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We use the recently developed Kinetic Field Theory (KFT) for cosmic structure formation to show how non-linear power spectra for cosmic density fluctuations can be calculated in a mean-field approximation to the particle interactions. Our…

Cosmology and Nongalactic Astrophysics · Physics 2021-06-23 Matthias Bartelmann , Johannes Dombrowski , Sara Konrad , Elena Kozlikin , Robert Lilow , Carsten Littek , Christophe Pixius , Felix Fabis

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or…

Human-Computer Interaction · Computer Science 2023-09-13 Jitesh Joshi , Katherine Wang , Youngjun Cho

We evaluate strategies for reducing the run time of fault-tolerant quantum computations, targeting practical utility in scientific or industrial workflows. Delivering a technology with broad impact requires scaling devices, while also…

The nuclear energy density functional method at finite temperature is a useful tool for studies of nuclear structure at high excitation, and also for researches of nuclear matter involved in explosive stellar phenomena and neutron stars.…

Nuclear Theory · Physics 2023-03-02 Takashi Nakatsukasa

[Background] Meticulous modeling of neutrino-nucleus interactions is essential to achieve the unprecedented precision goals of present and future accelerator-based neutrino-oscillation experiments. [Purpose] Confront our calculations of…

The development of systematic effective field theories (EFTs) for nuclear forces and advances in solving the nuclear many-body problem have greatly improved our understanding of dense nuclear matter and the structure of finite nuclei. For…

Nuclear Theory · Physics 2025-09-30 Brendan T. Reed , Matthias Heinz , Pierre Arthuis , Achim Schwenk , Ingo Tews

Quasi-Newton methods are widely used for solving convex optimization problems due to their ease of implementation, practical efficiency, and strong local convergence guarantees. However, their global convergence is typically established…

Optimization and Control · Mathematics 2025-08-28 Artem Agafonov , Vladislav Ryspayev , Samuel Horváth , Alexander Gasnikov , Martin Takáč , Slavomir Hanzely

Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) stands out as a pivotal process for precision tests of the Standard Model electroweak sector, investigations of neutrino properties, and searches for new physics (NP). Recent…

High Energy Physics - Phenomenology · Physics 2026-01-28 Gang Li , Chuan-Qiang Song , Feng-Jie Tang , Jiang-Hao Yu

The density functional theory (DFT) is based on the existence and uniqueness of a universal functional $E[\rho]$, which determines the dependence of the total energy on single-particle density distributions. However, DFT says nothing about…

Nuclear Theory · Physics 2017-04-26 Hana Gil , Panagiota Papakonstantinou , Chang Ho Hyun , Tae-Sun Park , Yongseok Oh

Nuclear lattice effective field theory has become an important framework for quantum many-body calculations in nuclear physics, yet its classical implementation remains increasingly challenging for more general interactions and larger…

Quantum Physics · Physics 2026-04-16 Zhushuo Liu , Jia-ai Shi , Bing-Nan Lu , Xiaosi Xu

Tests of models for new physics appearing in neutrino experiments often involve global fits to a quantum mechanical effect called neutrino oscillations. This paper introduces students to methods commonly used in these global fits starting…

High Energy Physics - Phenomenology · Physics 2024-08-09 J. M. Hardin

Embedding tables are usually huge in click-through rate (CTR) prediction models. To train and deploy the CTR models efficiently and economically, it is necessary to compress their embedding tables at the training stage. To this end, we…

Machine Learning · Computer Science 2024-08-07 Shiwei Li , Huifeng Guo , Lu Hou , Wei Zhang , Xing Tang , Ruiming Tang , Rui Zhang , Ruixuan Li

In recent years, the combination of precise quantum Monte Carlo (QMC) methods with realistic nuclear interactions and consistent electroweak currents, in particular those constructed within effective field theories (EFTs), has lead to new…

Nuclear Theory · Physics 2019-09-04 J. E. Lynn , I. Tews , S. Gandolfi , A. Lovato

The application of the effective field theory (EFT) method to nuclear systems is reviewed. The roles of degrees of freedom, QCD symmetries, power counting, renormalization, and potentials are discussed. EFTs are constructed for various…

Nuclear Theory · Physics 2008-11-26 U. van Kolck

We perform numerical fits of Grand Unified Models based on SO(10), using various combinations of 10-, 120- and 126-dimensional Higgs representations. Both the supersymmetric and non-supersymmetric versions are fitted, as well as both…

High Energy Physics - Phenomenology · Physics 2013-09-17 Alexander Dueck , Werner Rodejohann

This manuscript presents a practical method for incorporating trained Neural Networks (NNs) into the Finite Element (FE) framework using a user material (UMAT) subroutine. The work exemplifies crystal plasticity, a complex inelastic…

Computational Physics · Physics 2024-10-14 Yuqing He , Yousef Heider , Bernd Markert

We introduce CoinFT, a capacitive 6-axis force/torque (F/T) sensor that is compact, light, low-cost, and robust with an average root-mean-squared error of 0.16N for force and 1.08mNm for moment when the input ranges from 0~14N and 0~5N in…

Numerical simulation is an important method for verifying the quantum circuits used to simulate low-energy nuclear states. However, real-world applications of quantum computing for nuclear theory often generate deep quantum circuits that…

Quantum Physics · Physics 2024-06-06 Ang Li , Alessandro Baroni , Ionel Stetcu , Travis S. Humble

We introduce two classes of lightweight, adaptive calibration protocols for quantum computers that leverage fast feedback. The first enables shot-by-shot updates to device parameters using measurement outcomes from simple,…

Quantum Physics · Physics 2025-12-09 Alicia B. Magann , Nathan E. Miller , Robin Blume-Kohout , Peter Maunz , Kevin C. Young

Robust fitting of geometric models is a fundamental task in many computer vision pipelines. Numerous innovations have been produced on the topic, from improving the efficiency and accuracy of random sampling heuristics to generating novel…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Tam Ngoc-Bang Nguyen , Anh-Dzung Doan , Zhipeng Cai , Tat-Jun Chin