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Common functional languages incentivize tail-recursive functions, as opposed to general recursive functions that consume stack space and may not scale to large inputs. This distinction occasionally requires writing functions in a tail-recursive style that may be more complex and slower than the natural, non-tail-recursive definition. This work describes our implementation of the *tail modulo constructor* (TMC) transformation in the OCaml compiler, an optimization that provides stack-efficiency for a larger class of functions -- tail-recursive *modulo constructors* -- which includes in particular the natural definition of `List.map` and many similar recursive data-constructing functions. We prove the correctness of this program transformation in a simplified setting -- a small untyped calculus -- that captures the salient aspects of the OCaml implementation. Our proof is mechanized in the Coq proof assistant, using the Iris base logic. An independent contribution of our work is an extension of the Simuliris approach to define simulation relations that support different calling conventions. To our knowledge, this is the first use of Simuliris to prove the correctness of a compiler transformation., Comment: Published at POPL 2025

Everyday experience shows that cellular sheets are stiffened by the presence of a pressurized gas: from bicycle inner tubes to bubble wrap, the presence of an internal pressure increases the stiffness of otherwise floppy structures. The same is true of plants, with turgor pressure (due to the presence of water) taking the place of gas pressure; indeed, in the absence of water, many plants wilt. However, the mechanical basis of this stiffening is somewhat opaque: simple attempts to rationalize it suggest that the stiffness should be independent of the pressure, at odds with everyday experience. Here, we study the mechanics of sheets that are a single cell thick and show how a pressure-dependent bending stiffness may arise. Our model rationalizes observations of turgor-driven shrinkage in plant cells and also suggests that turgor is unlikely to provide significant structural support in many monolayer leaves, such as those found in mosses. However, for such systems, turgor does provide a way to control leaf shape, in accordance with observations of curling upon drying of moss leaves. Guided by our results, we also present a biomimetic actuator that un-curls upon pressurization., Comment: Paper: 14 pages, 9 figures; Supplemental Material: 8 pages, 2 figures

We present a new approach for simulating x-ray nanobeam Bragg coherent diffraction patterns based on the Takagi-Taupin equations. Compared to conventional methods, the current approach can be universally applied to any weakly strained system including semi-infinite crystals that diffract dynamically. It addresses issues such as the curved wavefront and re-divergence of the focused incident beam. We show excellent agreement against experimental data on a strained La0.7Sr0.3MnO3 thin film on SrTiO3 substrate, and a path to extracting physical information using automatic differentiation.

The Near-InfraRed Planet Searcher or NIRPS is a precision radial velocity spectrograph developed through collaborative efforts among laboratories in Switzerland, Canada, Brazil, France, Portugal and Spain. NIRPS extends to the 0.98-1.8 $\mu$m domain of the pioneering HARPS instrument at the La Silla 3.6-m telescope in Chile and it has achieved unparalleled precision, measuring stellar radial velocities in the infrared with accuracy better than 1 m/s. NIRPS can be used either stand-alone or simultaneously with HARPS. Commissioned in late 2022 and early 2023, NIRPS embarked on a 5-year Guaranteed Time Observation (GTO) program in April 2023, spanning 720 observing nights. This program focuses on planetary systems around M dwarfs, encompassing both the immediate solar vicinity and transit follow-ups, alongside transit and emission spectroscopy observations. We highlight NIRPS's current performances and the insights gained during its deployment at the telescope. The lessons learned and successes achieved contribute to the ongoing advancement of precision radial velocity measurements and high spectral fidelity, further solidifying NIRPS' role in the forefront of the field of exoplanets., Comment: Proceeding at the SPIE Astronomical Telescopes + Instrumentation conference [Yokohama,Japan; June 2024]

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

The cornea, as the outer element of the human eye, plays a pivotal role in vision. Any defects in its shape can result in visual impairments. Mechanical defect manifest as shape defects, as the cornea is under to pressure. Our study presents the first comprehensive observation of human corneal deformation throughout its entire thickness during an inflation test, through Optical Coherence Tomography (OCT). Horizontal deformation reveals depth-dependent heterogeneity, suggesting that the cornea's posterior part is softer than the anterior part. Vertical deformation was observed at levels significantly higher than expected and exhibited depth-dependent heterogeneity, delineating three distinct regions. The central region of the cornea initially experienced rapid swelling, possibly due to osmotic effects, followed by increasing compressions as pressure rose. Conversely, the anterior and posterior regions showed no sign of swelling, and a difference in the compressive response, possibly due to difference in stiffness. Our study shows the complexity of human corneal mechanics, highlighting strong anisotropy and depth-dependent behavior, and implicating osmotic and poroelastic properties.

The crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents is heavily influencing the macroscopic behaviour of the material. In order to study local crystallographic texture with both high spatial and angular resolution, we developed Texture tomography (TexTOM). This approach allows to model the diffraction data of polycrystalline materials by using the full reciprocal space of the ensemble of crystals and describe the texture in each voxel via a orientation distribution function. This means, it provides 3D reconstructions of the local texture by measuring the probabilities of all crystal orientations. The TexTOM approach addresses limitations associated with existing models: It correlates the intensities from several Bragg reflections, thus reduces ambiguities resulting from symmetry. Further, it yields quantitative probability distributions of local real space crystal orientations without further assumptions on the sample structure. Finally, its efficient mathematical formulation enables reconstructions faster than the time-scale of the experiment. In this manuscript, we present the mathematical model, the inversion strategy and its current experimental implementation. We show characterizations of simulated data as well as experimental data obtained from a synthetic, inorganic model sample, the silica-witherite biomorph. In conclusion, Tex-TOM provides a versatile framework to reconstruct 3D quantitative texture information for polycrystalline samples. In this way, it opens the door for unprecedented insights into the nanostructural makeup of natural and technical materials.

This work proposes an innovative approach to improve Bragg coherent diffraction imaging (BCDI) microscopy applied to time evolving crystals and/or non-homogeneous crystalline strain fields, identified as two major limitations of BCDI microscopy. Speckle BCDI (spBCDI), introduced here, rests on the ability of a strongly non-uniform illumination to induce a convolution of the three-dimensional (3D) frequency content associated with the finite-size crystal and a kernel acting perpendicularly to the illumination beam. In the framework of Bragg diffraction geometry, this convolution is beneficial as it encodes some 3D information about the sample in a single two-dimensional (2D) measurement, i.e., in the detector plane. With this approach, we demonstrate that we can drastically reduce the sampling frequency along the rocking curve direction and still obtain data sets with enough information to be inverted by a traditional phase retrieval algorithm. Numerical simulations, performed for a highly distorted crystal, show that spBCDI allows a gain in the sampling ratio ranging between 4 and 20 along the rocking curve scan, for a speckle illumination with individual speckle size of 50 nm. Furthermore, spBCDI allows working at low intensity levels, leading to an additional gain for the total scanning time. Reductions of a factor of about 32 were numerically observed. Thus, measurements in the 0.3 s time scale at 4th generation synchrotrons become feasible, with a remarkable performance for the imaging of strongly distorted crystals. Practical details on the implementation of the method are also discussed., Comment: 17 pages, 11 figures

We describe a phase-retrieval-based imaging method to directly spatially resolve the vector lattice distortions in an extended crystalline sample by explicit coupling of independent Bragg ptychography data sets into the reconstruction process. Our method addresses this multi-peak Bragg ptychography (MPBP) inverse problem by explicit gradient descent optimization of an objective function based on modeling of the probe-lattice interaction, along with corrective steps to address spurious reconstruction artifacts. Robust convergence of the optimization process is ensured by computing exact gradients with the automatic differentiation capabilities of high-performance computing software packages. We demonstrate MPBP reconstruction with simulated ptychography data mimicking diffraction from a single crystal membrane containing heterogeneities that manifest as phase discontinuities in the diffracted wave. We show the superior ability of such an optimization-based approach in removing reconstruction artifacts compared to existing phase retrieval and lattice distortion reconstruction approaches.

Improving the resolution of fluorescence microscopy beyond the diffraction limit can be achievedby acquiring and processing multiple images of the sample under different illumination conditions.One of the simplest techniques, Random Illumination Microscopy (RIM), forms the super-resolvedimage from the variance of images obtained with random speckled illuminations. However, thevalidity of this process has not been fully theorized. In this work, we characterize mathematicallythe sample information contained in the variance of diffraction-limited speckled images as a functionof the statistical properties of the illuminations. We show that an unambiguous two-fold resolutiongain is obtained when the speckle correlation length coincides with the width of the observationpoint spread function. Last, we analyze the difference between the variance-based techniques usingrandom speckled illuminations (as in RIM) and those obtained using random fluorophore activation(as in Super-resolution Optical Fluctuation Imaging, SOFI).

We propose a combination of microrheological and structural characterizations of fibrin networks to study blood hypercoagulability. Fibrin is the central element of coagulation as its polymerization creates the network of fibers in which platelets and red blood cells are included. This is a controlled process via cascades between various coagulation factors. An alteration in the concentrations of coagulation factors and inhibitors will lead to hypocoagulation or hypercoagulation. These changes in the conditions of polymerization of fibrin lead to the formation of networks with different architectures and thus modify its mechanical behavior. We have performed microrheology by recording Brownian motion of microbeads caught in the network of clots. The structure was quantified under the same polymerization conditions with confocal microscopy images. We have tested our approach by adding fibrinogen to the plasma, which leads to a stiffer, denser network with shorter fibers. The addition of coagulation Factor VIII at 400% induces the same correlated trend between a denser network and a higher modulus. This comparative approach is promising for the study of other conditions altering clot formation and may lead to a new diagnosis approach for hypercoagulability.

