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Concept

Transformation de Fourier discrète

Publications associées (30)

A low-temperature prismatic slip instability in Mg understood using machine learning potentials

William Curtin, Xin Liu, Binglun Yin

Prismatic slip in magnesium at temperatures T

PERGAMON-ELSEVIER SCIENCE LTD2023

DFT plus U-type functional derived to explicitly address the flat plane condition

Edward Baxter Linscott, David Daniel O'Regan

A DFT+U-type corrective functional is derived from first principles to enforce the flat plane condition on localized subspaces, thus dispensing with the need for an ad hoc derivation from the Hubbard model. Small, molecular test systems at the dissociated ...

AMER PHYSICAL SOC2023

Thermodynamic bounds on time-reversal asymmetry

Shiling Liang

Quantifying irreversibility of a system using finite information constitutes a major challenge in stochastic thermodynamics. We introduce an observable that measures the time-reversal asymmetry between two states after a given time lag. Our central result ...

Amer Physical Soc2023

Dissipative Solitons and Switching Waves in Dispersion-Modulated Kerr Cavities

Tobias Kippenberg, Rui Ning Wang, Johann Emmeram Riemensberger, Miles Henry Anderson, Alexey Tikan, Aleksandr Tusnin, Alisa Davydova

We theoretically and experimentally investigate the formation of dissipative coherent structures in Kerr nonlinear optical microresonators, whose spectrum encompasses an integrated dispersion that exceeds the cavity free-spectral range. We are able to acce ...

American Physical Society2023

A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Michel Bierlaire

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

2023

Electron spectrometer calibration method

Tobias Kippenberg, Fabrizio Carbone, Arslan Sajid Raja, Thomas La Grange, Yujia Yang, Alexey Sapozhnik, Bruce Michael Raleigh Weaver, Paolo Cattaneo

The present invention concerns an energy dispersion calibration method for calibrating an electron spectrometer of an electron spectrometer system including at least one electron emission source, electron optics and the electron spectrometer. The method co ...

2023

Fully solvable finite simplex lattices with open boundaries in arbitrary dimensions

Fabrizio Minganti

Finite simplex lattice models are used in different branches of science, e.g., in condensed-matter physics, when studying frustrated magnetic systems and non-Hermitian localization phenomena; or in chemistry, when describing experiments with mixtures. An n ...

Amer Physical Soc2023

Two-particle azimuthal correlations in γp interactions using pPb collisions at √sNN=8.16 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Jessica Prisciandaro, Peter Hansen, Xin Chen, Michele Bianco, Sebastiana Gianì, Davide Di Croce, Arvind Shah, Wei Sun, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Federica Legger, Bandeep Singh

The first measurements of the Fourier coefficients (V-n Delta) of the azimuthal distributions of charged hadrons emitted from photon-proton (gamma p) interactions are presented. The data are extracted from 68.8nb(-1) of ultra-peripheral proton-lead (pPb) c ...

Elsevier2023

Causal inference with recurrent and competing events

Mats Julius Stensrud, Pal Christie Ryalen, Matias Janvin

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023