arXiv subjects

Olivier Lopez

Publications and source records attributed to Olivier Lopez.

At least 19 recordsLinked to original sources

arXiv2026

International Optical Clock Comparison Using the European Optical Fiber Network

Optical clocks have achieved remarkable estimated fractional frequency uncertainties reaching the $10^{-18}$ level and below, enabling applications in fundamental physics, general relativity, and geodesy. However, the challenge of verifying the international consistency of optical clocks remains critical as efforts intensify toward redefining the SI second based on an optical transition or transitions. We report on a two-month international clock comparison campaign involving seven optical clocks in four national metrology institutes (INRIM, LNE-OP, NPL, and PTB) connected via the optical fiber network established in Europe. The campaign resulted in optical frequency ratios with uncertainties ranging from $7.7\times10^{-18}$ to $6.1\times10^{-17}$. Among the results, the $^{171}$Yb$^+$(E3) clocks at NPL and PTB demonstrated agreement within an uncertainty of $7.7\times10^{-18}$, marking the first international verification of two independently developed optical clocks below one part in $10^{17}$. The operation of the $^{199}$Hg clock at LNE-OP (formerly LNE-SYRTE) resulted in frequency ratios with improved uncertainties with $^{171}$Yb$^+$(E3), $^{171}$Yb, and $^{87}$Sr optical clocks. These results provide input for the redefinition of the second and underscore how fiber-linked clock networks can advance metrology and scientific applications.

physics.atom-ph↗

arXiv2026

Cloud failure and cyber insurance: calibration of stress scenarios and diversification

The expansion of the cyber insurance market remains exposed to the threat of accumulation events that could simultaneously affect a large number of policyholders. Although few such catastrophes have been observed so far, apart from worldwide cyberattacks such as WannaCry and NotPetya in 2017, the nature of cyber risk makes their occurrence plausible. Stress-testing tools are therefore needed to assess whether an insurance portfolio can withstand such crises. In this perspective, the European Insurance and Occupational Pensions Authority (EIOPA) has identified cloud outage as one of the key scenarios to consider in cyber insurance stress-testing frameworks. In this paper, we propose a framework to model and calibrate cloud-outage scenarios and to measure the diversification of a cyber insurance portfolio. We also show how this diversification can protect against accumulation risk and provide underwriting guidelines to reduce the vulnerability of a portfolio to cloud-outage scenarios.

q-fin.RM↗

arXiv2026

Gradient boosting for extremes: sampling theory and application to insurance

We develop a statistical learning theory for gradient boosting applied to the estimation of covariate-dependent Generalized Pareto (GP) distributions in the context of Peaks-over-Threshold modeling. After an orthogonal reparametrization of the GP likelihood that diagonalizes its Fisher information matrix, we cast the estimation problem within the Empirical Risk Minimization (ERM) framework and derive non-asymptotic error bounds for the boosting estimator. Our analysis accounts for three distinct sources of error in the process: statistical fluctuations, the approximation bias inherent to the asymptotic nature of the GP model-controlled under second-order regular variation-and the approximation error associated with the finite number of boosting iterates, making explicit the resulting bias-variance trade-off. We illustrate the practical benefits of the reparametrization through simulations, showing that it significantly reduces gradient correlation during training and improves convergence stability. The methodology is applied to a medical malpractice insurance dataset from the Texas Department of Insurance, comprising over 18 000 closed claims. The gradient boosting approach yields a good fit for the tail of settlement cost distributions and reveals that the number of days to settlement is the dominant predictor of tail heaviness, consistent with earlier findings in the reserving literature.

stat.ML↗

arXiv2026

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence

According to the United Nations Office for Disaster Risk Reduction (2025), the average annual cost of natural catastrophes increased from 70--80 billion USD between 1970 and 2000 to 180--200 billion USD between 2001 and 2020. Reports from organizations such as the IFOA and the WWF highlight the need for the insurance sector to adapt to this rapidly evolving context by developing medium- to long-term strategies that go beyond the one-year horizon of prudential regulations such as Solvency II. This paper introduces an artificial intelligence framework based on Conditional Generative Adversarial Networks (Conditional GANs) to generate future spatio-temporal trajectories of climatic indices. The approach focuses on the Soil Wetness Index (SWI), a key indicator used in France to assess drought severity. Drought accounts for approximately 30% of the indemnities paid under the French natural catastrophe insurance scheme. The proposed model, SwiGAN, simulates plausible drought propagation patterns up to 2050 for a region of France particularly exposed to this hazard. By generating realistic sequences of SWI maps, SwiGAN provides insights into drought dynamics under climate change scenarios and supports the design of adaptive risk management and insurance strategies. The methodology is also generalizable to other climate-related perils and actuarial applications such as economic scenario generation.

