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๐Ÿ” pedro cabalar ๐Ÿ“‚ Physics
Showing 596 results for "pedro cabalar" in Physics
Physics Preprint PDF DOI

Emergent Features in $U(N) \times U(\tilde{N})$ Bi-adjoint Cubic Theory

Lauren Smyth ยท 2026

This work investigates the role of the $U(N) \times U(\tilde{N})$ global symmetry in tree-level scattering amplitudes of the bi-adjoint $\phi^3$ theory from three perspectives: combinatorics, correlatโ€ฆ

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Physics Preprint PDF DOI

Do Quantum Transformers Help? A Systematic VQC Architecture Comparison on Tabular Benchmarks

Chi-Sheng Chen, En-Jui Kuo ยท 2026

Variational quantum circuits (VQCs) are a leading approach to quantum machine learning on near-term devices, yet it remains unclear which circuit architecture yields the best accuracy-parameter trade-โ€ฆ

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Physics Preprint PDF DOI

Benchmarking Quantum Kernel Support Vector Machines Against Classical Baselines on Tabular Data: A Rigorous Empirical Study with Hardware Validation

Siavash Kakavand, Christoph Strohmeyer, Michael Schlotter ยท 2026

Quantum kernel methods have been proposed as a promising approach for leveraging near-term quantum computers for supervised learning, yet rigorous benchmarks against strong classical baselines remain โ€ฆ

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Physics Preprint PDF DOI

The ubiquity of turbulence in the expanding kinematics of the ionized shells of Galactic planetary nebulae

Francisco Ruiz-Escobedo, Michael G. Richer, Jose Alberto Lopez ยท 2026

We present an analysis of the residual velocities from a sample of 105 Galactic planetary nebulae (PNe), the largest done to date on this subject. The analysis has been carried out with long-slit, higโ€ฆ

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Physics Preprint PDF DOI

SPATE: Spiking-Phase Adaptive Temporal Encoding for Quantum Machine Learning

Nouhaila Innan, Rachmad Vidya Wicaksana Putra, Muhammad Shafique ยท 2026

Most quantum machine learning (QML) pipelines still rely on static encodings such as angle and amplitude maps, and this limits their ability to handle temporal information. To address this limitation,โ€ฆ

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Physics Preprint PDF DOI

Evaluating Deep Learning Models for Multiclass Classification of LIGO Gravitational-Wave Glitches

Rudhresh Manoharan (Baylor University), Gerald Cleaver (Baylor University) ยท 2026

Gravitational-wave detectors are affected by short-duration non-Gaussian noise transients, commonly referred to as glitches, which can obscure astrophysical signals and complicate downstream analyses.โ€ฆ

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Physics Preprint PDF DOI

From Matrix Models to Gaussian Molecules and the Einstein-Hilbert Action

Manfred Herbst ยท 2026

A matrix model on a D-dimensional Euclidean space is introduced as a generalization of random matrix models and as a non-perturbative definition of discretized closed string theory. The free energy ofโ€ฆ

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Physics Preprint PDF DOI

QNAS: A Neural Architecture Search Framework for Accurate and Efficient Quantum Neural Networks

Kooshan Maleki, Alberto Marchisio, Muhammad Shafique ยท 2026

Designing quantum neural networks (QNNs) that are both accurate and deployable on NISQ hardware is challenging. Handcrafted ansatze must balance expressivity, trainability, and resource use, while limโ€ฆ

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Physics Preprint PDF DOI

Haematocrit and Shear Rate Modulate Local Cell-free Layer Thickness and Platelet Margination in Blood Flow Along a Sinusoidal Wall

Eleonora Pero, Giovanna Tomaiuolo, Stefano Guido, Claire Denham, Timm Krueger ยท 2026

The geometry of blood vessels strongly affects hemostasis and thrombosis through red blood cell (RBC) dynamics and platelet margination. Growing platelet aggregates, in turn, reshape the local vessel โ€ฆ

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Physics Preprint PDF DOI

Quantum-Inspired Geometric Classification with Correlation Group Structures and VQC Decision Modeling

Nishikanta Mohanty, Arya Ansuman Priyadarshi, Bikash K. Behera, Badshah Mukherjee ยท 2026

We propose a geometry-driven quantum-inspired classification framework that integrates Correlation Group Structures (CGR), compact SWAP-test-based overlap estimation, and selective variational quantumโ€ฆ

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Physics Preprint PDF DOI

Exact Solution of Chandrasekhar's H Function For the Isotropic Case

Fikret Anli ยท 2026

This study provides an exact solution to Chandrasekhar's H function for isotropic scattering. The H function, which is governed by a nonlinear integral equation, plays a central role in radiative tranโ€ฆ

