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DOE OSTI2023

Elsa: enhanced latent spaces for improved collider simulations

Abstract Simulations play a key role for inference in collider physics. We explore various approaches for enhancing the precision of simulations using machine learning, including interventions at the end of the simulation chain (reweighting), at the beginning of the simulation chain (pre-processing), and connections between the end and beginning (latent space refinement). To clearly illustrate our approaches, we use W + jets matrix element surrogate simulations based on normalizing flows as a prototypical example. First, weights in the data space are derived using machine learning classifiers. Then, we pull back the data-space weights to the latent space to produce unweighted examples and employ the Latent Space Refinement ( Laser ) protocol using Hamiltonian Monte Carlo. An alternative approach is an augmented normalizing flow, which allows for different dimensions in the latent and target spaces. These methods are studied for various pre-processing strategies, including a new and general method for massive particles at hadron colliders that is a tweak on the widely-used RamboOnDiet mapping. We find that modified simulations can achieve sub-percent precision across a wide range of phase space.

Nachman, Benjamin (ORCID:0000000310240932)↗

DOE OSTI2026

Direct and rapid uranium isotopic analysis of environmental sample swipes via microextraction – LS-APGD/Orbitrap mass spectrometry

Accurate and precise isotopic analysis of actinides collected on environmental sample swipes from within nuclear facilities is an important safeguarding measure for detecting undeclared materials and activities. Traditional isotope ratio (IR) analysis of actinides using a bulk digestion approach can be laborious and time-consuming. Recently, direct analysis of environmental swipe samples using a microextraction approach has been explored as an alternative to conventional bulk digestion methods. The present study further evaluates this approach for accurate and precise isotopic analysis of uranium (U) in cotton swipe samples using the liquid sampling-atmospheric pressure glow discharge (LS-APGD)/Orbitrap-FTMS Booster detection system. The instrumental parameters were optimized, and quantitative capabilities were demonstrated through excellent linearity (R2 = 0.99) across a deposited mass range of 1 to 500 ng, with a limit of detection of 90 pg (in a 2 × 4 mm region) for total U; well below typical U concentrations (ng–mg range) in environmental sample swipes. The 235U/238U ratio showed excellent accuracy (−0.3% relative difference from the certificate value), with ∼20× improvement over previous microextraction-Orbitrap methods. Precision (∼1% relative standard deviation) was also greatly enhanced by ∼5×. This study also demonstrates that figures of merit achieved with neat U solution were not highly degraded when various external interfering elements/matrices were introduced. Finally, the developed method was successfully applied to analyze practical swipe samples representative of laboratory and outdoor environments. The presented figures of merit and applicability to practical samples further validate the capability of the platform for rapid analysis (<7 minutes) of environmental swipe samples.

Shrestha, Suraj [Clemson University, SC]↗

DOE OSTI2020

Autonomous Selective Parts-Based Tracking

Object tracking from videos is still a challenging task due to various changes throughout a video sequence including occlusions, motion blur, scale and other deformation changes. In this paper, we propose a selective parts-based approach, using correlation filters, that makes choices based on a consensus of the parts and global tracking. Moreover, we further enhance our parts-based approach by introducing a segmentation-assisted parts initialization. In addition, we present a genetic algorithm-based method to autonomously select various parameters of the tracking algorithm, as opposed to the common practice of manually tuning those parameters. In contrast to existing part-based methods, the proposed method does not dilute accurate tracking by averaging results over multiple parts at every frame. Instead, we take a selective approach based on the relative weight of the responses across parts. Moreover, we only make location corrections when a part diverges, and rely on these location corrections to maintain an accurate appearance model. In the case of occlusions, which are among the main reasons for using a parts-based approach, our proposed approach consistently achieves the best performance. It is due to the ability to handle occlusion and not dilute decisions with incorrect parts, that our proposed approach enables state-of-the-art performance. The approach we propose was evaluated on videos from three different challenging benchmark datasets. Our approach has resulted in better overall precision and success rates for three different base tracking approaches.