cs.LG↗

arXiv2026

A stochastic SIR model for cyber contagion: application to granular growth of firms and to insurance portfolio

This work evaluates the impact of contagious cyber-events, over a finite horizon, on firms' financial health and on a cyber insurance portfolio. Our approach builds on key empirical findings from economics and cybersecurity. In economics, firm size and growth-rate distributions are non-Gaussian and exhibit heavy tails. In cybersecurity, contagion dynamics strongly depend on firm size and environmental conditions. To capture these features, we propose a stochastic multi-group SIR model coupled with a granular model of firm growth. This framework allows us to quantify the financial impact of cyber-attacks on firms' revenues and on the insurer's portfolio. In the model, the arrival time and duration of cyber-attacks are driven by a combination of a Cox process and a Bernoulli random variable. The Cox process represents external contagion, with an intensity given by the force of infection derived from the stochastic SIR dynamics. The Bernoulli component captures contagion originating from an infected sister or subsidiary firm. Environmental variability enables stochastic scenario generation and the computation of aggregate exceedance probabilities, a standard metric in catastrophe modeling that provides insurers with immediate insight into the financial severity of an event. We apply the framework to the LockBit ransomware attacks observed between May and July 2024. For a portfolio of 2,929 firms located in Ile-de-France, the model predicts that, with 50% probability, the insurer will need to compensate losses equivalent to up to two days of revenue over a 100-day cyber incident.

q-fin.RM↗

arXiv2026

Combination of traditional and parametric insurance: calibration method based on the optimization of a criterion adapted to heavy tail losses

In this paper, we address the problem of providing insurance protection against heavy-tailed losses, for which the expected loss may not even be finite. The product we study is based on a combination of traditional insurance up to a given limit and a parametric (or index-based) cover for larger losses. This second component of the coverage is computed from covariates available immediately after the loss occurs, allowing claim management costs to be reduced through rapid compensation. To optimize the design of this second component, we use a criterion adapted to extreme losses, that is, to loss distributions of Pareto type. We support the calibration procedure with theoretical results establishing its convergence rate, as well as empirical evidence from both a simulation study and a real-data analysis on tornado losses in the United States. We also propose a two-step optimization procedure as a potential solution to the issue of data scarcity in the tails of loss distributions. We conclude by empirically demonstrating that the proposed hybrid contract outperforms a traditional capped indemnity contract.

q-fin.RM↗

arXiv2026

Index insurance under demand and solvency constraints

Index insurance is often proposed to reduce protection gaps, especially for emerging risks. Unlike traditional insurance, it bases compensation on a measurable index, enabling faster payouts and lower claim management costs. This approach benefits both policyholders, through quick payments, and insurers, through reduced costs and better risk control due to reliable data and robust statistical estimates. An important difference with the concept of Cat Bonds is that the feasibility of such coverage relies on the possibility of mutualization. Mutualization, in turn, is achieved only if a sufficiently high number of policyholders agree to subscribe. The purpose of this paper is to introduce a model for the demand for index insurance and to provide conditions under which the solvency of the portfolio is achieved. From these conditions, we deduce a product that combines index and traditional indemnity insurance in order to benefit from the best of both approaches. We illustrate our results with a practical example involving the design of an index insurance product in the field of cyber insurance.

q-fin.RM↗

arXiv2025

Demonstration and frequency noise characterization of a 17 $μ$m quantum cascade laser

We evaluate the spectral performance of a novel continuous-wave room-temperature distributed feedback quantum cascade laser operating at the long wavelength of 17 $μ$m. By demonstrating broadband laser absorption spectroscopy of the $ν$2 fundamental vibrational mode of N2O molecules, we have determined the spectral range and established the spectroscopic potential of this laser. We have characterized the frequency noise and measured the line width of this new device, uncovering a discrepancy with the current consensus on the theoretical modeling of quantum cascade lasers. Our results confirm the potential of such novel narrow-line-width sources for vibrational spectroscopy. Extending laser spectroscopy to longer wavelength is a fascinating prospect that paves the way for a wide range of opportunities from chemical detection, to frequency metrology as well as for exploring light-matter interaction with an extended variety of molecules, from ultra-cold diatomic species to increasingly complex molecular systems.

physics.atom-ph↗

arXiv2025

WTNN: Weibull-Tailored Neural Networks for survival analysis

The Weibull distribution is a commonly adopted choice for modeling the survival of systems subject to maintenance over time. When only proxy indicators and censored observations are available, it becomes necessary to express the distribution's parameters as functions of time-dependent covariates. Deep neural networks provide the flexibility needed to learn complex relationships between these covariates and operational lifetime, thereby extending the capabilities of traditional regression-based models. Motivated by the analysis of a fleet of military vehicles operating in highly variable and demanding environments, as well as by the limitations observed in existing methodologies, this paper introduces WTNN, a new neural network-based modeling framework specifically designed for Weibull survival studies. The proposed architecture is specifically designed to incorporate qualitative prior knowledge regarding the most influential covariates, in a manner consistent with the shape and structure of the Weibull distribution. Through numerical experiments, we show that this approach can be reliably trained on proxy and right-censored data, and is capable of producing robust and interpretable survival predictions that can improve existing approaches.

