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arXiv preprints from January 1, 2026 through September 22, 2026 — 09:01:03 EST

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Posted in quant-ph · 2026-01-15 · Daniel Allepuz-Requena, Zohran Ali, Dennis Høj, Yingxuan Chen, Luiz Couto Correa Pinto Filho, Alexander Huck, Ulrik L. Andersen

Mitigating nonlinear transduction noise in high-cooperativity cavity optomechanics

Coupling mechanical motion to an optical resonator enables displacement measurements approaching the standard quantum limit (SQL). However, increasing the optomechanical coupling strength will inevitably lead to probing of the nonlinear response of the optical resonator. Thermal intermodulation noise (TIN) arising from the nonlinear...

💬 0 commentsarXiv:2601.10689v1PDF
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Posted in cs.HC · 2026-01-15 · Rubel Hassan Mollik, Vamsi Krishna Kosuri, Hans Djalali, Stephanie Ludi, Aboubakar Mountapmbeme

An Extension-Based Accessibility Framework for Making Blockly Accessible to Blind and Low-Vision Users

Block-based programming environments (BBPEs) such as Scratch and Code.org are now widely used in K-12 computer science classes, but they remain mostly inaccessible to blind or visually impaired (BVI) learners. A major problem is that prior accessibility solutions have relied on modifications to the Blockly library, making them...

💬 0 commentsarXiv:2601.10688v1PDF
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Posted in cs.CV · 2026-01-15 · Kumar Ashutosh, XuDong Wang, Xi Yin, Kristen Grauman, Adam Polyak, Ishan Misra, Rohit Girdhar

Human detectors are surprisingly powerful reward models

Video generation models have recently achieved impressive visual fidelity and temporal coherence. Yet, they continue to struggle with complex, non-rigid motions, especially when synthesizing humans performing dynamic actions such as sports, dance, etc. Generated videos often exhibit missing or extra limbs, distorted poses, or...

💬 0 commentsarXiv:2601.14037v2PDF
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Posted in eess.SP · 2026-01-15 · Nursultan Daupayev, Christian Engel, Ricky Bendyk, Soeren Hirsch

Adaptive algorithm for microsensor in sustainable environmental monitoring

Traditional data collection from sensors produce a lot of data, which lead to constant power consumption and require more storage space. This study proposes an algorithm for a data acquisition and processing method based on Fourier transform (DFT), which extracts dominant frequency components using harmonic analysis (HA) to identify...

💬 0 commentsarXiv:2601.10780v1PDF
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Posted in cs.LG · 2026-01-15 · Qingyue Zhang, Chang Chu, Haohao Fu, Tianren Peng, Yanru Wu, Guanbo Huang, Yang Li, Shao-Lun Huang

Unified Optimization of Source Weights and Transfer Quantities in Multi-Source Transfer Learning: An Asymptotic Framework

In multi-source transfer learning, a key challenge lies in how to appropriately differentiate and utilize heterogeneous source tasks. However, existing multi-source methods typically focus on optimizing either the source weights or the amount of transferred samples, largely neglecting their joint consideration. In this work, we...

💬 0 commentsarXiv:2601.10779v2PDF
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Posted in math.NT · 2026-01-15 · Daniel Barake, Owen Chuchman, Cameron Franc, Geoffrey Mason, Brett Nasserden

Vertex operator algebra bundles on modular curves and their associated modular forms

This paper describes the vector bundle on the elliptic modular curve that is associated to a vertex operator algebra $V$ (VOA) or more generally a quasi-vertex operator algebra (QVOA), with a view towards future applications aimed at studying the characters of VOAs. We explain how the modes of sections of $V$ give rise naturally to...

💬 0 commentsarXiv:2601.10686v1PDF
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Posted in cs.IT · 2026-01-15 · Jing Qiu, Weijun Fang, Shu-Tao Xia, Fang-Wei Fu

Reed-Solomon Codes with Optimal Repair Bandwidth: A Basis-Transformation Approach

Maximum distance separable (MDS) codes are widely used in distributed storage, but naively repairing a single failure in an $(n,k)$ MDS code requires downloading the full contents of $k$ surviving nodes. Minimum storage regenerating (MSR) codes, introduced by Dimakis et al., minimize repair bandwidth while preserving the MDS property...

💬 0 commentsarXiv:2601.10685v3PDF
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Posted in cs.LG · 2026-01-15 · Maissam Barkeshli, Alberto Alfarano, Andrey Gromov

On the origin of neural scaling laws: from random graphs to natural language

Scaling laws have played a major role in the modern AI revolution, providing practitioners predictive power over how the model performance will improve with increasing data, compute, and number of model parameters. This has spurred an intense interest in the origin of neural scaling laws, with a common suggestion being that they arise...

