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We revisit in this paper the problem of connectivity correlations in the Fortuin-Kasteleyn cluster representation of the two-dimensional $Q$-state Potts model conformal field theory. In a recent work [M. Picco, S. Ribault and R.…

Mathematical Physics · Physics 2018-10-02 Jesper Lykke Jacobsen , Hubert Saleur

We study five-point off-shell conformal integrals and the associated half-BPS correlation functions at two loops in the 't Hooft coupling expansion of maximally supersymmetric Yang-Mills theory. We construct a basis of…

High Energy Physics - Theory · Physics 2026-04-14 Chia-Kai Kuo , Qinglin Yang

We initiate the lightcone bootstrap analysis of multipoint correlators in a defect conformal field theory. The setup we consider is the three-point function of two bulk and one defect operator. Requiring consistency of the crossing equation…

High Energy Physics - Theory · Physics 2026-03-30 Lorenzo Bianchi , Andrea Mattiello , Lorenzo Quintavalle

This research addresses the numerical simulation of the Boltzmann transport equation for semiconductor devices by proposing a multidimensional self-adaptive numerical simulation framework. This framework is applied to two important…

Numerical Analysis · Mathematics 2025-09-22 Zeyu Zhang , Xiaoyu Zhang , Zhigang Song , Qing Fang

We review the recent developments in the study of conformal field theories in generic space time dimensions using the methods of the conformal bootstrap, in its analytic aspect. These techniques are based solely on symmetries, in particular…

High Energy Physics - Theory · Physics 2021-09-27 Agnese Bissi , Parijat Dey , Giulia Fardelli

Flip graphs of combinatorial and geometric objects are at the heart of many deep structural insights and connections between different branches of discrete mathematics and computer science. They also provide a natural framework for the…

Motivated by the pressing request of methods able to create prediction sets in a general regression framework for a multivariate functional response and pushed by new methodological advancements in non-parametric prediction for functional…

Methodology · Statistics 2021-06-04 Jacopo Diquigiovanni , Matteo Fontana , Simone Vantini

We present pySecDec, a new version of the program SecDec, which performs the factorisation of dimensionally regulated poles in parametric integrals, and the subsequent numerical evaluation of the finite coefficients. The algebraic part of…

High Energy Physics - Phenomenology · Physics 2017-11-28 S. Borowka , G. Heinrich , S. Jahn , S. P. Jones , M. Kerner , J. Schlenk , T. Zirke

We study four-point functions of critical percolation in two dimensions, and more generally of the Potts model. We propose an exact ansatz for the spectrum: an infinite, discrete and non-diagonal combination of representations of the…

High Energy Physics - Theory · Physics 2018-04-20 Marco Picco , Sylvain Ribault , Raoul Santachiara

In this note we report an improved determination of the scaling dimensions and OPE coefficients of the minimal supersymmetric extension of the 3d Ising model using the conformal bootstrap. We also show how this data can be used as input to…

High Energy Physics - Theory · Physics 2022-10-04 Alexander Atanasov , Aaron Hillman , David Poland , Junchen Rong , Ning Su

Conformal nets provide a mathematical formalism for conformal field theory. Associated to a conformal net with finite index, we give a construction of the `bundle of conformal blocks', a representation of the mapping class groupoid of…

Mathematical Physics · Physics 2017-01-23 Arthur Bartels , Christopher L. Douglas , André Henriques

We consider conformal prediction for multivariate data and focus on hierarchical data, where some components are linear combinations of others. Intuitively, the hierarchical structure can be leveraged to reduce the size of prediction…

Learning to infer object representations, and in particular part-whole hierarchies, has been the focus of extensive research in computer vision, in pursuit of improving data efficiency, systematic generalisation, and robustness. Models…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Jake Levi , Mark van der Wilk

Modern compression systems use linear transformations in their encoding and decoding processes, with transforms providing compact signal representations. While multiple data-dependent transforms for image/video coding can adapt to diverse…

Image and Video Processing · Electrical Eng. & Systems 2024-11-26 Alessandro Gnutti , Fabrizio Guerrini , Riccardo Leonardi , Antonio Ortega

Conformal prediction gives exact finite-sample coverage guarantees under exchangeability, but deployed systems are judged by more than coverage alone. For a fixed calibrated rule reused over a finite operational window, stakeholders also…

Methodology · Statistics 2026-03-12 Petrus H. Zwart

Developing soft circuits from individual soft logic gates poses a unique challenge: with increasing numbers of logic gates, the design and implementation of circuits leads to inefficiencies due to mathematically unoptimized circuits and…

We introduce a novel method to bootstrap crossing equations in Conformal Field Theory and apply it to finite temperature theories on $S^1\times \mathbb{R}^{d-1}$. The proposed approach does not rely on positivity constraints and does not…

High Energy Physics - Theory · Physics 2025-12-01 V. Niarchos , C. Papageorgakis , A. Stratoudakis , M. Woolley

The Schwinger-Dyson equations for Green functions and 3-vertexes in planar approximation used 50 years ago in the earlier theory of conformal bootstrap are written in frames of the AdS/CFT correspondence. The technique of "Wightman-Witten"…

High Energy Physics - Theory · Physics 2019-05-10 Boris L. Altshuler

This paper investigates a multi-terminal source coding problem under a logarithmic loss fidelity which does not necessarily lead to an additive distortion measure. The problem is motivated by an extension of the Information Bottleneck…

Information Theory · Computer Science 2021-11-29 Matías Vera , Leonardo Rey Vega , Pablo Piantanida

Existing conformal prediction algorithms estimate prediction intervals at target confidence levels to characterize the performance of a regression model on new test samples. However, considering an autonomous system consisting of multiple…

Machine Learning · Computer Science 2023-09-25 Yunye Gong , Yi Yao , Xiao Lin , Ajay Divakaran , Melinda Gervasio