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Nicolas Roy

Publications and source records attributed to Nicolas Roy.

18 recordsLinked to original sources
arXiv2026

Characterization of a low-power 3D photon-to-digital converter readout improved for system integration in meter-scale applications

Digital silicon photomultipliers (dSiPM) are arrays of single photon avalanche diodes (SPADs) where each SPAD has its own electronic readout. To maximize the photodetection area, we developed a readout integrated circuit (ROIC) 3D-integrated to a custom-designed SPAD layer fabricated at Teledyne Dalsa (Bromont, Canada) to form a photon-to-digital converter (PDC). This paper presents an improved version of a previously demonstrated ROIC, fabricated in TSMC 180 nm technology to manage a 64 x 64 pixel architecture. This ROIC has different outputs, such as a flag output that produces a pulse whenever one of the pixels triggers and a digital sum that samples the amount of triggered SPADs. Improvements lead to a reduction of the timing jitter on the flag output from 72.0 ps RMS to 22.6 ps RMS through optimized H-tree design. A tunable hold-off circuit provides adjustable dead time from 32 ns to 18 {\mu}s, addressing both afterpulsing mitigation and SPAD-to-SPAD variations due to process defects. Power consumption is lowered by 30% at trigger rates exceeding 10 kHz through digital logic optimization and clock gating. These measurements validated that the ROIC is ready for 3D integration into a PDC for systems in medical imaging, particle physics, and quantum sciences.

physics.ins-det↗
arXiv2026

The Effect of Geometry on Thermodynamic Response

At the nano- and microscale, various patterns influence and shape thermal and optical response, making them essential for the survival of various biological species. In addition, controlling thermal radiation is vital for a broad range of applications, such as thermal management, spectroscopy, optoelectronics, and energy conversion technologies. For this reason, there is strong pressure to elucidate the physics of thermal radiation at the nanoscale. In this article, we provide evidence that complex nanoscale geometries affect thermal management, leading to an unusual thermal response in heat-capacity measurements as a function of temperature. Beyond identifying the structural constraints associated with this unusual thermodynamic response, the current study introduces the possibility of shaping the apparent heat-capacity response through geometry without necessarily altering the system's chemistry.

cond-mat.mtrl-sci↗
arXiv2026

Dynamically twistable three-dimensional moir\'e photonic crystals

Three-dimensional woodpile photonic crystals constitute one of the most successful architectures for realizing photonic band gaps, yet their optical response is traditionally fixed by the geometry established during fabrication. Here, we introduce a twist-controlled woodpile photonic crystal in which the relative angular orientation between successive rod layers acts as an additional, in situ-tunable geometrical degree of freedom. Using an extension of rigorous coupled-wave analysis adapted to multilayer structures with rotated reciprocal lattices, we systematically investigate the evolution of the transmission spectrum as a function of twist angle. We show that twisting drives the structure through three distinct photonic regimes. In the fully aligned configuration, broad frequency intervals exhibit near-unity transmission. At intermediate twist angles, the spectrum becomes populated by strongly dispersive resonances displaying characteristic Fano line shapes, high quality-factor and pronounced angular sensitivity. As the twist angle approaches 90{\deg}, the conventional woodpile structure is recovered, and these resonances evolve into a broad photonic stop band characteristic of three-dimensional photonic crystals. A simplified analytical model based on reciprocal-lattice considerations accurately reproduces the principal resonance modification observed in the numerical calculations. Our results demonstrate a continuous twist-induced transition from broadband transmission to photonic stop bands through an intermediate Fano-resonant regime, establishing twisted woodpiles as a versatile platform for three-dimensional twist-engineered photonics.

physics.optics↗
arXiv2026

All-optical programming of polarization singularities in a photonic-crystal laser

Singular optics has emerged as an important research area with diverse applications, yet controlling optical singularities in nanophotonic emitters remains largely constrained by the fixed subwavelength geometry of optical resonators. Here, we circumvent this limitation and demonstrate all-optical programming of real-space polarization singularities in a photonic-crystal laser, while preserving a momentum-space vortex inherited from a symmetry-protected bound state in the continuum. The principle is to use a shaped optical pump to create a smooth mesoscopic potential, whose spatial variations are slow compared with the lattice period. This potential localizes a negative-mass Bloch band into trapped lasing states whose envelope functions, and therefore far-field singularity textures, are defined by the pump geometry. Using a honeycomb photonic crystal supporting a symmetry-protected bound state in the continuum, we achieve room-temperature telecom-band lasing with real-space polarization singularities pinned to the critical points of the envelope function, where its gradient vanishes, and reconfigurable in number and position by pump shaping, while the intrinsic momentum-space singularity at the $\Gamma$ point remains fixed. The experimental observations agree quantitatively with an analytical framework combining the Bloch mode of the photonic crystal with envelope-function theory, establishing optical envelope engineering as a route to programmable structured emission from active photonic lattices.

