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The nature of the progenitor systems and explosion mechanisms that give rise to Type Ia supernovae (SNe Ia) are still debated. The interaction signature of circumstellar material (CSM) being swept up by expanding ejecta can constrain the type of system from which it was ejected. Most previous studies have focused on finding CSM ejected shortly before the SN Ia explosion still residing close to the explosion site, resulting in short delay times until the interaction starts. We use a sample of 3627 SNe Ia from the Zwicky Transient Facility discovered between 2018 and 2020 and search for interaction signatures over 100 days after peak brightness. By binning the late-time light curve data to push the detection limit as deep as possible, we identify potential late-time rebrightening in 3 SNe Ia (SN 2018grt, SN 2019dlf, SN 2020tfc). The late-time detections occur between 550 and 1450 d after peak brightness, have mean absolute $r$-band magnitudes of -16.4 to -16.8 mag and last up to a few hundred days, significantly brighter than the late-time CSM interaction discovered in the prototype SN 2015cp. The late-time detections all occur within 0.8 kpc of the host nucleus and are not easily explained by nuclear activity, another transient at a similar sky position, or data quality issues. This suggests environment or specific progenitor characteristics playing a role in producing potential CSM signatures in these SNe Ia. By simulating the ZTF survey we estimate that <0.5 per cent of normal SNe Ia display late-time strong H $\alpha$-dominated CSM interaction. This is equivalent to an absolute rate of $8_{-4}^{+20}$ to $54_{-26}^{+91}$ Gpc$^{-3}$ yr$^{-1}$ assuming a constant SN Ia rate of $2.4\times10^{-5}$ Mpc$^{-3}$ yr$^{-1}$ for $z \leq 0.1$. Weaker interaction signatures, more similar to the strength seen in SN 2015cp, could be more common but are difficult to constrain with our survey depth., Comment: 24 pages, 13 figures, 6 tables, A&A accepted

The complex atomic structures and defects of metal-oxide surfaces are vital for a variety of applications in material science and chemistry. While scanning probe microscopy allows accessing atomic-scale structures in real space, elemental discrimination and defect characterization usually rely on indirect assumptions and extensive theoretical modelling. By investigating a variety of different sample systems with increasing structural complexity and inherent defects, we demonstrate that noncontact atomic force microscopy with an O-terminated copper tip allows imaging metal-oxide surfaces with a clear elemental contrast. This universal approach provides not only immediate access to the metal- and oxygen sub-lattices, but also to the chemical and structural configuration of atomic-scale defect structures. The observed contrast can be explained by purely electrostatic interactions between the negatively charged tip apex and the strongly varying electrostatic potential between metal- and oxygen surface sites. These results offer a standardized methodology for the direct structural characterization of even most-complex metal-oxide surfaces, which is highly relevant for a fundamental understanding of atomic-scale processes on these material systems., Comment: To be published

The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run., Comment: 32 pages, 19 figures

Multi-peaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility (ZTF). Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (-17.4 mag) and long (~100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew's spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak's photospheric phase, before H$\alpha$ resurfaces again during the nebular phase. The nebular lines ([O I], [Ca II], Mg I], H$\alpha$) exhibit a double-peaked structure which hints towards a clumpy or non-spherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than normal SESNe as well as requiring a very high $^{56}$Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak which also powers the second peak of the light curve through SN-CSM interaction., Comment: 22 pages, 11 figures, 5 tables

Obtaining spectroscopic observations of the progenitors of core-collapse supernovae is often unfeasible due to an inherent lack of knowledge as to which stars will go supernova and when they will explode. In this letter, we present photometric and spectroscopic observations of the progenitor activity of SN 2023fyq in the preceding 150 days before the He-rich progenitor exploded as a Type Ibn supernova. The progenitor of SN 2023fyq shows an exponential rise in flux prior to core-collapse. Complex He I emission line features are observed, with a P-Cygni like profile, as well as an evolving broad base with velocities on the order of 10,000 km/s, possibly due to electron scattering. The luminosity and evolution of SN 2023fyq are consistent with a faint Type Ibn, reaching a peak r-band magnitude of 18.1 mag, although there is some uncertainty in the distance to the host, NGC 4388, located in the Virgo cluster. We present additional evidence of asymmetric He-rich material being present prior to the explosion of SN 2023fyq, as well as after, suggesting this material has survived the ejecta-CSM interaction. Broad [O I] and the Ca II triplet lines are observed at late phases, confirming that SN 2023fyq was a genuine supernova rather than a non-terminal interacting transient. SN 2023fyq provides insight into the final moments of a massive star's life, highlighting that the progenitor is likely highly unstable before core-collapse., Comment: 7 Pages, 5 Figures, accepted to A&A Letters

