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The CALICE technological RPC-based SDHCAL prototype that fullfils all the requirements of compactness, hermeticity and power budget of the future lepton accelerator experiments, has been extensively tested and has provided excellent results in terms of the energy resolution and shower separation. A new phase of R&D to validate completely the SDHCAL option for the International Linear Detector (ILD) project of the ILC and also the Circular Electron Positron Collider (CEPC and FCCee) has started with the conception and the realization of new prototypes. The new prototype proposes to exploit the excellent time resolution that can be provided by multi-gap resistive plate chamber detectors in order to better build the hadronic showers with the aim to separate close-by ones and also to single out the contribution of delayed neutrons with the purpose to improve on the Particle Flow Algorithm performances and better reconstruct the showers energy. A new technique to build multi-gap resistive plate chambers has been developed and first results confirm the excellent efficiency of the new detectors. The timing performance is under study using the PETIROC ASIC developed by the OMEGA group. The progress realized on the different aspects of the new concept will be presented and the future steps will be discussed., Comment: 13 pages, 6 figures, Proceedings of the XVII Conference on Resistive Plate Chambers and Related Detectors, 9-13 Sept. 2024, Santiago de Compostela, Spain

We present and release MIDI-GPT, a generative system based on the Transformer architecture that is designed for computer-assisted music composition workflows. MIDI-GPT supports the infilling of musical material at the track and bar level, and can condition generation on attributes including: instrument type, musical style, note density, polyphony level, and note duration. In order to integrate these features, we employ an alternative representation for musical material, creating a time-ordered sequence of musical events for each track and concatenating several tracks into a single sequence, rather than using a single time-ordered sequence where the musical events corresponding to different tracks are interleaved. We also propose a variation of our representation allowing for expressiveness. We present experimental results that demonstrate that MIDI-GPT is able to consistently avoid duplicating the musical material it was trained on, generate music that is stylistically similar to the training dataset, and that attribute controls allow enforcing various constraints on the generated material. We also outline several real-world applications of MIDI-GPT, including collaborations with industry partners that explore the integration and evaluation of MIDI-GPT into commercial products, as well as several artistic works produced using it., Comment: AAAI 25

Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces. We introduce MACAT and MACataRT, two distinct musical agent systems crafted to enhance interactive music-making between human musicians and AI. MACAT is optimized for agent-led performance, employing real-time synthesis and self-listening to shape its output autonomously, while MACataRT provides a flexible environment for collaborative improvisation through audio mosaicing and sequence-based learning. Both systems emphasize training on personalized, small datasets, fostering ethical and transparent AI engagement that respects artistic integrity. This research highlights how interactive, artist-centred generative AI can expand creative possibilities, empowering musicians to explore new forms of artistic expression in real-time, performance-driven and music improvisation contexts., Comment: In Proceedings of the Creativity and Generative AI NIPS (Neural Information Processing Systems) Workshop 2024

This study explores the applications of the Prouhet-Thue-Morse (PTM) sequence in quantum computing, highlighting its mathematical elegance and practical relevance. We demonstrate the critical role of the PTM sequence in quantum error correction, in noise-resistant quantum memories, and in providing insights into quantum chaos. Notably, we demonstrate how the PTM sequence naturally appears in Ising X-X interacting systems, leading to a proposed robust encoding of quantum memories in such systems. Furthermore, connections to number theory, including the Riemann zeta function, bridge quantum computing with pure mathematics. Our findings emphasize the PTM sequence's importance in understanding the mathematical structure of quantum computing systems and the development of the full potential of quantum technologies and invite further interdisciplinary research.

