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This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

Synchrotron X-ray emission has been detected from nearly a dozen young supernova remnants (SNRs). X-rays of synchrotron origin exhibit linear polarization in a regular, non-randomly oriented magnetic field. The significant polarized X-ray emission from four such SNRs has already been reported on the basis of observations with the Imaging X-ray Polarimetry Explorer (IXPE). The magnetic-field structure as derived from IXPE observations is radial for Cassiopeia A, Tycho's SNR, and SN 1006, and tangential for RX J1713.7-3946. The latter together with the recent detection of a tangential magnetic field in SNR 1E 0102.2-7219 by the Australia Telescope Compact Array in the radio band shows that tangential magnetic fields can also be present in young SNRs. Thus, the dichotomy in polarization between young and middle-aged SNRs (radial magnetic fields in young SNRs, but tangential magnetic fields in middle-aged SNRs), previously noticed in the radio band, deserves additional attention. The present analysis of IXPE observations determines, for the first time, a magnetic-field structure in the northwestern rim of Vela Jr, also known as RX J0852.0-4622, and provides a new example of a young SNR with a tangential magnetic field., Comment: Accepted for publication in Astronomy and Astrophysics

X-ray polarization is a unique new probe of the particle acceleration in astrophysical jets made possible through the Imaging X-ray Polarimetry Explorer. Here we report on the first dense X-ray polarization monitoring campaign on the blazar Mrk 421. Our observations were accompanied by an even denser radio and optical polarization campaign. We find significant short-timescale variability in both X-ray polarization degree and angle, including a $\sim90^\circ$ angle rotation about the jet axis. We attribute this to random variations of the magnetic field, consistent with the presence of turbulence but also unlikely to be explained by turbulence alone. At the same time, the degree of lower-energy polarization is significantly lower and shows no more than mild variability. Our campaign provides further evidence for a scenario in which energy-stratified shock-acceleration of relativistic electrons, combined with a turbulent magnetic field, is responsible for optical to X-ray synchrotron emission in blazar jets., Comment: 23 pages, including 8 pages of appendices. 12 figures, 3 tables. Submitted to ApJ

The quest for radio signals from technologically-advanced extraterrestrial intelligence has traditionally concentrated on the vicinity of 1.4 GHz. In this paper, we extend the search to unprecedented territories, detailing our extensive observations at 6 GHz and initiating the first-ever survey at 18 GHz with the Sardinia Radio Telescope (SRT). Our strategy entailed rigorous observation sessions, totaling 36 hours, directed towards the Galactic Center and 72 selected TESS targets-making this the most comprehensive high-frequency technosignature search to date. Our narrowband signal search found no definitive evidence of drifting signals that could suggest an extraterrestrial origin from the surveyed regions. Nevertheless, our efforts have enabled us to set new constraints on the presence of radio emissions from approximately $5\times 10^{5}$ stars, establishing an isotropic radiated power limit of $1.8\times 10^{19} W$. We also provide a comparative analysis of the 'hits' recorded across both frequencies to highlight the significance of pursuing technosignature searches at higher frequencies, where the spectral landscape is less congested and more conducive to detection., Comment: Submitted to Acta Astronautica

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.

The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulnerability within the cerebral blood supply and can lead to severe conditions, such as Cerebral Small Vessel Diseases. The advent of 7 Tesla MRI systems has enabled the acquisition of higher spatial resolution images, making it possible to visualise such vessels in the brain. However, the lack of publicly available annotated datasets has impeded the development of robust, machine learning-driven segmentation algorithms. To address this, the SMILE-UHURA challenge was organised. This challenge, held in conjunction with the ISBI 2023, in Cartagena de Indias, Colombia, aimed to provide a platform for researchers working on related topics. The SMILE-UHURA challenge addresses the gap in publicly available annotated datasets by providing an annotated dataset of Time-of-Flight angiography acquired with 7T MRI. This dataset was created through a combination of automated pre-segmentation and extensive manual refinement. In this manuscript, sixteen submitted methods and two baseline methods are compared both quantitatively and qualitatively on two different datasets: held-out test MRAs from the same dataset as the training data (with labels kept secret) and a separate 7T ToF MRA dataset where both input volumes and labels are kept secret. The results demonstrate that most of the submitted deep learning methods, trained on the provided training dataset, achieved reliable segmentation performance. Dice scores reached up to 0.838 $\pm$ 0.066 and 0.716 $\pm$ 0.125 on the respective datasets, with an average performance of up to 0.804 $\pm$ 0.15.

For $\beta\in{\mathbb Z}$, let $G(\beta)=\langle A,B\,|\, A^{[A,B]}=A,\, B^{[B,A]}=B^\beta\rangle$ be the infinite Macdonald group, and set $C=[A,B]$. Then $G(\beta)$ is a nilpotent polycyclic group of the form $\langle A\rangle\ltimes\langle B,C\rangle$, where $A$ has infinite order. If $\beta\neq 1$, then $G(\beta)$ is of class 3 and $\langle B,C\rangle$ is a finite metacyclic group of order $|\beta-1|^3$, which is an extension of $C_{(\beta-1)^2}$ by $C_{|\beta-1|}$, split except when $v_2(\beta-1)=1$, while $G(1)$ is the integral Heisenberg group, of class 2 and $\langle B,C\rangle\cong{\mathbb Z}^2$. We give a full description of the automorphism group of $G(\beta)$. If $\beta\neq 1$, then $|\mathrm{Aut}(G(\beta))|=2(\beta-1)^4$ and we exhibit an imbedding $\mathrm{Aut}(G(\beta))\hookrightarrow {\mathrm GL}_4({\mathbb Z}/(\beta-1){\mathbb Z})$, but for the case $\beta\in\{-1,3\}$ when 5 is required instead of 4. When $\beta$ is even the automorphism group of $\langle B,C\rangle$ can be obtained from the work of Bidwell and Curran \cite{BC}, and we indicate which of their automorphisms extend to an automorphism of $G(\beta)$. In general, we give necessary and sufficient conditions for $G(\beta)$ to be isomorphic to $G(\gamma)$. When $\gcd(\beta-1,6)=1$, we determine the automorphism group of $L(\beta)=G(\beta)/\langle A^{\beta-1}\rangle$, which is a relative holomorph of $\langle B,C\rangle$, and $\langle A^{\beta-1}\rangle$ is a characteristic subgroup of $G(\beta)$. The map $\mathrm{Aut}(G(\beta))\to \mathrm{Aut}(L(\beta))$ is injective and $\mathrm{Aut}(L(\beta))$ is an extension of the Heisenberg group over ${\mathbb Z}/(\beta-1){\mathbb Z}$ direct product $C_{\beta-1}$, by the holomorph of $C_{\beta-1}$.

