the sound signals can be coupled to piezo ceramics glued to the inside of existing containers for electronics or measuring instruments of a deep sea infrastructure. The ANTARES neutrino telescope operated from 2006 until 2022 in the Mediterranean Sea at a depth exceeding 2000m. It comprised nearly 900 glass spheres with 432mm diameter and 15mm thickness, equipped with photomultiplier tubes to detect Cherenkov light from tracks of charged elementary particles. In an experimental setup within ANTARES, piezo sensors have been glued to the inside of such - otherwise empty - glass spheres. These sensors recorded signals from acoustic emitters with frequencies from 46545 to 60235Hz. Two waves propagating through the glass sphere are found as a result of the excitation by the waves in the water. These can be qualitatively associated with symmetric and asymmetric Lamb-like waves of zeroth order: a fast (early) one with $v_e \approx 5$mm/$\mu$s and a slow (late) one with $v_\ell \approx 2$mm/$\mu$s. Taking these findings into account improves the accuracy of the position calibration. The results can be transferred to the KM3NeT neutrino telescope, currently under construction at multiple sites in the Mediterranean Sea, for which the concept of piezo sensors glued to the inside of glass spheres has been adapted for monitoring the positions of the photomultiplier tubes., Comment: submitted to "Experimental Astronomy"

We provide tools to help automate the error analysis of algorithms that evaluate simple functions over the floating-point numbers. The aim is to obtain tight relative error bounds for these algorithms, expressed as a function of the unit round-off. Due to the discrete nature of the set of floating-point numbers, the largest errors are often intrinsically "arithmetic" in the sense that their appearance may depend on specific bit patterns in the binary representations of intermediate variables, which may be present only for some precisions. We focus on generic (i.e., parameterized by the precision) and analytic over-estimations that still capture the correlations between the errors made at each step of the algorithms. Using methods from computer algebra, which we adapt to the particular structure of the polynomial systems that encode the errors, we obtain bounds with a linear term in the unit round-off that is sharp in manycases. An explicit quadratic bound is given, rather than the $O()$-estimate that is more common in this area. This is particularly important when using low precision formats, which are increasingly common in modern processors. Using this approach, we compare five algorithms for computing the hypotenuse function, ranging from elementary to quite challenging.

Near-infrared long-slit spectroscopy has been used to study the stellar population (SP) of the low luminosity active galactic nuclei (AGN) and matched analogues (LLAMA) sample. To perform the SP fits we have employed the X-shooter simple stellar population models together with the \st\ code. Our main conclusions are: The star formation history of the AGNs is very complex, presenting many episodes of star formation during their lifetimes. In general, AGN hosts have higher fractions of intermediate-age SP (light-weighted mean ages, $_L\lesssim$ 4.5 Gyr) when compared with their analogues ($_L\lesssim$ 8.0 Gyr). AGN are more affected by reddening and require significant fractions of featureless continuum and hot dust components. The ratio between the AGN radiated energy and the gravitational potential energy of the molecular gas ($E_{Rad}$/$E_{PG}$) for the AGN is compared with the \maL\ and a possible anti-correlation is observed. This suggests that the AGN is affecting the star formation in these galaxies, in the sense that more energetic AGN (log$(E_{Rad}$/$E_{PG}) \gtrsim 3$) tend to host nuclear younger SP ($ _L \lesssim$4Gyr). We found that the recent ($t<$2~Gyr) returned (recycled) stellar mass is higher in AGN than in the controls. We also provide evidence that the mass loss of stars would be enough to feed the AGN, thus providing observational constraints for models that predict that AGN feeding is partially due to the recycled gas from dying stars., Comment: Accepted for publication in MNRAS

This paper tackles the challenges of implementing few-shot learning on embedded systems, specifically FPGA SoCs, a vital approach for adapting to diverse classification tasks, especially when the costs of data acquisition or labeling prove to be prohibitively high. Our contributions encompass the development of an end-to-end open-source pipeline for a few-shot learning platform for object classification on a FPGA SoCs. The pipeline is built on top of the Tensil open-source framework, facilitating the design, training, evaluation, and deployment of DNN backbones tailored for few-shot learning. Additionally, we showcase our work's potential by building and deploying a low-power, low-latency demonstrator trained on the MiniImageNet dataset with a dataflow architecture. The proposed system has a latency of 30 ms while consuming 6.2 W on the PYNQ-Z1 board.

