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Showing 220727 results for "theoretical" · Preprint
Physics Preprint PDF DOI

Observation of Vinen turbulence during far-from-equilibrium Bose-Einstein condensation

Sebastian J. Morris, Martin Gazo, Simon M. Fischer, Haoyu Zhang, Christopher J. Ho, Nigel R. Cooper, Christoph Eigen, Zoran Hadzibabic · 2026

Relaxation of far-from-equilibrium quantum fluids, intimately related to the emergence of long-range order, is theoretically associated with the decay of a turbulent isotropic tangle of vortex lines. …

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AI & Data Science Preprint PDF DOI

An adaptive wavelet-based PINN for problems with localized high-magnitude source

Himanshu Pandey, Ratikanta Behera · 2026

In recent years, physics-informed neural networks (PINNs) have gained significant attention for solving differential equations, although they suffer from two fundamental limitations, namely, spectral …

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Engineering Preprint PDF DOI

Sequential Inference for Gaussian Processes: A Signal Processing Perspective

Daniel Waxman, Fernando Llorente, Petar M. Djuric · 2026

The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support the…

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Computer Science Preprint PDF DOI

Optimal Transmitter Placement in Realistic Urban Environments

Lukas Taus, Richard Tsai, Jeffrey G. Andrews · 2026

In a wireless network, the spatial location of the transmitters has a large impact on the achievable rate at each user location. The optimal placement of -- for example -- cellular base stations is a …

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Physics Preprint PDF DOI

Multi-scale calculation of light-induced structural changes in low-angle twisted bilayer WSe$_2$

Rafael R. Del Grande, David A. Strubbe · 2026

Exciton-phonon interactions in transition metal dichalcogenides (TMD) are strong and lead to phenomena such as coherent phonon generation. When stacked and twisted, their properties can be tuned by th…

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Economics & Finance Preprint PDF DOI

Measuring the risk or reducing it, that is the question: is risk measurement necessary for risk reduction?

Pierpaolo Uberti · 2026

In this research, starting from a widely accepted definition of risk, we support the idea that risk reduction is a more realistic objective than risk minimization, which represents a theoretical utopi…

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AI & Data Science Preprint PDF DOI

Do Sparse Autoencoders Capture Concept Manifolds?

Usha Bhalla, Thomas Fel, Can Rager, Sheridan Feucht, Tal Haklay, Daniel Wurgaft, Siddharth Boppana, Matthew Kowal, Vasudev Shyam, Jack Merullo, Atticus Geiger, Ekdeep Singh Lubana · 2026

Sparse autoencoders (SAEs) are widely used to extract interpretable features from neural network representations, often under the implicit assumption that concepts correspond to independent linear dir…

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AI & Data Science Preprint PDF DOI

Kernel-based independence and mean independence tests for weakly dependent data

Daniel Diz-Castro, Manuel Febrero-Bande, Wenceslao Gonzalez-Manteiga · 2026

We provide a unified framework for independence and mean independence tests based on the Hilbert-Schmidt independence criterion, extending some previous results in the literature to hold in general to…

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Physics Preprint PDF DOI

Observation of the Magnus Nonlinear Hall effect from Chiral Weyl Monopoles

Heda Zhang, Nikolai Peshcherenko, Ning Mao, Nianlong Zou, Jiaqiang Yan, Claudia Felser, Yang Zhang · 2026

The nonlinear Hall effect (NLHE) connects crystalline symmetry to quantum geometry, offering a probe of band topology beyond linear transport. While most studies have focused on the Berry curvature di…

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Physics Preprint PDF DOI

Bound states of solitons in fiber lasers

Yudong Cui, Tianchang Lu, Yusheng Zhang, Dong Mao, Boris A. Malomed · 2026

This article presents a systematic review of theoretical and experimental findings for bound states of two and several dissipative solitons in fiber lasers. The theoretical basis underlying the format…

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Physics Preprint PDF DOI

Source-independent quantum key distribution without pre-sending entanglement

Rong-Zheng Liu, Hua-Lei Yin · 2026

Quantum key distribution (QKD) theoretically offers information-theoretic security. The prevailing approach is the prepare-and-measure BB84 protocol, which implements QKD using conventional laser rath…

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Mathematics Preprint PDF DOI

Hallucination, Abstention, and Recursive Inseparability

Takuma Imamura · 2026

The impossibility of eliminating hallucination, understood here as incorrect definite answers, in sufficiently expressive yes-or-no formal domains is an immediate consequence of classical undecidabili…

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Economics & Finance Preprint PDF DOI

Optimal Consumption and Investment with Energy-Efficiency Adoption

Anthony Britto, Carlos Oliveira, Max Kleinebrahm · 2026

Despite many decades of research, economically grounded models that analyse energy consumption and energy-efficiency adoption within a unified framework remain underdeveloped. This article addresses t…

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Physics Preprint PDF DOI

Topological Susceptibility and QCD at Finite Theta Angle

Claudio Bonanno, Claudio Bonati, Massimo D'Elia · 2026

In this chapter we provide a pedagogical introduction to the main theoretical aspects related to topology and $\theta$-dependence in Quantum Chromo-Dynamics (QCD), and to their phenomenological releva…

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AI & Data Science Preprint PDF DOI

MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness

Jeanne Monnier, Thomas George, Frederic Guyard, Christele Tarnec, Marios Kountouris · 2026

Fairness in machine learning remains challenging due to its ethical complexity, the absence of a universal definition, and the need for context-specific bias metrics. Existing methods still struggle w…

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AI & Data Science Preprint PDF DOI

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning

Zhiqiang Kou, Junxiang Wu, Wenke Huang, Wenwen He, Ming-Kun Xie, Changwei Wang, Yuheng Jia, Di Jiang, Yang Liu, Xin Geng, Qiang Yang · 2026

Federated Multi-Label Learning is a distributed paradigm where multiple clients possess heterogeneous multi-label data and perform collaborative learning under privacy constraints without sharing raw …

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AI & Data Science Preprint PDF DOI

Cost-Aware Learning

Clara Mohri, Amir Globerson, Haim Kaplan, Tomer Koren, Yishay Mansour · 2026

We consider the problem of Cost-Aware Learning, where sampling different component functions of a finite-sum objective incurs different costs. The objective is to reach a target error while minimizing…

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AI & Data Science Preprint PDF DOI

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning

Shijin Gong, Kai Ye, Jin Zhu, Xinyu Zhang, Hongyi Zhou, Chengchun Shi · 2026

Recent advances in large language models (LLMs) have increasingly relied on reinforcement learning (RL) to improve their reasoning capabilities. Three approaches have been widely adopted: (i) Proximal…

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Physics Preprint PDF DOI

Hadron properties at finite temperature

Juan M. Torres-Rincon, Gloria Montana · 2026

This review provides an overview of thermal effects on hadron properties, focusing on the theoretical frameworks used to describe in-medium modifications of masses, decay widths, and spectral function…

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AI & Data Science Preprint PDF DOI

Dynamic Scaled Gradient Descent for Stable Fine-Tuning for Classifications

Nghia Bui, Lijing Wang · 2026

Fine-tuning pretrained models has become a standard approach to adapting pretrained knowledge to improve the accuracy on new sparse, imbalance datasets. However, issues arise when optimization falls i…

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