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Cosmological and High Energy Physics implications from gravitational-wave background searches in LIGO-Virgo-KAGRA's O1-O4a runs
No full textInternational audienceWe search for gravitational-wave background signals produced by various early Universe processes in the Advanced LIGO O4a dataset, combined with the data from the earlier O1, O2, and O3 (LIGO-Virgo) runs. The absence of detectable signals enables powerful constraints on fundamental physics. We derive gravitational-wave background energy density upper limits from the O1-O4a data to constrain parameters associated with various possible processes in the early Universe: first-order phase transitions, cosmic strings, domain walls, stiff equation of state, axion inflation, second-order scalar perturbations, primordial black hole binaries, and parity violation. In our analyses, the presence of an astrophysical background produced by compact (black hole and neutron star) binary coalescences throughout the Universe is also considered. We address the implications for various cosmological and high energy physics models based on the obtained parameter constraints. We conclude that LIGO-Virgo data already yield significant constraints on numerous early Universe scenarios
Multiplicative Updates Beamforming Design for Hybrid Fully-connected Millimeter-Wave MIMO Systems
No full textInternational audienceAchieving the optimal design of analog and digital beamformers, provided by a hybrid architecture using phase shifters (PSs), is crucial for ensuring the spectral efficiency (SE) of millimeter-wave (mmWave) communication systems. To tackle the challenge of finding optimal hybrid beamformers that directly maximize SE, several studies have adopted the matrix factorization problem as a viable solution in designing at each transceiver side. However, the unit constant modulus (UCM) constraints on analog beamformers resulting from PSs and the joint optimization of digital and analog parts render the hybrid beamforming design problem highly non-convex. In this paper, we develop a hybrid algorithm via the multiplicative update rules technique for solving the matrix factorization problem of finding optimal analog and digital beamformers by easily taking into account practical constraints. By removing the nonnegativity constraints, the proposed method achieves optimal analog and digital beamformers in the hybrid fully connected mmWave multiple-input multiple-output (MIMO) architecture through a simple implementation enabled by simultaneous updates offered from the closed-form of the multiplicative update rules. According to the numerical simulations, the proposed design is more effective than state-of-the-art design algorithms and is less complex
Deep Search for Joint Sources of Gravitational Waves and High-Energy Neutrinos with IceCube During the Third Observing Run of LIGO and Virgo
No full textInternational audienceThe discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection of high-energy neutrinos and gravitational waves would provide insight into cosmic processes, from the dynamics of compact object mergers and stellar collapses to the mechanisms driving relativistic outflows. The joint detection of multiple cosmic messengers can also elevate the significance of the common observation even when some or all of the constituent messengers are sub-threshold, i.e. not significant enough to declare their detection individually. Using data from the LIGO, Virgo, and IceCube observatories, including sub-threshold events, we searched for common sources of gravitational waves and high-energy neutrinos during the third observing run of Advanced LIGO and Advanced Virgo detectors. Our search did not identify significant joint sources. We derive constraints on the rate densities of joint sources. Our results constrain the isotropic neutrino emission from gravitational-wave sources for very high values of the total energy emitted in neutrinos (> erg)
Intégrer des enjeux éthiques, sociétaux et environnementaux dans un cours de conception d'algorithmes
No full textThis document, intended for computer science teachers, describes a case study that puts into practice a questioning of ethical, societal and environmental issues when designing or implementing a decision support system. This study is based on a very popular application, namely road navigation software that informs users of real-time traffic conditions and suggests routes between a starting point and a destination, taking these conditions into account (such as Waze). The approach proposes to intertwine technical considerations (optimal path algorithms, data needed for location, etc.) with a broader view of the ethical, environmental and societal issues raised by the tools studied. Based on the authors' experience conducting sessions with students over several years, this document discusses the context of such a study, suggests teaching resources for implementing it, describes ways to structure discussions, and shares scenarios in different teaching contexts.Ce document, à destination des enseignants d'informatique, décrit une étude de cas qui met en pratique un questionnement sur les enjeux éthiques, sociétaux et environnementaux lors de la conception ou de la mise en œuvre d’un algorithme d'aide à la décision. Cette étude s'appuie sur une application très populaire, à savoir un logiciel d’aide à la navigation routière informant les utilisateurs des conditions de trafic en temps réel, et leur proposant des itinéraires entre une origine et une destination en tenant compte de ces conditions (type Waze). L'approche propose d'entrelacer des considérations techniques (algorithmes de chemins optimaux, données nécessaires pour se localiser, etc.) et une prise de recul sur les enjeux éthiques, environnementaux et sociétaux des outils étudiés. En s'appuyant sur l'expérience conduite par les auteurs depuis plusieurs années en séance face à des étudiants, ce document discute le contexte d'une telle étude, propose des ressources pédagogiques pour mettre en œuvre cette étude, décrit des pistes pour structurer les échanges et partage des scénarisations dans différents contextes pédagogiques
Markov Decision Process for Mixed-Model Assembly Line design under process time uncertainty