physics.optics↗
arXiv2025

Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches

Chiral photonic metasurfaces provide unique capabilities for tailoring light-matter interactions, which are essential for next-generation photonic devices. Here, we report an advanced optimization framework that combines deep learning and evolutionary algorithms to significantly improve both the design and performance of chiral photonic nanostructures. Building on previous work utilizing a three-layer perceptron reinforced learning and stochastic evolutionary algorithm with decaying changes and mass extinction for chiral photonic optimization, our study introduces a refined pipeline featuring a two-output neural network architecture to reduce the trade-off between high chiral dichroism (CD) and reflectivity. Additionally, we use an improved fitness function, and efficient data augmentation techniques. A comparative analysis between a neural network (NN)-based approach and a genetic algorithm (GA) is presented for structures of different interface pattern depth, material combinations, and geometric complexity. We demonstrate a twice higher CD and the impact of both the corner number and the refractive index contrast at the example of a GaP/air and PMMA/air metasurface as a result of superior optimization performance. Additionally, a substantial increase in the number of structures explored within limited computational resources is highlighted, with tailored spectral reflectivity suggested by our electromagnetic simulations, paving the way for chiral mirrors applicable to polarization-selective light-matter interaction studies.

physics.optics↗
arXiv2025

Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models

Photonic crystals enable fine control over light propagation at the nanoscale, and thus play a central role in the development of photonic and quantum technologies. Photonic band diagrams (BDs) are a key tool to investigate light propagation into such inhomogeneous structured materials. However, computing BDs requires solving Maxwell's equations across many configurations, making it numerically expensive, especially when embedded in optimization loops for inverse design techniques, for example. To address this challenge, we introduce the first approach for BD generation based on diffusion models, with the capacity to later generalize and scale to arbitrary three dimensional structures. Our method couples a transformer encoder, which extracts contextual embeddings from the input structure, with a latent diffusion model to generate the corresponding BD. In addition, we provide insights into why transformers and diffusion models are well suited to capture the complex interference and scattering phenomena inherent to photonics, paving the way for new surrogate modeling strategies in this domain.

physics.optics↗
arXiv2024

Twist-Induced Beam Steering and Blazing Effects in Photonic Crystal Devices

Twisted bilayer photonic crystals introduce a twist between two stacked photonic crystal slabs, enabling strong modulation of their electromagnetic properties. The change in the twist angle strongly influences the resonant frequencies and available propagating diffraction orders with applications including sensing, lasing, slow light or wavefront engineering. In this work, we design and analyze twisted bilayer crystals capable of steering light in a direction controlled by the twist angle. In order to achieve beam steering, the device efficiently routes input power into a single, twist-dependent, transmitted diffraction order. The outgoing light then follows the orientation of this diffraction order, externally controlled by the twist angle. The optimization is performed using high-efficiency heuristic optimization method which enabled a data-oriented approach to further understand the design operation. The optimized device demonstrates an efficiency above 90% across twist angles ranging from 0 to 30 degrees for both TE and TM polarizations. Extending the optimization to include left- and right-handed polarizations yields overall accuracy nearing 90% when averaged across the entire 0 to 60 degrees control range. Finally, we show how the device resembles blazed gratings by effectively canceling the undesired diffraction orders. The optimized devices exhibit a shared slant dependent on the selected diffraction order. Our analysis is supported by a structural blazing model arising from the data-oriented statistical analysis.

physics.optics↗
arXiv2023

Photonic Structures Optimization Using Highly Data-Efficient Deep Learning: Application To Nanofin And Annular Groove Phase Masks

