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Recently a novel real-space RG algorithm was introduced, identifying the relevant degrees of freedom of a system by maximizing an information-theoretic quantity, the real-space mutual information (RSMI), with machine learning methods.…

Conformal field theory (CFT) is an extremely powerful tool for explicitly computing critical exponents and correlation functions of statistical mechanics systems at a second order phase transition, or of condensed matter systems at a…

Mathematical Physics · Physics 2021-02-23 Alessandro Giuliani

With the help of a smooth scaling and coarse-graining approach of observables, developed recently by us in the context of so-called fluctuation operators (inspired by prior work of Verbeure et al) we perform a rigorous renormalisation group…

Mathematical Physics · Physics 2007-05-23 Manfred Requardt

The study of variational quantum algorithms (VQCs) has received significant attention from the quantum computing community in recent years. These hybrid algorithms, utilizing both classical and quantum components, are well-suited for noisy…

We argue that the choice of an appropriate, massive, renormalization scheme can greatly improve the apparent convergence of perturbation theory at finite temperature. This is illustrated by the calculation of the pressure of a scalar field…

High Energy Physics - Phenomenology · Physics 2018-05-09 Jean-Paul Blaizot , Nicolas Wschebor

Commensurate scale relations are perturbative QCD predictions which relate observable to observable at fixed relative scale, such as the ``generalized Crewther relation", which connects the Bjorken and Gross-Llewellyn Smith deep inelastic…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. J. Brodsky , J. Rathsman

In order to model risk aversion in reinforcement learning, an emerging line of research adapts familiar algorithms to optimize coherent risk functionals, a class that includes conditional value-at-risk (CVaR). Because optimizing the…

Machine Learning · Computer Science 2021-03-09 Audrey Huang , Liu Leqi , Zachary C. Lipton , Kamyar Azizzadenesheli

Adaptive importance sampling (AIS) methods are increasingly used for the approximation of distributions and related intractable integrals in the context of Bayesian inference. Population Monte Carlo (PMC) algorithms are a subclass of AIS…

Computation · Statistics 2022-06-08 Víctor Elvira , Émilie Chouzenoux

We investigate the renormalization group optimized perturbation theory (RGOPT) at the next-to-next-to-leading order (NNLO) for the thermal scalar field theory. From comparing three thus available successive RGOPT orders we illustrate the…

High Energy Physics - Phenomenology · Physics 2021-12-01 Loïc Fernandez , Jean-Loïc Kneur

Entropy regularized algorithms such as Soft Q-learning and Soft Actor-Critic, recently showed state-of-the-art performance on a number of challenging reinforcement learning (RL) tasks. The regularized formulation modifies the standard RL…

Machine Learning · Statistics 2019-10-15 Elena Smirnova , Elvis Dohmatob

We study the optimization of nonperturbative renormalization group equations truncated both in fields and derivatives. On the example of the Ising model in three dimensions, we show that the Principle of Minimal Sensitivity can be…

High Energy Physics - Theory · Physics 2010-05-11 L. Canet , B. Delamotte , D. Mouhanna , J. Vidal

Using quantum electrodynamics as an example, a dependence of physical predictions of quantum field theory in a finite perturbation theory order on the choice of renormalization scheme is studied. It is shown that On-Mass-Shell…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. V. Konychev

The renormalization-scheme and scale dependence of the truncated QCD perturbative expansions is one of the main sources of theoretical error of the standard model predictions, especially at intermediate energies. Recently, a class of…

High Energy Physics - Phenomenology · Physics 2018-09-26 Irinel Caprini

Conventional particle theories such as the Standard Model have a number of freely adjustable coupling constants and mass parameters, depending on the symmetry algebra of the local gauge group and the representations chosen for the spinor…

General Relativity and Quantum Cosmology · Physics 2015-05-27 Gerard 't Hooft

In the paper, we analyze the properties of Gross-Llewellyn Smith (GLS) sum rule by using the $\mathcal{O}(\alpha_s^4)$-order QCD corrections with the help of principle of maximum conformality (PMC). By using the PMC single-scale approach,…

High Energy Physics - Phenomenology · Physics 2021-06-23 Xu-Dong Huang , Xing-Gang Wu , Qing Yu , Xu-Chang Zheng , Jun Zeng

In effective field theories, the concept of renormalization of perturbative divergences is replaced by renormalization group concepts such as relevance and universality. Universality is related to cutoff scheme independence in…

High Energy Physics - Theory · Physics 2025-10-09 Jose Gaite

Experimental characterizations of a quantum system involve the measurement of expectation values of observables for a preparable state |psi> of the quantum system. Such expectation values can be measured by repeatedly preparing |psi> and…

Quantum Physics · Physics 2009-11-13 Emanuel Knill , Gerardo Ortiz , Rolando D. Somma

The generator coordinate method (GCM) is an important tool of choice for modeling large-amplitude collective motion in atomic nuclei. The computational complexity of the GCM increases rapidly with the number of collective coordinates. It…

Nuclear Theory · Physics 2023-02-10 X. Zhang , W. Lin , J. M. Yao , C. F. Jiao , A. M. Romero , T. R. Rodríguez , H. Hergert

QCD contributions to the $b \to u \ell^- \bar{\nu}_\ell$ decay rate, which are known to two-loop order in the $\bar{MS}$ scheme, exhibit sufficient dependence on the renormalization mass $\mu$ to compromise phenomenological predictions for…

High Energy Physics - Phenomenology · Physics 2009-11-07 M. R. Ahmady , F. A. Chishtie , V. Elias , A. H. Fariborz , D. G. C. McKeon , T. N. Sherry , T. G. Steele

The phenomenological renormalization group (PRG) has been applied to the study of scaleinvariant phenomena in neuronal data, providing evidence for critical phenomena in the brain. However, it remains unclear how reliably these observed…

Disordered Systems and Neural Networks · Physics 2025-06-18 Kaio F. R. Nascimento , Daniel M. Castro , Gustavo G. Cambrainha , Mauro Copelli