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arXiv preprints from January 1, 2026 through September 12, 2026 — 18:01:46 EST

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Posted in math.AT · 2026-01-21 · Marco Praderio Bova

Computing higher limits over the fusion orbit category via amalgams

We study higher limits over the centric orbit category of a fusion system realized by an amalgamated product. In so doing we provide a novel technique for studying the Diaz-Park sharpness conjecture and prove it (in the case of the cohomology Mackey functors) for all the Clelland-Parker and Parker-Stroth fusion systems. This...

💬 0 commentsarXiv:2601.14983v1PDF
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Posted in cs.CR · 2026-01-21 · David Ricardo Saavedra

Interoperable Architecture for Digital Identity Delegation for AI Agents with Blockchain Integration

Verifiable delegation in digital identity systems remains unresolved across centralized, federated, and self-sovereign identity (SSI) environments, particularly where both human users and autonomous AI agents must exercise and transfer authority without exposing primary credentials or private keys. We introduce a unified framework...

💬 0 commentsarXiv:2601.14982v1PDF
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Posted in cond-mat.supr-con · 2026-01-21 · Yi-Li Sun, Ze-Zhong Li, Yang Li, Hong-Lin Zhou, Amit Pokhriyal, Haranath Ghosh, Shi-Liang Li, Hui-Qian Luo

Crystal growth and characterization of a hole-doped iron-based superconductor Ba(Fe$_{0.875}$Ti$_{0.125}$)$_2$As$_2$

We report the crystal growth of a new hole-doped iron-based superconductor Ba(Fe$_{0.875}$Ti$_{0.125}$)$_2$As$_2$ by substituting Ti on the Fe site. The crystals are accidentally obtained in trying to grow Ni doped Ba$_2$Ti$_2$Fe$_2$As$_4$O. After annealing at 500 \textcelsius $ $ in vacuum for one week, superconductivity is observed...

💬 0 commentsarXiv:2601.14981v1PDF
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Posted in cs.DC · 2026-01-21 · Mengchun Xia, Zhicheng Dong, Donghong Cai, Fang Fang, Lisheng Fan, Pingzhi Fan

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks

Distributed computing has been widely applied in distributed edge networks for reducing the processing burden of high-dimensional data centralization, where a high-dimensional computational task is decomposed into multiple low-dimensional collaborative processing tasks or multiple edge nodes use distributed data to train a global...

💬 0 commentsarXiv:2601.14980v1PDF
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Posted in gr-qc · 2026-01-21 · Takuya Katagiri, Vitor Cardoso

The relativistic restricted three-body problem: geometry and motion around tidally perturbed black holes

We investigate the geometry of a tidally deformed, rotating black hole and timelike geodesics in its vicinity. Our framework provides a local picture of the structural evolution of a relativistic restricted three-body problem around a deformed black hole in an adiabatically evolving binary, motivated by various astrophysical settings...

💬 0 commentsarXiv:2601.14979v2PDF
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Posted in cs.CV · 2026-01-21 · Nilanjana Chatterjee, Sidharatha Garg, A V Subramanyam, Brejesh Lall

Unified Multi-Dataset Training for TBPS

Text-Based Person Search (TBPS) has seen significant progress with vision-language models (VLMs), yet it remains constrained by limited training data and the fact that VLMs are not inherently pre-trained for pedestrian-centric recognition. Existing TBPS methods therefore rely on dataset-centric fine-tuning to handle distribution...

💬 0 commentsarXiv:2601.14978v1PDF
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Posted in cs.SI · 2026-01-21 · Nikita Deniskin, Ernesto Estrada

Fractional Diffusion on Graphs: Superposition of Laplacian Semigroups and Memory

Subdiffusion on graphs is often modeled by time-fractional diffusion equations, yet its structural and dynamical consequences remain unclear. We show that subdiffusive transport on graphs is a memory-driven process generated by a random time change that compresses operational time, produces long-tailed waiting times, and breaks...

💬 0 commentsarXiv:2601.14977v1PDF
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Posted in astro-ph.GA · 2026-01-21 · Mengting Ju, Xin Wang, Tucker Jones, Ivana Barišić, Juan M. Espejo Salcedo, Karl Glazebrook, Danail Obreschkow, Takafumi Tsukui, Qianqiao Zhou, Kevin Bundy, Alaina Henry, Matthew A. Malkan, Themiya Nanayakkara, Namrata Roy, Xunda Sun

MSA-3D: Connecting the Chemical and Kinematic Structures of Galaxies at $z \sim 1$

We investigate the connection between ionized gas kinematics and gas-phase metallicity gradients in 21 star-forming galaxies at $0.5 < z < 1.7$ from the MSA-3D survey, using spatially resolved JWST/NIRSpec slit-stepping observations. Galaxy kinematics are characterized by the ratio of rotational velocity to intrinsic velocity...