💬 0 commentsarXiv:2601.10684v1PDF
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Posted in quant-ph · 2026-01-15 · Kean Chen, Zhicheng Zhang, Nengkun Yu

Optimal lower bound for quantum channel tomography in away-from-boundary regime

Consider quantum channels with input dimension $d_1$, output dimension $d_2$ and Kraus rank at most $r$. Any such channel must satisfy the constraint $rd_2\geq d_1$, and the parameter regime $rd_2=d_1$ is called the boundary regime. In this paper, we show an optimal query lower bound $Ω(rd_1d_2/\varepsilon^2)$ for quantum channel...

💬 0 commentsarXiv:2601.10683v1PDF
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Posted in cs.IT · 2026-01-15 · Praneeth Kumar Vippathalla, Justin P. Coon, Mihai-Alin Badiu

On the Entropy of a Random Geometric Graph

In this paper, we study the entropy of a hard random geometric graph (RGG), a commonly used model for spatial networks, where the connectivity is governed by the distances between the nodes. Formally, given a connection range $r$, a hard RGG $G_m$ on $m$ vertices is formed by drawing $m$ random points from a spatial domain, and then...

💬 0 commentsarXiv:2601.10778v1PDF
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Posted in cs.IT · 2026-01-15 · Pin-Hsun Lin, Hadi Aghaee, Christian Deppe, Eduard A. Jorswieck, Holger Boche

Implementation of Oblivious Transfer over Binary-Input AWGN Channels by Polar Codes

We develop a one-out-of-two oblivious transfer protocol over the binary-input additive white Gaussian noise (BI-AWGN) channel using polar codes. The scheme uses two decoder views linked by automorphisms of the polar transform and publicly draws the encoder at random from the corresponding automorphism group. This yields perfect...

💬 0 commentsarXiv:2601.10682v2PDF
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Posted in cs.AI · 2026-01-15 · Amir Khurshid, Abhishek Sehgal

Structure and Diversity Aware Context Bubble Construction for Enterprise Retrieval Augmented Systems

Large language model (LLM) contexts are typically constructed using retrieval-augmented generation (RAG), which involves ranking and selecting the top-k passages. The approach causes fragmentation in information graphs in document structures, over-retrieval, and duplication of content alongside insufficient query context, including...

💬 0 commentsarXiv:2601.10681v1PDF
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Posted in hep-th · 2026-01-15 · V. E. Didenko

Irregular higher-spin generating equations and chiral perturbation theory

We present a complementary approach to the standard Vasiliev framework for nonlinear higher-spin interactions in four dimensions, aimed at identifying their minimally nonlocal form. Our proposal introduces a generating system for higher-spin vertices at the level of classical equations, which we refer to as irregular, in contrast to...

💬 0 commentsarXiv:2601.10680v1PDF
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Posted in cs.AI · 2026-01-15 · Zirui Ren, Ziming Liu

Are Your Reasoning Models Reasoning or Guessing? A Mechanistic Analysis of Hierarchical Reasoning Models

Hierarchical reasoning model (HRM) achieves extraordinary performance on various reasoning tasks, significantly outperforming large language model-based reasoners. To understand the strengths and potential failure modes of HRM, we conduct a mechanistic study on its reasoning patterns and find three surprising facts: (a) Failure of...

💬 0 commentsarXiv:2601.10679v2PDF
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Posted in cs.IT · 2026-01-15 · Aviv Adler, Jennifer Tang

Synchronizing Probabilities in Model-Driven Lossless Compression

It is well-known in the field of lossless data compression that probabilistic next-symbol prediction can be used to compress sequences of symbols. Deep neural networks are able to capture rich dependencies in data, offering a powerful means of estimating these probabilities and hence an avenue towards more effective compression...

💬 0 commentsarXiv:2601.10678v2PDF
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Posted in cs.IT · 2026-01-15 · Lei Hu, Mohamed Nomeir, Alptug Aytekin, Sennur Ulukus

Breaking the Storage-Bandwidth Tradeoff in Distributed Storage with Quantum Entanglement

This work investigates the use of quantum resources in distributed storage systems. Consider an $(n,k,d)$ distributed storage system in which a file is stored across $n$ nodes such that any $k$ nodes suffice to reconstruct the file. When a node fails, any $d$ helper nodes transmit information to a newcomer to rebuild the system. In...

💬 0 commentsarXiv:2601.10676v1PDF
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Posted in astro-ph.SR · 2026-01-15 · Haopeng Wang, Stefaan Poedts, Andrea Lani, Junyan Liu, Quentin Noraz, Luis Linan, Tinatin Baratashvili, Hyun-Jin Jeong, Rayan Dhib, Wenwen Wei, Jia Huang, Mahdi Najafi-Ziyazi, Hao Wu, Rui Zhuo, José M. L. Murteira, Ketevan Arabuli, Brigitte Schmieder, Jasmina Magdalenić Zhukov

MHD modeling of magnetic flux evolution around solar maximum by the coronal model COCONUT

In this paper, we simulate the magnetic flux evolution at different heliocentric distances during two solar-maximum Carrington rotations (CRs) using the time-evolving coronal magnetohydrodynamic (MHD) model COCONUT to investigate the ``open flux problem". The simulated open magnetic flux (OMF) near the solar surface is comparable to...