42 ENGINEERING↗

DOE OSTI2024

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Leon, Sami↗

DOE OSTI2020

Quantum Monte Carlo Methods for Astrophysical Applications

In recent years, new astrophysical observations have provided a wealth of exciting input for nuclear physics. For example, the observations of two-solar-mass neutron stars put strong constraints on possible phase transitions to exotic phases in strongly interacting matter at high densities. Furthermore, the recent observation of a neutron-star merger in both the electromagnetic spectrum and gravitational waves has provided compelling evidence that neutron-star mergers are an important site for the production of extremely neutron-rich nuclei within the r-process. In the coming years, an abundance of new observations is expected, which will continue to provide crucial constraints on the nuclear physics of these events. To reliably analyze such astrophysical observations and extract information on nuclear physics, it is very important that a consistent approach to nuclear systems is used. Such an approach consists of a precise and accurate method to solve the nuclear many-body problem in nuclei and nuclear matter, combined with modern nuclear Hamiltonians that allow to estimate the theoretical uncertainties. Quantum Monte Carlo methods are ideally suited for such an approach and have been successfully used to describe atomic nuclei and nuclear matter. In this contribution, I will present a detailed description of Quantum Monte Carlo methods focusing on the application of these methods to astrophysical problems. In particular, I will discuss how to use Quantum Monte Carlo methods to describe nuclear matter of relevance to the physics of neutron stars.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2019

High-Resolution, Lightweight, and Low-cost X-Ray Optics for the Lynx Observatory

We describe an approach to build an x-ray mirror assembly that can meet Lynx’s requirements of high-angular resolution, large effective area, light weight, short production schedule, and low-production cost. Adopting a modular hierarchy, the assembly is composed of 37,492 mirror segments, each of which measures ∼100 mm × 100 mm × 0.5 mm. These segments are integrated into 611 modules, which are individually tested and qualified to meet both science performance and spaceflight environment requirements before they in turn are integrated into 12 metashells. The 12 metashells are then integrated to form the mirror assembly. This approach combines the latest precision polishing technology and the monocrystalline silicon material to fabricate the thin and lightweight mirror segments. Because of the use of commercially available equipment and material and because of its highly modular and hierarchical building-up process, this approach is highly amenable to automation and mass production to maximize production throughput and to minimize production schedule and cost. As of fall 2018, the basic elements of this approach, including substrate fabrication, coating, alignment, and bonding, have been validated by the successful building and testing of single-pair mirror modules. In the next few years, the many steps of the approach will be refined and perfected by repeatedly building and testing mirror modules containing progressively more mirror segments to fully meet science performance, spaceflight environments, as well as programmatic requirements of the Lynx mission and other proposed missions, such as AXIS.

Zhang, William W.↗

NASA NTRS2018

The OpenSE Cookbook: A Practical, Recipe Based Collection of Patterns, Procedures, and Best Practices for Executable Systems Engineering for the Thirty Meter Telescope

The OpenSE Cookbook is an open-sourced collection of patterns, procedures, and best practices targeted for systems engineers who seek guidance on applying model-based and executable systems engineering (MBSE) using SysML. Its content has emerged from the system level modeling effort on the European Framework Program 6 (FP6) and the Thirty Meter Telescope (TMT). The TMT MBSE approach applied the Executable Systems Engineering Method (ESEM) and the open-source Engineering Environment (OpenMBEE) to specify, analyze, and verify requirements of TMT’s Alignment and Phasing System (APS) and the Narrow Field Infrared Adaptive Optics System (NFIRAOS). In these applications, implicit dependencies are made explicit in a formal model through the use of ESEM, OpenMBEE, and SysML modeling constructs. The value proposition for applying this MBSE approach was to establish precise requirements and fine-grained traceability to system designs, and to verify key requirements beginning early in development. The integration of ESEM and the OpenMBEE tooling infrastructure (providing linked-data and web-operability) is a significant added value for the MBSE approach. The APS is responsible for the overall pre-adaptive optics wavefront quality, using starlight to measure wavefront errors and align the TMT optics. In the formally integrated and executable SysML model, simulations are performed to analyze the impact of changed requirements and verify specified constraints for various operational scenarios. The APS team used several modeling patterns to capture information such as the requirements, the operational scenarios, involved subsystems and their interaction points, the estimated or required time durations, and the mass and power consumption. Adaptive optics systems are designed to sense real-time atmospheric turbulence and correct the telescope’s optical beam to remove its effect. The system model for the adaptive optics operational modes was developed to capture sequence behaviors and operational scenarios to run Monte-Carlo simulations for verifying acquisition time, observing efficiency, and operational behavior requirements. The model is particularly useful for investigating the effect of parallelization, identifying interface issues, and re-ordering sequence acquisition tasks. A former version of the Cookbook (which is now updated to MBSE challenges, goals, and lessons learned) included modeling guidelines and conventions for all system aspects, hierarchy levels, and views, which were developed during for the Active Phasing Experiment (APE), an opto-mechatronical system technology demonstrator for the Extremely Large Telescope (ELT). The Cookbook utilizes the above mentioned system models as real-world case-studies to demonstrate and document the applications of the recipes, providing also instructional examples and addressing the available tooling support. The Cookbook is accompanied by a number of SysML models and aodel libraries which facilitate model authoring and maintenance. The Cookbook covers the different aspects of Systems Engineering such as management of Requirements, Design (behavior and structure), Interfaces, Interdisciplinary Integration, Analysis, Trade Studies, and Technical Resources. This paper presents the background, motivation, architecture, and highlights some key content of the Cookbook. For example, interface management, error budget management, requirements verification, Monte Carlo driven analysis, and timing analysis of operational scenarios. The paper discusses how the capabilities of OpenMBEE contributed significantly to the adoption of executable systems engineering.