Search for the optimizer in computationally demanding model predictive control (MPC) setups can be facilitated by Cloud as a service provider in cyber-physical systems. This advantage introduces the risk that Cloud can obtain unauthorized access to the privacy-sensitive parameters of the system and cost function. To solve this issue, i.e., preventing Cloud from accessing the parameters while benefiting from Cloud computation, random affine transformations provide an exact yet light weight in computation solution. This research deals with analyzing privacy preserving properties of these transformations when they are adopted for MPC problems. We consider two common strategies for outsourcing the optimization required in MPC problems, namely separate and dense forms, and establish that random affine transformations utilized in these forms are vulnerable to side-knowledge from Cloud. Specifically, we prove that the privacy guarantees of these methods and their extensions for separate form are undermined when a mild side-knowledge about the problem in terms of structure of MPC cost function is available. In addition, while we prove that outsourcing the MPC problem in the dense form inherently leads to some degree of privacy for the system and cost function parameters, we also establish that affine transformations applied to this form are nevertheless prone to be undermined by a Cloud with mild side-knowledge. Numerical simulations confirm our results.

We use Koopman theory for data-driven model reduction of nonlinear dynamical systems with controls. We propose generic model structures combining delay-coordinate encoding of measurements and full-state decoding to integrate reduced Koopman modeling and state estimation. We present a deep-learning approach to train the proposed models. A case study demonstrates that our approach provides accurate control models and enables real-time capable nonlinear model predictive control of a high-purity cryogenic distillation column.

When employing Direct Volume Rendering (DVR) for visualizing volumetric scalar fields, classification is generally performed on a piecewise constant or piecewise linear approximation of the field on a viewing ray. Smoothed Particle Hydrodynamics (SPH) data sets define volumetric scalar fields as the sum of individual particle contributions, at highly varying spatial resolution. We present an approach for approximating SPH scalar fields along viewing rays with piece-wise polynomial functions of higher order. This is done by approximating each particle contribution individually and then efficiently summing the results, thus generating a higher-order representation of the field with a resolution adapting to the data resolution in the volume.

SN 2021adxl is a slowly evolving, luminous, Type IIn supernova with asymmetric emission line profiles, similar to the well-studied SN 2010jl. We present extensive optical, near-ultraviolet, and near-infrared photometry and spectroscopy covering ~1.5 years post discovery. SN 2021adxl occurred in an unusual environment, atop a vigorously star-forming region that is offset from its host galaxy core. The appearance of Ly-alpha, O II, as well as the compact core, would classify the host of SN 2021adxl as a Blueberry galaxy, analogous to the higher redshift Green Pea galaxies. Using several abundance indicators, we find a metallicity of the explosion environment of only 10% solar, the lowest reported metallicity for a Type IIn SN environment. SN 2021adxl reaches a peak magnitude of r ~ -20.2 mag and since discovery, SN 2021adxl has faded by only ~4 magnitudes in the r band with a cumulative radiated energy of ~1.5e50 erg over 18 months. SN 2021adxl shows strong signs of interaction with a complex circumstellar medium, seen by the detection of X-rays, revealed by the detection of coronal emission lines, and through multi-component hydrogen and helium profiles. In order to further understand this interaction, we model the H{\alpha} profile using a Monte-Carlo electron scattering code. The blueshifted high-velocity component is consistent with emission from a radially thin, spherical shell resulting in the broad emission components due to electron scattering. Using the velocity evolution of this emitting shell, we find that the SN ejecta collide with circumstellar material of at least 5 Msun, assuming a steady-state mass-loss rate of 4-6e-3 Msun per year for the first ~200 days of evolution. Continuing the observations of SN 2021adxl may reveal signatures of dust formation or an infrared excess, similar to that seen for SN 2010jl., Comment: 21 pages with 27 Figures. Accepted for publication to A&A. MC line scattering code can be found at https://github.com/Astro-Sean/escatter

A bar-joint framework $(G,p)$ is the combination of a finite simple graph $G=(V,E)$ and a placement $p:V\rightarrow \mathbb{R}^d$. The framework is rigid if the only edge-length preserving continuous motions of the vertices arise from isometries of the space. Motivated by applications where boundary conditions play a significant role, one may generalise and consider linearly constrained frameworks where some vertices are constrained to move on fixed affine subspaces. Streinu and Theran characterised exactly which linearly constrained frameworks are generically rigid in 2-dimensional space. In this article we extend their characterisation to symmetric frameworks. In particular necessary combinatorial conditions are given for a symmetric linearly constrained framework in the plane to be isostatic (i.e. minimally infinitesimally rigid) under any finite point group symmetry. In the case of rotation symmetry groups whose order is either 2 or odd, these conditions are then shown to be sufficient under suitable genericity assumptions, giving precise combinatorial descriptions of symmetric isostatic graphs in these contexts., Comment: 26 pages, 9 figures. arXiv admin note: text overlap with arXiv:2210.06060