💬 0 commentsarXiv:2601.10675v2PDF
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Posted in hep-th · 2026-01-15 · Lorenzo Ricci, Raman Sundrum

Energy Correlators in Warped Geometries

We study Energy Correlators as probes of strongly-coupled nearly-conformal field theories within their holographically dual descriptions, focusing on the important features that appear in realistic theories going beyond the standard model. In particular, we study warped geometries which asymptote to $\text{AdS}_5$, as well as...

💬 0 commentsarXiv:2601.10674v1PDF
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Posted in cs.LG · 2026-01-15 · Aditya Agrawal, Albert Magyar, Hiteshwar Eswaraiah, Patrick Sheridan, Pradeep Janedula, Ravi Krishnan Venkatesan, Krishna Nair, Ravi Iyer

Single-Stage Huffman Encoder for ML Compression

Training and serving Large Language Models (LLMs) require partitioning data across multiple accelerators, where collective operations are frequently bottlenecked by network bandwidth. Lossless compression using Huffman codes is an effective way to alleviate the issue, however, its three-stage design requiring on-the-fly frequency...

💬 0 commentsarXiv:2601.10673v1PDF
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Posted in quant-ph · 2026-01-15 · Carlo Cafaro, James Schneeloch

Efficiency, Curvature, and Complexity of Quantum Evolutions for Qubits in Nonstationary Magnetic Fields

In optimal quantum-mechanical evolutions, motion can take place along paths of minimal length within an optimal time frame. Alternatively, optimal evolutions may occur along established paths without any waste of energy resources and achieving 100% speed efficiency. Unfortunately, realistic physical scenarios often lead to...

💬 0 commentsarXiv:2601.10672v1PDF
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Posted in eess.SY · 2026-01-15 · Trager Joswig-Jones, Baosen Zhang

Safe Trajectory Gradient Flow Control of a Grid-Interfacing Inverter

Grid-interfacing inverters serve as the interface between renewable energy resources and the electric power grid, offering fast, programmable control capabilities. However, their operation is constrained by hardware limitations, such as bounds on the current magnitude. Existing control methods for these systems often neglect these...

💬 0 commentsarXiv:2601.10671v1PDF
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Posted in math.RT · 2026-01-15 · Archita Gupta, Tejbir Lohan, Pooja Singla

Real characters and real classes of $\mathrm{GL}_2$ and $\mathrm{GU}_2$ over discrete valuation rings

Let $\mathfrak{o}$ be the ring of integers of a non-archimedean local field with residue field of odd characteristic, $\mathfrak{p}$ be its maximal ideal and let $\mathfrak{o}_\ell = \mathfrak{o}/\mathfrak{p}^\ell$ for $\ell\ge 2$. In this article, we study real-valued characters and real representations of the finite groups...

💬 0 commentsarXiv:2601.10670v1PDF
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Posted in cs.LG · 2026-01-15 · Zhang Xiaocai, Xiao Zhe, Liang Maohan, Liu Tao, Li Haijiang, Zhang Wenbin

Realistic Curriculum Reinforcement Learning for Autonomous and Sustainable Marine Vessel Navigation

Sustainability is becoming increasingly critical in the maritime transport, encompassing both environmental and social impacts, such as Greenhouse Gas (GHG) emissions and navigational safety. Traditional vessel navigation heavily relies on human experience, often lacking autonomy and emission awareness, and is prone to human errors...

💬 0 commentsarXiv:2601.10911v1PDF
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Posted in math.CA · 2026-01-15 · Shrikant Chand, James Nolen, Hau-Tieng Wu

On spectral interference of the short-time Fourier transform and its nonlinear variations

Spectral interference, the frequency counterpart of the beating phenomenon in the time domain, can severely distort time-frequency representations (TFRs) in physical applications. We study this phenomenon for the short-time Fourier transform (STFT) with a Gaussian window and for nonlinear refinements based on the reassignment method,...

💬 0 commentsarXiv:2601.10910v1PDF
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Posted in cs.CV · 2026-01-15 · Chuqiao Li, Xianghui Xie, Yong Cao, Andreas Geiger, Gerard Pons-Moll

FrankenMotion: Part-level Human Motion Generation and Composition

Human motion generation from text prompts has made remarkable progress in recent years. However, existing methods primarily rely on either sequence-level or action-level descriptions due to the absence of fine-grained, part-level motion annotations. This limits their controllability over individual body parts. In this work, we...

💬 0 commentsarXiv:2601.10909v1PDF