Brower, Eric↗

DOE OSTI2025

Automated segmentation of soft X-ray tomography: Native cellular structure with submicron resolution at high-throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at suboptical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based autosegmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline uses manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the three-dimensional (3D) whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single-cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts.

Chen, Jianhua [Lawrence Berkeley National Laborato↗

DOE OSTI2020

Rational synthesis of atomically precise graphene nanoribbons directly on metal oxide surfaces

Atomically precise graphene nanoribbons (GNRs) attract great interest because of their highly tunable electronic, optical, and transport properties. However, on-surface synthesis of GNRs is typically based on metal surface–assisted chemical reactions, where metallic substrates strongly screen their designer electronic properties and limit further applications. In this work, we present an on-surface synthesis approach to forming atomically precise GNRs directly on semiconducting metal oxide surfaces. The thermally triggered multistep transformations preprogrammed in our precursors’ design rely on highly selective and sequential activations of carbon-bromine (C-Br) and carbon-fluorine (C-F) bonds and cyclodehydrogenation. The formation of planar armchair GNRs terminated by well-defined zigzag ends is confirmed by scanning tunneling microscopy and spectroscopy, which also reveal weak interaction between GNRs and the rutile titanium dioxide substrate.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Surface Complexation/Ion Exchange Hybrid Model for Radionuclide Sorption to Clay Minerals (M4SF-23LL010301062)

This progress report (Level 4 Milestone Number M4SF-23LL010301062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite International Collaborations Activity Number SF-23LL01030106. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. The focus of this milestone is the establishment of international collaborations for surface complexation modeling and the associated impacts of unlocking larger, community-based datasets. More specifically, we are developing a database framework for Spent Fuel and Waste and Science Technology (SFWST) that is aligned with the Helmholtz Zentrum Dresden Rossendorf (HZDR) sorption database development group in support of the database needs of the SFWST program. In our FY22 effort, we described a detailed analysis of U(VI) sorption to quartz through both traditional surface complexation modeling and through a hybrid ML framework. In FY23, effort was placed on publication of these results and expansion of the LLNL surface complexation and ion exchange database (L-SCIE) in order to assess mineral-based radionuclide retardation under a wider variety of geochemical conditions (e.g., ionic strength, varying electrolyte compositions). Efforts were initiated to expand L-SCIE to include radionuclide surface complexation and ion exchange to clays that are relevant to subsurface geochemical processes occurring at nuclear waste repositories. In particular, a large source of sorption data for clays resides at the Paul Scherrer Institute (PSI) (work primarily by Bradbury and Baeyens) and we initiated discussions on how to retrieve those data and apply FAIR principles to those datasets. In addition to L-SCIE development, two hybrid models that incorporate AI/ML were investigated and compared to discern the most promising approaches for accurate and precise estimations of radionuclide retardation. Key considerations for future model development include (1) the ability to reduce computational burden on determining retardation coefficients for PA and (2) the ability to quantify and predict radionuclide-mineral partitioning at a more efficient, rapid pace due to automated workflows. Upon the careful consideration of the most effective modeling approaches, we are identifying ways to implement these approaches into PA. Ultimately, the data science-based workflows will provide a major incentive for other institutions to adopt a FAIR-formatted, interoperable database. LLNL will play a key role in disseminating sorption data and acting as good data stewards by updating the database in a consistent format and assessing the quality of the newly assimilated data in an organized fashion. To this end, all data and workflows are open access and made available on the LLNL Seaborg research website (https://seaborg.llnl.gov/resources/geochemical-databases-modeling-codes).