We introduce CaLES, a GPU-accelerated finite-difference solver designed for large-eddy simulations (LES) of incompressible wall-bounded flows in massively parallel environments. Built upon the existing direct numerical simulation (DNS) solver CaNS, CaLES relies on low-storage, third-order Runge-Kutta schemes for temporal discretization, with the option to treat viscous terms via an implicit Crank-Nicolson scheme in one or three directions. A fast direct solver, based on eigenfunction expansions, is used to solve the discretized Poisson/Helmholtz equations. For turbulence modeling, the classical Smagorinsky model with van Driest near-wall damping and the dynamic Smagorinsky model are implemented, along with a logarithmic law wall model. GPU acceleration is achieved through OpenACC directives, following CaNS-2.3.0. Performance assessments were conducted on the Leonardo cluster at CINECA, Italy. Each node is equipped with one Intel Xeon Platinum 8358 CPU (2.60 GHz, 32 cores) and four NVIDIA A100 GPUs (64 GB HBM2e), interconnected via NVLink 3.0 (200 GB/s). The inter-node communication bandwidth is 25 GB/s, supported by a DragonFly+ network architecture with NVIDIA Mellanox InfiniBand HDR. Results indicate that the computational speed on a single GPU is equivalent to approximately 15 CPU nodes, depending on the treatment of viscous terms and the subgrid-scale model, and that the solver efficiently scales across multiple GPUs. The predictive capability of CaLES has been tested using multiple flow cases, including decaying isotropic turbulence, turbulent channel flow, and turbulent duct flow. The high computational efficiency of the solver enables grid convergence studies on extremely fine grids, pinpointing non-monotonic grid convergence for wall-modeled LES.

Social robots are required not only to understand human intentions but also to effectively communicate their intentions or own internal states to users. This study explores the use of sonification to provide explicit auditory feedback, enhancing mutual understanding in HRI. We introduce a novel sonification approach that conveys the robot's internal state, linked to its perception of nearby individuals and their interaction intentions. The approach is evaluated through a two-fold user study: an online video-based survey with $26$ participants and live experiments with $10$ participants. Results indicate that while sonification improves the robot's expressivity and communication effectiveness, the design of the auditory feedback needs refinement to enhance user experience. Participants found the auditory cues useful but described the sounds as uninteresting and unpleasant. These findings underscore the importance of carefully designed auditory feedback in developing more effective and engaging HRI systems.

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach using information from the muscular activity of the forearm and the motion of the exoskeleton to reconstruct the hand's opening degree and compliance level. Such information can be used to evaluate the therapy progress and develop adaptive control behaviors. Our approach is validated with a real light exoskeleton. The experiments demonstrate good predictive performance of our approach when trained on data coming from a single user and tested on the same user, even across different sessions. This generalization capability makes our system promising for practical use in real rehabilitation.

The dominant accretion process leading to the formation of the terrestrial planets of the Solar System is a subject of intense scientific debate. Two radically different scenarios have been proposed. The classic scenario starts from a disk of planetesimals which, by mutual collisions, produce a set of Moon to Mars-mass planetary embryos. After the removal of gas from the disk, the embryos experience mutual giant impacts which, together with the accretion of additional planetesimals, lead to the formation of the terrestrial planets on a timescale of tens of millions of years. In the alternative, pebble accretion scenario, the terrestrial planets grow by accreting sunward-drifting mm-cm sized particles from the outer disk. The planets all form within the lifetime of the disk, with the sole exception of Earth, which undergoes a single post-disk giant impact with Theia (a fifth protoplanet formed by pebble accretion itself) to form the Moon. To distinguish between these two scenarios, we revisit all available constraints: compositional (in terms of nucleosynthetic isotope anomalies and chemical composition), dynamical and chronological. We find that the pebble accretion scenario is unable to match these constraints in a self-consistent manner, unlike the classic scenario., Comment: In press as a Frontier paper in Earth and Planetary Science Letters

With the goal of increasing the speed and efficiency in robotic manipulation, a control approach is presented that aims to utilize intentional simultaneous impacts to its advantage. This approach exploits the concept of the time-invariant reference spreading framework, in which partly-overlapping ante- and post-impact reference vector fields are used. These vector fields are coupled via an impact model in proximity of the expected impact area, minimizing the otherwise large impact-induced velocity errors and control efforts. We show how a nonsmooth physics engine can be used to construct this impact model for complex scenarios, which warrants applicability to a large range of possible impact states without requiring contact stiffness and damping parameters. In addition, a novel interim-impact control mode provides robustness in the execution against the inevitable lack of exact impact simultaneity and the corresponding unreliable velocity error during the time when contact is only partially established. This interim mode uses a position feedback signal that is derived from the ante-impact velocity reference to promote contact completion, and smoothly transitions into the post-impact mode. An experimental validation of time-invariant reference spreading control is presented for the first time through a set of 600 robotic hit-and-push and dual-arm grabbing experiments., Comment: 15 pages, 10 figures. Submitted to IEEE Transactions on Robotics (T-RO)

