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Current data-driven methodologies for point cloud matching demand extensive training time and computational resources, presenting significant challenges for model deployment and application. In the point cloud matching task, recent advancements with an encoder-only Transformer architecture have revealed the emergence of semantically meaningful patterns in the attention heads, particularly resembling Gaussian functions centered on each point of the input shape. In this work, we further investigate this phenomenon by integrating these patterns as fixed attention weights within the attention heads of the Transformer architecture. We evaluate two variants: one utilizing predetermined variance values for the Gaussians, and another where the variance values are treated as learnable parameters. Additionally we analyze the performances on noisy data and explore a possible way to improve robustness to noise. Our findings demonstrate that fixing the attention weights not only accelerates the training process but also enhances the stability of the optimization. Furthermore, we conducted an ablation study to identify the specific layers where the infused information is most impactful and to understand the reliance of the network on this information.

Reliable, real-time state estimation in nuclear reactors is of critical importance for monitoring, control and safety. It further empowers the development of digital twins that are sufficiently accurate for real-world deployment. As nuclear engineering systems are typically characterised by extreme environments, their in-core sensing is a challenging task, even more so in Generation-IV reactor concepts, which feature molten salt or liquid metals as thermal carriers. The emergence of data-driven methods allows for new techniques for accurate and robust estimation of the full state space vector characterising the reactor (mainly composed by neutron fluxes and the thermal-hydraulics fields). These techniques can combine different sources of information, including computational proxy models and local noisy measurements on the system, in order to robustly estimate the state. This work leverages the Shallow Recurrent Decoder (SHRED) architecture to estimate the entire state vector of a reactor from three, out-of-core time-series neutron flux measurements alone. Specifically, the Molten Salt Fast Reactor, in the EVOL geometry (Evaluation and Viability of Liquid Fuel Fast Reactor System project), is demonstrated as a test case, with neutron flux measurements alone allowing for reconstruction of the 20 coupled field variables of the dynamics. This approach can further quantify the uncertainty associated with the state estimation due to its considerably low training cost on compressed data. The accurate reconstruction of every characteristic field in real-time makes this approach suitable for monitoring and control purposes in the framework of a reactor digital twin.

In open quantum systems theory, reduced models are invaluable for conceptual understanding and computational efficiency. Adiabatic elimination is a useful model reduction method for systems with separated timescales, where a reduced model is derived by discarding rapidly decaying degrees of freedom. So far, adiabatic elimination has been formulated using a geometric approach, which provides a versatile and general framework. This article introduces a reformulation of adiabatic elimination through the framework of the time-convolutionless (TCL) master equation, a widely recognized tool for computing projected time-evolution in open quantum systems. We show that the TCL master equation formulation yields results equivalent to those obtained from the geometric formulation. By applying the TCL master equation formulation to typical examples, we demonstrate a practical methodology for performing adiabatic elimination calculation. This study not only bridges two previously independent approaches, thereby making the adiabatic elimination method accessible to a broader audience, but also enables the analysis of complex cases that are challenging within the geometric formulation. Additionally, it reveals a novel geometric interpretation of the TCL master equation formalism., Comment: Comments welcome

We present a detailed study of the gas and galaxy properties of the cluster PSZ2 G282.28+49.94 detected in the Planck all-sky survey. The intracluster medium (ICM) of this object at z=0.56 exhibits a cometary-like shape. Combining Chandra and TNG observations, we characterised the spatially resolved thermodynamical properties of the gas and the spatial and velocity distribution of 73 galaxy members. The cluster structure is quite complex with an elongated core region containing the two brightest cluster galaxies and one dense group to the south-east. Since there is no velocity difference between the core and the south-east group, we suggest the presence of a merger along the plane of the sky. This structure is related to complex X-ray and radio features, and thus the merger has likely been caught during the post-merger phase. Comparing the distribution of the ICM and of member galaxies, we find a large offset of $\sim 350$ kpc between the position of the X-ray peak and the centre of a concentration of galaxies, preceding it in the likely direction of motion. This configuration is similar to the famous Bullet Cluster, leading us to dub PSZ2 G282.28+49.94 the "Planck bullet", and represents an ideal situation to provide astrophysical constraints to the self-interaction cross-section ($\sigma/m$) of dark matter particles. These results illustrate the power of a multi-wavelength approach to probe the merging scenario of such complex and distant systems., Comment: Accepted for publication in A&A

Using the Schwinger-Keldysh "in-in" effective field theory (EFT) framework, we complete the knowledge of nonlinear gravitational radiation-reaction effects in the (relative) dynamics of binary systems at fifth Post-Newtonian (5PN) order. Diffeomorphism invariance plays a key role guaranteeing that the Ward identities are obeyed (in background-field gauge). Nonlocal-in-time (memory) effects appear in the soft-frequency limit as boundary terms in the effective action, consistently with the loss of (canonical) angular momentum. We identify a conservative sector through Feynman's $i0^+$-prescription. Notably, terms at second order in the (linear) radiation-reaction force also produce conservative-like effects (as we likewise demonstrate in electromagnetism). For the sake of comparison, we derive the ${\cal O}(G^4)$ contribution to the total (even-in-velocity) 5PN relative scattering angle. We find perfect agreement in the overlap with the state of the art in the Post-Minkowskian expansion, both in the conservative and dissipative sectors, resolving the (apparent) discrepancy with previous EFT results. We will return to the full conservative part of the 5PN dynamics elsewhere., Comment: 33+15 pages. 4 figures. 1 ancillary file