Knit fabrics are mechanically durable and tough while sufficiently flexible to conform to curved substrates such as the human body. Recent advancements in industrial knitting enable unprecedented control over the pattern design and functionality of next generation knit fabrics. However, the ability to leverage this granular control to predict and tune the mechanical behavior of these fabrics remains limited due to their complex hierarchical and entangled microstructure. This study establishes a comprehensive experimental and numerical framework to characterize and model the mechanical properties of industrial knitted fabrics. By integrating precise experiments, finite element modeling, and a strain energy-based homogenization approach, we provide an accurate demonstration of how stitch length, pattern, and yarn material govern the anisotropic mechanical response of knitted fabrics. In doing so, we establish clear quantitative links between these parameters and key material properties, including stiffness and anisotropy, that emerge directly from our energy-based model. Recognizing that industrial knitting systems can produce fabrics with spatially varying parameters, we extend our framework to predict heterogeneous knits. We show that material transitions have minimal impact on the fabric's overall mechanical response, so heterogeneous fabrics can be modeled with our framework as patchworks of homogeneous samples. We design the first industrially knit sleeve explicitly optimized for both fit and function, using heterogeneous patterns that conform to target arm musculature and ensure uniform stress distribution. This work bridges the gap between computational modeling and scalable manufacturing, unlocking new possibilities for wearable devices, assistive textiles, and functional applications.

HI-rich absorbers seen within quasar spectra contain the bulk of neutral gas in the Universe. However, the spatial extent of these reservoirs are not extensively studied due to the pencil beam nature of quasar sightlines. Using two giant gravitational arc fields (at redshifts 1.17 and 2.06) as 2D background sources with known strong MgII absorption observed with the MUSE integral field spectrograph (IFS), we investigated whether spatially mapped MgII absorption can predict the presence of strong HI systems, and determine both the physical extent and HI mass of the two absorbing systems. We created a simple model of an ensemble of gas clouds in order to simultaneously predict the HI column density and gas covering fraction of HI-rich absorbers based on observations of the MgII rest-frame equivalent width in IFS spaxels. We first test the model on the field with HI observations already available from the literature, finding that we can recover HI column densities consistent with the previous estimates (although with large uncertainties). We then use our framework to simultaneously predict the gas covering fraction, HI column density and total HI mass ($M_{\rm{HI}}$) for both fields. We find that both of the observed strong systems have a covering fraction of $\approx70$% and are likely damped Lyman $\alpha$ systems (DLAs) with $M_{\rm{HI}}>10^9\ M_{\odot}$. Our model shows that the typical MgII metrics used in the literature to identify the presence of DLAs are sensitive to the gas covering fraction. However, these MgII metrics are still sensitive to strong HI, and can be still applied to absorbers towards gravitational arcs or other spatially extended background sources. Based on our results, we speculate that the two strong absorbers are likely representative of a neutral inner circumgalactic medium and are a significant reservoir of fuel for star formation within the host galaxies., Comment: 15 pages, 6 Figures, 3 appendices. Accepted for publication on Astronomy & Astrophysics

We aim to constrain the average star formation associated with neutral hydrogen gas reservoirs at cosmic noon. Using a unprecedented sample of 1716 high column density Damped Ly-$\alpha$ absorbers (DLAs) from the Sloan Digital Sky Survey with log($N$(HI) / cm$^{-2}$) $\ge$21, we generated the average Ly-$\alpha$ emission spectrum associated to DLAs, free from emission from the background quasar. We measured Ly$\alpha$ emission at $> 5.8\sigma$ level with luminosity $8.95\pm 1.54 \times \rm 10^{40}\ \text{erg}\ \text{s}^{-1}$ (corresponding to about 0.02 L$^{\star}$ at $z \sim$ 2-3) in systems with average log($N$(HI)/ $cm^{-2}$) $\approx$21.2 and at median redshift of $z \sim$ 2.64. The peak of the Ly$\alpha$ emission is apparently redshifted by $\sim$300 km s$^{-1}$ relative to the absorption redshift, which is seemingly due to suppression of blue Ly-$\alpha$ photons by radiative transfer through expanding gas. We infer that DLAs form stars with an average rate of (0.08 $\pm$ 0.01)/$\text{f}_\text{esc}\ \rm \text{M}_{\odot}\ \text{yr}^{-1}$, i.e, $\approx (0.54\pm 0.09)\rm \text{M}_{\odot}\ \text{yr}^{-1}$ for a typical escape fraction, $\text{f}_{\text{esc}} =0.15$, of Lyman-$\alpha$ emitting galaxies. DLA galaxies follows the star formation main sequence of star-forming galaxies at high redshift, suggesting that the DLA population is dominated by the lower mass end of Lyman-$\alpha$ emitting galaxies., Comment: 5 pages, 3 figures, accepted for publication in A&A (Letters)