💬 0 commentsarXiv:2601.14976v2PDF
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Posted in astro-ph.GA · 2026-01-21 · D. Russeil, H. Plana, P. Amram, A. Zavagno, F. Michel

Kinematics of the HII region NGC 7538 from study of the Ha line

Aims. Massive stars impact their surrounding initiating star-formation along their photo-dissociation region. Once the HII region is formed it is unclear if and how the second generation of stars impacts its aspect and evolution. Methods. We performed high spectral resolution (R ~ 23400) Ha Fabry-Perot observations in five fields...

💬 0 commentsarXiv:2601.14975v1PDF
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Posted in cs.RO · 2026-01-21 · Faryal Batool, Iana Zhura, Valerii Serpiva, Roohan Ahmed Khan, Ivan Valuev, Issatay Tokmurziyev, Dzmitry Tsetserukou

HumanDiffusion: A Vision-Based Diffusion Trajectory Planner with Human-Conditioned Goals for Search and Rescue UAV

Reliable human--robot collaboration in emergency scenarios requires autonomous systems that can detect humans, infer navigation goals, and operate safely in dynamic environments. This paper presents HumanDiffusion, a lightweight image-conditioned diffusion planner that generates human-aware navigation trajectories directly from RGB...

💬 0 commentsarXiv:2601.14973v2PDF
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Posted in cond-mat.mtrl-sci · 2026-01-21 · Neeraj Thakur, Anjna Bhardwaj, Arun Kumar, Amarjeet Singh

Pristine and Doped MoS2 Monolayers as Potential HCN Gas Sensors: A DFT Study

Two-dimensional transition metal dichalcogenides (TMDCs) have been extensively investigated due to their tunable properties. In this work, density functional theory (DFT) is employed to investigate the adsorption behavior and sensing characteristics of HCN on pristine and doped MoS2 monolayers (X-MoS2, where X = P, N, Si, Al, B, Cl)....

💬 0 commentsarXiv:2601.14972v1PDF
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Posted in cs.LG · 2026-01-21 · Liping Chen, Mujie Liu, Haytham Fayek

Fine-Grained Traceability for Transparent ML Pipelines

Modern machine learning systems are increasingly realised as multistage pipelines, yet existing transparency mechanisms typically operate at a model level: they describe what a system is and why it behaves as it does, but not how individual data samples are operationally recorded, tracked, and verified as they traverse the pipeline....

💬 0 commentsarXiv:2601.14971v1PDF
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Posted in physics.med-ph · 2026-01-21 · Sune Nørhøj Jespersen, Filip Szczepankiewicz

Beyond directions: Symmetry-aware rotation sets for triaxial diffusion encoding by geometric filter optimization

Purpose: To improve the accuracy of diffusion-weighted powder average signals for diffusion encoding with arbitrary b-tensors. Methods: We identify an intrinsic dihedral ($D_2$) symmetry of diffusion signals for arbitrary diffusion encoding, which defines their natural signal space (a quotient of 3D rotations). Based on this, we...

💬 0 commentsarXiv:2601.14970v2PDF
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Posted in cs.GT · 2026-01-21 · Matthias Gehnen, Julius Stannat

Fog of War Chess

Fog of War chess is a popular variant of classical chess, in which both players have only partial information about the position of the opponent's pieces. This study provides the first theoretical analysis of endgames in Fog of War chess. In particular, we analyze the setups king and queen versus king, king and rook versus king, and...

💬 0 commentsarXiv:2601.18813v1PDF
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Posted in quant-ph · 2026-01-21 · Ernesto Mamedaliev, Vladyslav Libov, Albert Nieto-Morales, Oskar Słowik, Arit Kumar Bishwas

A framework to evaluate the performance of Variational Quantum Algorithms

Variational Quantum Algorithms (VQAs) are promising methods for solving combinatorial optimization problems on noisy intermediate-scale quantum (NISQ) devices. However, benchmarking VQAs is difficult due to their stochastic behavior and the lack of standardized performance criteria. This work introduces a general framework for...

💬 0 commentsarXiv:2601.18812v1PDF
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Posted in q-bio.GN · 2026-01-21 · Yiyao Yang

Robust Machine Learning for Regulatory Sequence Modeling under Biological and Technical Distribution Shifts

Robust machine learning for regulatory genomics is studied under biologically and technically induced distribution shifts. Deep convolutional and attention based models achieve strong in distribution performance on DNA regulatory sequence prediction tasks but are usually evaluated under i.i.d. assumptions, even though real...