Metasurfaces offer a flexible framework for the manipulation of light properties in the realm of thin film optics. Specifically, the polarization of light can be effectively controlled through the use of thin phase plates. This study aims to introduce a surrogate optimization framework for these devices. The framework is applied to develop two kinds of vortex phase masks (VPMs) tailored for application in astronomical high-contrast imaging. Computational intelligence techniques are exploited to optimize the geometric features of these devices. The large design space and computational limitations necessitate the use of surrogate models like partial least squares Kriging, radial basis functions, or neural networks. However, we demonstrate the inadequacy of these methods in modeling the performance of VPMs. To address the shortcomings of these methods, a data-efficient evolutionary optimization setup using a deep neural network as a highly accurate and efficient surrogate model is proposed. The optimization process in this study employs a robust particle swarm evolutionary optimization scheme, which operates on explicit geometric parameters of the photonic device. Through this approach, optimal designs are developed for two design candidates. In the most complex case, evolutionary optimization enables optimization of the design that would otherwise be impractical (requiring too much simulations). In both cases, the surrogate model improves the reliability and efficiency of the procedure, effectively reducing the required number of simulations by up to 75% compared to conventional optimization techniques.

physics.optics↗
arXiv2009

On the geometry of the space of fibrations

We study geometrical aspects of the space of fibrations between two given manifolds M and B, from the point of view of Frechet geometry. As a first result, we show that any connected component of this space is the base space of a Frechet-smooth principal bundle with the identity component of the group of diffeomorphisms of M as total space. Second, we prove that the space of fibrations is also itself the total space of a smooth Frechet principal bundle with structure group the group of diffeomorphisms of the base B.

math.DG↗
arXiv2008

Semi-classical approach for Anosov diffeomorphisms and Ruelle resonances

In this paper, we show that some spectral properties of Anosov diffeomorphisms can be obtained by semi-classical analysis. In particular the Ruelle resonances which are eigenvalues of the Ruelle transfer operator acting in suitable anisotropic Sobolev spaces and which govern the decay of dynamical correlations, can be treated as the quantum resonances of open quantum systems in the Aguilar-Baslev-Combes theory or the more recent Helffer-Sjostrand phase-space theory.

nlin.CD↗
arXiv2006

Ruelle-Pollicott resonances for real analytic hyperbolic map

We study two simple real analytic uniformly hyperbolic dynamical systems: expanding maps on the circle S1 and hyperbolic maps on the torus T2. We show that the Ruelle-Pollicott resonances which describe time correlation functions of the chaotic dynamics can be obtained as the eigenvalues of a trace class operator in Hilbert space L2(S1) or L2(T2) respectively. The trace class operator is obtained by conjugation of the Ruelle transfer operator in a similar way quantum resonances are obtained in open quantum systems. We comment this analogy.

nlin.CD↗
arXiv2006

Intersections of Lagrangian submanifolds and the Mel'nikov 1-form

We make explicit the geometric content of Mel'nikov's method for detecting heteroclinic points between transversally hyperbolic periodic orbits. After developing the general theory of intersections for pairs of family of Lagrangian submanifolds constrained to live in an auxiliary family of submanifolds, we explain how the heteroclinic orbits are detected by the zeros of the Mel'nikov 1 -form. This 1 -form admits an integral expression, which is non-convergent in general. Finally, we discuss different solutions to this convergence problem.

math-ph↗
arXiv2006

Regular deformations of completely integrable systems

We study several aspects of the regular deformations of completely integrable systems. Namely, we prove the existence of a Hamiltonian normal form for these deformations and we show the necessary and sufficient conditions a perturbation has to satisfy in order for the perturbed Hamiltonian to be a first order deformation.

math.SG↗
arXiv2005

A semi-classical K.A.M. theorem

We consider a semi-classical completely integrable system defined by a $\hbar$-pseudodifferential operator $\hat{H}$ on the torus $\mathbb{T}^{d}$. In order to study perturbed operators of the form $\hat{H}+\hbar^κ\hat{K}$, where $\hat{K}$ is an arbitrary pseudodifferential operator and $κ>0$, we prove the conjugacy to a suitable normal form. This is then used to construct a large number of quasimodes.

math-ph↗
arXiv2004

The geometry of nondegeneracy conditions in completely integrable systems

Nondegeneracy conditions need to be imposed in K.A.M. theorems to insure that the set of diophantine tori has a large measure. Although they are usually expressed in action coordinates, it is possible to give a geometrical formulation using the notion of regular completely integrable systems defined by a fibration of a symplectic manifold by lagrangian tori together with a Hamiltonian function constant on the fibers. In this paper, we give a geometrical definition of different nondegeneracy conditions, we show the implication relations that exist between them, and we show the uniqueness of the fibration for non-degenerate Hamiltonians.

math.DG↗