stat.ML↗

arXiv2025

Isotopic Transparency in Central Xe+Sn Collisions at 100 MeV/nucleon

A new method, based on comparing isotopic yield ratios measured at forward and sideward polar angles and on cross-bombarding heavy nuclei with different neutron-to-proton ratios, is used to quantify the stopping power of nuclear matter in heavy-ion collisions. For central collisions of isotopically separated $^{124,129}$Xe+$^{112,124}$Sn at 100~MeV/nucleon bombarding energy, measured with the 4$π$ multidetector INDRA at GSI, a moderate transparency is deduced for hydrogen isotopes, whereas for heavier fragmentation products with atomic number $Z \ge 3$ a high transparency exceeding 50\% is observed. An anomalously large transparency is found for alpha particles, and possible explanations are presented.

nucl-ex↗

arXiv2025

Coordinated international comparisons between optical clocks connected via fiber and satellite links

Optical clocks provide ultra-precise frequency references that are vital for international metrology as well as for tests of fundamental physics. To investigate the level of agreement between different clocks, we simultaneously measured the frequency ratios between ten optical clocks in six different countries, using fiber and satellite links. This is the largest coordinated comparison to date, from which we present a subset of 38 optical frequency ratios and an evaluation of the correlations between them. Four ratios were measured directly for the first time, while others had significantly lower uncertainties than previously achieved, supporting the advance towards a redefinition of the second and the use of optical standards for international time scales.

physics.atom-ph↗

arXiv2025

Extending frequency metrology to increasingly complex molecules: SI-traceable sub-Doppler mid-IR spectroscopy of trioxane

Bringing increasingly complex polyatomic molecules within reach of precision measurement experiments offers fascinating and far-reaching prospects ranging from Earth sciences and astrophysics, to metrology and quantum sciences. Here, we demonstrate sub-Doppler spectroscopic measurements in the mid-IR fingerprint region of, to our knowledge, the largest molecule to date. To this end, we use a high-resolution ~10.3 $μ$m spectrometer based on a sub-Hz quantum cascade laser remotely calibrated against state-of-the-art primary frequency standards via a metrology-grade fibre link. We perform saturated absorption spectroscopy in the v5 CO stretching mode of 1,3,5-trioxane, (H2CO)3, at a resolution of ~100 kHz, allowing us to measure the absolute frequency of hundreds of rovibrational transitions at unprecedented uncertainties for such a complex species, as low as ~5 kHz. Our work demonstrates the extension of frequency metrology methodologies to ever larger molecular system, confirming the potential of the technologies we develop for bringing increasingly complex species within reach of ultra-precise measurement experiments.

physics.atom-ph↗

arXiv2025

Heterodyne coherent detection of phase modulation in a mid-infrared unipolar device

Phase modulation is demonstrated in a quantum Stark effect modulator designed to operate in the mid-infrared at wavelength around 10 $μ$m. Both phase and amplitude modulation are simultaneously resolved through the measurement of the heterodyne signal arising from the beating of a quantum cascade laser with a highly stabilized frequency comb. The highest measured phase shift is more than 5 degrees with an associated intensity modulation of 5%. The experimental results are in full agreement with our model in which the complex susceptibility is precisely described considering the linear voltage dependent Stark shift of the optical resonance.

physics.optics↗

arXiv2024

Ultra-sensitive heterodyne detection at room temperature in the atmospheric windows

We report room temperature heterodyne detection of a quantum cascade laser beaten with a local oscillator on a unipolar quantum photodetector in two different atmospheric windows, at 4.8 $μ$m and 9 $μ$m. A noise equivalent power of few pW is measured by employing an active stabilization technique in which the local oscillator and the signal are locked in phase. The measured heterodyne noise equivalent power is six orders of magnitude lower than that obtained with direct detection.

physics.optics↗

arXiv2024

Near-to mid-IR spectral purity transfer with a tunable frequency comb: methanol frequency metrology over a record frequency span