This is the second part of a project aimed at formalizing Rozansky-Witten models in the functorial field theory framework. In the first part we constructed a symmetric monoidal $(\infty, 3)$-category $\mathscr{CRW}$ of commutative Rozansky-Witten models with the goal of approximating the $3$-category of Kapustin and Rozansky. In this paper we extend work of Brunner, Carqueville, Fragkos, and Roggenkamp on the affine Rozansky-Witten models: we exhibit a functor connecting their $2$-category of matrix factorizations with the homotopy $2$-category of $\mathscr{CRW}$, and calculate the associated TFTs., Comment: Comments welcome

With sub-microarcsecond angular accuracy, the \theia telescope will be capable of revealing the architectures of nearby exoplanetary systems down to the mass of Earth. This research addresses the challenges inherent in space astrometry missions, focusing on focal plane calibration and telescope optical distortion. We propose to assess the future feasibility of large-format detectors (50 to 200 megapixels) in a controlled laboratory environment. The aim is to improve the architecture of the focal plane while ensuring that specifications are met. The use of field stars as metrological sources for calibrating the optical distortion of the field may help to constrain telescope stability. The paper concludes with an attempt to confirm in the laboratory the performance predicted by simulations. We will also address the possibility of using such techniques with a dedicated instrument for the Habitable World Observatory., Comment: SPIE Conference "Space Telescopes and Instrumentation 2024: Optical, Infrared, and Millimeter Wave", Yokohama, Japan. arXiv admin note: text overlap with arXiv:2207.12540

We provide an approach enabling one to employ physics-informed neural networks (PINNs) for uncertainty quantification. Our approach is applicable to systems where observations are scarce (or even lacking), these being typical situations associated with subsurface water bodies. Our novel physics-informed neural network under uncertainty (PINN-UU) integrates the space-time domain across which processes take place and uncertain parameter spaces within a unique computational domain. PINN-UU is then trained to satisfy the relevant physical principles (e.g., mass conservation) in the defined input domain. We employ a stage training approach via transfer learning to accommodate high-dimensional solution spaces. We demonstrate the effectiveness of PINN-UU in a scenario associated with reactive transport in porous media, showcasing its reliability, efficiency, and applicability to sensitivity analysis. PINN-UU emerges as a promising tool for robust uncertainty quantification, with broad applicability to groundwater systems. As such, it can be considered as a valuable alternative to traditional methods such as multi-realization Monte Carlo simulations based on direct solvers or black-box surrogate models., Comment: 25 pages, 9 figures

Similarity measures play a central role in various data science application domains for a wide assortment of tasks. This guide describes a comprehensive set of prevalent similarity measures to serve both non-experts and professional. Non-experts that wish to understand the motivation for a measure as well as how to use it may find a friendly and detailed exposition of the formulas of the measures, whereas experts may find a glance to the principles of designing similarity measures and ideas for a better way to measure similarity for their desired task in a given application domain., Comment: 27 pages

We consider the Poisson equation with homogeneous Dirichlet conditions in a family of domains in $R^{n}$ indexed by a small parameter $\epsilon$. The domains depend on $\epsilon$ only within a ball of radius proportional to $\epsilon$ and, as $\epsilon$ tends to zero, they converge in a self-similar way to a domain with a conical boundary singularity. We construct an expansion of the solution as a series of fractional powers of $\epsilon$, and prove that it is not just an asymptotic expansion as $\epsilon\to0$, but that, for small values of $\epsilon$, it converges normally in the Sobolev space $H^{1}$. The phenomenon that solutions to boundary value problems on singularly perturbed domains may have convergent expansions is the subject of the Functional Analytic Approach by Lanza de Cristoforis and his collaborators. This approach was originally adopted to study small holes shrinking to interior points of a smooth domain and heavily relies on integral representations obtained through layer potentials. To relax all regularity assumptions, we forgo boundary layer potentials and instead exploit expansions in terms of eigenfunctions of the Laplace-Beltrami operator on the intersection of the cone with the unit sphere. Our analysis is based on a two-scale cross-cutoff ansatz for the solution. Specifically, we write the solution as a sum of a function in the slow variable multiplied by a cutoff function depending on the fast variable, plus a function in the fast variable multiplied by a cutoff function depending on the slow variable. While the cutoffs are considered fixed, the two unknown functions are solutions to a $2\times2$ system of partial differential equations that depend on $\epsilon$ in a way that can be analyzed in the framework of generalized power series when the right-hand side of the Poisson equation vanishes in a neighborhood of the perturbation.

In this work, we present a new stabilization method aimed at removing spurious oscillations in the pressure approximation of Biot's model for poroelasticity with low permeabilities and/or small time steps. We consider different finite-element discretizations and illustrate how not only does such a stabilized scheme provide numerical solutions that are free of non-physical oscillations, but it also allows one to iterate the fluid and mechanics problems in a fashion similar to the well-known fixed-stress split method. The resulting solution method is convergent without the necessity for additional terms to stabilize the iteration. Finally, we present numerical results illustrating the robust behavior of both the stabilization and iterative solver with respect to the physical and discretization parameters of the model.

