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Related papers: A variance reduction technique for hadronic correl…

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To take sample biases and skewness in the observations into account, practitioners frequently weight their observations according to some marginal distribution. The present paper demonstrates that such weighting can indeed improve the…

Methodology · Statistics 2018-11-05 Tobias Niebuhr , Mathias Trabs

We present a new method for reducing the stochastic noise of all-to-all propagators based on stopping the inversion of the propagator before convergence. The method is easy to implement, unbiased and independent of the quark action.…

High Energy Physics - Lattice · Physics 2010-01-18 S. Collins , G. Bali , A. Schäfer

We present and test a new method to compute the hadronic vacuum polarization function in lattice simulations. This can then be used, e.g., to determine the leading hadronic contribution to the anomalous magnetic moment of the muon. The…

High Energy Physics - Lattice · Physics 2015-09-30 Gunnar Bali , Gergely Endrodi

Simulations of strongly interacting lattice field theories are typically performed using Markov chain Monte Carlo algorithms. Therefore estimators of statistical errors must incorporate the effect of autocorrelations by integrating the…

High Energy Physics - Lattice · Physics 2026-05-11 Mattia Bruno , Gabriele Morandi

In this paper, we consider the problem of solving a constrained system of nonlinear equations. We propose an algorithm based on a combination of the Newton and conditional gradient methods, and establish its local convergence analysis. Our…

Optimization and Control · Mathematics 2016-08-25 Max L. N. Goncalves , Jefferson G. Melo

Variational hybrid quantum-classical algorithms are some of the most promising workloads for near-term quantum computers without error correction. The aim of these variational algorithms is to guide the quantum system to a target state that…

Quantum Physics · Physics 2021-03-18 Shavindra P. Premaratne , A. Y. Matsuura

A number of machine learning algorithms are using a metric, or a distance, in order to compare individuals. The Euclidean distance is usually employed, but it may be more efficient to learn a parametric distance such as Mahalanobis metric.…

Machine Learning · Computer Science 2016-12-16 Hoel Le Capitaine

We propose a new Nitsche-type approach for weak enforcement of normal velocity boundary conditions for a Lagrangian discretization of the compressible shock-hydrodynamics equations using high-order finite elements on curved boundaries.…

Numerical Analysis · Mathematics 2023-09-06 Nabil M. Atallah , Vladimir Z. Tomov , Guglielmo Scovazzi

We reconsider the option of extracting the transversity distribution by using interference fragmentation functions into two leading hadrons inside the same current jet. To this end, we perform a new study of two-hadron fragmentation…

High Energy Physics - Phenomenology · Physics 2009-11-07 Alessandro Bacchetta , Marco Radici

A sliding-mode-based adaptive boundary control law is proposed for a class of uncertain thermal reaction-diffusion processes subject to matched disturbances. The disturbances are assumed to be bounded, but the corresponding bounds are…

Systems and Control · Electrical Eng. & Systems 2025-10-13 Paul Mayr , Alessandro Pisano , Stefan Koch , Markus Reichhartinger

In this short review paper, we discuss some of the recent advances in the field of parton fragmentation processes into hadrons as well as their possible modifications in QCD media. Hadron production data in e+e-, deep inelastic scattering…

High Energy Physics - Phenomenology · Physics 2009-07-22 Francois Arleo

In this article, we describe an approach for solving partial differential equations with general boundary conditions imposed on arbitrarily shaped boundaries. A continuous function, the domain parameter, is used to modify the original…

Mathematical Physics · Physics 2015-05-28 Hui-Chia Yu , Hsun-Yi Chen , K. Thornton

We present a novel approach for modeling bounded count time series data, by deriving accurate upper and lower bounds for the variance of a bounded count random variable while maintaining a fixed mean. Leveraging these bounds, we propose…

Methodology · Statistics 2024-05-03 Tianqing Liu , Xiaohui Yuan

We propose a novel extremal dependence measure called the partial tail-correlation coefficient (PTCC), in analogy to the partial correlation coefficient in classical multivariate analysis. The construction of our new coefficient is based on…

Methodology · Statistics 2022-11-23 Yan Gong , Peng Zhong , Thomas Opitz , Raphaël Huser

We propose a real-space renormalization group algorithm for accurately coarse-graining two-dimensional tensor networks. The central innovation of our method lies in utilizing variational boundary tensors as a globally optimized environment…

Statistical Mechanics · Physics 2026-03-03 Feng-Feng Song , Naoki Kawashima

High-speed machinery is often designed to pass several $"$critical$"$ speeds, where vibration levels can be very high. To reduce vibrations, rotors usually undergo a mass balancing process, where the machine is rotated at its full speed…

Applied Physics · Physics 2018-03-08 Shachar Tresser , Amit Dolev , Izhak Bucher

We investigate higher-order corrections to correlators in a general CFT (conformal field theory) with the double-trace $T\bar{T}$ deformation. Standard perturbation theory proves inadequate for this problem due to the intricate…

High Energy Physics - Theory · Physics 2025-07-31 Song He , Yuan Sun , Jiashi Yin

The Schroedinger functional provides a valuable tool to perform non-perturbative renormalization on the lattice, in particular in a mass independent scheme. We study two different types of chirally rotated Schroedinger functional boundary…

High Energy Physics - Lattice · Physics 2009-04-14 J. Gonzalez Lopez , K. Jansen , A. Shindler

In this work, we study and evaluate the impact of a periodic spin-lattice coupling in an Ising-like system on a 2D triangular lattice. Our proposed simple Hamiltonian considers this additional interaction as an effect of preferential phonon…

Statistical Mechanics · Physics 2024-01-30 R. M. L. Nascimento , Claudio J. DaSilva , L. S. Ferreira , A. A. Caparica

Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compression on arbitrary graphs. In particular, we introduce a…

Quantum Physics · Physics 2024-01-30 Johnnie Gray , Garnet Kin-Lic Chan
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