Unconventional superconductivity, where electron pairing does not involve electron-phonon interactions, is often attributed to magnetic correlations in a material. Well known examples include high-T_c cuprates and uranium-based heavy fermion superconductors. Less explored are unconventional superconductors with strong spin-orbit coupling, where interactions between spin-polarised electrons and external magnetic field can result in multiple superconducting phases and field-induced transitions between them, a rare phenomenon in the superconducting state. Here we report a magnetic-field driven phase transition in \beta-PdBi2, a layered non-magnetic superconductor. Our tunnelling spectroscopy on thin PdBi2 monocrystals incorporated in planar superconductor-insulator-normal metal junctions reveals a marked discontinuity in the superconducting properties with increasing in-plane field, which is consistent with a transition from conventional (s-wave) to nodal pairing. Our theoretical analysis suggests that this phase transition may arise from spin polarisation and spin-momentum locking caused by locally broken inversion symmetry, with p-wave pairing becoming energetically favourable in high fields. Our findings also reconcile earlier predictions of unconventional multigap superconductivity in \beta-PdBi2 with previous experiments where only a single s-wave gap could be detected., Comment: 29 pages, including 4 main Figures, Methods, 8 Supplementary Figures and 5 Supplementary Notes

We present OBJS, a new transpiler project featuring the implementation of typified variables and functions call management in Javascript, as well as several new operators and syntax patterns that could make coding more agile and versatile. The goal is to empower this language. According to this point of view, this transpiler aims at implementing Object Oriented Programming paradigms into Javascript. The author opines that this would be likely the best evolution of this language in ways that should be proper to the original syntax, that is, by adopting native C++standards, so that there would be no promiscuity between old and new patterns, benefiting those who come from similar languages.

We present a technique for rendering limit sets for kleinian groups, based upon the base transformation of integers and which aims at saving memory resources and being faster than the traditional dictionary based approach.

One of the most important and topical challenges of quantum circuits is their scalability. Rapid Single Flux Quantum (RSFQ) technology is at the forefront of replacing current standard CMOS-based control architectures for a number of applications, including quantum computing and quantum sensor arrays. By condensing the control and readout to SFQ-based on-chip devices that are directly connected to the quantum systems, it is possible to minimise the total system overhead, improving scalability and integration. In this work, we present a novel RSFQ device that generates multi tone digital signals, based on complex pulse train sequences using a Circular Shift Register (CSR) and a comb filter stage. We show that the frequency spectrum of the pulse trains is dependent on a preloaded pattern on the CSR, as well as on the delay line of the comb filter stage. By carefully selecting both the pattern and delay, the desired tones can be isolated and amplified as required. Finally, we propose architectures where this device can be implemented to control and readout arrays of quantum devices, such as qubits and single photon detectors., Comment: Submitted to IEEE Transactions on Quantum Engineering

The phase evolution of gravitational waves (GWs) can be modulated by the astrophysical environment surrounding the source, which provides a probe for the origin of individual binary black holes (BBHs) using GWs alone. We here study the evolving phase of the GW waveform derived from a large set of simulations of BBH mergers forming in dense stellar clusters through binary-single interactions. We uncover that a well-defined fraction of the assembled eccentric GW sources will have a notable GW phase shift induced by the remaining third object. The magnitude of the GW phase shift often exceeds conservative analytical estimates due to strong 3-body interactions, which occasionally results in GW sources with clearly shifted and perturbed GW waveforms. This opens up promising opportunities for current and future GW detectors, as observing such a phase shift can identify the formation environment of a BBH, as well as help to characterise the local properties of its surrounding environment.

Tabulated chemistry methods are a well-known strategy to efficiently store the flows thermochemical properties. In particular, the Flamelet-Generated Manifold (FGM) is a widely used technique that generates the database with a small number of control variables. In order to build such a manifold, these coordinates must be monotonic in space and time. However, the high diffusivity of hydrogen can prevent such requisite. To avoid the non-monotonicity of control variables (the progress variable, in particular), one practical workaround is to perform the tabulation on zero-dimensional (0D) reactors rather than on one-dimensional (1D) flamelets. Various works already implemented and tested such 0D-based manifold, but mainly in the context of spray engines, where most of the composition is lean and information past the flammability limit is not relevant. The present work aims at investigating, for the first time, the applicability of a tabulation based on homogeneous reactors to study auto-igniting turbulent hydrogen jets. It is shown that a combined use of homogeneous reactors at the lean side and an extrapolation with 1D flamelets on the richer side is required to capture both chemistry and diffusive effects accurately in pure hydrogen flames. Then, this manifold is coupled to Large-Eddy Simulation (LES) of three-dimensional turbulent mixing layers and evaluated against direct numerical simulation with detailed chemistry. Good agreement is found, in terms of both ignition delay and the following steady-state burning process. Further analyses are carried out on statistics and modelling. In particular, the sensitivity of the LES solution to filter width, turbulence-chemistry interaction and multidimensional flame effects is investigated to provide new relevant insights on modelling non-premixed auto-igniting turbulent hydrogen flames.

Large Language Models (LLMs) are revolutionizing the landscape of Generative Artificial Intelligence (GenAI), with innovative LLM-backed solutions emerging rapidly. However, when applied to database technologies, specifically query generation for graph databases and Knowledge Graphs (KGs), LLMs still face significant challenges. While research on LLM-driven query generation for Structured Query Language (SQL) exists, similar systems for graph databases remain underdeveloped. This paper presents a comparative study addressing the challenge of generating Cypher queries a powerful language for interacting with graph databases using open-access LLMs. We rigorously evaluate several LLM agents (OpenAI ChatGPT 4o, Claude Sonnet 3.5, Google Gemini Pro 1.5, and a locally deployed Llama 3.1 8B) using a designed few-shot learning prompt and Retrieval Augmented Generation (RAG) backed by Chain-of-Thoughts (CoT) reasoning. Our empirical analysis of query generation accuracy reveals that Claude Sonnet 3.5 outperforms its counterparts in this specific domain. Further, we highlight promising future research directions to address the identified limitations and advance LLM-driven query generation for graph databases., Comment: Paper accepted and will be presented at CSCI2024 in December 2024, Later will be published at Springer LNCS

Thermodynamic (TUR) and kinetic (KUR) uncertainty relations are fundamental bounds constraining the fluctuations of current observables in classical, non-equilibrium systems. Several works have verified, however, violations of these classical bounds in open quantum systems, motivating the derivation of new quantum TURs and KURs that account for the role of quantum coherence. Here, we go one step further by deriving multidimensional KUR and TUR for multiple observables in open quantum systems undergoing Markovian dynamics. Our derivation exploits a multi-parameter metrology approach, in which the Fisher information matrix plays a central role. Crucially, our bounds are tighter than previously derived quantum TURs and KURs for single observables, precisely because they incorporate correlations between multiple observables. We also find an intriguing quantum signature of correlations that is captured by the off-diagonal element of the Fisher information matrix, which vanishes for classical stochastic dynamics. By considering two examples, namely a coherently driven qubit system and the three-level maser, we demonstrate that the multidimensional quantum KUR bound can even be saturated when the observables are perfectly correlated.

