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Semi-supervised anomaly detection is based on the principle that potential anomalies are those records that look different from normal training data. However, in some cases we are specifically interested in anomalies that correspond to high…

Machine Learning · Computer Science 2025-06-06 Oliver Urs Lenz , Matthijs van Leeuwen

Within the framework proposed by Caron-Huot and Wilhelm, we give a recipe for computing infrared anomalous dimensions purely on-shell, efficiently up to two loops in any massless theory. After introducing the general formalism and reviewing…

High Energy Physics - Theory · Physics 2023-05-29 Pietro Baratella , Sara Maggio , Michael Stadlbauer , Tobias Theil

The low energy effective action of gravity in any even dimension generally acquires non-local terms associated with the trace anomaly, generated by the quantum fluctuations of massless fields. The local auxiliary field description of this…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Emil Mottola , Ruslan Vaulin

Commute Time Distance (CTD) is a random walk based metric on graphs. CTD has found widespread applications in many domains including personalized search, collaborative filtering and making search engines robust against manipulation. Our…

Artificial Intelligence · Computer Science 2011-07-28 Nguyen Lu Dang Khoa , Sanjay Chawla

Geometric optics is often described as tracing the paths of non-diffracting rays through an optical system. In the paraxial limit, ray traces can be calculated using ray transfer matrices (colloquially, ABCD matrices), which are 2x2…

Optics · Physics 2023-05-24 Theodore A. Corcovilos

Symmetries and anomalies of a $d$-dimensional quantum field theory are often encoded in a $(d+1)$-dimensional topological action, called symmetry topological field theory (TFT). We derive the symmetry TFT for the 2-form and 1-form…

High Energy Physics - Theory · Physics 2022-11-30 Fabio Apruzzi

This paper presents some relations for orthonormal bases in the Minkowski space and isotropic tetrads constructed from the vectors of these bases. As an example of an application of the obtained formulae, in particular recursion relations,…

High Energy Physics - Phenomenology · Physics 2007-05-23 Alexander L. Bondarev

Given trajectories with gaps (i.e., missing data), we investigate algorithms to identify abnormal gaps in trajectories which occur when a given moving object did not report its location, but other moving objects in the same geographic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Arun Sharma , Shashi Shekhar

Quantum communication, while promising unparalleled security, faces significant practical challenges due to imperfections in quantum devices, particularly in single-photon detectors (SPDs). One of the key issues is the impact of dark…

Quantum Physics · Physics 2024-12-12 Hao Shu

We study, in d-dimensions, the random walker with geometrically shrinking step sizes at each hop. We emphasize the integrated quantities such as expectation values, cumulants and moments rather than a direct study of the probability…

Statistical Mechanics · Physics 2009-11-11 Tonguc Rador

Due to the COVID-19 pandemic, there is an increasing demand for portable CT machines worldwide in order to diagnose patients in a variety of settings. This has led to a need for CT image reconstruction algorithms that can produce high…

Numerical Analysis · Mathematics 2025-12-10 Mai Phuong Pham Huynh , Manuel Santana , Ana Castillo

Many stochastic systems in physics and biology are investigated by recording the two-dimensional (2D) positions of a moving test particle in regular time intervals. The resulting sample trajectories are then used to induce the properties of…

Quantitative Methods · Quantitative Biology 2012-08-27 Claus Metzner

The trace anomaly for nonminimally coupled scalars in spherically reduced gravity obtained by Bousso and Hawking (hep-th/9705236) is incorrect. We explain the reasons for the deviations from our correct (published) result which is supported…

High Energy Physics - Theory · Physics 2016-08-25 W. Kummer , H. Liebl , D. V. Vassilevich

When gauging a $(d-1)$-form symmetry in $d$ spacetime dimensions, one formally expects the gauged theory to carry a dual $-1$-form symmetry. This work focuses on the study of such symmetries, in particular via the spacetime-filling…

High Energy Physics - Theory · Physics 2022-11-09 Thomas Vandermeulen

We study the random walk $X$ on the range of a simple random walk on $\mathbb{Z}^d$ in dimensions $d\geq 4$. When $d\geq 5$ we establish quenched and annealed scaling limits for the process $X$, which show that the intersections of the…

Probability · Mathematics 2015-06-11 David A. Croydon

In the domain of anomaly detection, methods often excel in either high-level semantic or low-level industrial benchmarks, rarely achieving cross-domain proficiency. Semantic anomalies are novelties that differ in meaning from the training…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Luc P. J. Sträter , Mohammadreza Salehi , Efstratios Gavves , Cees G. M. Snoek , Yuki M. Asano

We give a new computational method to obtain symmetries of ordinary differential equations. The proposed approach appears as an extension of a recent algorithm to compute variational symmetries of optimal control problems [Comput. Methods…

Classical Analysis and ODEs · Mathematics 2009-11-13 Paulo D. F. Gouveia , Delfim F. M. Torres

In this article we propose a consistent scheme of doing computations directly in four dimensions using conventional quantum field theory methods. This work is continuation of a stochastic quantization program reported earlier.

High Energy Physics - Theory · Physics 2021-07-20 A. K. Kapoor

We give a dimensionality reduction procedure to approximate the sum of distances of a given set of $n$ points in $R^d$ to any "shape" that lies in a $k$-dimensional subspace. Here, by "shape" we mean any set of points in $R^d$. Our…

Data Structures and Algorithms · Computer Science 2021-06-25 Zhili Feng , Praneeth Kacham , David P. Woodruff

Learning a latent embedding to understand the underlying nature of data distribution is often formulated in Euclidean spaces with zero curvature. However, the success of the geometry constraints, posed in the embedding space, indicates that…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Jie Hong , Pengfei Fang , Weihao Li , Junlin Han , Lars Petersson , Mehrtash Harandi