In many fact-finding investigations, notably parliamentary inquiries, process chronologies are created to reconstruct how a controversial policy or decision came into existence. Current approaches, like timelines, lack the expressiveness to represent the variety of relations in which historic events may link to the overall chronology. This obfuscates the nature of the interdependence among the events, and the texts from which they are distilled. Based on explorative interviews with expert analysts, we propose an extended, rich set of relationships. We describe how these can be visualized as TimeFlows. We provide an example of such a visualization by illustrating the Childcare Benefits Scandal -- an affair that deeply affected Dutch politics in recent years. This work extends the scope of existing process discovery research into the direction of unveiling non-repetitive processes from unstructured information objects., Comment: 16 pages, accepted at RCIS 2024

Gamma-ray bursts are promising candidate sources of high-energy astrophysical neutrinos. The recent GRB 221009A event, identified as the brightest gamma-ray burst ever detected, provides a unique opportunity to investigate hadronic emissions involving neutrinos. The KM3NeT undersea neutrino detectors participated in the worldwide follow-up effort triggered by the event, searching for neutrino events. In this letter, we summarize subsequent searches, in a wide energy range from MeV up to a few PeVs. No neutrino events are found in any of the searches performed. Upper limits on the neutrino emission associated with GRB 221009A are computed., Comment: 11 pages, 2 PDF figures. Submitted to JCAP

The physical properties of galactic molecular outflows are important as they could constrain outflow formation mechanisms. We study the properties of the southwest (SW) outflow streamer including gas kinematics, optical depth, dense gas fraction, and shock strength in the central molecular zone of the starburst galaxy NGC 253. We image the molecular emission at a spatial resolution of $\sim$27 pc based on data from the ALCHEMI program. We trace the kinematics of molecular gas with CO(1-0) line. We constrain the optical depth of CO emission with CO/$^{13}$CO(1-0) ratio, the dense gas fraction with HCN/CO(1-0) ratio, as well as the shock strength with SiO(2-1)/$^{13}$CO(1-0) ratio. The CO/$^{13}$CO(1-0) integrated intensity ratio is $\sim$21 in the SW streamer region, which approximates the C/$^{13}$C isotopic abundance ratio. The higher integrated intensity ratio compared to the disk can be attributed to the optically thinner environment for CO(1-0) emission inside the SW streamer. The HCN/CO(1-0) and SiO(2-1)/$^{13}$CO(1-0) integrated intensity ratios both approach $\sim$0.2 in three giant molecular clouds (GMCs) at the base of the outflow streamers, which implies the higher dense gas fraction and enhanced strength of fast shocks in those GMCs than in the disk. The contours of those two integrated intensity ratios are extended towards the directions of outflow streamers, which connects the enhanced dense gas fraction and shock strength with molecular outflow. Moreover, the molecular gas with enhanced dense gas fraction and shock strength located at the base of the SW streamer shares the same velocity with the outflow. These phenomena suggest that the star formation inside the GMCs can trigger the shocks and further drive the molecular outflow., Comment: Accepted for publication in A&A, 14 pages, 11 figures

Unlike non-polar semiconductors such as silicon, the broken inversion symmetry of the wide bandgap semiconductor gallium nitride leads to a large electronic polarization along a unique crystal axis. This makes the two surfaces of the semiconductor wafer perpendicular to the polar axis dramatically different in their physical and chemical properties. In the last three decades, the cation (gallium) face of gallium nitride has been used for photonic devices such as LEDs and lasers. Though the cation face has also been predominantly used for electronic devices, the anion (nitrogen) face has recently shown promise for high electron mobility transistors due to favorable polarization discontinuities. In this work we introduce dualtronics, showing that it is possible to make photonic devices on the cation face, and electronic devices on the anion face, of the same semiconductor wafer. This opens the possibility for leveraging both faces of polar semiconductors in a single structure, where electronic, photonic, and acoustic properties can be implemented on opposite faces of the same wafer, dramatically enhancing the functional capabilities of this revolutionary semiconductor family.

