Publication

The local Callan-Symanzik equation: structure and applications

Publications associées (32)

Bootstrapping amplitudes of scalar particles

Quantum Field Theories are a central object of interest of modern physics, describing fundamental interactions of matter. However, current methods give limited insight into strongly coupling theories. S-matrix bootstrap program, described in this thesis, a ...

EPFL2024

Null energy constraints on two-dimensional RG flows

Grégoire Olivier Mathys

We study applications of spectral positivity and the averaged null energy condition (ANEC) to renormalization group (RG) flows in two-dimensional quantum field theory. We find a succinct new proof of the Zamolodchikov c-theorem, and derive further independ ...

Springer Nature2024

Flux correlators and semiclassics

Riccardo Rattazzi, Alexander Monin, Eren Clément Firat, Matthew Thomas Walters

We consider correlators for the flux of energy and charge in the background of operators with large global U(1) charge in conformal field theory (CFT). It has recently been shown that the corresponding Euclidean correlators generically admit a semiclassica ...

Springer Nature2024

Holography and localization of information in quantum gravity

Kyriakos Papadodimas, Alexandre Mathieu Frédéric Belin

Within the AdS/CFT correspondence, we identify a class of CFT operators which represent diff-invariant and approximately local observables in the gravitational dual. Provided that the bulk state breaks all asymptotic symmetries, we show that these operator ...

Springer Nature2024

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Daniel Kressner, Alice Cortinovis

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Siam Publications2024

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

In this work, we investigate the effect of momentum on the optimisation trajectory of gradient descent. We leverage a continuous-time approach in the analysis of momentum gradient descent with step size

\gamma

and momentum parameter

\beta

that allows u ...

2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

On the Generalization of Stochastic Gradient Descent with Momentum

Volkan Cevher, Kimon Antonakopoulos

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Microtome Publishing2024

Bootstrapping smooth conformal defects in Chern-Simons-matter theories

Barak Gabai, Amit Sever

The expectation value of a smooth conformal line defect in a CFT is a conformal invariant functional of its path in space-time. For example, in large N holographic theories, these fundamental observables are dual to the open-string partition function in Ad ...

Springer Nature2024

Bootstrapping amplitudes of scalar particles

Jan Krzysztof Marucha

EPFL2024

Null energy constraints on two-dimensional RG flows

Grégoire Olivier Mathys

Springer Nature2024

Flux correlators and semiclassics

Riccardo Rattazzi, Alexander Monin, Eren Clément Firat, Matthew Thomas Walters

Springer Nature2024

Holography and localization of information in quantum gravity

Kyriakos Papadodimas, Alexandre Mathieu Frédéric Belin

Springer Nature2024

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Daniel Kressner, Alice Cortinovis

Siam Publications2024

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

\gamma

and momentum parameter

\beta

that allows u ...

2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

EPFL2024

On the Generalization of Stochastic Gradient Descent with Momentum

Volkan Cevher, Kimon Antonakopoulos

Microtome Publishing2024

Bootstrapping smooth conformal defects in Chern-Simons-matter theories

Barak Gabai, Amit Sever

Springer Nature2024

Topological photonic transport in disordered scattering networks

Zhechen Zhang

This Ph.D. thesis unveils the unique topological phenomena occurring in such networks, focusing on the intricate interplay between their Floquet topology, the presence of disorder, and their unitary scattering at microscopic and macroscopic scales. Using t ...

EPFL2024