We present our numerical simulation approach for the End-to-End (E2E) model applied to various astronomical spectrographs, such as SOXS (ESO-NTT), CUBES (ESO-VLT), and ANDES (ESO-ELT), covering multiple wavelength regions. The E2E model aim at simulating the expected astronomical observations starting from the radiation of the scientific sources (or calibration sources) up to the raw-frame data produced by the detectors. The comprehensive description includes E2E architecture, computational models, and tools for rendering the simulated frames. Collaboration with Data Reduction Software (DRS) teams is discussed, along with efforts to meet instrument requirements. The contribution to the cross-correlation algorithm for the Active Flexure Compensation (AFC) system of CUBES is detailed., Comment: 19 pages, 17 figures, SPIE Astronomical Telescopes + Instrumentation, Yokohama 2024. arXiv admin note: text overlap with arXiv:2209.07185, arXiv:2012.12684

SOXS (Son Of X-Shooter) will be the new medium-resolution (R 4500 for 1 slit), high-efficiency, wide-band spectrograph for the ESO NTT at La Silla Observatory, Chile. It will be dedicated to the follow-up of any kind of transient events, ensuring fast time, high efficiency, and availability. It consists of a central structure (common path) that supports two spectrographs optimized for the UV-Visible and a Near-Infrared range. Attached to the common path is the Acquisition and Guiding Camera system (AC), equipped with a filter wheel that can provide science-grade imaging and moderate high-speed photometry. The AC Unit was integrated and aligned during the summer months of 2022 and has since been mounted in the NTTs telescope simulator. This work gives an update on the Acquisition Camera Unit status, describes the Image Quality Tests that were performed, and discusses the AC Optical Performance., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 1309672 (2024)

SOXS (Son Of X-Shooter) is the new single object spectrograph for the ESO New Technology Telescope (NTT) at the La Silla Observatory, able to cover simultaneously both the UV-VIS and NIR bands (350-2000 nm). The instrument is currently in the integration and test phase, approaching the Preliminary Acceptance in Europe (PAE) before shipment to Chile for commissioning. After the assembly and preliminary test of the control electronics at INAF - Astronomical Observatory of Capodimonte (Napoli), the two main control cabinets of SOXS are now hosted in Padova, connected to the real hardware. This contribution describes the final electronic cabinets layout, the control strategy and the different integration phases, waiting for the Preliminary Acceptance in Europe and the installation of the instrument in Chile.

The Son Of X-Shooter (SOXS) will be the specialized facility to observe any transient event with a flexible scheduler at the ESO New Technology Telescope (NTT) at La Silla, Chile. SOXS is a single object spectrograph offering simultaneous spectral coverage in UV-VIS (350-850 nm) and NIR (800-2000 nm) wavelength regimes with an average of R~4500 for a 1arcsec slit. SOXS also has imaging capabilities in the visible wavelength regime. Currently, SOXS is being integrated at the INAF-Astronomical Observatory of Padova. Subsystem- and system-level tests and verification are ongoing to ensure and confirm that every requirement and performance are met. In this paper, we report on the integration and verification of SOXS as the team and the instrument prepare for the Preliminary Acceptance Europe (PAE).

The Son Of X-Shooter (SOXS) is a single object spectrograph, built by an international consortium for the 3.58-m ESO New Technology Telescope at the La Silla Observatory [1]. It offers a simultaneous spectral coverage over 350-2000 nm, with two separate spectrographs. In this paper we present the status of the Near InfraRed (NIR) cryogenic echelle cross-dispersed spectrograph [1], in the range 0.80-2.00 {\mu}m with 15 orders, equipped with an 2k x 2k Hawaii H2RG IR array from Teledyne, working at 40K, that is currently assembled and tested on the SOXS instrument, in the premises of INAF in Padova. We describe the different tests and results of the cryo, vacuum, opto-mechanics and detector subsystems that finally will be part of the PAE by ESO., Comment: 8 Pages, 7 Figures, Astronomical Telescopes and Instrumentation, SPIE Proceedings 2024

We present the advancements in the development of the scheduler for the Son Of X-shooter instrument at the ESO-NTT 3.58-m telescope in La Silla, Chile. SOXS is designed as a single-object spectroscopic facility and features a high-efficiency spectrograph with two arms covering the spectral range of 350-2000 nm and a mean resolving power of approximately R=4500. It will conduct UV-visible and near-infrared follow-up observations of astrophysical transients, drawing from a broad pool of targets accessible through the streaming services of wide-field telescopes, both current and future, as well as high-energy satellites. The instrument will cater to various scientific objectives within the astrophysical community, each entailing specific requirements for observation planning. SOXS will operate at the European Southern Observatory (ESO) in La Silla, without the presence of astronomers on the mountain. This poses a unique challenge for the scheduling process, demanding a fully automated algorithm that is autonomously interacting with the appropriate databases and the La Silla Weather API, and is capable of presenting the operator not only with an ordered list of optimal targets (in terms of observing constraints) but also with optimal backups in the event of changing weather conditions. This imposes the necessity for a scheduler with rapid-response capabilities without compromising the optimization process, ensuring the high quality of observations and best use of the time at the telescope. We thus developed a new highly available and scalable architecture, implementing API Restful applications like Docker Containers, API Gateway, and Python-based Flask frameworks. We provide an overview of the current state of the scheduler, which is now ready for the approaching on-site testing during Commissioning phase, along with insights into its web interface and preliminary performance tests.