We introduce classical many-body dynamics on a one-dimensional lattice comprising local two-body maps arranged on discrete space-time mesh that serve as discretizations of Hamiltonian dynamics with arbitrarily time-varying coupling constants. Time evolution is generated by passing an auxiliary degree of freedom along the lattice, resulting in a `fishnet' circuit structure. We construct integrable circuits consisting of Yang-Baxter maps and demonstrate their general properties, using the Toda and anisotropic Landau-Lifschitz models as examples. Upon stochastically rescaling time, the dynamics is dominated by fluctuations and we observe solitons undergoing Brownian motion.

Textile pneumatic actuators can provide useful wearable haptic feedback when embedded in gloves, armbands, and other smart garments. Here we investigate actuators fabricated from thermoplastic coated textiles. We measure the effects of fabrication parameters on the robustness and airtightness of small, round pneumatic pouch actuators made from heat-sealed thermoplastic polyurethane-coated nylon. We determine the optimal temperature, time, and pressure for heat-pressing of the textile to create strong bonds and identify the most effective glue to create an airtight seal at the inlet. Compared to elastomeric pneumatic actuators, these textile pneumatic actuators reduce the thickness of the actuator by 96.4% and the mass by 57.2%, increasing their wearability while maintaining a strong force output. We evaluated the force output of the actuators, along with their performance over time. In a blocked force test, the maximum force transmission of the pneumatic textile actuators was 36.1N, which is 95.3% of the peak force output of an elastomeric pneumatic actuator with the same diameter and pressure. Cyclical testing showed that the textile actuators had more stable behavior over time. These results provide best practices for fabrication and indicate the feasibility of textile pneumatic actuators for future wearable applications.

In this study, we propose a novel approach to uncover subgroup-specific and subgroup-common latent factors addressing the challenges posed by the heterogeneity of neurological and mental disorders, which hinder disease understanding, treatment development, and outcome prediction. The proposed approach, sparse Group Factor Analysis (GFA) with regularised horseshoe priors, was implemented with probabilistic programming and can uncover associations (or latent factors) among multiple data modalities differentially expressed in sample subgroups. Synthetic data experiments showed the robustness of our sparse GFA by correctly inferring latent factors and model parameters. When applied to the Genetic Frontotemporal Dementia Initiative (GENFI) dataset, which comprises patients with frontotemporal dementia (FTD) with genetically defined subgroups, the sparse GFA identified latent disease factors differentially expressed across the subgroups, distinguishing between "subgroup-specific" latent factors within homogeneous groups and "subgroup common" latent factors shared across subgroups. The latent disease factors captured associations between brain structure and non-imaging variables (i.e., questionnaires assessing behaviour and disease severity) across the different genetic subgroups, offering insights into disease profiles. Importantly, two latent factors were more pronounced in the two more homogeneous FTD patient subgroups (progranulin (GRN) and microtubule-associated protein tau (MAPT) mutation), showcasing the method's ability to reveal subgroup-specific characteristics. These findings underscore the potential of sparse GFA for integrating multiple data modalities and identifying interpretable latent disease factors that can improve the characterization and stratification of patients with neurological and mental health disorders., Comment: 38 pages, 14 figures

Given a family of rotationally symmetric compact manifolds indexed by the dimension and a weight function, the goal of this paper is to investigate the cut-off phenomenon for the Brownian motions on this family. We provide a class of compact manifolds with non-negative Ricci curvatures for which the cut-off in separation with windows occurs, in high dimension, with different explicit mixing times. We also produce counter-examples, still with non-negative Ricci curvatures, where there are no cut-off in separation. In fact we show a phase transition for the cut-off phenomenon concerning the Brownian motions on a rotationally symmetric compact manifolds. Our proof is based on a previous construction of a sharp strong stationary times by the authors, and some quantitative estimates on the two first moments of the covering time of the dual process. The concentration of measure phenomenon for the above family of manifolds appears to be relevant for the study of the corresponding cut-off.