We report the upgrade and operation of a frequency-comb-assisted high-resolution mid-infrared molecular spectrometer allowing us to combine high spectral purity, SI-traceability, wide tunability and high sensitivity. An optical frequency comb is used to transfer the spectral purity of a SI-traceable 1.54 $μ$m metrology-grade frequency reference to a 10.3 $μ$m quantum cascade laser (QCL). The near-infrared reference is operated at the French time/frequency metrology institute, calibrated there to primary frequency standards, and transferred to Laboratoire de Physique des Lasers via the REFIMEVE fiber network. The QCL exhibits a line width of $δν\sim 0.1$ Hz, a sub-$10^{-15}$ relative frequency stability from 0.1 to 10 s and its frequency is traceable to the SI with a total relative uncertainty better than $4\times10^{-14}$ after 1-s averaging time. We have developed the instrumentation allowing comb modes to be continuously tuned over 9 GHz resulting in a QCL of record spectral purity uninterruptedly tunable at the precision of the reference over an unprecedented span of $Δν$ = 1.4 GHz. We have used our apparatus to conduct sub-Doppler spectroscopy of methanol in a multi-pass cell, demonstrating state-of-art frequency uncertainties down to the few kilohertz level ($\sim10^{-10}$ in relative value). We have observed weak intensity resonances unreported so far, resolved subtle doublets never seen before and brought to light discrepancies with the HITRAN database. This demonstrates the potential of our apparatus for probing subtle internal molecular processes, building accurate spectroscopic models of polyatomic molecules of atmospheric or astrophysical interest, and carrying out precise spectroscopic tests of fundamental physics.

physics.atom-ph↗

arXiv2024

International comparison of optical frequencies with transportable optical lattice clocks

Optical clocks have improved their frequency stability and estimated accuracy by more than two orders of magnitude over the best caesium microwave clocks that realise the SI second. Accordingly, an optical redefinition of the second has been widely discussed, prompting a need for the consistency of optical clocks to be verified worldwide. While satellite frequency links are sufficient to compare microwave clocks, a suitable method for comparing high-performance optical clocks over intercontinental distances is missing. Furthermore, remote comparisons over frequency links face fractional uncertainties of a few $10^{-18}$ due to imprecise knowledge of each clock's relativistic redshift, which stems from uncertainty in the geopotential determined at each distant location. Here, we report a landmark campaign towards the era of optical clocks, where, for the first time, state-of-the-art transportable optical clocks from Japan and Europe are brought together to demonstrate international comparisons that require neither a high-performance frequency link nor information on the geopotential difference between remote sites. Conversely, the reproducibility of the clocks after being transported between countries was sufficient to determine geopotential height offsets at the level of 4 cm. Our campaign paves the way for redefining the SI second and has a significant impact on various applications, including tests of general relativity, geodetic sensing for geosciences, precise navigation, and future timing networks.

physics.atom-ph↗

arXiv2024

Isospin diffusion from $^{40,48}$Ca$+^{40,48}$Ca experimental data at Fermi energies: Direct comparisons with transport model calculations

This article presents an investigation of isospin equilibration in cross-bombarding $^{40,48}$Ca$+^{40,48}$Ca reactions at 35 MeV/nucleon, by comparing experimental data with filtered transport model calculations. Isospin diffusion is studied using the evolution of the isospin transport ratio with centrality. The asymmetry parameter $δ=(N-Z)/A$ of the quasiprojectile (QP) residue is used as isospin-sensitive observable, while a recent method for impact parameter reconstruction is used for centrality sorting. A benchmark of global observables is proposed to assess the relevance of the antisymmetrized molecular dynamics (AMD) model, coupled to GEMINI++, in the study of dissipative collisions. Our results demonstrate the importance of considering cluster formation to reproduce observables used for isospin transport and centrality studies. Within the AMD model, we prove the applicability of the impact parameter reconstruction method, enabling a direct comparison to the experimental data for the investigation of isospin diffusion. For both, we evidence a tendency to isospin equilibration with an impact parameter decreasing from 9 to 3 fm, while the full equilibration is not reached. A weak sensitivity to the stiffness of the equation of state employed in the model is also observed, with a better reproduction of the experimental trend for the neutron-rich reactions.

nucl-ex↗

arXiv2024

Tree-based conditional copula estimation

This paper proposes a regression tree procedure to estimate conditional copulas. The associated algorithm determines classes of observations based on covariate values and fits a simple parametric copula model on each class. The association parameter changes from one class to another, allowing for non-linearity in the dependence structure modeling. It also allows the definition of classes of observations on which the so-called "simplifying assumption" [see Derumigny and Fermanian, 2017] holds reasonably well. When considering observations belonging to a given class separately, the association parameter no longer depends on the covariates according to our model. In this paper, we derive asymptotic consistency results for the regression tree procedure and show that the proposed pruning methodology, that is the model selection techniques selecting the appropriate number of classes, is optimal in some sense. Simulations provide finite sample results and an analysis of data of cases of human influenza presents the practical behavior of the procedure.

math.ST↗