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We consider unitary CFTs with continuous global symmetries in $d>2$. We consider a state created by the lightest operator of large charge $Q \gg 1$ and analyze the correlator of two light charged operators in this state. We assume that the…

High Energy Physics - Theory · Physics 2018-06-13 Daniel Jafferis , Baur Mukhametzhanov , Alexander Zhiboedov

Pretraining reinforcement learning methods with demonstrations has been an important concept in the study of reinforcement learning since a large amount of computing power is spent on online simulations with existing reinforcement learning…

Machine Learning · Computer Science 2019-05-10 Xiaoqin Zhang , Yunfei Li , Huimin Ma , Xiong Luo

In this thesis, we analyze unitary conformal field theories in three dimensional spaces by applying analytic conformal bootstrap techniques to correlation functions of non-scalar operators, in particular Majorana fermions. Via the analysis…

High Energy Physics - Theory · Physics 2021-07-30 Soner Albayrak

Fast adversarial training (FAT) is beneficial for improving the adversarial robustness of neural networks. However, previous FAT work has encountered a significant issue known as catastrophic overfitting when dealing with large perturbation…

Machine Learning · Computer Science 2023-08-25 Mengnan Zhao , Lihe Zhang , Yuqiu Kong , Baocai Yin

Two and three-point functions of primary fields in four dimensional CFT have a simple space-time dependences factored out from the combinatoric structure which enumerates the fields and gives their couplings. This has led to the formulation…

High Energy Physics - Theory · Physics 2022-02-22 Robert de Mello Koch , Sanjaye Ramgoolam

This is the second in a series of three articles about recovering the full algebraic structure of a boundary conformal field theory (CFT) from the scaling limit of the critical Ising model in slit-strip geometry. Here we study the fusion…

Mathematical Physics · Physics 2021-08-12 Taha Ameen , Kalle Kytölä , S. C. Park

Foundational optimization embeddings have recently emerged as powerful pre-trained representations for mixed-integer programming (MIP) problems. These embeddings were shown to enable cross-domain transfer and reduce reliance on…

Machine Learning · Computer Science 2026-04-20 Koyena Pal , Serdar Kadioglu

Logarithmic conformal field theories have a vast range of applications, from critical percolation to systems with quenched disorder. In this paper we thoroughly examine the structure of these theories based on their symmetry properties. Our…

High Energy Physics - Theory · Physics 2017-11-22 Matthijs Hogervorst , Miguel Paulos , Alessandro Vichi

Various relations between conformal quantum field theories in one, two and four dimensions are explored. The intention is to obtain a better understanding of 4D CFT with the help of methods from lower dimensional CFT.

Mathematical Physics · Physics 2010-02-03 Marcel Bischoff , Daniel Meise , Karl-Henning Rehren , Ingo Wagner

We study one and two point functions of conformal field theories on spaces of maximal symmetry with and without boundaries and investigate their spectral representations. Integral transforms are found, relating the spectral decomposition to…

High Energy Physics - Theory · Physics 2015-09-30 Kurt Hinterbichler , James Stokes , Mark Trodden

The concept of conformal field theory provides a general classification of statistical systems on two-dimensional geometries at the point of a continuous phase transition. Considering the finite-size scaling of certain special observables,…

Statistical Mechanics · Physics 2017-09-27 M. Weigel , W. Janke

Conformal prediction constructs a confidence set for an unobserved response of a feature vector based on previous identically distributed and exchangeable observations of responses and features. It has a coverage guarantee at any nominal…

Machine Learning · Statistics 2022-12-08 Eugene Ndiaye , Ichiro Takeuchi

This paper deals with the geometric multi-model fitting from noisy, unstructured point set data (e.g., laser scanned point clouds). We formulate multi-model fitting problem as a sequential decision making process. We then use a deep…

Computer Vision and Pattern Recognition · Computer Science 2018-12-31 Zongliang Zhang , Hongbin Zeng , Jonathan Li , Yiping Chen , Chenhui Yang , Cheng Wang

We investigate the structure of conformal manifolds around AdS$_3 \times S^3$ which lift from continuous flat directions in the scalar potential of gauged supergravity resulting from six-dimensional $\mathcal{N}=(1,1)$ supergravity. Our…

High Energy Physics - Theory · Physics 2025-11-06 Bastien Duboeuf , Camille Eloy , Gabriel Larios

In large part, the future utility of modern numerical conformal bootstrap depends on its ability to accurately predict the existence of hitherto unknown non-trivial conformal field theories (CFTs). Here we investigate the extent to which…

High Energy Physics - Theory · Physics 2021-03-31 Matthew T. Dowens , Chris A. Hooley

The soft bootstrap is an on-shell method to constrain the landscape of effective field theories (EFTs) of massless particles via the consistency of the low-energy S-matrix. Given assumptions on the on-shell data (particle spectra, linear…

High Energy Physics - Theory · Physics 2019-02-20 Henriette Elvang , Marios Hadjiantonis , Callum R. T. Jones , Shruti Paranjape

The challenge in the widely applicable online matching problem lies in making irrevocable assignments while there is uncertainty about future inputs. Most theoretically-grounded policies are myopic or greedy in nature. In real-world…

Machine Learning · Computer Science 2022-11-01 Mohammad Ali Alomrani , Reza Moravej , Elias B. Khalil

Quantum field theory (QFT) for interacting many-electron systems is fundamental to condensed matter physics, yet achieving accurate solutions confronts computational challenges in managing the combinatorial complexity of Feynman diagrams,…

High Energy Physics - Theory · Physics 2025-07-21 Pengcheng Hou , Tao Wang , Daniel Cerkoney , Xiansheng Cai , Zhiyi Li , Youjin Deng , Lei Wang , Kun Chen

In this work, we propose an adaptive sparse learning algorithm that can be applied to learn the physical processes and obtain a sparse representation of the solution given a large snapshot space. Assume that there is a rich class of…

Machine Learning · Computer Science 2022-07-26 Yating Wang , Wing Tat Leung , Guang Lin

These pedagogical lectures present some material, classical or more recent, on (Rational) Conformal Field Theories and their general setting ``in the bulk'' or in the presence of a boundary. Two well posed problems are the classification of…

High Energy Physics - Theory · Physics 2007-05-23 Jean-Bernard Zuber