In recent work, Lusztig's positive root vectors (with respect to a distinguished choice of reduced decomposition of the longest element of the Weyl group) were shown to give a quantum tangent space for every $A$-series Drinfeld--Jimbo full quantum flag manifold $\mathcal{O}_q(\mathrm{F}_n)$. Moreover, the associated differential calculus $\Omega^{(0,\bullet)}_q(\mathrm{F}_n)$ was shown to have classical dimension, giving a direct $q$-deformation of the classical anti-holomorphic Dolbeault complex of $\mathrm{F}_n$. Here we examine in detail the rank two case, namely the full quantum flag manifold of $\mathcal{O}_q(\mathrm{SU}_3)$. In particular, we examine the $*$-differential calculus associated to $\Omega^{(0,\bullet)}_q(\mathrm{F}_3)$ and its non-commutative complex geometry. We find that the number of almost-complex structures reduces from $8$ (that is $2$ to the power of the number of positive roots of $\frak{sl}_3$) to $4$ (that is $2$ to the power of the number of simple roots of $\frak{sl}_3$). Moreover, we show that each of these almost-complex structures is integrable, which is to say, each of them is a complex structure. Finally, we observe that, due to non-centrality of all the non-degenerate coinvariant $2$-forms, none of these complex structures admits a left $\mathcal{O}_q(\mathrm{SU}_3)$-covariant noncommutative K\"ahler structure.

Josephson element-based parametric amplifiers (JPAs) typically require rf pump power that is several orders of magnitude stronger than the maximum signal power they can handle. The low power efficiency and strong pump leakage towards signal circuitry could be critical concerns in application. In this work, we discuss how to optimize the pump coupling scheme for a three-wave mixing JPA by employing microwave filtering techniques, with the goal of maximizing the pump power efficiency and minimize pump leakage without sacrificing other properties of interest. We implement the corresponding filter design in a SNAIL-based JPA and demonstrate more than three orders of magnitude improvement in both power efficiency and pump leakage suppression compared to a similar device with regular capacitive coupling, while maintaining state-of-the-art dynamic range and near-quantum-limited noise performance. Furthermore, we show experimentally that the filter-coupled JPA is more robust against noise input from the pump port, exhibiting no significant change in added noise performance with up to 4 K of effective noise temperature at the pump port.

As modern web services increasingly rely on REST APIs, their thorough testing has become crucial. Furthermore, the advent of REST API specifications such as the OpenAPI Specification has led to the emergence of many black-box REST API testing tools. However, these tools often focus on individual test elements in isolation (e.g., APIs, parameters, values), resulting in lower coverage and less effectiveness in detecting faults (i.e., 500 response codes). To address these limitations, we present AutoRestTest, the first black-box framework to adopt a dependency-embedded multi-agent approach for REST API testing, integrating Multi-Agent Reinforcement Learning (MARL) with a Semantic Property Dependency Graph (SPDG) and Large Language Models (LLMs). Our approach treats REST API testing as a separable problem, where four agents -- API, dependency, parameter, and value -- collaborate to optimize API exploration. LLMs handle domain-specific value restrictions, the SPDG model simplifies the search space for dependencies using a similarity score between API operations, and MARL dynamically optimizes the agents' behavior. Evaluated on 12 real-world REST services, AutoRestTest outperforms the four leading black-box REST API testing tools, including those assisted by RESTGPT (which augments realistic test inputs using LLMs), in terms of code coverage, operation coverage, and fault detection. Notably, AutoRestTest is the only tool able to identify an internal server error in Spotify. Our ablation study underscores the significant contributions of the agent learning, SPDG, and LLM components., Comment: To be published in the 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025)

The microphysics of the intracluster medium (ICM) in galaxy clusters is still poorly understood. Observational evidence suggests that the effective viscosity is suppressed by plasma instabilities that reduce the mean free path of particles. Measuring the effective viscosity of the ICM is crucial to understanding the processes that govern its physics on small scales. The trails of ionized interstellar medium left behind by the so-called jellyfish galaxies can trace the turbulent motions of the surrounding ICM and constrain its local viscosity. We present the results of a systematic analysis of the velocity structure function (VSF) of the H$\alpha$ line for ten galaxies from the GASP sample. The VSFs show a sub-linear power law scaling below 10 kpc which may result from turbulent cascading and extends to 1 kpc, below the supposed ICM dissipation scales of tens of kpc expected in a fluid described by Coulomb collisions. Our result constrains the local ICM viscosity to be 0.3-25$\%$ of the expected Spitzer value. Our findings demonstrate that either the ICM particles have a smaller mean free path than expected in a regime defined by Coulomb collisions, or that we are probing effects due to collisionless physics in the ICM turbulence., Comment: 24 pages, 14 figures, accepted for publication on ApJ on 11/11/2024

We investigate the orientational properties of a homogeneous and inhomogeneous tetrahedral 4-patch fluid (Kern--Frenkel model). Using integral equations, either (i) HNC or (ii) a modified HNC scheme with simulation input, the full orientational dependence of pair and direct correlation functions is determined. Density functionals for the inhomogeneous problem are constructed via two different methods. The first, molecular density functional theory, utilizes the full direct correlation function and an isotropic hard-sphere bridge functional. The second method, a machine learning approach, uses a decomposition of the functional into an isotropic reference part and a mean-field orientational part, where both parts are improved by machine learning techniques. Comparison to simulation data at hard walls and around hard tracers show a similar performance of the two functionals. Machine learning strategies are discussed to eliminate residual differences, with the goal of obtaining machine-learning enhanced functionals for the general anisotropic fluid.

