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Analysis of CMS noise reduction for 65 nm CIS

Publications associées (31)

Ultrabroadband sound control with deep-subwavelength plasmacoustic metalayers

Hervé Lissek, Romain Christophe Rémy Fleury, Stanislav Sergeev

Controlling audible sound requires inherently broadband and subwavelength acoustic solutions, which are to date, crucially missing. This includes current noise absorption methods, such as porous materials or acoustic resonators, which are typically ineffic ...

Nature Research2023

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Claudio Bruschini, Edoardo Charbon, Andrei Ardelean, Mohit Gupta

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

Cosmological Fisher forecasts for next-generation spectroscopic surveys

Jean-Paul Richard Kneib, Jiaxi Yu, Cheng Zhao

Next-generation spectroscopic surveys such as the MegaMapper, MUltiplexed Survey Telescope (MUST), MaunaKea Spectroscopic Explorer (MSE), and WideField Spectroscopic Telescope (WST) are foreseen to increase the number of galaxy/quasar redshifts by an order ...

OXFORD UNIV PRESS2023

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Aude Billard, Harshit Khurana

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approa ...

IEEE2023

Front-End Circuits for Radiation-Hard Monolithic CMOS Sensors targeting High-Energy Physics Applications

Francesco Piro

Monolithic pixel sensors integrate the sensor matrix and readout in the same silicon die, and therefore present several advantages over the more largely used hybrid detectors in high-energy physics. They offer an easier detector assembly, lower cost, lower ...

EPFL2023

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

Christoph Max Strössner

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 ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Federated Linear Bandit Learning via Over-the-air Computation

Xin Liu, Ting Wang, Yuning Jiang

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...

IEEE2023

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Emilio Maddalena

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

EPFL2023

Analytical prediction of the final error due to noise in a ϕ-OTDR system

Luc Thévenaz, Li Zhang, Malak Mohamed Hossameldeen Omar Mohamed Galal, Suneetha Sebastian, Yuting Yang

An analytical expression to estimate the uncertainty on the frequency shift in ϕ-OTDR systems is established and confirmed by actual data. ...

Optica Publishing Group2022

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

Alcherio Martinoli, Cyrill Silvan Baumann

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

2022