The eBPF framework enables execution of user-provided code in the Linux kernel. In the last few years, a large ecosystem of cloud services has leveraged eBPF to enhance container security, system observability, and network management. Meanwhile, incessant discoveries of memory safety vulnerabilities have left the systems community with no choice but to disallow unprivileged eBPF programs, which unfortunately limits eBPF use to only privileged users. To improve run-time safety of the framework, we introduce SafeBPF, a general design that isolates eBPF programs from the rest of the kernel to prevent memory safety vulnerabilities from being exploited. We present a pure software implementation using a Software-based Fault Isolation (SFI) approach and a hardware-assisted implementation that leverages ARM's Memory Tagging Extension (MTE). We show that SafeBPF incurs up to 4% overhead on macrobenchmarks while achieving desired security properties., Comment: 15 pages, 9 figures

Malaria remains a significant global health challenge, necessitating rapid and accurate diagnostic methods. While computer-aided diagnosis (CAD) tools utilizing deep learning have shown promise, their generalization to diverse clinical settings remains poorly assessed. This study evaluates the generalization capabilities of a CAD model for malaria diagnosis from thin blood smear images across four sites. We explore strategies to enhance generalization, including fine-tuning and incremental learning. Our results demonstrate that incorporating site-specific data significantly improves model performance, paving the way for broader clinical application., Comment: MICCAI 2024 AMAI Workshop, Accepted for presentation, Submitted Manuscript Version, 10 pages

High-dimensional quantum computing has generated significant interest due to its potential to address scalability and error correction challenges faced by traditional qubit-based systems. This paper investigates the Average Gate Fidelity (AGF) of single qudit systems under Markovian noise in the Lindblad formalism, extending previous work by developing a comprehensive theoretical framework for the calculation of higher-order correction terms. We derive general expressions for the perturbative expansion of the Average Gate Infidelity (AGI) in terms of the environmental coupling coefficient and validate these with extensive numerical simulations, emphasizing the transition from linear to nonlinear behaviour in the strong coupling regime. Our findings highlight the dependence of AGI on qudit dimensionality, quantum gate choice, and noise strength, providing critical insights for optimising quantum gate design and error correction protocols. Additionally, we utilise our framework to identify universal bounds for the AGI in the strong coupling regime and explore the practical implications for enhancing the performance of near-term qudit architectures. This study offers a robust foundation for future research and development in high-dimensional quantum computing, contributing to the advancement of robust, high-fidelity quantum operations.

Scanning Tunneling Spectroscopy (STS) is a unique technique to probe the local density of states (LDOS) at the atomic scale by measuring the tunneling conductance between a sharp tip and a sample surface. However, the technique suffers of well-known limitations, the so-called set-point effect, which can potentially introduce artifacts in the measurements. We compare several STS imaging schemes applied to the LDOS modulations of the charge density wave state on atomically flat surfaces, and demonstrate that only constant-height STS is capable of mapping the intrinsic LDOS. In the constant-current STS, commonly used and easier-to-implement, the tip-sample distance variations imposed by the feedback loop result in set-point-dependent STS images and possibly mislead the identification of the CDW gap edges., Comment: 7 pages, 6 figures

In this paper, we map out the landscape of options available to visual artists for creating personal artworks, including crafting, adapting and navigating deep generative models. Following that, we argue for revisiting model crafting, defined as the design and manipulation of generative models for creative goals, and motivate studying and designing for model crafting as a creative activity in its own right., Comment: Accepted to CHI 2024 workshop on Generative AI and HCI