Knots and links play a crucial role in understanding topology and discreteness in nature. In magnetic systems, twisted, knotted and braided vortex tubes manifest as Skyrmions, Hopfions, or screw dislocations. These complex textures are characterized by topologically non-trivial quantities, such as a Skyrmion number, a Hopf index $H$, a Burgers vector (quantified by an integer $\nu$), and linking numbers. In this work, we introduce a discrete geometric definition of $H$ for periodic magnetic textures, which can be separated into contributions from the self-linking and inter-linking of flux tubes. We show that fractional Hopfions or textures with non-integer values of $H$ naturally arise and can be interpreted as states of ``mixed topology" that are continuously transformable to one of the multiple possible topological sectors. Our findings demonstrate a solid physical foundation for the Hopf index to take integer, non-integer, or specific fractional values, depending on the underlying topology of the system., Comment: 14 pages

In this paper, we extend the Virtual Localization Formula of Levine to a wide class of motivic ring spectra, obtaining in particular a localization formula for virtual fundamental classes in Witt theory $ \mathrm{KW} $. Applying standard tools of $\mathbb A^1$-intersection theory to any $ SL_{\eta} $-oriented spectra $ \mathrm A $, we obtain an additive presentation of $ \mathrm A(BN) $, for $ N $ the normaliser of the torus in $ SL_2 $. Then we establish an equivariant Atiyah-Bott localization theorem for $ \mathrm A_N^{\mathrm{BM}}(X) $ and we conclude with the $N$-equivariant virtual localisation formula. Of independent interest, we also describe the ring structure of $ \mathrm{KW}(BN) $., Comment: This is part of the author's PhD thesis. Comments are very welcome

In this paper we are going to compute the $ \mathrm{KW} $-Euler classes for rank 2 vector bundles on the classifying stack $ \mathcal{B}N $, where $N$ is the normaliser of the standard torus in $SL_2$ and $\mathrm{KW}$ represents Balmer's derived Witt groups. Using these computations we will recover, through a new and different strategy, the formulas previously obtained by Levine in Witt-sheaf cohomology. In order to obtain our results, we will prove K\"unneth formulas for products of $GL_n$'s and $SL_n$'s classifying spaces and we will develop from scratch the basic theory of twisted symplectic bundles with their associated twisted Borel classes in $SL$-oriented theories.

Impact-aware robotic manipulation benefits from an accurate map from ante-impact to post-impact velocity signals to support, e.g., motion planning and control. This work proposes an approach to generate and experimentally validate such impact maps from simulations with a physics engine, allowing to model impact scenarios of arbitrarily large complexity. This impact map captures the velocity jump assuming an instantaneous contact transition between rigid objects, neglecting the nearly instantaneous contact transition and impact-induced vibrations. Feedback control, which is required for complex impact scenarios, will affect velocity signals when these vibrations are still active, making an evaluation solely based on velocity signals as in previous works unreliable. Instead, the proposed validation approach uses the reference spreading control framework, which aims to reduce peaks and jumps in the control feedback signals by using a reference consistent with the rigid impact map together with a suitable control scheme. Based on the key idea that selecting the correct rigid impact map in this reference spreading framework will minimize the net feedback signal, the rigid impact map is experimentally determined and compared with the impact map obtained from simulation, resulting in a 3.1% average error between the post-impact velocity identified from simulations and from experiments., Comment: 13 pages, 9 figures. Submitted to IEEE Transactions on Robotics

Transitional millisecond pulsars (tMSPs) are neutron-star systems that alternate between a rotation-powered radio millisecond pulsar state and an accretion-disk-dominated low-mass X-ray binary (LMXB)-like state on multi-year timescales. During the LMXB-like state, the X-ray emission from tMSPs switches between "low" and "high" X-ray brightness modes on a timescale of seconds to minutes (or longer), while the radio emission shows variability on timescales of roughly minutes. Coordinated VLA and Chandra observations of the nearby tMSP PSR J1023+0038 uncovered a clear anti-correlation between radio and X-ray luminosities such that the radio emission consistently peaks during the X-ray low modes. In addition, there are sometimes also radio/X-ray flares that show no obvious correlation. In this paper, we present simultaneous radio and X-ray observations of a promising tMSP candidate system, 3FGL J1544.6-1125, which shows optical, gamma-ray, and X-ray phenomena similar to PSR J1023+0038, but which is challenging to study because of its greater distance. Using simultaneous VLA and Chandra observations we find that the radio and X-ray emission are consistent with being anti-correlated in a manner similar to PSR J1023+0038. We discuss how our results help in understanding the origin of bright radio emission from tMSPs. The greater sensitivity of upcoming telescopes like the Square Kilometre Array will be crucial for studying the correlated radio/X-ray phenomena of tMSP systems., Comment: 21 pages, 14 figures, 2 tables. Submitted to MNRAS

This letter proposes a new approach for Inertial Measurement Unit (IMU) preintegration, a fundamental building block that can be leveraged in different optimization-based Inertial Navigation System (INS) localization solutions. Inspired by recent advancements in equivariant theory applied to biased INSs, we derive a discrete-time formulation of the IMU preintegration on $\mathbf{G}(3) \ltimes \mathfrak{g}(3)$, the tangent group of the inhomogeneous Galilean group $\mathbf{G}(3)$. We define a novel preintegration error that geometrically couples the navigation states and the bias leading to lower linearization error. Our method improves in consistency compared to existing preintegration approaches which treat IMU biases as a separate state-space. Extensive validation against state-of-the-art methods, both in simulation and with real-world IMU data, implementation in the Lie++ library, and open-sourcing of the code are provided.

