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arXiv preprints from January 1, 2026 through September 15, 2026 — 10:37:36 EST

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Posted in cs.CV · 2026-01-20 · Pavlo Melnyk, Cuong Le, Urs Waldmann, Per-Erik Forssén, Bastian Wandt

On the Role of Rotation Equivariance in Monocular 2D-to-3D Human Pose Lifting

Estimating 3D from 2D is one of the central tasks in computer vision. In this work, we consider the monocular setting, i.e. single-view input, for 3D human pose estimation (HPE), where the goal is to predict a 3D point set of human skeletal joints from a single 2D image, typically via 2D keypoint detection followed by 2D-to-3D...

💬 0 commentsarXiv:2601.13913v2PDF
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Posted in astro-ph.CO · 2026-01-20 · Mikołaj Korzyński, Mateusz Kulejewski

Frequency shift and viewing direction variations in gravitational lensing

In a gravitational lensing system, the relative transverse velocities of the lens, source, and observer induce a frequency shift in the observed radiation. While this shift is typically negligible in most astrophysical contexts, strategies for its detection have been proposed for both electromagnetic and gravitational waves. This...

💬 0 commentsarXiv:2601.13912v1PDF
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Posted in math.OC · 2026-01-20 · Ewa Rokita-Magdziarz, Barbara Gronostajska, Marcin Magdziarz

Designing sustainable barn-type houses: Optimal shapes for minimal envelope and energy use

Barn-type houses have become one of the most popular single-family housing typologies in Poland and across Europe due to their simplicity, functionality, and potential for energy efficiency. Despite their widespread use, systematic methods for optimizing their geometry in terms of envelope area and energy performance remain limited....

💬 0 commentsarXiv:2601.13911v1PDF
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Posted in eess.AS · 2026-01-20 · Changhao Pan, Dongyu Yao, Yu Zhang, Wenxiang Guo, Jingyu Lu, Zhiyuan Zhu, Zhou Zhao

Synthetic Singers: A Review of Deep-Learning-based Singing Voice Synthesis Approaches

Recent advances in singing voice synthesis (SVS) have attracted substantial attention from both academia and industry. With the advent of large language models and novel generative paradigms, producing controllable, high-fidelity singing voices has become an attainable goal. Yet the field still lacks a comprehensive survey that...

💬 0 commentsarXiv:2601.13910v1PDF
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Posted in quant-ph · 2026-01-20 · Heewoo Kim, Bojeong Seo, Han Seb Moon

Superradiance of entangled photon pairs from a high-density chip-scale Cs vapor cell

Superradiance is one of the most fundamental collective quantum phenomena in light-matter interactions and has been studied extensively since Dicke's seminal work. However, its practical implementation remains challenging because superradiant enhancement requires strict experiment conditions for strong collective coupling among...

💬 0 commentsarXiv:2601.13909v2PDF
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Posted in math.NA · 2026-01-20 · I. S. Popov

Improving the local solution of the DG predictor of the ADER-DG method for solving systems of ordinary differential equations and its applicability to systems of differential-algebraic equations

Improved local numerical solution for the ADER-DG numerical method with a local DG predictor for solving the initial value problem for a first-order ODE system is proposed. The improved local numerical solution demonstrates convergence orders of one higher than the convergence order of the local numerical solution of the original...

💬 0 commentsarXiv:2601.13908v2PDF
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Posted in cs.CR · 2026-01-20 · Cosmin-Iulian Irimia

Decentralized Infrastructure for Digital Notarizing, Signing and Sharing Files using Blockchain

Traditional paper-based document management has long posed challenges related to security, authenticity, and efficiency. Despite advances in digitalization, official documents remain vulnerable to forgery, loss, and unauthorized access. This thesis proposes a decentralized infrastructure for digital notarization, signing, and sharing...

💬 0 commentsarXiv:2601.13907v1PDF
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Posted in math.CO · 2026-01-20 · Andrzej Dudek, Jarosław Grytczuk, Jakub Przybyło, Andrzej Ruciński

Homogeneous substructures in random ordered uniform matchings

An ordered $r$-uniform matching of size $n$ is a collection of $n$ pairwise disjoint $r$-subsets of a linearly ordered set of $rn$ vertices. For $n=2$, such a matching is called an $r$-pattern, as it represents one of $\tfrac12\binom{2r}r$ ways two disjoint edges may intertwine. Given a set $\mathcal{P}$ of $r$-patterns, a...

💬 0 commentsarXiv:2601.13906v1PDF
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Posted in cs.LG · 2026-01-20 · Hao Deng, Zhang Guo, Shuiping Gou, Bo Liu

SPGCL: Simple yet Powerful Graph Contrastive Learning via SVD-Guided Structural Perturbation

Graph Neural Networks (GNNs) are sensitive to structural noise from adversarial attacks or imperfections. Existing graph contrastive learning (GCL) methods typically rely on either random perturbations (e.g., edge dropping) for diversity or spectral augmentations (e.g., SVD) to preserve structural priors. However, random perturbations...

