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Observation of the open-charm tetraquark state in the decay
No full textInternational audienceAn amplitude analysis of decays is performed using proton-proton collision data, corresponding to an integrated luminosity of , collected with the LHCb detector at center-of-mass energies of 7, 8, and 13. A resonant structure of spin-parity is observed in the invariant-mass spectrum with a significance of . The mass and width of the state, modeled with a BreitWigner lineshape, are determined to be and respectively, where the first uncertainties are statistical and the second systematic. These properties and the quark content are consistent with those of the open-charm tetraquark state observed previously in the final state of the decay. This result confirms the existence of the state in a new decay mode. The state, reported in the decay, is also searched for in the invariant-mass spectrum of the decay, without finding evidence for it
Measurement of meson production in fixed-target Ne collisions at = 68.5 GeV
No full textInternational audienceThe first measurement of meson production in fixed-target Ne collisions at GeV is presented. The mesons are reconstructed in their decay in a data sample consisting of proton collisions on neon nuclei at rest, corresponding to an integrated luminosity of nb, collected by the LHCb detector at CERN. The production cross-section in the centre-of-mass rapidity range of and transverse momentum range of MeV/c is found to be b/nucleon. A double-differential measurement of the cross-section is also provided in four regions of rapidity and six regions of transverse momentum of the meson and compared with the predictions from Pythia and EPOS4, which are found to underestimate the experimental values
Saddlepoint Monte Carlo and its Application to Exact Ecological Inference
No full textAssuming X is a random vector and A a non-invertible matrix, one sometimes need to perform inference while only having access to samples of Y = AX. The corresponding likelihood is typically intractable. One may still be able to perform exact Bayesian inference using a pseudo-marginal sampler, but this requires an unbiased estimator of the intractable likelihood. We propose saddlepoint Monte Carlo, a method for obtaining an unbiased estimate of the density of Y with very low variance, for any model belonging to an exponential family. Our method relies on importance sampling of the characteristic function, with insights brought by the standard saddlepoint approximation scheme with exponential tilting. We show that saddlepoint Monte Carlo makes it possible to perform exact inference on particularly challenging problems and datasets. We focus on the ecological inference problem, where one observes only aggregates at a fine level. We present in particular a study of the carryover of votes between the two rounds of various French elections, using the finest available data (number of votes for each candidate in about 60,000 polling stations over most of the French territory). We show that existing, popular approximate methods for ecological inference can lead to substantial bias, which saddlepoint Monte Carlo is immune from. We also present original results for the 2024 legislative elections on political centre-to-left and left-to-centre conversion rates when the far-right is present in the second round. Finally, we discuss other exciting applications for saddlepoint Monte Carlo, such as dealing with aggregate data in privacy or inverse problems
Characterization of the optical model of the T2K 3D segmented plastic scintillator detector
No full textInternational audienceThe magnetised near detector (ND280) of the T2K long-baseline neutrino oscillation experiment has been recently upgraded aiming to satisfy the requirement of reducing the systematic uncertainty from measuring the neutrinonucleus interaction cross section, which is the largest systematic uncertainty in the search for leptonic charge-parity symmetry violation. A key component of the upgrade is SuperFGD, a 3D segmented plastic scintillator detector made of approximately 2,000,000 optically-isolated 1 cm3 cubes. It will provide a 3D image of GeV neutrino interactions by combining tracking and stopping power measurements of final state particles with sub-nanosecond time resolution. The performance of SuperFGD is characterized by the precision of its response to charged particles as well as the systematic effects that might affect the physics measurements. Hence, a detailed Geant4 based optical simulation of the SuperFGD building block, i.e. a plastic scintillating cube read out by three wavelength shifting fibers, has been developed and validated with the different datasets collected in various beam tests. In this manuscript the description of the optical model as well as the comparison with data are reported
Causal and Stable Superfluid Hydrodynamics
No full textInternational audienceWe investigate the linearized stability and causality properties of relativistic viscous superfluid hydrodynamics. The Landau-Lifshitz-Clark-Putterman formulation for the theory of relativistic viscous superfluids suffers from the same instability and acausality issues as the relativistic Navier-Stokes equation for normal fluids when written in the formulations of Eckart or Landau and Lifshitz. We show that conditions to ensure stability and causality can be satisfied with judicious redefinitions of the hydrodynamic variables. The conditions we obtain hold at non-zero superfluid velocity as well
Beyond indices: Profiles of social vulnerability for flood risk reduction