We discuss how the two existing approximate N$^3$LO (aN$^3$LO) sets of parton distributions (PDFs) from the MSHT20 and NNPDF4.0 series can be combined for LHC phenomenology, both in the pure QCD case and for the QCD$\otimes$QED sets that include the photon PDF. Using the resulting combinations, we present predictions for the total inclusive cross-section for Higgs production in gluon fusion, vector boson fusion, and associated production at the LHC Run-3. For the gluon fusion and vector boson fusion channels, the corrections that arise when using correctly matched aN$^3$LO PDFs with N$^3$LO cross section calculations, compared to using NNLO PDFs, are significant, in many cases larger than the PDF uncertainty, and generally larger than the differences between the two aN$^3$LO PDF sets entering the combination. The combined aN$^3$LO PDF sets, MSHT20xNNPDF40_an3lo and MSHT20xNNPDF40_an3lo_qed, are made publicly available in the LHAPDF format and can be readily used for LHC phenomenology., Comment: 22 pages, 11 figures, LHAPDF grids available from https://zenodo.org/records/13843626

We analyze the post-quantum security of succinct interactive arguments constructed from interactive oracle proofs (IOPs) and vector commitment schemes. We prove that an interactive variant of the BCS transformation is secure in the standard model against quantum adversaries when the vector commitment scheme is collapsing. Our proof builds on and extends prior work on the post-quantum security of Kilians succinct interactive argument, which is instead based on probabilistically checkable proofs (PCPs). We introduce a new quantum rewinding strategy that works across any number of rounds. As a consequence of our results, we obtain standard-model post-quantum secure succinct arguments with the best asymptotic complexity known.

The nucleosynthetic isotope signatures of meteorites and the bulk silicate Earth (BSE) indicate that Earth consists of a mixture of "carbonaceous" (CC) and "non-carbonaceous" (NC) materials. We show that the fration of CC material recorded in the isotopic composition of the BSE varies for different elements, and depends on the element's tendency to partition into metal and its volatility. The observed behaviour indicates that the majority of material accreted to the Earth was NC-dominated, but that CC-dominated material enriched in moderately-volatile elements by a factor of ~10 was delivered during the last ~2-10% of Earth's acccretion. The late delivery of CC material to Earth contrasts with dynamical evidence for the early implantation of CC objects into the inner solar system during the growth and migration of the giant planets. This, together with the NC-dominated nature of both Earth's late veneer and bulk Mars, suggests that material scattered inwards had the bulk of its mass concentrated in a few, large CC embryos rather than in smaller planetesimals. We propose that Earth accreted a few of these CC embryos while Mars did not, and that at least one of the CC embryos impacted Earth relatively late (when accretion was 90-90% complete). This scenario is consistent with the subsequent Moon-formign impact of a large NC body, as long as this impact did not re-homogenize the entire Earth's mantle.

We study $\frac{1}{4}$-BPS Wilson loops in four-dimensional SU$(N$) ${\cal N}=2$ super-Yang-Mills theories with conformal matter in an arbitrary representation $\mathcal{R}$. These operators are special examples of loops consisting of two meridians on the two-sphere separated by an arbitrary opening angle. We conjecture an exact expression for the observable based on Pestun's matrix model and show that it perfectly reproduces the perturbative calculations at three loops in the theories under examination and at four loops in special setups characterized by hypermultiplets in the (rank-2) symmetric and antisymmetric representation of the gauge group. Moreover, we show that our conjecture is consistent with the known expression for the Bremsstrahlung function of ${\cal N}=2$ SYM theories. Finally, exploiting the matrix model representation of these Wilson loops, we study the large-$N$ limit at strong coupling of $\mathcal{N}=2$ superconformal QCD, finding a surprising transition in the vacuum expectation value for a critical opening angle., Comment: 32 pages + appendices

A surprising relation between 4d $\mathcal{N}=2$ class $\mathcal{S}$ superconformal field theories of Type-$A$ and 6d $\mathcal{N}=(1,0)$ orbi-instanton theories is investigated. We find that all of the theories in the former class can be obtained by a series of deformations of the 4d theories arising from compactifying the latter on a torus. This is demonstrated by examining Fayet--Iliopoulos (FI) deformations of the $E_8$-shaped magnetic quivers of the orbi-instanton theories whose body fits into the affine $E_8$ Dynkin diagram with a tail attached. Turning on FI parameters at the appropriate gauge groups leads, in stages, to $E_7$-shaped, $E_6$-shaped, and general star-shaped quivers, where the latter are magnetic quivers for the class $\mathcal{S}$ theory of Type-$A$ on a sphere with punctures. Deforming a suitable star-shaped quiver, one obtains a magnetic quiver of the Type-$A$ class $\mathcal{S}$ theory with general genus and an arbitrary number of punctures. Given such a theory, we also propose the inverse algorithm, thereby determining a parent orbi-instanton theory. This is achieved by uplifting the corresponding magnetic quiver step by step to the star-shaped, $E_6$-shaped, $E_7$-shaped, and $E_8$-shaped quivers, where at each step all of the underbalanced nodes, possessing non-zero FI parameters, are dualized. The latter $E_8$-shaped quiver then characterizes the 6d orbi-instanton theory from which the class $\mathcal{S}$ theory in question originates., Comment: 63 pages + appendices

The dynamics of growth and innovation often exhibit sudden, explosive surges, where systems remain quasi stable for extended periods before accelerating dramatically-often surpassing traditional exponential growth. This pattern is evident across various domains, including world population increases and rapid technological advancements. Although these phenomena share common characteristics, they are driven by different underlying mechanisms. In this paper, we introduce a unified framework to capture these phenomenologies through a theory of combinatorial innovation. Inspired by the Theory of the Adjacent Possible, we model growth and innovation as emerging from the recombination processes of existing elements of a system. By formalizing these qualitative ideas, we provide a mathematical structure that explains diverse phenomena, enables cross-system comparisons, and offers grounded predictions for future growth trajectories. Our approach distils the complexity of innovation into a more accessible yet robust framework, paving the way for a deeper and more flexible mathematical understanding of growth and innovation processes., Comment: 10 pages, 3 figures

We prove a characterization of F-rationality in terms of tight closure of products of parameter ideals. Our results are inspired by the theory of complete ideals for surfaces and, in particular, the fundamental results of Lipman-Teissier and Cutkosky characterizing rational surface singularities in terms of products of complete ideals, but are valid also in higher dimensions.