The SOXS spectrograph, designed for the ESO NTT telescope, operates in both the optical (UV-VIS: 350-850 nm) and NIR (800-2000 nm) bands. This article provides an overview of the final tests conducted on the UV-VIS camera system using a telescope simulator. It details the system's performance evaluation, including key metrics such as gain, readout noise, and linearity, and highlights the advancements made in the upgraded acquisition system. The testing process, conducted in the Padua laboratory, involved comprehensive simulations of the telescope environment to ensure the results closely resemble those expected at the ESO-NTT telescope. The successful completion of these tests confirms the system's readiness for deployment to Chile, where it will be installed on the NTT telescope, marking a significant milestone in the SOXS project., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 130962U (2024)

This paper presents the opto-mechanical integration and alignment, functional and optical performance verification of the NIR arm of Son Of X-Shooter (SOXS) instrument. SOXS will be a single object spectroscopic facility for the ESO-NTT 3.6-m telescope, made by two arms high efficiency spectrographs, able to cover the spectral range 350 2050 nm with a mean resolving power R~4500. In particular the NIR arm is a cryogenic echelle cross-dispersed spectrograph spanning the 780-2050 nm range. We describe the integration and alignment method performed to assemble the different opto-mechanical elements and their installation on the NIR vacuum vessel, which mostly relies on mechanical characterization. The tests done to assess the image quality, linear dispersion and orders trace in laboratory conditions are summarized. The full optical performance verification, namely echellogram format, image quality and resulting spectral resolving power in the whole NIR arm (optical path and science detector) is detailed. Such verification is one of the most relevant prerequisites for the subsequent full instrument assembly and provisional acceptance in Europe milestone, foreseen in 2024., Comment: SPIE Proceedings Volume 13096, Ground-based and Airborne Instrumentation for Astronomy X; 130962T (2024)

SOXS (Son Of X-Shooter) is the new ESO instrument that is going to be installed on the 3.58-m New Technology Telescope at the La Silla Observatory. SOXS is a single object spectrograph offering a wide simultaneous spectral coverage from U- to H-band. Although such an instrument may have potentially a large variety of applications, the consortium designed it with a clear science case: it is going to provide the spectroscopic counterparts to the ongoing and upcoming imaging surveys, becoming one of the main follow-up instruments in the Southern hemisphere for the classification and characterization of transients. The NTT+SOXS system is specialized to observe all transients and variable sources discovered by imaging surveys with a flexible schedule maintained by the consortium, based on a remote scheduler which will interface with the observatory software infrastructure. SOXS is realized timely to be highly synergic with transients discovery machines like the Vera C. Rubin Observatory. The instrument has been integrated and tested in Italy, collecting and assembling subsystems coming from all partners spread over six countries in three continents. The first preparatory activities in Chile have been completed at the telescope. This article gives an updated status of the project before the shipping of the instrument to Chile., Comment: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

The Instrument Control Software of SOXS (Son Of X-Shooter), the forthcoming spectrograph for the ESO New Technology Telescope at the La Silla Observatory, has reached a mature state of development and is approaching the crucial Preliminary Acceptance in Europe phase. Now that all the subsystems have been integrated in the laboratories of the Padova Astronomical Observatory, the team operates for testing purposes with the whole instrument at both engineering and scientific level. These activities will make use of a set of software peculiarities that will be discussed in this contribution. In particular, we focus on the synoptic panel, the co-rotator system special device, on the Active Flexure Compensation system which controls two separate piezo tip-tilt devices., Comment: 6 pages, 3 figures, SPIE conference

Although LLMs and other artificial intelligence systems demonstrate cognitive skills similar to humans, like concept learning and language acquisition, the way they process information fundamentally differs from biological cognition. To better understand these differences this paper introduces Psychomatics, a multidisciplinary framework bridging cognitive science, linguistics, and computer science. It aims to better understand the high-level functioning of LLMs, focusing specifically on how LLMs acquire, learn, remember, and use information to produce their outputs. To achieve this goal, Psychomatics will rely on a comparative methodology, starting from a theory-driven research question - is the process of language development and use different in humans and LLMs? - drawing parallels between LLMs and biological systems. Our analysis shows how LLMs can map and manipulate complex linguistic patterns in their training data. Moreover, LLMs can follow Grice's Cooperative Principle to provide relevant and informative responses. However, human cognition draws from multiple sources of meaning, including experiential, emotional, and imaginative facets, which transcend mere language processing and are rooted in our social and developmental trajectories. Moreover, current LLMs lack physical embodiment, reducing their ability to make sense of the intricate interplay between perception, action, and cognition that shapes human understanding and expression. Ultimately, Psychomatics holds the potential to yield transformative insights into the nature of language, cognition, and intelligence, both artificial and biological. Moreover, by drawing parallels between LLMs and human cognitive processes, Psychomatics can inform the development of more robust and human-like AI systems., Comment: 15 pages, 4 tables, 2 figures

