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Low-energy nuclear structure and reactions can be described in a systematically improvable way using the framework of chiral effective field theory. This requires solving the quantum mechanical many-body problem with regularized nuclear…

Nuclear Theory · Physics 2023-12-22 Hermann Krebs , Evgeny Epelbaum

An inverse boundary value problem for the 1+1 dimensional wave equation $(\partial_t^2 - c(x)^2 \partial_x^2)u(x,t)=0,\quad x\in\mathbb{R}_+$ is considered. We give a discrete regularization strategy to recover wave speed $c(x)$ when we are…

Analysis of PDEs · Mathematics 2018-03-29 Jussi Korpela , Matti Lassas , Lauri Oksanen

We illustrated via the sunset diagram that dimensional regularization 'deforms' the nonlocal contents of multi-loop diagrams with its equivalence to cut-off regularization scheme recovered only after sub-divergence were subtracted. Then we…

High Energy Physics - Phenomenology · Physics 2018-01-17 Ji-Feng Yang

We study the regularization and renormalization of a finite range inverse cube potential in the two- and three-body sectors. Specifically, we compare and contrast three different regulation schemes frequently used to study few-body systems…

Nuclear Theory · Physics 2019-11-13 Daniel Odell , Arnoldas Deltuva , Jose Bonilla , Lucas Platter

Non-stationary blind super-resolution is an extension of the traditional super-resolution problem, which deals with the problem of recovering fine details from coarse measurements. The non-stationary blind super-resolution problem appears…

Information Theory · Computer Science 2019-10-09 Shuang Li , Michael B. Wakin , Gongguo Tang

I comment and summarize the principles underlying the Four Dimensional Regularization/Renormalization (FDR) approach to the UV and IR infinities. A few recent results are also reviewed.

High Energy Physics - Phenomenology · Physics 2018-01-09 Roberto Pittau

We introduce a new class of effective interactions to be used within the energy-density-functional approaches. They are based on regularized zero-range interactions and constitute a consistent application of the effective-theory methodology…

Nuclear Theory · Physics 2012-10-29 J. Dobaczewski , K. Bennaceur , F. Raimondi

A method is introduced to calculate the UV-divergent parts at one-loop level in dimensional regularization. The method is based on the recursion, and the basic integrals are just the scaleless integrals after the recursive reduction, which…

High Energy Physics - Phenomenology · Physics 2012-02-21 Feng Feng

A symmetry-preserving regularization procedure for dealing with the contact interaction model is proposed in this work. This regularization procedure follows a series of consistency conditions which are necessary to maintain gauge symmetry.…

High Energy Physics - Phenomenology · Physics 2023-02-01 Zanbin Xing , Lei Chang

Renormalization group methods can be applied to the nuclear many-body problem using the approach proposed by Shankar. We start with the two-body low momentum interaction V_{low k} and use the RG flow from the particle-hole channels to…

Nuclear Theory · Physics 2008-11-26 Achim Schwenk , Bengt Friman , Gerald E. Brown

The utility of the non-relativistic large-charge EFT for physical systems, and neutron matter in particular, relies on controlled Schr\"odinger-symmetry breaking deformations due to scattering length and effective-range effects in the…

Nuclear Theory · Physics 2025-01-22 Silas R. Beane , Domenico Orlando , Susanne Reffert

We study the ultraviolet problem for models of a finite-dimensional quantum mechanical system linearly coupled to a bosonic quantum field, such as the (many-)spin boson model or its rotating-wave approximation. If the state change of the…

Mathematical Physics · Physics 2025-02-10 Benjamin Hinrichs , Jonas Lampart , Javier Valentín Martín

In this paper, we study the iteration complexity of cubic regularization of Newton method for solving composite minimization problems with uniformly convex objective. We introduce the notion of second-order condition number of a certain…

Optimization and Control · Mathematics 2021-05-21 Nikita Doikov , Yurii Nesterov

Recently, deep learning based methods appeared as a new paradigm for solving inverse problems. These methods empirically show excellent performance but lack of theoretical justification; in particular, no results on the regularization…

Numerical Analysis · Mathematics 2019-01-30 Johannes Schwab , Stephan Antholzer , Markus Haltmeier

Regularization is a popular technique in machine learning for model estimation and avoiding overfitting. Prior studies have found that modern ordered regularization can be more effective in handling highly correlated, high-dimensional data…

Machine Learning · Computer Science 2019-11-01 Mahammad Humayoo , Xueqi Cheng

In this paper, we present a dynamic non-diagonal regularization for interior point methods. The non-diagonal aspect of this regularization is implicit, since all the off-diagonal elements of the regularization matrices are cancelled out by…

Optimization and Control · Mathematics 2019-02-19 Spyridon Pougkakiotis , Jacek Gondzio

Over the last decade, new developments in Similarity Renormalization Group techniques and nuclear many-body methods have dramatically increased the capabilities of ab initio nuclear structure and reaction theory. Ground and excited-state…

Nuclear Theory · Physics 2020-10-09 H. Hergert

A regularization renormalization method ($RRM$) in quantum field theory ($QFT$) is discussed with simple rules: Once a divergent integral $I$ is encountered, we first take its derivative with respect to some mass parameter enough times,…

Quantum Physics · Physics 2010-07-20 Guang-jiong Ni , Jianjun Xu , Senyue Lou

We discuss methods used in mean-field theories to treat pairing correlations within the local density approximation. Pairing renormalization and regularization procedures are compared in spherical and deformed nuclei. Both prescriptions…

Nuclear Theory · Physics 2009-11-11 P. J. Borycki , J. Dobaczewski , W. Nazarewicz , M. V. Stoitsov

Inverse problems are fundamental in fields like medical imaging, geophysics, and computerized tomography, aiming to recover unknown quantities from observed data. However, these problems often lack stability due to noise and…

Numerical Analysis · Mathematics 2024-06-26 Andrea Ebner , Matthias Schwab , Markus Haltmeier