In clinical practice, decision-making relies heavily on established protocols, often formalised as rules. Concurrently, Machine Learning (ML) models, trained on clinical data, aspire to integrate into medical decision-making processes. However, despite the growing number of ML applications, their adoption into clinical practice remains limited. Two critical concerns arise, relevant to the notions of consistency and continuity of care: (a) accuracy - the ML model, albeit more accurate, might introduce errors that would not have occurred by applying the protocol; (b) interpretability - ML models operating as black boxes might make predictions based on relationships that contradict established clinical knowledge. In this context, the literature suggests using ML models integrating domain knowledge for improved accuracy and interpretability. However, there is a lack of appropriate metrics for comparing ML models with clinical rules in addressing these challenges. Accordingly, in this article, we first propose metrics to assess the accuracy of ML models with respect to the established protocol. Secondly, we propose an approach to measure the distance of explanations provided by two rule sets, with the goal of comparing the explanation similarity between clinical rule-based systems and rules extracted from ML models. The approach is validated on the Pima Indians Diabetes dataset by training two neural networks - one exclusively on data, and the other integrating a clinical protocol. Our findings demonstrate that the integrated ML model achieves comparable performance to that of a fully data-driven model while exhibiting superior accuracy relative to the clinical protocol, ensuring enhanced continuity of care. Furthermore, we show that our integrated model provides explanations for predictions that align more closely with the clinical protocol compared to the data-driven model.

The eXTP mission is a major project of the Chinese Academy of Sciences (CAS), with a large involvement of Europe. Its scientific payload includes four instruments: SFA, PFA, LAD and WFM. They offer an unprecedented simultaneous wide-band Xray timing and polarimetry sensitivity. A large European consortium is contributing to the eXTP study, both for the science and the instrumentation. Europe is expected to provide two of the four instruments: LAD and WFM; the LAD is led by Italy and the WFM by Spain. The WFM for eXTP is based on the design originally proposed for the LOFT ESA M3 mission, that underwent a Phase A feasibility study. It will be a wide field of view X-ray monitor instrument working in the 2-50 keV energy range, achieved with large-area Silicon Drift Detectors (SDDs), similar to the ones used for the LAD but with better spatial resolution. The WFM will consist of 3 pairs of coded mask cameras with a total combined field of view (FoV) of 90x180 degrees at zero response and a source localisation accuracy of ~1 arc min. The main goal of the WFM is to provide triggers for the target of opportunity observations of the SFA, PFA and LAD, in order to perform the core science programme, dedicated to the study of matter under extreme conditions of density, gravity and magnetism. In addition, the unprecedented combination of large field of view and imaging capability, down to 2 keV, of the WFM will allow eXTP to make important discoveries of the variable and transient X-ray sky, and provide X-ray coverage of a broad range of astrophysical objects covered under 'observatory science', such as gamma-ray bursts, fast radio bursts, gravitational wave electromagnetic counterparts. In this paper we provide an overview of the WFM instrument, explaining its design, configuration, and anticipated performance., Comment: 15 pages, 13 figures, Proceedings of SPIE 13093, Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray; Proceedings Volume 13093, Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray; 130931Y (2024); doi: 10.1117/12.3020020

We combine new and archival MUSE observations with data from the MeerKAT Fornax Survey and the ALMA Fornax Cluster Survey to study the ionised, atomic, and molecular gas in six gas-rich dwarf galaxies in the Fornax cluster in detail. We compare the distributions and velocity fields of the three gas phases with each other, with MUSE white-light images, and with the stellar velocity fields. Additionally, we derive the resolved molecular Kennicutt-Schmidt relation for each object, and compare these with existing relations for field galaxies and for the Fornax and Virgo clusters. Finally, we explore global measurements such as gas deficiencies and star formation rates to paint as complete a picture of their evolutionary state as possible. We find that all six gas-rich dwarf galaxies have very disturbed ISM, with all three gas phases being irregular both in terms of spatial distribution and velocity field. Most objects lie well below the Kennicutt-Schmidt relations from the literature. Furthermore, they are quite deficient in HI (with def_HI between ~1 and ~2 dex), and moderately deficient in H2 (with def_H2 between ~0 and ~1), suggesting that, while both cold gas phases are affected simultaneously, HI is removed in significant quantities before H2. We suggest that these dwarfs are on their first infall into the cluster, and are in the process of transitioning from star-forming to passive. A combination of tidal interactions, mergers/pre-processing, and ram pressure stripping is likely responsible for these transformations., Comment: Accepted for publication in MNRAS. 34 pages including 14 figures, 2 tables, and 1 appendix

We elaborate further on the one-loop effective action of the IKKT model on 3 + 1 dimensional covariant quantum spacetime in the presence of fuzzy extra dimensions. In particular, we describe the one-loop effective action in terms of a remarkable $SO(1, 9)$ character, which allows to evaluate the pertinent traces over the internal modes explicitly. This also allows to estimate the higher-order contributions (in the internal flux $\mathcal{F}_{\mathtt{IJ}}$) to the one-loop effective action in a systematic way. We show that all higher-order contributions are generally suppressed and UV finite, which justifies the previous treatment of the induced gravitational action. We also obtain explicit expressions for the effective Newton constant, and determine the dynamics of the Kaluza-Klein scale $\Delta_{\mathcal{K}}$ of the fuzzy extra dimensions $\mathcal{K}$., Comment: 2 figures

Identifying procedural errors online from egocentric videos is a critical yet challenging task across various domains, including manufacturing, healthcare, and skill-based training. The nature of such mistakes is inherently open-set, as unforeseen or novel errors may occur, necessitating robust detection systems that do not rely on prior examples of failure. Currently, however, no technique effectively detects open-set procedural mistakes online. We propose a dual branch architecture to address this problem in an online fashion: one branch continuously performs step recognition from the input egocentric video, while the other anticipates future steps based on the recognition module's output. Mistakes are detected as mismatches between the currently recognized action and the action predicted by the anticipation module. The recognition branch takes input frames, predicts the current action, and aggregates frame-level results into action tokens. The anticipation branch, specifically, leverages the solid pattern-matching capabilities of Large Language Models (LLMs) to predict action tokens based on previously predicted ones. Given the online nature of the task, we also thoroughly benchmark the difficulties associated with per-frame evaluations, particularly the need for accurate and timely predictions in dynamic online scenarios. Extensive experiments on two procedural datasets demonstrate the challenges and opportunities of leveraging a dual-branch architecture for mistake detection, showcasing the effectiveness of our proposed approach. In a thorough evaluation including recognition and anticipation variants and state-of-the-art models, our method reveals its robustness and effectiveness in online applications.