No full textInternational audienceThe industry is increasingly confronted with the challenge of process duration uncertainty in production systems. These variations are particularly problematic for manufacturers that utilize Multi-Manned Mixed-Model Assembly Lines, as they can cause significant disruptions that may stop the production line. Our study explores the benefit of walking workers to dynamically adjust the workforce in response to unexpected variations in process durations at different stations, a common scenario in the automotive industry. We model the dynamic workforce assignment decision as a Markov Decision Process, and this MDP accounts for uncertainties in process times, and it incorporates dynamic task assignment and workers' movements. This MDP is subsequently translated into a linear program that we integrate into a higher-level Mixed-Integer Linear Programming model responsible for dimensioning the workforce and selecting equipment in the station. This approach results in the creation of assembly lines designed to be resilient in the face of unexpected variations in task process durations.To deal with scalability issues, we employ the Benders decomposition algorithm. The paper also presents a validation with data from a car manufacturer that reinforces the practical applicability of our methodology. Additionally, we provide managerial insights on effectively managing process time uncertainty in automotive production systems, empowering decision-makers with optimization strategies, cost-reduction approaches, and resilience-building techniques to enhance the performance and reliability of Mixed-Model Assembly Lines
Multi-technique radiometric assessment of a desert-marine ecosystem facilitating radiological-environmental safety in hyper-arid regions
No full textInternational audienceThis paper presents a rigorous, multi-technique assessment of radiometric and physiochemical characteristics of a desert-marine ecosystem in the United Arab Emirates (UAE). Current models and empirical data on the release, dispersion, retention and migration of radionuclides in hyper-arid regions are inadequate. This is a critical gap in the radiological-environmental assessments in the Arabian Peninsula, where industries producing radioactivity, such as oil and gas, mining, and both thermal and nuclear power generations, are expanding rapidly. This study offers the most diverse baseline data to date, laying the groundwork for an evidence-based radionuclide transport modeling in hyper-arid environments. It identifies the key isotopes to track and carefully selects a representative region for a comprehensive sampling. The Al Dhafra region of Abu Dhabi was chosen due to its importance in hosting oil, gas, and nuclear industries, and because it covers 71 % of the total area of the emirate. Around 30 different samples were collected, including rock, sand, groundwater, seawater, plants, and farm products. A tailored combination of advanced radiometric methods with XRD, ICP-MS, IC, and gamma spectrometry was developed for this complex and rare sample set. Majority of the instrumentation for this project were hosted in the Subatech Laboratories (France). The study yielded radioactivity compositions in the main arid environmental matrices, consistent with the previous research, and introduced novel findings on the probable host rocks to study for nuclear waste storage, desert shrubs as bioindicators, and camel milk as a medium for transfers to humans. •Diverse and multi-method radiometric characterization of an expansive hyper-arid desert region.•Baseline radionuclide concentrations measured for rocks, sand, waters, plants, and farm produces.•Identified primary rock types, groundwater chemistry and salinity, and plants for transport mechanisms.•Vital empirical data for nuclear and radioactivity-producing industries in hyper-arid ecosystems
The Design Multiverse: A Scientific Model for Design Evolution and Co-evolution
No full textInternational audienceModel-Based Systems Engineering lacks a formal model that treats design evolution, with its inherent branching, rework, and contextsensitivity, as a first-class citizen. Current approaches reduce rich design trajectories to repository artifacts, losing the semantics of design decisions. This paper calls for a scientific model for design evolution and introduces the Design Multiverse that frames design dynamics as a context-sensitive, nondeterministic transition system, while orthogonally separating observational link theories (e.g., conformance, refinement) for consistency reasoning. We demonstrate the model's explanatory power through co-evolution. Furthermore, we outline a research agenda grounded by Design Multiverse Experiments (DMX), which enable empirical validation and pave the way for scalable, history-aware modeling environments.</div
Ultra-sensitive radon assay using an electrostatic chamber in a recirculating system
No full textInternational audienceRare event searches such as neutrinoless double beta decay and Weakly Interacting Massive Particle detection require ultra-low background detectors. Radon contamination is a significant challenge for these experiments, which employ highly sensitive radon assay techniques to identify and select low-emission materials. This work presents the development of ultra-sensitive electrostatic chamber (ESC) instruments designed to measure radon emanation in a recirculating gas loop, for future lower background experiments. Unlike traditional methods that separate emanation and detection steps, this system allows continuous radon transport and detection. This is made possible with a custom-built recirculation pump. A Python-based analysis framework, PyDAn, was developed to process and fit time-dependent radon decay data. Radon emanation rates are given for various materials measured with this instrument. A radon source of known activity provides an absolute calibration, enabling statistically-limited minimal detectable activities of 20 Bq. These devices are powerful tools for screening materials in the development of low-background particle physics experiments
Vehicle routing problem with multiple fleets and carrier limit
No full textInternational audienceWe address the distribution problem of a company that ships goods from a single depot to multiple customers. This distribution is outsourced to several carriers, each with distinct transportation rates and limited, heterogeneous vehicle fleets. Multiple carriers provide Full-Truckload (FTL) transportation via predefined routes operated by diverse vehicle types, with each carrier offering a limited number of trucks. Additionally, the Less-Than-Truckload (LTL) mode can be used to transport goods from origin to destination. We formulate this problem as a variant of the vehicle routing problem with a private fleet and common carriers. To solve it, we propose a matheuristic approach that combines a Large Neighborhood Search (LNS) metaheuristic with a set partitioning component. Our algorithm integrates filtering strategies to efficiently incorporate specific constraints into the LNS operators. We demonstrate that our method is competitive on established problem benchmarks and introduce new instances. Finally, we present a case study from the French retail industry,illustrating how combining FTL and LTL shipping can generate significant cost savings compared to relying solely on FTL or LTL