The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of $\sim$100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 $\mu$m with the goal of extending it to 0.35-2.4 $\mu$m with the addition of a U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allow ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coud\'e room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases, there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states., Comment: SPIE astronomical telescope and instrumentation 2024, in press

Comparing survival experiences of different groups of data is an important issue in several applied problems. A typical example is where one wishes to investigate treatment effects. Here we propose a new Bayesian approach based on restricted mean survival times (RMST). A nonparametric prior is specified for the underlying survival functions: this extends the standard univariate neutral to the right processes to a multivariate setting and induces a prior for the RMST's. We rely on a representation as exponential functionals of compound subordinators to determine closed form expressions of prior and posterior mixed moments of RMST's. These results are used to approximate functionals of the posterior distribution of RMST's and are essential for comparing time--to--event data arising from different samples.

We study bounds arising from the analyticity and unitarity of scattering amplitudes in the context of effective field theories with massless particles. We provide an approach that only uses dispersion relations away from the forward limit. This is suitable to derive constraints in the presence of gravity, in a way that is robust with respect to radiative corrections. Our method not only allows us to avoid the Coulomb pole, but also the singularities associated with calculable loop effects, which would otherwise diverge., Comment: 36 pages, 9 figures, 2 tables

Determining the local coordination of the active site is a pre-requisite for the reliable modeling of single-atom catalysts (SACs). Obtaining such information is difficult on powder-based systems, so much emphasis is placed on density functional theory-based computations based on idealized low-index surfaces of the support. In this work, we investigate how Pt atoms bind to the (1-102) facet of Fe2O3, a common support material in SAC. Using a combination of scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), and an extensive computational evolutionary search, we find that Pt atoms significantly reconfigure the support lattice to facilitate a pseudo-linear coordination to surface oxygen atoms. Despite breaking three surface Fe-O bonds, this geometry is favored by 0.84 eV over the best configuration involving an unperturbed support. We suggest that the linear O-Pt-O configuration is common in reactive Pt-based SAC systems because it balances thermal stability with the ability to adsorb reactants from the gas phase, and that extensive structural searches are likely necessary to determine realistic active site geometry in single-atom catalysis.

Low-energy electron diffraction (LEED) is a widely used technique in surface-science. Yet, it is rarely used to its full potential. The quantitative information about the surface structure, contained in the modulation of the intensities of the diffracted beams as a function of incident electron energy, LEED I(V), is underutilized. To acquire these data, minor adjustments would be required in most experimental setups, but existing analysis software is cumbersome to use. ViPErLEED (Vienna package for Erlangen LEED) lowers these barriers, introducing a combined solution for data acquisition, extraction, and computational analysis. These parts are discussed in three separate publications. Here, the focus is on the computational part of ViPErLEED, which performs automated LEED-I(V) calculations and structural optimization. Minimal user input is required, and the functionality is significantly enhanced compared to existing solutions. Computation is performed by embedding the Erlangen tensor-LEED package (TensErLEED). ViPErLEED manages parallelization, monitors convergence, and processes input and output. This makes LEED I(V) more accessible to new users while minimizing the potential for errors and the manual labor. Added functionality includes structure-dependent defaults, automatic detection of bulk and surface symmetries and their relationship, automated symmetry-preserving search procedures, adjustments to the TensErLEED code to handle larger systems, as well as parallelization and optimization. Modern file formats are used as input and output, and there is a direct interface to the Atomic Simulation Environment (ASE) package. The software is implemented primarily in Python (version >=3.7) and provided as an open-source package (GNU GPLv3 or later). A structure determination of the $\alpha$-Fe2O3(1-102)-(1x1) surface is presented as an example for the application of the software.

As part of the ViPErLEED project (Vienna package for Erlangen LEED, low-energy electron diffraction), computer programs have been developed for facile and user-friendly data extraction from movies of LEED images. The programs make use of some concepts from astronomical image processing and analysis. As a first step, flat-field and dark-frame corrections reduce the effects of inhomogeneities of the camera and screen. In a second step, for identifying all diffraction maxima ("spots"), it is sufficient to manually mark and label a single spot or very few spots. Then the program can automatically identify all other spots and determine the distortions of the image. This forms the basis for automatic spot tracking (following the "beams" as they move across the LEED screen) and intensity measurement. Even for complex structures with hundreds to a few thousand diffraction beams, this step takes less than a minute. The package also includes a program for further processing of these I(V) curves (averaging of equivalent beams, manual and/or automatic selection, smoothing) as well as several utilities. The software is implemented as a set of plugins for the public-domain image processing program ImageJ and provided as an open-source package.

In a recent letter [Phys. Rev. Lett. 131, 216401] we presented the multichannel Dyson equation (MCDE) in which two or more many-body Green's functions are coupled. In this work we will give further details of the MCDE approach. In particular we will discuss: 1) the derivation of the MCDE and the definition of the space in which it is to be solved; 2) the rationale of the approximation to the multichannel self-energy; 3) a diagrammatic analysis of the MCDE; 4) the recasting of the MCDE on an eigenvalue problem with an effective Hamiltonian that can be solved using standard numerical techniques. This work mainly focuses on the coupling between the one-body Green's function and the three-body Green's function to describe photoemission spectra, but the MCDE method can be generalized to the coupling of other many-body Green's functions and to other spectroscopies.