Exploring new strategies for controlling the magnetic domain propagation is the key to realize ultrafast, high-density domain wall-based memory and logic devices for next generation computing. These strategies include strain modulation in multiferroic devices, geometric confinement and area-selective pinning of domain wall. 2D Van der Waals materials introduce localized modifications to the interfacial magnetic order, enabling control over the propagation of magnetic domains. Here, using Lorentz-Transmission Electron Microscopy (L-TEM) along with the Modified Transport of Intensity equations (MTIE), we demonstrate controlled domain expansion with in-situ magnetic field in a ferromagnet (Permalloy, NiFe) interfacing with a 2D Van der Waals material Graphene (Gr). The Gr/NiFe interface exhibits distinctive domain expansion rate with magnetic field selectively near the interface which is further analyzed using micromagnetic simulations. Our findings are crucial for comprehending direct visualization of interface controlled magnetic domain expansion, offering insights for developing future domain wall-based technology., Comment: Merged Manuscript and supplementary file. Submitted to Communications Physics (under review)

The selection of best variables is a challenging problem in supervised and unsupervised learning, especially in high dimensional contexts where the number of variables is usually much larger than the number of observations. In this paper, we focus on two multivariate statistical methods: principal components analysis and partial least squares. Both approaches are popular linear dimension-reduction methods with numerous applications in several fields including in genomics, biology, environmental science, and engineering. In particular, these approaches build principal components, new variables that are combinations of all the original variables. A main drawback of principal components is the difficulty to interpret them when the number of variables is large. To define principal components from the most relevant variables, we propose to cast the best subset solution path method into principal component analysis and partial least square frameworks. We offer a new alternative by exploiting a continuous optimization algorithm for best subset solution path. Empirical studies show the efficacy of our approach for providing the best subset solution path. The usage of our algorithm is further exposed through the analysis of two real datasets. The first dataset is analyzed using the principle component analysis while the analysis of the second dataset is based on partial least square framework., Comment: Main paper 26 pages including references and 17 pages for the supplementary material

This chapter, which is an extended and revised version of the conference paper 'Predator: Byte-Precise Verification of Low-Level List Manipulation', concentrates on a detailed description of the algorithms behind the Predator shape analyser based on abstract interpretation and symbolic memory graphs. Predator is particularly suited for formal analysis and verification of sequential non-recursive C code that uses low-level pointer operations to manipulate various kinds of linked lists of unbounded size as well as various other kinds of pointer structures of bounded size. The tool supports practically relevant forms of pointer arithmetic, block operations, address alignment, or memory reinterpretation. We present the overall architecture of the tool, along with selected implementation details of the tool as well as its extension into so-called Predator Hunting Party, which utilises multiple concurrently-running Predator analysers with various restrictions on their behaviour. Results of experiments with Predator within the SV-COMP competition as well as on our own benchmarks are provided., Comment: Book chapter preview

We revisit the topic of common lines between projection images in single particle cryo-electron microscopy (cryo-EM). We derive a novel low-rank constraint on a certain $2n \times n$ matrix storing properly-scaled basis vectors for the common lines between $n$ projection images of one molecular conformation. Using this algebraic constraint and others, we give optimization algorithms to denoise common lines and recover the unknown 3D rotations associated to the images. As an application, we develop a clustering algorithm to partition a set of noisy images into homogeneous communities using common lines, in the case of discrete heterogeneity in cryo-EM. We demonstrate the methods on synthetic and experimental datasets.

How galaxies regulate nuclear growth through gas accretion by supermassive black holes (SMBHs) is one of the most fundamental questions in galaxy evolution. One potential way to regulate nuclear growth is through a galactic wind that removes gas from the nucleus. It is unclear whether galactic winds are powered by jets, mechanical winds, radiation, or via magnetohydrodynamic (MHD) processes. Compact obscured nuclei (CONs) represent a significant phase of galactic nuclear growth. These galaxies hide growing SMBHs or unusual starbursts in their very opaque, extremely compact (r $<$ 100 pc) centres. They are found in approximately 30 % of the luminous and ultra-luminous infrared galaxy (LIRG and ULIRG) population. Here, we present high-resolution ALMA observations ($\sim$30 mas, $\sim$5 pc) of ground-state and vibrationally excited HCN towards ESO 320-G030 (IRAS 11506-3851). ESO 320-G030 is an isolated luminous infrared galaxy known to host a compact obscured nucleus and a kiloparsec-scale molecular wind. Our analysis of these high-resolution observations excludes the possibility of a starburst-driven wind, a mechanically or energy driven active galactic nucleus (AGN) wind, and exposes a molecular MDH wind. These results imply that the nuclear evolution of galaxies and the growth of SMBHs are similar to the growth of hot cores or protostars where gravitational collapse of the nuclear torus drives a MHD wind. These results mean galaxies are capable, in part, of regulating the evolution of their nuclei without feedback., Comment: 9 pages, 10 figures