Background: Direct dental restoration implies a drying of the dentin substrate. This drying may induce significant strain in the dentin, affecting the bonding efficiency of the restoration. Objective: We measure the dilatation of dentine under changes of relative humidity as well as the impact of humidity on dentin elastic properties. This investigates the role of relative humidity variation during dental surgery on restoration lifetime. Methods: We have coupled an environmental chamber to control both temperature and humidity on the sample, with an optical microscope to measure precisely the strain on the sample surface, after a quantification of the measurement noise. This set-up is used on carefully prepared samples placed on a compression device to measure the elastic parameters. Results: Dentin dilates when the relative humidity increases, with a coefficient of hygroscopic expansion of typically 6.10-3 %.(%RH)-1. This dilatation occurs in about ten minutes. Young modulus and Poisson's ratio are not modified by the variation of relative humidity. Conclusions: Hygroscopic expansion is an order of magnitude larger than thermal expansion during dental surgery: around 0.3% with respect to 0.03%. These levels are low with respect to dental rupture, but may induce a significant decrease of the life-expectancy of a restoration.

Temporal point processes (TPP) are a natural tool for modeling event-based data. Among all TPP models, Hawkes processes have proven to be the most widely used, mainly due to their adequate modeling for various applications, particularly when considering exponential or non-parametric kernels. Although non-parametric kernels are an option, such models require large datasets. While exponential kernels are more data efficient and relevant for specific applications where events immediately trigger more events, they are ill-suited for applications where latencies need to be estimated, such as in neuroscience. This work aims to offer an efficient solution to TPP inference using general parametric kernels with finite support. The developed solution consists of a fast $\ell_2$ gradient-based solver leveraging a discretized version of the events. After theoretically supporting the use of discretization, the statistical and computational efficiency of the novel approach is demonstrated through various numerical experiments. Finally, the method's effectiveness is evaluated by modeling the occurrence of stimuli-induced patterns from brain signals recorded with magnetoencephalography (MEG). Given the use of general parametric kernels, results show that the proposed approach leads to an improved estimation of pattern latency than the state-of-the-art.

One of the major challenges of mid-infrared astronomical heterodyne interferometry is its sensitivity limitations. Detectors capable of handling several 10 GHz bandwidths have been identified as key building blocks of future instruments. Intersubband detectors based on heterostructures have recently demonstrated their ability to provide such performances. In this work we characterize a Quantum Well Infrared Photodetector in terms of noise, dynamic range and bandwidth in a non-interferometric heterodyne set-up. We discuss the possibility to use them on astronomical systems to measure the beating between the local oscillator and the astronomical signal., Comment: 10 pages, 5 figures, SPIE Astronomical Telescopes + Instrumentation, 2022, Montr\'eal, Qu\'ebec, Canada

We present a general analytic approach to spatially resolve the nano-scale lattice distortion field of strained and defected compact crystals with Bragg coherent x-ray diffraction imaging (BCDI). Our approach relies on fitting a differentiable forward model simultaneously to multiple BCDI datasets corresponding to independent Bragg reflections from the same single crystal. It is designed to be faithful to heterogeneities that potentially manifest as phase discontinuities in the coherently diffracted wave, such as lattice dislocations in an imperfect crystal. We retain fidelity to such small features in the reconstruction process through a Fourier transform -based resampling algorithm designed to largely avoid the point spread tendencies of commonly employed interpolation methods. The reconstruction model defined in this manner brings BCDI reconstruction into the scope of explicit optimization driven by automatic differentiation. With results from simulations and experimental diffraction data, we demonstrate significant improvement in the final image quality compared to conventional phase retrieval, enabled by explicitly coupling multiple BCDI datasets into the reconstruction loss function., Comment: 30 pages, 23 figures

The quantitative analysis of non-invasive electrophysiology signals from electroencephalography (EEG) and magnetoencephalography (MEG) boils down to the identification of temporal patterns such as evoked responses, transient bursts of neural oscillations but also blinks or heartbeats for data cleaning. Several works have shown that these patterns can be extracted efficiently in an unsupervised way, e.g., using Convolutional Dictionary Learning. This leads to an event-based description of the data. Given these events, a natural question is to estimate how their occurrences are modulated by certain cognitive tasks and experimental manipulations. To address it, we propose a point process approach. While point processes have been used in neuroscience in the past, in particular for single cell recordings (spike trains), techniques such as Convolutional Dictionary Learning make them amenable to human studies based on EEG/MEG signals. We develop a novel statistical point process model-called driven temporal point processes (DriPP)-where the intensity function of the point process model is linked to a set of point processes corresponding to stimulation events. We derive a fast and principled expectation-maximization (EM) algorithm to estimate the parameters of this model. Simulations reveal that model parameters can be identified from long enough signals. Results on standard MEG datasets demonstrate that our methodology reveals event-related neural responses-both evoked and induced-and isolates non-task specific temporal patterns.