A Scaling Law for SPAD Pixel Miniaturization

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All-solid-state time-resolved cameras based on CMOS single-photon avalanche diode (SPAD) arrays have made very significant advances since the fabrication of the first CMOS SPADs back in 2003. These natively digital sensors are now available in large format ...

The objective of this paper is to investigate a new numerical method for the approximation of the self-diffusion matrix of a tagged particle process defined on a grid. While standard numerical methods make use of long-time averages of empirical means of de ...

Designing SPADs with high sensitivity in a wide wavelength range is crucial since the applications utilizing SPAD-based sensors target different parts of the spectrum. Here, we introduce a novel technique to achieve a wider sensitivity spectrum through the ...

Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

Permeability measurements of engineering textiles exhibit large variability as no standardization method currently exists; numerical permeability prediction is thus an attractive alternative. It has all advantages of virtual material characterization, incl ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data. Yet, wi ...

This 5th annual "Emerging PV Report" highlights the latest advancements in the performance of emerging photovoltaic (e-PV) devices across various e-PV research areas, as documented in peer-reviewed articles published since August 2023. Updated graphs, tabl ...

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

Induced seismicity caused by anthropogenic modification of the subsurface effective stress state has been observed in a number of industrial applications -- from hydrocarbon extraction (e.g., Groningen [1]), drilling waste-water disposal (e.g., [2]) to the ...

The impact of electron cyclotron current drive (ECCD)-driven current on toroidicity-induced Alfven eigenmodes (TAEs) in experiments on the AUG tokamak is investigated numerically. The dynamical evolution of the plasma profiles and equilibria are modelled w ...

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

We study the compact support property for solutions of the following stochastic partial differential equations: partial derivative tu=aijuxixj(t,x)+biuxi(t,x)+cu+h(t,x,u(t,x))F-center dot(t,x),(t,x)is an element of(0,infinity)xRd,where F-center dot is a sp ...

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

A Scaling Law for SPAD Pixel Miniaturization

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A review of recent developments on CMOS single-photon avalanche diode-based cameras for biomedical time-resolved applications

Tensor approximation of the self-diffusion matrix of tagged particle processes

A new double multiplication region method to design high sensitivity and wide spectrum SPADs in standard CMOS technologies

Distributionally Robust Linear Quadratic Control

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Benchmark exercise on image-based permeability determination of engineering textiles: Microscale predictions

Exploiting the Signal-Leak Bias in Diffusion Models

Multi-agent Learning with Privacy Guarantees

Universal and adaptive methods for robust stochastic optimization

The Privacy Power of Correlated Noise in Decentralized Learning

Device Performance of Emerging Photovoltaic Materials (Version 5)

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

A fully-coupled highly-parallelized geomechanical simulator for assessing induced seismicity

Modelling of energetic particle drive and damping effects on TAEs in AUG experiment with ECCD

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

THE COMPACT SUPPORT PROPERTY FOR SOLUTIONS TO THE STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS WITH COLORED NOISE

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

The time-domain Cartesian multipole expansion of electromagnetic fields