We initiate a systematic study of the deep points of a cluster algebra; that is, the points in the associated variety which are not in any cluster torus. We describe the deep points of cluster algebras of type A, rank 2, Markov, and unpunctured surface type., Comment: 43 pages, 18 figures

We present James Webb Space Telescope (JWST) Integral Field Spectrograph observations of NGC 3256, a local infrared-luminous late-stage merging system with two nuclei about 1 kpc apart, both of which have evidence of cold molecular outflows. Using JWST NIRSpec and MIRI datasets, we investigate this morphologically complex system on spatial scales of $<$100 pc, where we focus on the warm molecular H$_2$ gas surrounding the nuclei. We detect collimated outflowing warm H$_2$ gas originating from the southern nucleus, though we do not find significant outflowing warm H$_2$ gas surrounding the northern nucleus. Within the observed region, the maximum intrinsic velocities of the outflow reach up to $\sim$1,000 km s$^{-1}$, and extend out to a distance of 0.7 kpc. Based on H$_2$ S(7)/S(1) line ratios, we find a larger fraction of warmer gas near the S nucleus, which decreases with increasing distance from the nucleus, signifying the S nucleus as a primary source of H$_2$ heating. The gas mass of the warm H$_2$ outflow component is estimated to be $M\rm{_{warm,out}}$ = 8.9$\times$10$^5\;M_{\odot}$, as much as 4$\%$ of the cold H$_2$ mass as estimated using ALMA CO data. The outflow time scale is about $7\times10^5$ yr, resulting in a mass outflow rate of $\dot{M}\rm{_{warm,out}}$ = 1.3 M$_{\odot}$ yr$^{-1}$ and kinetic power of $P\rm{_{warm,out}}\;\sim\;2\times10^{41}$ erg s$^{-1}$. Lastly, the regions where the outflowing gas reside show high [FeII]/Pa$\beta$ and H$_2$/Br$\gamma$ line ratios, indicating enhanced mechanical heating caused by the outflows. At the same time, the 3.3 $\mu$m and 6.2 $\mu$m Polycyclic Aromatic Hydrocarbon fluxes in these regions are not significantly suppressed compared to those outside the outflows, suggesting the outflows have no clear negative feedback effect on the local star formation., Comment: 16 pages, 8 figures. Submitted to ApJ

Highly integrated multichannel readout electronics is crucial in contemporary particle physics experiments. A novel silicon photomultiplier readout system based on the VMM3a ASIC was developed, for the first time exploiting this chip for calorimetric purposes. To extend the dynamic range the signal from each SiPM channel was processed by two electronics channels with different gain. A fully operational prototype system with 256 SiPM readout channels allowed the collection of data from a prototype of the ALICE Forward Hadron Calorimeter (FoCal-H). The design and the test beam results using high energy hadron beams are presented and discussed, confirming the applicability of VMM3a-based solutions for energy measurements in a high rate environment., Comment: 12 pages, 10 figures

We present a knowledge augmentation strategy for assessing the diagnostic groups and gait impairment from monocular gait videos. Based on a large-scale pre-trained Vision Language Model (VLM), our model learns and improves visual, textual, and numerical representations of patient gait videos, through a collective learning across three distinct modalities: gait videos, class-specific descriptions, and numerical gait parameters. Our specific contributions are two-fold: First, we adopt a knowledge-aware prompt tuning strategy to utilize the class-specific medical description in guiding the text prompt learning. Second, we integrate the paired gait parameters in the form of numerical texts to enhance the numeracy of the textual representation. Results demonstrate that our model not only significantly outperforms state-of-the-art methods in video-based classification tasks but also adeptly decodes the learned class-specific text features into natural language descriptions using the vocabulary of quantitative gait parameters. The code and the model will be made available at our project page: https://lisqzqng.github.io/GaitAnalysisVLM/., Comment: MICCAI 2024

The widespread adoption of quadrotors for diverse applications, from agriculture to public safety, necessitates an understanding of the aerodynamic disturbances they create. This paper introduces a computationally lightweight model for estimating the time-averaged magnitude of the induced flow below quadrotors in hover. Unlike related approaches that rely on expensive computational fluid dynamics (CFD) simulations or drone specific time-consuming empirical measurements, our method leverages classical theory from turbulent flows. By analyzing over 16 hours of flight data from drones of varying sizes within a large motion capture system, we show for the first time that the combined flow from all drone propellers is well-approximated by a turbulent jet after 2.5 drone-diameters below the vehicle. Using a novel normalization and scaling, we experimentally identify model parameters that describe a unified mean velocity field below differently sized quadrotors. The model, which requires only the drone's mass, propeller size, and drone size for calculations, accurately describes the far-field airflow over a long-range in a very large volume which is impractical to simulate using CFD. Our model offers a practical tool for ensuring safer operations near humans, optimizing sensor placements and drone control in multi-agent scenarios. We demonstrate the latter by designing a controller that compensates for the downwash of another drone, leading to a four times lower altitude deviation when passing below., Comment: 7+1 pages