In 1864, J. C. Maxwell introduced a link between self-stressed frameworks in the plane and piecewise linear liftings to 3-space. This connection has found numerous applications in areas such as discrete geometry, control theory and structural engineering. While there are some generalisations of this theory to liftings of $d$-complexes in $d$-space, extensions for liftings of frameworks in $d$-space for $d\geq 3$ have been missing. In this paper, we introduce and study differential liftings on general graphs using differential forms associated with the elements of the homotopy groups of the complements to the frameworks. Such liftings play the role of integrands for the classical notion of liftings for planar frameworks. We show that these differential liftings have a natural extension to self-stressed frameworks in higher dimensions. As a result we generalise the notion of classical liftings to both graphs and multidimensional $k$-complexes in $d$-space ($k=2,\ldots, d$). Finally we discuss a natural representation of generalised liftings as real-valued functions on Grassmannians., Comment: 26 pages, 11 figures

The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs have only released partial artifacts, such as the final model weights or inference code, and technical reports increasingly limit their scope to high-level design choices and surface statistics. These choices hinder progress in the field by degrading transparency into the training of LLMs and forcing teams to rediscover many details in the training process. We present LLM360, an initiative to fully open-source LLMs, which advocates for all training code and data, model checkpoints, and intermediate results to be made available to the community. The goal of LLM360 is to support open and collaborative AI research by making the end-to-end LLM training process transparent and reproducible by everyone. As a first step of LLM360, we release two 7B parameter LLMs pre-trained from scratch, Amber and CrystalCoder, including their training code, data, intermediate checkpoints, and analyses (at https://www.llm360.ai). We are committed to continually pushing the boundaries of LLMs through this open-source effort. More large-scale and stronger models are underway and will be released in the future.

Care robotics as a research field has developed a lot in recent years, driven by the rapidly increasing need for it. However, these technologies are mostly limited to a very concrete and usually relatively simple use case. The bimanual robot House of Living Labs intelligent Escort (HoLLiE) includes an omnidirectional mobile platform. This paper presents how HoLLiE is adapted, by flexible software and hardware modules, for different care applications. The design goal of HoLLiE was to be human-like but abstract enough to ensure a high level of acceptance, which is very advantageous for its use in hospitals. After a short retrospect of previous generations of HoLLiE, it is highlighted how the current version is equipped with a variety of additional sensors and actuators to allow a wide range of possible applications. Then, the software stack of HoLLiE is depicted, with the focus on navigation and force sensitive intention recognition., Comment: 18th international conference on Intelligent Autonomous Systems (IAS18 - 2023)

The process engineering domain widely uses Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&IDs) to represent process flows and equipment configurations. However, the P&IDs and PFDs, hereafter called flowsheets, can contain errors causing safety hazards, inefficient operation, and unnecessary expenses. Correcting and verifying flowsheets is a tedious, manual process. We propose a novel generative AI methodology for automatically identifying errors in flowsheets and suggesting corrections to the user, i.e., autocorrecting flowsheets. Inspired by the breakthrough of Large Language Models (LLMs) for grammatical autocorrection of human language, we investigate LLMs for the autocorrection of flowsheets. The input to the model is a potentially erroneous flowsheet and the output of the model are suggestions for a corrected flowsheet. We train our autocorrection model on a synthetic dataset in a supervised manner. The model achieves a top-1 accuracy of 80% and a top-5 accuracy of 84% on an independent test dataset of synthetically generated flowsheets. The results suggest that the model can learn to autocorrect the synthetic flowsheets. We envision that flowsheet autocorrection will become a useful tool for chemical engineers.

We prove Ilmanen's resolution of point singularities conjecture by establishing short-time smoothness of the level set flow of a smooth hypersurface with isolated conical singularities. This shows how the mean curvature flow evolves through asymptotically conical singularities. Precisely, we prove that the level set flow of a smooth hypersurface $M^n\subset \mathbb{R}^{n+1}$, $2\leq n\leq 6$, with an isolated conical singularity is modeled on the level set flow of the cone. In particular, the flow fattens (instantaneously) if and only if the level set flow of the cone fattens., Comment: 22 pages, 3 figures. Final version, to appear in Invent. Math