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Physics Preprint PDF DOI

The CAVITY project. The spatially resolved SFR of galaxies in voids

Ana M. Conrado, Ruben Garcia-Benito, Rosa M. Gonzalez Delgado, Bahar Bidaran, Helene M. Courtois, Salvador Duarte Puertas, Daniel Espada, Andoni Jimenez, Ignacio del Moral-Castro, Isabel Perez, Tomas Ruiz-Lara, Laura Sanchez-Menguiano, Gloria Torres-Rios, Simon Verley, Maria Argudo-Fernandez, Simon B. De Daniloff, Estrella Florido, Yllari K. Gonzalez-Koda, Alejandra Z. Lugo-Aranda, Javier Roman, Smitha Subramanian, Pedro Villalba-Gonzalez, Manuel Alcazar-Laynez, Monica Hernandez-Sanchez, Monica Rodriguez Martinez, Paulo Vasquez-Bustos, Martin Blazek ยท 2026

The mass in the Universe is distributed non-uniformly, originating the Large Scale Structure (LSS), characterised by clusters, filaments, walls and voids. Galaxies in voids are bluer, later type, lessโ€ฆ

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Physics Preprint PDF DOI

Toward a Comprehensive Grid of Cepheid Models with MESA. III. Evolutionary and Pulsation Relations for Models with Core and Envelope Overshooting

R. Smolec, O. Zio{l}kowska, R. Singh Rathour, V. Hocde, P. Wielgorski ยท 2026

Evolutionary tracks for 2-8M$_\odot$ models, covering a [Fe/H]=$-$1.0 ($Z=0.0014$) to [Fe/H]=+0.2 ($Z=0.02$) metallicity range are computed with Modules for Experiments in Stellar Astrophysics, MESA, โ€ฆ

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Physics Preprint PDF DOI

Combining data and metadata: hybrid tabular file formats

Mark Taylor ยท 2026

When working with astronomical data, metadata is also important. A general-purpose file format for transmission, processing and archiving large datasets should facilitate, among other things, both effโ€ฆ

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Physics Preprint PDF DOI

Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery

Jeffrey Hu, Rongzhi Dong, Ying Feng, Ming Hu, Jianjun Hu ยท 2026

Active learning (AL) has emerged as a powerful paradigm for accelerating materials discovery by iteratively steering experiments toward promising candidates, reducing the number of costly synthesis-anโ€ฆ

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Physics Preprint PDF DOI

Integral Field Spectroscopy of Collisional Ring Galaxies I: Stellar Populations Analysis

M. Chow-Martinez, A. Robleto-Orus, Y.D. Mayya, J.P. Torres-Papaqui, R.A. Ortega-Minakata, D.F. Castro-Hidalgo, C.A. Caretta, J.J. Trejo-Alonso, A. Morales-Vargas, R. Garcia-Benito, H.E. Jacamo-Delgado, M. Gudino ยท 2026

Collisional ring galaxies are produced by the collision of a disk galaxy with a compact galaxy plunging through the disk, forming a ring-shaped expanding density wave, triggering star formation at itsโ€ฆ

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Physics Preprint PDF DOI

Data reduction method for OPTICAM multiband time series of transiting exoplanets

S. Paez, Y. Gomez Maqueo Chew, L. H. Hebb ยท 2026

We present a methodology for acquiring and reducing transiting exoplanet light curves obtained with the OPTICAM instrument in the Observatorio Astron\'omico Nacional en la Sierra de San Pedro M\'artirโ€ฆ

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Physics Preprint PDF DOI

PolyMon: A Unified Framework for Polymer Property Prediction

Gaopeng Ren, Yijie Yang, Jiajun Zhou, Kim E. Jelfs ยท 2026

Accurate prediction of polymer properties is essential for materials design, but remains challenging due to data scarcity, diverse polymer representations, and the lack of systematic evaluation acrossโ€ฆ

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Physics Preprint PDF DOI

Scaling Relations across Galaxy Classification Schemes: I. Star Formation Rate-Stellar Mass Plane of CALIFA Nearby Galaxies

Veselina Kalinova, Keiichi Kodaira, Dario Colombo ยท 2026

To gain deeper insights into galaxy evolution and the mechanisms driving transitions between different galaxy morphologies, we analyse the connection between star formation rate and stellar mass for 2โ€ฆ

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Physics Preprint PDF DOI

Local and Multi-Scale Strategies to Mitigate Exponential Concentration in Quantum Kernels

Claudia Zendejas-Morales, Debashis Saikia, Utkarsh Singh ยท 2026

Fidelity-based quantum kernels provide a direct interface between quantum feature maps and classical kernel methods, but they can exhibit exponential concentration: with increasing system size or circโ€ฆ

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