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We study two--loop renormalization in $(2+\epsilon)$--dimensional quantum gravity. As a first step towards the full calculation, we concentrate on the divergences which are proportional to the number of matter fields. We calculate the…

High Energy Physics - Theory · Physics 2016-09-06 Toshiaki Aida , Yoshihisa Kitazawa , Jun Nishimura , Asato Tsuchiya

Recent progress concerning regularization of supersymmetric theories is reviewed. Dimensional reduction is reformulated in a mathematically consistent way, and an elegant and general method is presented that allows to study the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Dominik Stöckinger

The Riesz-Sobolev inequality relates the convolution of nonnegative functions on Euclidean space to the convolution of their symmetric nonincreasing rearrangements. We show that for dimension one, for indicator functions of sets, if the…

Classical Analysis and ODEs · Mathematics 2011-12-19 Michael Christ

High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible to obtain consistent procedures unless $p/n\rightarrow0$, a…

Statistics Theory · Mathematics 2013-03-13 Sahand N. Negahban , Pradeep Ravikumar , Martin J. Wainwright , Bin Yu

We study the multi-channel Gel'fand-Calder\'on inverse problem in two dimensions, i.e. the inverse boundary value problem for the equation $-\Delta \psi + v(x) \psi = 0$, $x\in D$, where $v$ is a smooth matrix-valued potential defined on a…

Analysis of PDEs · Mathematics 2011-07-06 Roman Novikov , Matteo Santacesaria

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to…

Data augmentation has been proven to be an effective technique for developing machine learning models that are robust to known classes of distributional shifts (e.g., rotations of images), and alignment regularization is a technique often…

Machine Learning · Computer Science 2022-06-07 Haohan Wang , Zeyi Huang , Xindi Wu , Eric P. Xing

This work studies the problem of estimating a two-dimensional superposition of point sources or spikes from samples of their convolution with a Gaussian kernel. Our results show that minimizing a continuous counterpart of the $\ell_1$ norm…

Numerical Analysis · Mathematics 2020-08-05 Joseph McDonald , Brett Bernstein , Carlos Fernandez-Granda

The $T\bar{T}$ deformation of a supersymmetric two-dimensional theory preserves the original supersymmetry. Moreover, in several interesting cases the deformed theory possesses additional non-linearly realized supersymmetries. We show this…

High Energy Physics - Theory · Physics 2020-03-18 Christian Ferko , Hongliang Jiang , Savdeep Sethi , Gabriele Tartaglino-Mazzucchelli

We consider a renormalizable two-dimensional model of dilaton gravity coupled to a set of conformal fields as a toy model for quantum cosmology. We discuss the cosmological solutions of the model and study the effect of including the…

High Energy Physics - Theory · Physics 2009-10-22 F. D. Mazzitelli , J. G. Russo

This paper derives a new class of adaptive regularization parameter choice strategies that can be effectively and efficiently applied when regularizing large-scale linear inverse problems by combining standard Tikhonov regularization and…

Numerical Analysis · Mathematics 2019-07-15 Silvia Gazzola , Malena Sabate Landman

We study Tikhonov regularization for solving ill--posed operator equations where the solutions are functions defined on surfaces. One contribution of this paper is an error analysis of Tikhonov regularization which takes into account…

Numerical Analysis · Mathematics 2016-12-15 Guozhi Dong , Bert Juettler , Otmar Scherzer , Thomas Takacs

Initial-boundary value problems in a half-strip with different types of boundary conditions for two-dimensional Zakharov-Kuznetsov equation are considered. Results on global well-posedness in classes of regular solutions in the cases of…

Analysis of PDEs · Mathematics 2019-01-16 Andrei Faminskii

This paper studies an inverse boundary value problem for a semilinear Helmholtz equation with Neumann boundary conditions in a bounded domain $\Omega \subset \mathbb{R}^n$ ($n\ge2$). The objective is to recover the unknown linear and…

Numerical Analysis · Mathematics 2026-03-10 Long-Ling Du , Zejun Sun , Li-Li Wang , Guang-Hui Zheng

As a first application of our renormalisation group approach to non-local matrix models [hep-th/0305066], we prove (super-)renormalisability of Euclidean two-dimensional noncommutative \phi^4-theory. It is widely believed that this model is…

High Energy Physics - Theory · Physics 2016-09-06 Harald Grosse , Raimar Wulkenhaar

The total least squares problem with the general Tikhonov regularization can be reformulated as a one-dimensional parametric minimization problem (PM), where each parameterized function evaluation corresponds to solving an n-dimensional…

Optimization and Control · Mathematics 2018-10-30 Yong Xia , Longfei Wang , Meijia Yang

We formulate a systematic elegant perturbative scheme for determining the eigenvalues of the Helmholtz equation (\bigtriangledown^{2} + k^{2}){\psi} = 0 in two dimensions when the normal derivative of {\psi} vanishes on an irregular closed…

Mathematical Physics · Physics 2013-11-21 S. Panda , S. Chakraborty , S. P. Khastgir

We consider the inverse problem of reconstructing the boundary curve of a cavity embedded in a bounded domain. The problem is formulated in two dimensions for the wave equation. We combine the Laguerre transform with the integral equation…

Numerical Analysis · Mathematics 2025-03-25 Roman Chapko , Leonidas Mindrinos

It is well-known in practice, that L^1 data fitting leads to improved robustness compared to standard L^2 data fitting. However, it is unclear whether resulting algorithms will perform as well in case of regular data without outliers. In…

Numerical Analysis · Mathematics 2026-01-16 Kristina Bätz , Frank Werner

Regularisation allows one to handle ill-posed inverse problems. Here we focus on discrete unfolding problems. The properties of the results are characterised by the consistency between measurements and unfolding result and by the posterior…

Data Analysis, Statistics and Probability · Physics 2023-09-07 Michael Schmelling
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