We consider the heat equation in a domain that has a hole in its interior. We impose a Neumann condition on the exterior boundary and a nonlinear Robin condition on the boundary of the hole. The shape of the hole is determined by a suitable diffeomorphism $\phi$ defined on the boundary of a reference domain. Assuming that the problem has a solution $u_0$ when $\phi$ is the identity map, we demonstrate that a solution $u_\phi$ continues to exist for $\phi$ close to the identity map and that the "domain-to-solution" map $\phi\mapsto u_\phi$ is of class $C^\infty$. Moreover, we show that the family of solutions $\{u_\phi\}_{\phi}$ is, in a sense, locally unique. Our argument relies on tools from Potential Theory and the Implicit Function Theorem. Some remarks on the linear case complete the paper.

The MPSDynamics.jl package provides an easy to use interface for performing open quantum systems simulations at zero and finite temperatures. The package has been developed with the aim of studying non-Markovian open system dynamics using the state-of-the-art numerically exact Thermalized-Time Evolving Density operator with Orthonormal Polynomials Algorithm (T-TEDOPA) based on environment chain mapping. The simulations rely on a tensor network representation of the quantum states as matrix product states (MPS) and tree tensor network (TTN) states. Written in the Julia programming language, MPSDynamics.jl is a versatile open-source package providing a choice of several variants of the Time-Dependent Variational Principle (TDVP) method for time evolution (including novel bond-adaptive one-site algorithms). The package also provides strong support for the measurement of single and multi-site observables, as well as the storing and logging of data, which makes it a useful tool for the study of many-body physics. It currently handles long-range interactions, time-dependent Hamiltonians, multiple environments, bosonic and fermionic environments, and joint system-environment observables., Comment: 11 pages, 3 figures

Autonomous agents that control computer interfaces to accomplish human tasks are emerging. Leveraging LLMs to power such agents has been of special interest, but unless fine-tuned on human-collected task demonstrations, performance is still relatively low. In this work we study whether fine-tuning alone is a viable approach for building real-world computer control agents. In particularly, we investigate how performance measured on both high and low-level tasks in domain and out of domain scales as more training data is collected. To this end we collect and release a new dataset, AndroidControl, consisting of 15,283 demonstrations of everyday tasks with Android apps. Compared to existing datasets, each AndroidControl task instance includes both high and low-level human-generated instructions, allowing us to explore the level of task complexity an agent can handle. Moreover, AndroidControl is the most diverse computer control dataset to date, including 15,283 unique tasks over 833 Android apps, thus allowing us to conduct in-depth analysis of the model performance in and out of the domain of the training data. Using the dataset, we find that when tested in domain fine-tuned models outperform zero and few-shot baselines and scale in such a way that robust performance might feasibly be obtained simply by collecting more data. Out of domain, performance scales significantly more slowly and suggests that in particular for high-level tasks, fine-tuning on more data alone may be insufficient for achieving robust out-of-domain performance.

Large-language models and large-vision models are increasingly capable of solving compositional reasoning tasks, as measured by breakthroughs in visual-question answering benchmarks. However, state-of-the-art solutions often involve careful construction of large pre-training and fine-tuning datasets, which can be expensive. The use of external tools, whether other ML models, search engines, or APIs, can significantly improve performance by breaking down high-level reasoning questions into sub-questions that are answerable by individual tools, but this approach has similar dataset construction costs to teach fine-tuned models how to use the available tools. We propose a technique in which existing training sets can be directly used for constructing computational environments with task metrics as rewards. This enables a model to autonomously teach itself to use itself or another model as a tool. By doing so, we augment training sets by integrating external signals. The proposed method starts with zero-shot prompts and iteratively refines them by selecting few-shot examples that maximize the task metric on the training set. Our experiments showcase how Gemini learns how to use itself, or another smaller and specialized model such as ScreenAI, to iteratively improve performance on training sets. Our approach successfully generalizes and improves upon zeroshot performance on charts, infographics, and document visual question-answering datasets

Exploring the conduction mechanism in the chalcogenide perovskite BaZrS$_3$ is of significant interest due to its potential suitability as a top absorber layer in silicon-based tandem solar cells and other optoelectronic applications. Theoretical and experimental studies anticipate native ambipolar doping in BaZrS$_3$, although experimental validation remains limited. This study reveals a transition from highly insulating behavior to n-type conductivity in BaZrS$_3$ through annealing in an S-poor environment. BaZrS$_3$ thin films are synthesized $\textit{via}$ a two step process: co-sputtering of Ba-Zr followed by sulfurization at 600 $^{\circ}$C, and subsequent annealing in high vacuum. UV-Vis measurement reveal a red-shift in the absorption edge concurrent with sample color darkening after annealing. The increase in defect density with vacuum annealing, coupled with low activation energy and n-type character of defects, strongly suggests that sulfur vacancies (V$_{\mathrm{S}}$) are responsible, in agreement with theoretical predictions. The shift of the Fermi level towards conduction band minimum, quantified by Hard X-ray Photoelectron Spectroscopy (Ga K$\alpha$, 9.25 keV), further corroborates the induced n-type of conductivity in annealed samples. Our findings indicate that vacuum annealing induces V$_{\mathrm{S}}$ defects that dominate the charge transport, thereby making BaZrS$_3$ an n-type semiconductor under S-poor conditions. This study offers crucial insights into understanding the defect properties of BaZrS$_3$, facilitating further improvements for its use in solar cell applications., Comment: 19 pages (single column), 6 figures in main manuscript and 8 figures in supplementary information