As independently-contracted employees, gig workers disproportionately suffer the consequences of workplace surveillance, which include increased pressures to work, breaches of privacy, and decreased digital autonomy. Despite the negative impacts of workplace surveillance, gig workers lack the tools, strategies, and workplace social support to protect themselves against these harms. Meanwhile, some critical theorists have proposed sousveillance as a potential means of countering such abuses of power, whereby those under surveillance monitor those in positions of authority (e.g., gig workers collect data about requesters/platforms). To understand the benefits of sousveillance systems in the gig economy, we conducted semi-structured interviews and led co-design activities with gig workers. We use "care ethics" as a guiding concept to understand our interview and co-design data, while also focusing on empathic sousveillance technology design recommendations. Through our study, we identify gig workers' attitudes towards and past experiences with sousveillance. We also uncover the type of sousveillance technologies imagined by workers, provide design recommendations, and finish by discussing how to create empowering, empathic spaces on gig platforms., Comment: Published as a conference paper at the ACM Conference on Human Factors in Computing Systems, CHI 2024, 3 figures, 30 pages

Low dimensional hybrid organic-inorganic perovskites (HOIPs) represent a promising class of electronically active materials for both light absorption and emission. The design space of HOIPs is extremely large, since a diverse space of organic cations can be combined with different inorganic frameworks. This immense design space allows for tunable electronic and mechanical properties, but also necessitates the development of new tools for in silico high throughput analysis of candidate structures. In this work, we present an accurate, efficient, transferable and widely applicable machine learning interatomic potential (MLIP) for predicting the structure of new 2D HOIPs. Using the MACE architecture, an MLIP is trained on 86 diverse experimentally reported HOIP structures. The model is tested on 73 unseen perovskite compositions, and achieves chemical accuracy with respect to the reference electronic structure method. Our model is then combined with a simple random structure search algorithm to predict the structure of hypothetical HOIPs given only the proposed composition. Success is demonstrated by correctly and reliably recovering the crystal structure of a set of experimentally known 2D perovskites. Such a random structure search is impossible with ab initio methods due to the associated computational cost, but is relatively inexpensive with the MACE potential. Finally, the procedure is used to predict the structure formed by a new organic cation with no previously known corresponding perovskite. Laboratory synthesis of the new hybrid perovskite confirms the accuracy of our prediction. This capability, applied at scale, enables efficient screening of thousands of combinations of organic cations and inorganic layers., Comment: 14 pages and 9 figures in the main text. Supplementary included in pdf

In a world driven by data visualization, ensuring the inclusive accessibility of charts for Blind and Visually Impaired (BVI) individuals remains a significant challenge. Charts are usually presented as raster graphics without textual and visual metadata needed for an equivalent exploration experience for BVI people. Additionally, converting these charts into accessible formats requires considerable effort from sighted individuals. Digitizing charts with metadata extraction is just one aspect of the issue; transforming it into accessible modalities, such as tactile graphics, presents another difficulty. To address these disparities, we propose Chart4Blind, an intelligent user interface that converts bitmap image representations of line charts into universally accessible formats. Chart4Blind achieves this transformation by generating Scalable Vector Graphics (SVG), Comma-Separated Values (CSV), and alternative text exports, all comply with established accessibility standards. Through interviews and a formal user study, we demonstrate that even inexperienced sighted users can make charts accessible in an average of 4 minutes using Chart4Blind, achieving a System Usability Scale rating of 90%. In comparison to existing approaches, Chart4Blind provides a comprehensive solution, generating end-to-end accessible SVGs suitable for assistive technologies such as embossed prints (papers and laser cut), 2D tactile displays, and screen readers. For additional information, including open-source codes and demos, please visit our project page https://moured.github.io/chart4blind/., Comment: Accepted to IUI 2024. 19 pages, 7 figures, 2 table. For a demo video, see this https://moured.github.io/chart4blind/ . The source code is available at https://github.com/moured/chart4blind_code/