No full textInternational audienceSocial vulnerability indices are increasingly employed as policy and planning instruments for disaster risk reduction. Although indices model the magnitude and spatial distribution of vulnerability, they are coarse and often misleading tools for revealing who is most vulnerable, due to uncertainty and information loss during aggregation. The mismatch inhibits the capacity to reveal intersectional vulnerability drivers and tailor risk reduction interventions. This study seeks to identify the major archetypes of compound social vulnerability in the context of flood exposure in the United States. Based on spatial inputs of demographic variables, pluvial and fluvial flood extent, and high-resolution building footprints, we used Hierarchical Clustering on Principal Components to classify, map, and analyze social vulnerability profiles. Six distinct profiles emerged from the analysis, two of which describe the confluence of high levels of both social vulnerability characteristics and flood exposure. The first profile is characterized by linguistic isolation, Hispanic populations, low educational attainment, high population density, and lack of health insurance, while the second is distinguished by a cluster of Black populations, low vehicle access, poverty, and female-headed households. The profile configurations span levels of social vulnerability and flood exposure, revealing intersectional complexity obscured by aggregate index scores. We conclude by discussing how profile typologies and their geographies advance understanding of social vulnerability and can inform strategies for equitable flood adaptation
First-order factors of linear Mahler operators
No full textDedicated to the memory of Marko Petkovšek.International audienceWe develop and compare two algorithms for computing first-order right-hand factors in thering of linear Mahler operatorswhere are polynomials in~ and for someinteger~.In other words, we give algorithms for finding all formal infinite productsolutions of linear functional equations.The first of our algorithms is adapted from Petkovšek's classical algorithm forthe analogous problem in the case of linear recurrences.The second one proceedsby computing a basis of generalized power series solutions of the functional equationand by using Hermite--Padé approximants to detect those linear combinations of the solutionsthat correspond to first-order factors.We present implementations of both algorithms and discuss their usein combination with criteria from the literatureto prove the differential transcendence of power series solutions of Mahlerequations
A Gated Residual Kolmogorov-Arnold Networks for Mixtures of Experts
No full textInternational audienceThis paper introduces KAMoE, a novel Mixture of Experts (MoE) framework based on Gated Residual KolmogorovArnold Networks (GRKAN). We propose GRKAN as an alternative to the traditional gating function, aiming to enhance efficiency and interpretability in MoE modeling. Through extensive experiments on digital asset markets and real estate valuation, wedemonstrate that KAMoE consistently outperforms traditional MoE architectures across various tasks and model types. Our results show that GRKAN exhibits superior performance compared to standard Gating Residual Networks, particularly in LSTMbased models for sequential tasks. We also provide insights into the trade-offs between model complexity and performance gains in MoE and KAMoE architectures
On the structure of the Schur squares of Twisted Generalized Reed-Solomon codes and application to cryptanalysis
No full textInternational audienceTwisted generalized Reed-Solomon (TGRS) codes constitute an interesting family of evaluation codes, containing a large class of maximum distance separable codes non-equivalent to generalized Reed-Solomon (GRS) ones. Moreover, the Schur squares of TGRS codes may be much larger than those of GRS codes with same dimension. Exploiting these structural differences, in 2018, Beelen, Bossert, Puchinger and Rosenkilde proposed a subfamily of Maximum Distance Separable (MDS) Twisted Reed-Solomon (TRS) codes over with twists for McEliece encryption, claiming their resistance to both Sidelnikov Shestakov attack and Schur products--based attacks. In short, they claimed these codes to resist to classical key recovery attacks on McEliece encryption scheme instantiated with Reed-Solomon (RS) or GRS codes. In 2020, Lavauzelle and Renner presented an original attack on this system based on the computation of the subfield subcode of the public TRS code. In this paper, we show that the original claim on the resistance of TRS and TGRS codes to Schur products based--attacks is wrong. We identify a broad class of codes including TRS and TGRS ones that is distinguishable from random by computing the Schur square of some shortening of the code. Then, we focus on the case of single twist (i.e., ), which is the most efficient one in terms of decryption complexity, to derive an attack. The technique is similar to the distinguisher-based attacks of RS code-based systems given by Couvreur, Gaborit, Gauthier-Uma\~na, Otmani, Tillich in 2014
Apollon Real-Time Adaptive Optics (ARTAO) -- Astronomy-Inspired Wavefront Stabilization in Ultraintense Lasers
No full textInternational audienceTraditional wavefront control in high-energy, high-intensity laser systems usually lacks real-time capability, failing to address dynamic aberrations. This limits experimental accuracy due to shot-to-shot fluctuations and necessitates long cool-down phases to mitigate thermal effects, particularly as higher repetition rates become essential, e.g. in Inertial Fusion research. This paper details the development and implementation of a real-time capable adaptive optics system at the Apollon laser facility. Inspired by astronomical adaptive optics, the system uses a fiber-coupled 905 nm laser diode as a pilot beam that allows for spectral separation, bypassing the constraints of pulsed lasers. A GPU-based controller, built on the open-source CACAO framework, manages a loop comprising a bimorph deformable mirror and high-speed Shack-Hartmann sensor. Initial tests showed excellent stability and effective aberration correction. However, integration into the Apollon laser revealed critical challenges unique to the laser environment that must be resolved to ensure safe operation with amplified shots