Stars have been recognized as optimal laboratories to probe axion properties. In the last decades there have been significant advances in this field due to a better modelling of stellar systems and accurate observational data. In this work we review the current status of constraints on axions from stellar physics. We focus in particular on the Sun, globular cluster stars, white dwarfs and (proto)-neutron stars., Comment: 127 pages, 59 figures, 9 tables. Prepared for the submission to Physics Reports. Comments are welcome!

Leveraging recent advancements in machine learning-based flavor tagging, we develop an optimal analysis for measuring the hadronic cross-section ratios $R_b$, $R_c$, and $R_s$ at the FCC-ee during its $WW$, $Zh$, and $t\bar{t}$ runs. Our results indicate up to a two-order-of-magnitude improvement in precision, providing an unprecedented test of the SM. Using these observables, along with $R_\ell$ and $R_t$, we project sensitivity to flavor non-universal four-fermion (4F) interactions within the SMEFT, contributing both at the tree level and through the renormalization group (RG). We highlight a subtle complementarity with RG-induced effects at the FCC-ee's $Z$-pole. Our analysis demonstrates significant improvements over the current LEP-II and LHC bounds in probing flavor-conserving 4F operators involving heavy quark flavors and all lepton flavors. As an application, we explore simplified models addressing current $B$-meson anomalies, demonstrating that FCC-ee can effectively probe the relevant parameter space. Finally, we design optimized search strategies for quark flavor-violating 4F interactions., Comment: 16 pages + appendices, 5 figures, 11 tables. v2: minor corrections, added plot for W,Y projections

Matrix-vector multiplications (MVMs) are essential for a wide range of applications, particularly in modern machine learning and quantum computing. In photonics, there is growing interest in developing architectures capable of performing linear operations with high speed, low latency, and minimal loss. Traditional interferometric photonic architectures, such as the Clements design, have been extensively used for MVM operations. However, as these architectures scale, improving stability and robustness becomes critical. In this paper, we introduce a novel photonic braid interferometer architecture that outperforms both the Clements and Fldzhyan designs in these aspects. Using numerical simulations, we evaluate the performance of these architectures under ideal conditions and systematically introduce non-idealities such as insertion losses, beam splitter imbalances, and crosstalk. The results demonstrate that the braid architecture offers superior robustness due to its symmetrical design and reduced layer count. Further analysis shows that the braid architecture is particularly advantageous in large-scale implementations, delivering better performance as the size of the interferometer increases. We also assess the footprint and total insertion losses of each architecture. Although waveguide crossings in the braid architecture slightly increase the footprint and insertion loss, recent advances in crossing technology significantly minimize these effects. Our study suggests that the braid architecture is a robust solution for photonic neuromorphic computing, maintaining high fidelity in realistic conditions where imperfections are inevitable.

General state-space models (SSMs) are widely used in statistical machine learning and are among the most classical generative models for sequential time-series data. SSMs, comprising latent Markovian states, can be subjected to variational inference (VI), but standard VI methods like the importance-weighted autoencoder (IWAE) lack functionality for streaming data. To enable online VI in SSMs when the observations are received in real time, we propose maximising an IWAE-type variational lower bound on the asymptotic contrast function, rather than the standard IWAE ELBO, using stochastic approximation. Unlike the recursive maximum likelihood method, which directly maximises the asymptotic contrast, our approach, called online sequential IWAE (OSIWAE), allows for online learning of both model parameters and a Markovian recognition model for inferring latent states. By approximating filter state posteriors and their derivatives using sequential Monte Carlo (SMC) methods, we create a particle-based framework for online VI in SSMs. This approach is more theoretically well-founded than recently proposed online variational SMC methods. We provide rigorous theoretical results on the learning objective and a numerical study demonstrating the method's efficiency in learning model parameters and particle proposal kernels.

The use of data-driven techniques for tactile data processing and classification has recently increased. However, collecting tactile data is a time-expensive and sensor-specific procedure. Indeed, due to the lack of hardware standards in tactile sensing, data is required to be collected for each different sensor. This paper considers the problem of learning the mapping between two tactile sensor outputs with respect to the same physical stimulus -- we refer to this problem as touch-to-touch translation. In this respect, we proposed two data-driven approaches to address this task and we compared their performance. The first one exploits a generative model developed for image-to-image translation and adapted for this context. The second one uses a ResNet model trained to perform a regression task. We validated both methods using two completely different tactile sensors -- a camera-based, Digit and a capacitance-based, CySkin. In particular, we used Digit images to generate the corresponding CySkin data. We trained the models on a set of tactile features that can be found in common larger objects and we performed the testing on a previously unseen set of data. Experimental results show the possibility of translating Digit images into the CySkin output by preserving the contact shape and with an error of 15.18% in the magnitude of the sensor responses., Comment: This paper was initially submitted at the International Conference on Intelligent Robots and Systems (IROS) 2023

In this work, we present a numerical model specifically designed for 3D multilayer devices, with a focus on nanobridge junctions and coplanar waveguides. Unlike existing numerical models, ours does not approximate the physical layout or limit the number of constituent materials, providing a more accurate and flexible design tool. We calculate critical currents, current phase relationships, and the energy gap where relevant. We validate our model by comparing it with published data. Through our analysis, we found that using multilayer films significantly enhances control over these quantities. For nanobridge junctions in particular, multilayer structures improve qubit anharmonicity compared to monolayer junctions, offering a substantial advantage for qubit performance. For coated multilayer microwave circuits it allows for better studies of the proximity effect, including their effective kinetic inductance.