Monolithic operating systems, where all kernel functionality resides in a single, shared address space, are the foundation of most mainstream computer systems. However, a single flaw, even in a non-essential part of the kernel (e.g., device drivers), can cause the entire operating system to fall under an attacker's control. Kernel hardening techniques might prevent certain types of vulnerabilities, but they fail to address a fundamental weakness: the lack of intra-kernel security that safely isolates different parts of the kernel. We survey kernel compartmentalization techniques that define and enforce intra-kernel boundaries and propose a taxonomy that allows the community to compare and discuss future work. We also identify factors that complicate comparisons among compartmentalized systems, suggest new ways to compare future approaches with existing work meaningfully, and discuss emerging research directions., Comment: 24 pages, 7 figures

This chapter investigates the complexities surrounding the iron biogeochemical cycle from the Archean to present, with a focus on assessing the balance between iron sources and sinks during long periods of Earth's history with relatively invariable redox conditions, when steady state can be safely assumed. Currently, the residence time of iron in the ocean may be as short as approximately 5 years. The input flux of iron is highly sensitive to redox cycling in sediments, while its removal primarily occurs through dispersed processes of oxidation and precipitation. In the Archean, we find a significant imbalance between continental and hydrothermal inputs, which collectively contribute between 61,500 to 263,000 Gg/yr of dissolved iron to the oceans, and the most obvious sinks such as iron formations (IFs), which sequester up to ~43,000 Gg/yr of iron. A possible solution to this imbalance involves the dispersed abiotic precipitation and removal of iron as silicates, sulfides, and carbonates in marine basins. Additionally, we calculate the residence time of dissolved iron in the Archean oceans to be between 6 kyr and 3 Myr, which is significantly longer than the ocean mixing timescale. Our estimates indicate that under the anoxic Archean atmosphere, the iron cycle was more protracted than today, and the isotopic compositions and concentrations of dissolved iron were likely more uniform. Distinct water bodies were likely confined to limited areas or specific, dynamic systems with intense iron turnover, such as regions where deep-sea upwelling currents brought hydrothermal iron to photic zones rich in biotic or abiotic oxidants., Comment: In press, Treatise on Geochemistry, 3rd Edition. 23954 words, 18 figures, 3 tables

High-resolution absorption spectroscopy toward bright background sources has had a paramount role in understanding early galaxy formation, the evolution of the intergalactic medium and the reionisation of the Universe. However, these studies are now approaching the boundaries of what can be achieved at ground-based 8-10m class telescopes. The identification of primeval systems at the highest redshifts, within the reionisation epoch and even into the dark ages, and of the products of the first generation of stars and the chemical enrichment of the early Universe, requires observing very faint targets with a signal-to-noise ratio high enough to detect very faint spectral signatures. In this paper, we describe the giant leap forward that will be enabled by ANDES, the high-resolution spectrograph for the ELT, in these key science fields, together with a brief, non-exhaustive overview of other extragalactic research topics that will be pursued by this instrument, and its synergistic use with other facilities that will become available in the early 2030s., Comment: Accepted for publication in Experimental Astronomy. Version updated to match the published one

The evolution of the cosmic dust content and the cycle between metals and dust in the interstellar medium (ISM) play a fundamental role in galaxy evolution. The chemical enrichment of the Universe can be traced through the evolution of the dust-to-metals ratio (DTM) and the dust-to-gas ratio (DTG) with metallicity. We use a novel method to determine mass estimates of the DTM, DTG and dust composition based on our previous measurements of the depletion of metals in different environments (the Milky Way, the Magellanic Clouds, and damped Lyman-$\alpha$ absorbers, DLAs, toward quasars and towards gamma-ray bursts, GRBs), which were calculated from the relative abundances of metals in the ISM through absorption-line spectroscopy column densities observed mainly from VLT/UVES and X-shooter, and HST/STIS. We derive the dust extinction from the estimated dust depletion ($A_{V, \rm depl}$) and compare with the $A_{V}$ from extinction. We find that the DTM and DTG ratios increase with metallicity and with the dust tracer [Zn/Fe]. This suggests that grain growth in the ISM is a dominant process of dust production. The increasing trend of the DTM and DTG with metallicity is in good agreement with a dust production and evolution model. Our data suggest that the stellar dust yield is much lower than the metal yield and thus that the overall amount of dust in the warm neutral medium that is produced by stars is much lower. We find that $A_{V,\rm depl}$ is overall lower than $A_{V, \rm ext}$ for the Milky Way and a few Magellanic Clouds lines of sight, a discrepancy that is likely related to the presence of carbonaceous dust. We show that the main elements that contribute to the dust composition are, O, Fe, Si, Mg, C, S, Ni and Al for all the environments. Abundances at low dust regimes suggest the presence of pyroxene and metallic iron in dust., Comment: Accepted for publication in A&A. Abstract abridged