Autonomous agents that execute human tasks by controlling computers can enhance human productivity and application accessibility. However, progress in this field will be driven by realistic and reproducible benchmarks. We present AndroidWorld, a fully functional Android environment that provides reward signals for 116 programmatic tasks across 20 real-world Android apps. Unlike existing interactive environments, which provide a static test set, AndroidWorld dynamically constructs tasks that are parameterized and expressed in natural language in unlimited ways, thus enabling testing on a much larger and more realistic suite of tasks. Reward signals are derived from the computer's system state, making them durable across task variations and extensible across different apps. To demonstrate AndroidWorld's benefits and mode of operation, we introduce a new computer control agent, M3A. M3A can complete 30.6% of the AndroidWorld's tasks, leaving ample room for future work. Furthermore, we adapt a popular desktop web agent to work on Android, which we find to be less effective on mobile, suggesting future research is needed to achieve universal, cross-domain agents. Finally, we conduct a robustness analysis by testing M3A against a range of task variations on a representative subset of tasks, demonstrating that variations in task parameters can significantly alter a task's complexity and, consequently, an agent's performance, highlighting the importance of testing agents under diverse conditions. AndroidWorld and the experiments in this paper are available at https://github.com/google-research/android_world.

A common problem for agents operating in real-world environments is that the response of an environment to their actions may be non-deterministic and observed through noise. This renders environmental state and progress towards completing a task latent. Despite recent impressive demonstrations of LLM's reasoning abilities on various benchmarks, whether LLMs can build estimates of latent state and leverage them for reasoning has not been explicitly studied. We investigate this problem in the real-world domain of autonomous UI agents. We establish that appropriately prompting LLMs in a zero-shot manner can be formally understood as forming point estimates of latent state in a textual space. In the context of autonomous UI agents we then show that LLMs used in this manner are more than $76\%$ accurate at inferring various aspects of latent state, such as performed (vs. commanded) actions and task progression. Using both public and internal benchmarks and three reasoning methods (zero-shot, CoT-SC & ReAct), we show that LLM-powered agents that explicitly estimate and reason about latent state are able to successfully complete up to 1.6x more tasks than those that do not.

Finite discrete-time dynamical systems (FDDS) model phenomena that evolve deterministically in discrete time. It is possible to define sum and product operations on these systems (disjoint union and direct product, respectively) giving a commutative semiring. This algebraic structure led to several works employing polynomial equations to model hypotheses on phenomena modelled using FDDS. To solve these equations, algorithms for performing the division and computing $k$-th roots are needed. In this paper, we propose two polynomial algorithms for these tasks, under the condition that the result is a connected FDDS. This ultimately leads to an efficient solution to equations of the type $AX^k=B$ for connected $X$. These results are some of the important final steps for solving more general polynomial equations on FDDS.

Measurable linear scattering polarization signals have been predicted and detected at the solar disk center in the core of chromospheric lines. These forward-scattering polarization signals, which are of high interest for magnetic field diagnostics, have always been modeled either under the assumption of complete frequency redistribution (CRD), or taking partial frequency redistribution (PRD) effects into account under the angle-averaged (AA) approximation. This work aims at assessing the suitability of the CRD and PRD-AA approximations for modeling the forward-scattering polarization signals produced by the presence of an inclined magnetic field, the so-called forward-scattering Hanle effect, in the chromospheric CaI 4227 A line. Radiative transfer calculations are performed in semi-empirical 1D solar atmospheres, out of local thermodynamic equilibrium (LTE). A two-step solution strategy is applied: the non-LTE RT problem is first solved considering a multilevel atom and neglecting polarization phenomena. The same problem is then solved including polarization, considering a two-level atom and keeping fixed the lower-level population calculated at the previous step. The emergent linear polarization signals calculated under the CRD and PRD-AA approximations are analyzed and compared to those obtained by modeling PRD effects in their general angle-dependent (AD) formulation. With respect to the PRD-AD case, the CRD and PRD-AA calculations significantly underestimate the amplitude of the line-center polarization signals produced by the forward-scattering Hanle effect. The results of this work suggest that a PRD-AD modeling is required in order to develop reliable diagnostic techniques exploiting the forward-scattering polarization signals observed in the CaI 4227 A line. These results need to be confirmed by full 3D calculations including non-magnetic symmetry-breaking effects.

