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Related papers: Snowmass White Paper: The Numerical Conformal Boot…

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In this thesis, we introduce new tools for the conformal bootstrap, autoboot and qboot. Each tool solves a different step in the whole computational stack, and combined with an existing efficient tool SDPB which solves semidefinite…

High Energy Physics - Theory · Physics 2020-06-09 Mocho Go

The bootstrap is a method for estimating the distribution of an estimator or test statistic by re-sampling the data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap…

Econometrics · Economics 2018-09-12 Joel L. Horowitz

This is a review of two-dimensional conformal field theory including some of the relations to integrable models. An effort is made to develop the basic formalism in a way which is as elementary and flexible as possible at the same time.…

High Energy Physics - Theory · Physics 2017-08-04 Joerg Teschner

The status of stochastic cooling and developments over the years are reviewed with reference to much of the original work. Both theoretical and technological subjects are considered.

Accelerator Physics · Physics 2008-11-26 John Marriner

In this paper, we will provide an overview of the current state-of-the-art with regards to so-called cold boot attacks, their practical applicability and feasibility, potential counter-measures and their effectiveness.

Cryptography and Security · Computer Science 2014-08-05 Jos Wetzels

We study the numerical bounds obtained using a conformal-bootstrap method - advocated in ref. [1] but never implemented so far - where different points in the plane of conformal cross ratios $z$ and $\bar z$ are sampled. In contrast to the…

High Energy Physics - Theory · Physics 2016-11-04 Alejandro Castedo Echeverri , Benedict von Harling , Marco Serone

The numerical conformal bootstrap is used to study mixed correlators in $\mathcal{N}=1$ superconformal field theories (SCFTs) in $d=4$ spacetime dimensions. Systems of four-point functions involving scalar chiral and real operators are…

High Energy Physics - Theory · Physics 2017-08-02 Daliang Li , David Meltzer , Andreas Stergiou

Conformal nets are a mathematical model for conformal field theory, and defects between conformal nets are a model for an interaction or phase transition between two conformal field theories. In the preceding paper of this series, we…

Category Theory · Mathematics 2019-05-17 Arthur Bartels , Christopher L. Douglas , André Henriques

This is the working summary of the Accelerator Science working group of the Computing Frontier of the Snowmass meeting 2013. It summarizes the computing requirements to support accelerator technology in both Energy and Intensity Frontiers.

The Snowmass 2021 Implementation Task Force has been established to evaluate the proposed future accelerator projects for performance, technology readiness, schedule, cost, and environmental impact. Corresponding metrics has been developed…

We propose a multi-scale extension of conformal prediction, an approach that constructs prediction sets with finite-sample coverage guarantees under minimal statistical assumptions. Classic conformal prediction relies on a single notion of…

Statistics Theory · Mathematics 2025-02-11 Ali Baheri , Marzieh Amiri Shahbazi

This paper proposes a new method of probabilistic prediction, which is based on conformal prediction. The method is applied to the standard USPS data set and gives encouraging results.

Machine Learning · Computer Science 2014-06-24 Vladimir Vovk , Ivan Petej , Valentina Fedorova

In this paper, we present a general review of the status of numerical modelling applied to the design of high temperature superconductor (HTS) devices. The importance of this tool is emphasized at the beginning of the paper, followed by…

Superconductivity · Physics 2017-05-30 Frédéric Sirois , Francesco Grilli

Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable. It is popular as it comes with theoretical guarantees on…

Machine Learning · Statistics 2025-12-01 Jase Clarkson , Wenkai Xu , Mihai Cucuringu , Yvik Swan , Gesine Reinert

This review aims to offer a pedagogical introduction to the analytic conformal bootstrap program via a journey through selected topics. We review analytic methods which include the large spin perturbation theory, Mellin space methods and…

High Energy Physics - Theory · Physics 2022-10-26 Agnese Bissi , Aninda Sinha , Xinan Zhou

This guide aims at providing a general introduction to bootstrap methods. By using simple examples taken from nuclear physics, I discuss how such a method can be used to quantify error bars of an estimator. I also investigate the use of…

Nuclear Theory · Physics 2019-05-22 A. Pastore

These notes are from courses given at TASI and the Advanced Strings School in summer 2015. Starting from principles of quantum field theory and the assumption of a traceless stress tensor, we develop the basics of conformal field theory,…

High Energy Physics - Theory · Physics 2016-02-26 David Simmons-Duffin

We provide a process on the space of coalescing cadlag stable paths and show convergence in the appropriate topology for coalescing stable random walks on the integer lattice.

Probability · Mathematics 2019-05-21 Thomas Mountford , Krishnamurthi Ravishankar , Glauco Valle

We provide an overview of the xFitter open-source software package, review the general capabilities of the program, and highlight applications relevant to the Snowmass study. An updated version of the program (2.2.0) is available on CERN…

In recent years, increasingly unpredictable and severe global weather patterns have frequently caused long-lasting power outages. Building resilience, the ability to withstand, adapt to, and recover from major disruptions, has become…

Machine Learning · Statistics 2024-11-27 Hanyang Jiang , Yao Xie , Feng Qiu