The PAW method has been used to compute the iron L$_{2,3}$ edges of x-ray absorption spectra (XAS) and x-ray magnetic circular dichroism (XMCD) of the spin-crossover Fe(phen)$_{2}$(NCS)$_{2}$ molecule when adsorbed on Cu(001) surface and in the gas phase, for both the high spin (HS) and low spin (LS) states. It is found that the calculated XAS and XMCD with the static core hole or the Slater transition state half hole are in less good agreement with experiment than those using the so called initial state. This disagreement is due to the reduction of the iron spin magnetic moment caused by the static screening of the core hole by the photo-electron. The L$_{2,3}$ XAS formula is found to be directly related to the unoccupied $3d$ density of states (DOS), and hence the symmetry broken $e_g$ and the $t_{2g}$ iron DOS are used to explain the XAS and XMCD results. It is demonstrated that the dependence of the HS XMCD on the direction of incident x-ray circularly polarized light with respect to the magnetization direction can be used to determine the iron octahedron deformation, while the XMCD for various magnetization directions is directly related to the anisotropy of the orbital magnetic moment and the magneto-crystalline energy. It is also shown that the magnetic dipole moment $T_z$ is very large due to the strong distortion of the iron octahedron and is necessary for an accurate determination of the sum rule computed spin magnetic moment., Comment: 39 pages, 5 figures

The applicability of DFT+$U$ to the star-of-David phase of $1T$-TaS$_2$ is examined. The viability of a Mott phase as a ground state for the bulk of this material is briefly discussed in light of the available experimental evidence.

Provenance graphs are structured audit logs that describe the history of a system's execution. Recent studies have explored a variety of techniques to analyze provenance graphs for automated host intrusion detection, focusing particularly on advanced persistent threats. Sifting through their design documents, we identify four common dimensions that drive the development of provenance-based intrusion detection systems (PIDSes): scope (can PIDSes detect modern attacks that infiltrate across application boundaries?), attack agnosticity (can PIDSes detect novel attacks without a priori knowledge of attack characteristics?), timeliness (can PIDSes efficiently monitor host systems as they run?), and attack reconstruction (can PIDSes distill attack activity from large provenance graphs so that sysadmins can easily understand and quickly respond to system intrusion?). We present KAIROS, the first PIDS that simultaneously satisfies the desiderata in all four dimensions, whereas existing approaches sacrifice at least one and struggle to achieve comparable detection performance. Kairos leverages a novel graph neural network-based encoder-decoder architecture that learns the temporal evolution of a provenance graph's structural changes to quantify the degree of anomalousness for each system event. Then, based on this fine-grained information, Kairos reconstructs attack footprints, generating compact summary graphs that accurately describe malicious activity over a stream of system audit logs. Using state-of-the-art benchmark datasets, we demonstrate that Kairos outperforms previous approaches., Comment: 24 pages, 16 figures, to appear in the 45th IEEE Symposium on Security and Privacy (S&P'24)

For safety reasons, unprivileged users today have only limited ways to customize the kernel through the extended Berkeley Packet Filter (eBPF). This is unfortunate, especially since the eBPF framework itself has seen an increase in scope over the years. We propose SandBPF, a software-based kernel isolation technique that dynamically sandboxes eBPF programs to allow unprivileged users to safely extend the kernel, unleashing eBPF's full potential. Our early proof-of-concept shows that SandBPF can effectively prevent exploits missed by eBPF's native safety mechanism (i.e., static verification) while incurring 0%-10% overhead on web server benchmarks., Comment: 8 pages, 5 figures, to appear in the 1st SIGCOMM Workshop on eBPF and Kernel Extensions