This is the first part of a project aimed at formalizing Rozansky-Witten models in the functorial field theory framework. Motivated by work of Calaque-Haugseng-Scheimbauer, we construct a family of symmetric monoidal $(\infty,3)$-categories parametrized by an $\infty$-category with finite limits and a functor into symmetric monoidal $\infty$-categories, such that the functor admits pushforwards. This $(\infty,3)$-category contains correspondences in the base $\infty$-category equipped with local systems, which compose via a push-pull formula. We apply this general construction to provide an approximation to the $3$-category of Rozansky-Witten models whose existence was conjectured by Kapustin-Rozansky-Saulina; this approximation behaves like a "commutative" version of the conjectured $3$-category and is related to work of Stefanich on higher quasicoherent sheaves., Comment: Comments welcome! Edit #1: Reworked the introduction for submission

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 \pm 0.82 M\odot BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way., Comment: 23 pages, accepted fro publication in A&A Letters. New version with small fixes

We propose and analyse a new microscopic second order Follow-the-Leader type scheme to describe traffic flows. The main novelty of this model consists in multiplying the second order term by a nonlinear function of the global density, with the intent of considering the attentiveness of the drivers in dependence of the amount of congestion. Such term makes the system highly degenerate; indeed, coherently with the modellistic viewpoint, we allow for the nonlinearity to vanish as soon as consecutive vehicles are very close to each other. We first show existence of solutions to the degenerate discrete system. We then perform a rigorous discrete-to-continuum limit, as the number of vehicles grows larger and larger, by making use of suitable piece-wise constant approximations of the relevant macroscopic variables. The resulting continuum system turns out to be described by a degenerate pressure-less Euler-type equation, and we discuss how this could be considered an alternative to the groundbreaking Aw-Rascle-Zhang traffic model. Finally, we study the singular limit to first order dynamics in the spirit of a vanishing-inertia argument. This eventually validates the use of first order macroscopic models with nonlinear mobility to describe a congested traffic stream.

Background: Sleep staging is a fundamental component in the diagnosis of sleep disorders and the management of sleep health. Traditionally, this analysis is conducted in clinical settings and involves a time-consuming scoring procedure. Recent data-driven algorithms for sleep staging, using the photoplethysmogram (PPG) time series, have shown high performance on local test sets but lower performance on external datasets due to data drift. Methods: This study aimed to develop a generalizable deep learning model for the task of four class (wake, light, deep, and rapid eye movement (REM)) sleep staging from raw PPG physiological time-series. Six sleep datasets, totaling 2,574 patients recordings, were used. In order to create a more generalizable representation, we developed and evaluated a deep learning model called SleepPPG-Net2, which employs a multi-source domain training approach.SleepPPG-Net2 was benchmarked against two state-of-the-art models. Results: SleepPPG-Net2 showed consistently higher performance over benchmark approaches, with generalization performance (Cohen's kappa) improving by up to 19%. Performance disparities were observed in relation to age, sex, and sleep apnea severity. Conclusion: SleepPPG-Net2 sets a new standard for staging sleep from raw PPG time-series.

Boolean networks are extensively applied as models of complex dynamical systems, aiming at capturing essential features related to causality and synchronicity of the state changes of components along time. Dynamics of Boolean networks result from the application of their Boolean map according to a so-called update mode, specifying the possible transitions between network configurations. In this paper, we explore update modes that possess a memory on past configurations, and provide a generic framework to define them. We show that recently introduced modes such as the most permissive and interval modes can be naturally expressed in this framework. We propose novel update modes, the history-based and trapping modes, and provide a comprehensive comparison between them. Furthermore, we show that trapping dynamics, which further generalize the most permissive mode, correspond to a rich class of networks related to transitive dynamics and encompassing commutative networks. Finally, we provide a thorough characterization of the structure of minimal and principal trapspaces, bringing a combinatorial and algebraic understanding of these objects.

The so-called ``adiabatic elimination'' of fast decaying degrees of freedom in open quantum systems can be performed with a series expansion in the timescale separation. The associated computations are significantly more difficult when the remaining degrees of freedom (center manifold) follow fast unitary dynamics instead of just being slow. This paper highlights how a formulation with Sylvester's equation and with adjoint dynamics leads to systematic, explicit expressions at high orders for settings of physical interest., Comment: Accepted paper at IEEE Conference on Decision and Control 2024

The increasing polarisation in our societies is a major international concern. Current approaches to defining and detecting polarisation largely rely on finding evidence of bimodality in social networks or voter opinion surveys. It is difficult to detect temporal trends in polarisation, as the results usually fall into a binary of polarised or non-polarised, which cannot robustly show that subsequent increases in bimodality are statistically significant. Our work is aligned with Baldassari and Gelman's theory that polarisation should be defined as increasing correlation between positions in the ideological field. We also draw from post-structuralist work which argues that polarisation is the process of both the ideological and material layers of society being segregated into two poles, as in cases of apartheid. Thus, in order to measure the polarisation in a society, it would be beneficial to be able to assess social networks directly. In this paper we use Random Dot Product Graphs to embed social networks in metric spaces. In the case of a social network, the embedded dimensionality corresponds to the number of reasons any two people may form a social connection. A decrease in the optimal dimensionality for the embedding of the network graph, as measured using truncated Singular Value Decomposition of the graph adjacency matrix, indicates increasing polarisation in the network. We apply this method to two different Twitter networks based on discussions of climate change, and show that our methods agree with other researchers' detection of polarisation in this space. We also use networks generated by stochastic block models to explore how an increase of the isolation between distinct communities in a network, or the increase in the predominance of one community over the other, are identifiable as polarisation processes., Comment: 24 pages, 7 figures, abstract presented at ICCS 2023