💬 0 commentsarXiv:2602.00064v2PDF
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Posted in physics.plasm-ph · 2026-01-20 · Thomas Kluge, Uwe Hernandez Acosta, Klaus Steiniger, Ulrich Schramm, Thomas E. Cowan

Reduction of SAXS Signal due to Doppler Broadening Induced Loss of Coherence

We present an analytical and numerical study of how Doppler-induced spectral broadening in laser-heated plasmas degrades the coherence of small-angle X-ray scattering (SAXS) signals, and show that the resulting loss of temporal coherence reduces the SAXS intensity. Applying this formalism to two benchmark geometries - single density...

💬 0 commentsarXiv:2601.13905v1PDF
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Posted in quant-ph · 2026-01-20 · Ailsa Robertson, Christian Schaffner, Sebastian R. Verschoor

Integrity from Algebraic Manipulation Detection in Trusted-Repeater QKD Networks

Quantum Key Distribution (QKD) allows secure communication without relying on computational assumptions, but can currently only be deployed over relatively short distances due to hardware constraints. To extend QKD over long distances, networks of trusted repeater nodes can be used, wherein QKD is executed between neighbouring nodes...

💬 0 commentsarXiv:2602.00069v1PDF
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Posted in quant-ph · 2026-01-20 · Stefano Longhi

Quantum Pontus-Mpemba Effect Enabled by the Liouvillian Skin Effect

We unveil a quantum Pontus-Mpemba effect enabled by the Liouvillian skin effect in a dissipative tight-binding chain with asymmetric incoherent hopping and coherent boundary coupling. The skin effect, induced by non-reciprocal dissipation, localizes relaxation modes near the system boundaries and gives rise to non-orthogonal spectral...

💬 0 commentsarXiv:2601.14083v1PDF
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Posted in physics.soc-ph · 2026-01-20 · Sam Turley, Matthew Turner

Causal Entropy, Control and Leadership Dynamics

Collective motion in animal groups provide examples of emergent, decentralised coordination. Here, we examine a bottom-up model of collective behavior based on Future State Maximisation (FSM). In this model agents seek to maximise the diversity of their future visual states over a finite time horizon. We further assume that a subset...

💬 0 commentsarXiv:2601.14344v1PDF
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Posted in cond-mat.soft · 2026-01-20 · Gabriele Costa, Santi Prestipino

Onset of stripe order in classical fluids: Lessons from lattice-gas mixtures

When two molecular species with mutual affinity are mixed together, various self-assembled phases can arise at low temperature, depending on the shape of like and unlike interactions. Among them, stripes -- where layers of one type are regularly alternated with layers of another type -- hold a prominent place in materials science,...

💬 0 commentsarXiv:2601.14082v1PDF
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Posted in cs.SE · 2026-01-20 · Xingcheng Chen, Oliver Weissl, Andrea Stocco

Feature-Aware Test Generation for Deep Learning Models

As deep learning models are widely used in software systems, test generation plays a crucial role in assessing the quality of such models before deployment. To date, the most advanced test generators rely on generative AI to synthesize inputs; however, these approaches remain limited in providing semantic insight into the causes of...

💬 0 commentsarXiv:2601.14081v1PDF
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Posted in eess.SP · 2026-01-20 · Alexander Ihlow, Marius Schmidt, Carsten Andrich, Reiner S. Thomä

Background Subtraction with Drift Correction for Bistatic Radar Reflectivity Measurements

Fundamental research on bistatic radar reflectivity is highly relevant, e.g., to the upcoming mobile communication standard 6G, which includes integrated sensing and communication (ISAC). We introduce a model for correcting instrumentation drift during bistatic radar measurements in anechoic chambers. Usually, background subtraction...

💬 0 commentsarXiv:2601.14080v1PDF
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Posted in cs.CV · 2026-01-20 · Paul Walker, James A. D. Gardner, Andreea Ardelean, William A. P. Smith, Bernhard Egger

VENI: Variational Encoder for Natural Illumination

Inverse rendering is an ill-posed problem, but priors such as illumination priors can help simplify it. Existing work either disregards the spherical and rotation-equivariant nature of illumination environments or does not provide a well-behaved latent space. We propose a rotation-equivariant variational autoencoder that models...

💬 0 commentsarXiv:2601.14079v2PDF
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Posted in cs.FL · 2026-01-20 · Mathieu Lehaut, Anca Muscholl, Nir Piterman

From Trees to Tree-Like: Distribution and Synthesis for Asynchronous Automata

We revisit constructions for distribution and synthesis of Zielonka's asynchronous automata in restricted settings. We show first a simple, quadratic, distribution construction for asynchronous automata, where the process architecture is tree-like. An architecture is tree-like if there is an underlying spanning tree of the...