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Impact of the MARATHON data on F 2⁢n⁡ /F 2⁢p and off-shell effects in light nuclei

The neutron structure function, F 2⁢n⁡ , has historically been extracted from measurements of the deuteron structure function, which is limited by our understanding of the nuclear effects on the bound proton and neutron. The MARATHON Collaboration recently extracted F 2⁢n⁡ from the comparison of 3 H and 3 He targets, where the nuclear effects are larger but nearly identical, yielding a precise extraction of F 2⁢n⁡ /F 2⁢p . Here, to ensure that this comparison is not biased by the specific model of nuclear effects used by MARATHON, we examine a range of models of the nuclear effects to obtain a more conservative, but more model-independent, extraction of F 2⁢n⁡ /F 2⁢p for comparison with deuteron extractions. Even with this approach, the results are precise enough to compare to deuteron extractions, providing new constraints on the nuclear effects in the deuteron and indicating the need for larger nuclear corrections than those included in most models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Quantum-amplified global-phase spectroscopy on an optical clock transition

Optical lattice clocks are at the forefront of precision metrology, operating near a standard quantum limit set by quantum noise. Harnessing quantum entanglement offers a promising route to surpass this limit; however, there are practical difficulties in terms of scalability and measurement resolution requirements. Here we adapt the holonomic quantum gate concept to develop a new Rabi-type ‘global-phase spectroscopy’ that uses the detuning-sensitive global Aharonov–Anandan phase19. With this approach, we can demonstrate quantum-amplified time-reversal spectroscopy on an optical clock transition that achieves directly measured 2.4(7) dB metrological gain and 4.0(8) dB improvement in laser noise sensitivity beyond the standard quantum limit. To this end, we introduce rotary echo to protect the dynamics from inhomogeneities in light–atom coupling and implement a laser-noise-cancelling differential measurement through symmetric phase encoding in two nuclear spin states. Our technique is not limited by measurement resolution, scales easily because of the global nature of entangling interaction and exhibits high resilience to typical experimental imperfections. As a result, we expect it to be broadly applicable to next-generation atomic clocks and other quantum sensors approaching the fundamental quantum precision limits.

Zaporski, Leon [Massachusetts Institute of Technol↗

NASA NTRSDate not supplied

Artemis Navigation Architecture: Early Capabilities and Long Term Evolvability and Evolution

With the awarding of multiple contracts within the Artemis program and building on the success of Artemis I, NASA is investing in and demonstrating the vehicle capabilities necessary for a return to human crewed Lunar Missions. To support activities on the lunar surface, NASA is also assessing architecture options and approaches to enable high precision in-situ navigation within the lunar sphere of influence. These capabilities build on decades of research and advancements within the field, building and evolving the techniques used during Apollo. To support inter-operability and broad application within its elements, NASA conducted a trade on Orbital and Surface Lunar Architecture for PNT. Time-defined mission requirements were captured across elements to inform a phased approach and deployment of needed capability. The architecture must also address unique aspects of the South Pole lunar environments, specifically in terms of harsh lighting and hazardous terrain. To inform the study, documentation of primary users, operational concepts of operations, driving scenarios, and mission needs were used to define performance constraints and phasing. Multiple technologies were assessed in terms of maturity, applicability, and performance to meet the primary user needs forecast. The results of this study support the utilization of in-situ orbital infrastructure to provide a back-bone for navigation and emphasize the need for a common Lunar Reference System and Lunar Time Reference. This deployment can ensure compatibility and enable a high-accuracy in-situ capability. This provides further justification for the capabilities being invested in and deployed by NASA and other international agencies. In addition to including advancements in terrestrial surface navigation, NASA is also applying lessons learned and innovation in the contractual approach to the individual elements by means of a services-based contract mechanism. This impacts the navigation architecture heavily in terms of government and provider roles, in terms of levels of implementation, interoperability, and verification. These distinctions in roles provide constraints to the architecture approach in terms of implementation and integration and will be discussed. The development, use, and mandate of interoperability standards are being deployed to support cross-element compatibility. This paper will provide a summary of the NASA Lunar Navigation needs across its various elements and the proposed deployment of an integrated navigation architecture to support early mission needs with inherent extensibility towards the future.

Evan Anzalone↗

NASA NTRS1976

Detection and mapping of mineralized areas in the Cortez-Uinta Belt, Utah-Nevada, using computer-enhanced ERTS imagery

The author has identified the following significant results. An approach to obtain spatial precision utilizes large scale black and white ratio images with high geometric precision. These images have a precision of .005 inch across the diagonals. Evaluation of a color ratio composite image of south central Nevada using ratio images recorded at this scale shows that the respective pixels are registered throughout the scene. Thus reconnaissance mapping can be carried out for the entire scene at 1:300,000 scale and then at larger scales by analyzing photographic enlargements of the original color ratio composite image. The advantages to this approach are elimination of repetitive computer processing and considerable flexibility as to specific scales.

