Publications related to Bootstrapping massive quantum field theories

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

Philadelphia2024

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Michel Bierlaire

In this paper, we present a spatial branch and bound algorithm to tackle the continuous pricing problem, where demand is captured by an advanced discrete choice model (DCM). Advanced DCMs, like mixed logit or latent class models, are capable of modeling de ...

2023

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Nonperturbative aspects of scattering amplitudes

Miguel Alexandre Ribeiro Correia

In this thesis we study how physical principles imposed on the S-matrix, such as Lorentz invariance, unitarity, crossing symmetry and analyticity constrain quantum field theories at the nonperturbative level. We start with a pedagogical introduction to the ...

EPFL2023

Towards a nonperturbative construction of the S-matrix

Francesco Riva, Matthew Thomas Walters, Brian Quinn Henning

We present a nonperturbative recipe for directly computing the S-matrix in strongly-coupled QFTs. The method makes use of spectral data obtained in a Hamiltonian framework and can be applied to a wide range of theories, including potentially QCD. We demons ...

SPRINGER2023

Quantum Field Theory in AdS Space instead of Lehmann-Symanzik-Zimmerman Axioms

Xiang Zhao

The boundary correlation functions for a quantum field theory (QFT) in a fixed anti-de Sitter (AdS) background should reduce to S-matrix elements in the flat-space limit. We consider this procedure in detail for four-point functions. With minimal assumptio ...

AMER PHYSICAL SOC2023

IMPROVED VARIANTS OF THE HUTCH plus plus ALGORITHM FOR TRACE ESTIMATION

Daniel Kressner, Ulf David Persson, Alice Cortinovis

This paper is concerned with two improved variants of the Hutch++ algorithm for estimating the trace of a square matrix, implicitly given through matrix-vector products. Hutch++ combines randomized low-rank approximation in a first phase with stochastic tr ...

SIAM PUBLICATIONS2022

Bounds on photon scattering

Denis Karateev, Kelian Philippe Häring, Marco Meineri, Aditya Hebbar

We study 2-to-2 scattering amplitudes of massless spin one particles in

d=4

space-time dimensions, like real world photons. We define a set of non-perturbative observables (Wilson coefficients) which describe these amplitudes at low energies. We use full ...

2022

Non-intrusive double-greedy parametric model reduction by interpolation of frequency-domain rational surrogates

Fabio Nobile, Davide Pradovera

We propose a model order reduction approach for non-intrusive surrogate modeling of parametric dynamical systems. The reduced model over the whole parameter space is built by combining surrogates in frequency only, built at few selected values of the param ...

2021

Bootstrapping massive quantum field theories

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COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Nonperturbative aspects of scattering amplitudes

Towards a nonperturbative construction of the S-matrix

Quantum Field Theory in AdS Space instead of Lehmann-Symanzik-Zimmerman Axioms

IMPROVED VARIANTS OF THE HUTCH plus plus ALGORITHM FOR TRACE ESTIMATION

Bounds on photon scattering

Non-intrusive double-greedy parametric model reduction by interpolation of frequency-domain rational surrogates

Quantum Field Theory in AdS Space instead of Lehmann-Symanzik-Zimmerman Axioms

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Nonperturbative aspects of scattering amplitudes

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Non-intrusive double-greedy parametric model reduction by interpolation of frequency-domain rational surrogates

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Towards a nonperturbative construction of the S-matrix

IMPROVED VARIANTS OF THE HUTCH plus plus ALGORITHM FOR TRACE ESTIMATION

Bounds on photon scattering