💬 0 commentsarXiv:2601.14969v2PDF
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Posted in cs.LG · 2026-01-21 · Mingyue Cheng, Xiaoyu Tao, Huajian Zhang, Qi Liu, Zhiding Liu, Yucong Luo, Yiheng Chen, Enhong Chen

InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement

Most existing time series classification methods adopt a discriminative paradigm that maps input sequences directly to one-hot encoded class labels. While effective, this paradigm struggles to incorporate contextual features and fails to capture semantic relationships among classes. To address these limitations, we propose...

💬 0 commentsarXiv:2601.14968v2PDF
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Posted in hep-lat · 2026-01-21 · Heng-Tong Ding, Hai-Tao Shu, Cheng Zhang

Shear and bulk viscosities of the gluon plasma across the transition temperature from lattice QCD

We investigate the temperature dependence of the shear viscosity ($η$) and bulk viscosity ($ζ$) of the gluon plasma using lattice QCD over the range 0.76--2.25$\,T_c$, extending from below the transition temperature $T_c$ across the transition region and into the deconfined phase. At each temperature, we employ three large, fine...

💬 0 commentsarXiv:2601.14967v2PDF
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Posted in hep-ph · 2026-01-21 · Sagar Airen, Roberto Franceschini

Top quark FCNC in Randall-Sundrum models: post-LHC allowed rates and searches at $e^+e^-$ and $μ^+ μ^-$ colliders

We present the sensitivity to Flavor Changing Neutral Currents (FCNC) in interactions involving the top quark at future $e^+e^-$ and $μ^+μ^-$ machines. We consider the $Ztc$ vertex as well as four-fermion contact interactions involving top and charm quarks. To incorporate limits from (HL-)LHC we consider FCNC from Randall-Sundrum...

💬 0 commentsarXiv:2601.14966v1PDF
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Posted in cs.CE · 2026-01-21 · Moritz Flaschel, Miguel Angel Moreno-Mateos, Simon Wiesheier, Paul Steinmann, Ellen Kuhl

Unsupervised Material Fingerprinting: Ultra-fast hyperelastic model discovery from full-field experimental measurements

Material Fingerprinting is a lookup table-based strategy to discover material models from experimental measurements, which completely avoids the need to solve an optimization problem. In an offline phase, a comprehensive database of simulated material responses, so-called material fingerprints, is generated for a predefined...

💬 0 commentsarXiv:2601.14965v1PDF
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Posted in quant-ph · 2026-01-21 · Robert Amelung, Hanno Sahlmann

Multipartite entanglement in the quantum tetrahedron

The space $\mathrm{Inv}(j_1,j_2,j_3,j_4)$ of SU(2)-invariant four-valent tensors, also known as intertwiners, can be understood as the quantum states of a tetrahedron in Euclidean space with fixed areas. In loop quantum gravity, they are states of the smallest "atom of space" with non-zero volume. At the same time they correspond to...

💬 0 commentsarXiv:2601.14964v1PDF
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Posted in quant-ph · 2026-01-21 · Devashish Pandey, Corne Koks, Martijn Wubs, Nicolas Stenger, Jake Iles-Smith

Resonant Excitation Induced Vibronic Mollow Triplets

The Mollow triplet is the definitive spectral signature of an optically dressed quantum emitter. We predict that for emitters coupled to localized phonons, this signature is not confined to the zero-phonon line. Under a strong resonant drive, we show that Mollow triplets are strikingly replicated on the associated phonon sidebands -a...

💬 0 commentsarXiv:2601.14963v1PDF
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Posted in physics.ed-ph · 2026-01-21 · C. J. A. P. Martins

How to Improve Portuguese Secondary Education

I share some personal thoughts on the status of Portuguese secondary education in general, and of the physics part thereof in particular, drawn from several decades of experience of organizing training activities for students and school teachers, as well as several hundred visits to secondary schools and similar numbers of interviews...

💬 0 commentsarXiv:2601.14962v1PDF
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Posted in q-bio.NC · 2026-01-21 · Zhengdi Zhang, Cong Han, Wenjun Xia

Power-Law Scaling in the Classification Performance of Small-Scale Spiking Neural Networks

This paper investigates the classification capability of small-scale spiking neural networks based on the Leaky Integrate-and-Fire (LIF) neuron model. We analyze the relationship between classification accuracy and three factors: the number of neurons, the number of stimulus nodes, and the number of classification categories. Notably,...

💬 0 commentsarXiv:2601.14961v2PDF