Rowan, L. C.↗

NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

… or, “It’s in the details, how to make complicated software perform like complicated hardware.” In attempts to minimize development time and quickly build an operational vehicle, NASA’s Space Launch System (SLS) has had to be intentional about integrated testing. Constraints on budget and schedule have required balance between testing needs and the desire for an integrated flight vehicle as soon as possible. To provide key insights early in design and analysis cycles, a large amount of effort has shifted into maturing and validating models at the component level with integrated testing as a means to validate their integration. In terms of SLS Navigation, this, and the model-based design approach have pushed explicit requirements for sensor models to be validated against flight hardware to high precision. This paper covers the approach taken to verify and validate the models for the two key navigation sensors on the SLS vehicle, the Redundant Inertial Navigation Sensor and the Rate Gyro Assembly. These models are used in performance evaluation, fault detection, and operations development extensively. Using a mix of data from hardware vendor documentation and testing reports, limited in-house testing, and integration activities, these models were able to be validated against flight hardware at multiple levels, from the internal software design to statistical behavior at the raw sensor and integrated box levels. The high level of insight into the hardware elements is instrumental to support flight certification activities and building confidence in SLS Navigation capability. Focused testing enabled additional insight and validation that proved invaluable and the resulting insights were used to focus and mature models. Additionally, of having validated performance-based hardware models enables a wide breadth of activities including detailed fault detection studies and integration into future vehicle frameworks, such as an upper stage and provide a valuable asset to continued SLS analysis and design.

Evan J Anzalone↗

NASA NTRS2020

Hardware Verification and Validation for a Navigation Sensor Software Model in Support of Flight Vehicle Performance Analysis

Thomas Park↗

DOE OSTI2024

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures

We introduce an explainable variational autoencoder for three-dimensional (3D) localization of acoustic emission sources in hollow cylindrical structures, with an unsupervised approach. This research capitalizes on multi-arrival waveforms generated by helical path propagation in cylindrical geometries to enable efficient two-receiver localization. By integrating the modal characteristics of Lamb modes under multi-path conditions, we demonstrate that two sets of time-of-arrival differences and peak amplitudes extracted from one receiver can serve as effective localization features. This initial approach identifies four potential source locations, highlighting the feasibility of two-receiver source localization using traditional feature extraction methods. However, direct extraction can be challenging when mode overlaps occur, complicating the localization process. To address this, our work proposes a novel waveform-based method. This method leverages the consistent dispersion characteristics within isotropic materials, where each unique combination of mode arrival times and peak amplitudes constructs a distinct waveform. This distinctiveness overcomes the ambiguities associated with mode overlaps, significantly enhancing the method’s precision and robustness. Our approach adopts a data-driven strategy for waveform-based localization using variational autoencoder (VAE). VAE discerns waveform patterns for localization, while also addressing data uncertainties. The VAE’s encoder and decoder networks capture the localization process and the source’s influence on waveform generation, respectively, guiding latent variables to segregate waveforms by source in the latent space. The design of the learning process focuses on specific localization characteristics to enhance result explainability. Localization predictions are generated by projecting test waveforms, not included in the training set, onto a trained latent space. The prediction is determined using a nearest-neighbor approach based on the closest latent representation of a source. Validation with pencil-lead-break tests on a metallic pipe confirmed our method’s effectiveness, achieving an averaged 3D localization accuracy of 0.84.

Lee, Guan-Wei↗

NASA NTRS2004

A Scalable Nonuniform Pointer Analysis for Embedded Program

In this paper we present a scalable pointer analysis for embedded applications that is able to distinguish between instances of recursively defined data structures and elements of arrays. The main contribution consists of an efficient yet precise algorithm that can handle multithreaded programs. We first perform an inexpensive flow-sensitive analysis of each function in the program that generates semantic equations describing the effect of the function on the memory graph. These equations bear numerical constraints that describe nonuniform points-to relationships. We then iteratively solve these equations in order to obtain an abstract storage graph that describes the shape of data structures at every point of the program for all possible thread interleavings. We bring experimental evidence that this approach is tractable and precise for real-size embedded applications.

Venet, Arnaud↗