💬 0 commentsarXiv:2601.14078v1PDF
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Posted in q-bio.NC · 2026-01-20 · Lars C. Reining, Thabo Matthies, Luisa Haussner, Rabea Turon, Thomas S. A. Wallis

MooneyMaker: A Python package to create ambiguous two-tone images

Mooney images are high-contrast, two-tone visual stimuli, created by thresholding photographic images. They allow researchers to separate image content from image understanding, making them valuable for studying visual perception. An ideal Mooney image for this purpose achieves a specific balance: it initially appears unrecognizable...

💬 0 commentsarXiv:2601.14077v1PDF
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Posted in astro-ph.EP · 2026-01-20 · Jiaxin Tang, Sharon X. Wang, Yaguang Li, Timothy R. Bedding, Guang-Yao Xiao, Fabo Feng, Jie Yu, Zun Wang, Jennifer A. Burt, R. Paul Butler, Brad Carter, Jeffrey D. Crane, Matías R. Díaz, Samuel K. Grunblatt, Daniel Huber, Hugh R. A. Jones, Stephen R. Kane, Jacob K. Luhn, Stephen A. Shectman, Johanna Teske, Rob Wittenmyer, Jason T. Wright, Jeremy Bailey, Simon J. O'Toole, Chris G. Tinney

RV$\times$TESS I: Modeling Asteroseismic Signals with Simultaneous Photometry and RVs

Detecting small planets via the radial velocity method remains challenged by signals induced by stellar variability, versus the effects of the planet(s). Here, we explore using Gaussian Process (GP) regression with Transiting Exoplanet Survey Satellite (TESS) photometry in modeling radial velocities (RVs) to help to mitigate stellar...

💬 0 commentsarXiv:2601.14076v1PDF
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Posted in cs.IT · 2026-01-20 · Sahan Liyanaarachchi, Sennur Ulukus, Nail Akar

Utilizing the Perceived Age to Maximize Freshness in Query-Based Update Systems

Query-based sampling has become an increasingly popular technique for monitoring Markov sources in pull-based update systems. However, most of the contemporary literature on this assumes an exponential distribution for query delay and often relies on the assumption that the feedback or replies to the queries are instantaneous. In this...

💬 0 commentsarXiv:2601.14075v2PDF
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Posted in math.PR · 2026-01-20 · José Arcia-Manoleskos, Manuel Domínguez de la Iglesia

LU-type factorizations for birth--death processes and their Darboux transformations

We study LU-type factorizations of the infinitesimal generator of a birth--death process on $\mathbb{N}_0$. Our goal is to characterize those factorizations whose Darboux transformations (that is, inverting the order of the factors) yield new infinitesimal generators of birth--death processes. Two types are considered: lower--upper...

💬 0 commentsarXiv:2601.14074v1PDF
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Posted in physics.chem-ph · 2026-01-20 · P. D. Varuna S. Pathirage, Konstantinos D. Vogiatzis

DDCCNet: Physics-enhanced Multitask Neural Networks for Data-driven Coupled-cluster

We present the data-driven coupled-cluster deep network (DDCCNet), a family of multitask, physics-enhanced deep learning architectures designed to predict coupled-cluster singles and doubles (CCSD) amplitudes and correlation energies from lower-level electronic structure methods. The three DDCCNet variants (termed as v1, v2, and v3)...

💬 0 commentsarXiv:2601.14073v2PDF
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Posted in cond-mat.supr-con · 2026-01-20 · Heng Wang, Haoliang Huang, Wei Lv, Xianfeng Wu, Guangdi Zhou, Zihao Nie, Yueying Li, Cui Ding, Danfeng Li, Hongtao Yuan, Qi-Kun Xue, Zhuoyu Chen

Superconductor-insulator transitions in infinite-layer nickelates controlled via ${operando}$ monitored reduction

Nickelates represent an emerging class of superconductors that demand innovative approaches for structural and electronic phase modulations. Continuous control over superconductor-insulator transition (SIT) in nickelates remains particularly challenging, hindering both fundamental understanding and potential applications. Here, we...

💬 0 commentsarXiv:2601.14072v1PDF
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Posted in econ.GN · 2026-01-20 · Douglas Cumming, Hisham Farag, Santosh Koirala, Danny McGowan

How Disruptive is Financial Technology?

We study whether Fintech disrupts the banking sector by intensifying competition for scarce deposits funds and raising deposit rates. Using difference-in-difference estimation around the exogenous removal of marketplace platform investing restrictions by US states, we show the cost of deposits increase by approximately 11.5% within...

💬 0 commentsarXiv:2601.14071v2PDF