Evidence for Hydrostatic Equilibrium in the Extragalactic Molecular Clouds of M31

Este estudio confirma que las nubes moleculares en M31 exhiben perfiles de densidad consistentes con el equilibrio hidrostático, demostrando que comparten un estado dinámico similar al de las nubes galácticas y reforzando la comprensión de la interacción entre la turbulencia, la estabilidad gravitacional y la evolución de las nubes en el medio interestelar.

Eric Keto, Charles Lada, Jan Frobrich2026-03-09🔭 astro-ph

DESI DR2 reference mocks: clustering results from Uchuu-BGS and LRG

Este trabajo presenta catálogos de galaxias simuladas (mocks) de alta fidelidad para las muestras de galaxias rojas luminosas (LRG) y brillantes (BGS) del DESI, generados mediante la técnica de emparejamiento de abundancia de subhalos (SHAM) en la simulación Uchuu, los cuales reproducen con gran precisión la evolución del agrupamiento y las propiedades bariónicas observadas, proporcionando herramientas robustas para el análisis del resto de la encuesta.

E. Fernández-García, F. Prada, A. Smith, J. DeRose, A. J. Ross, S. Bailey, M. S. Wang, Z. Ding, C. Guandalin, C. Lamman, R. Vaisakh, R. Kehoe, J. Lasker, T. Ishiyama, S. M. Moore, S. Cole, M. Siudek, A. Amalbert, A. Salcedo, A. Hearin, B. Joachimi, A. Rocher, S. Saito, A. Krolewski, Z. Slepian, Q. Li, K. S. Dawson, E. Jullo, J. Aguilar, S. Ahlen, D. Bianchi, D. Brooks, T. Claybaugh, A. de la Macorra, P. Doel, S. Ferraro, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, K. Honscheid, M. Ishak, R. Joyce, S. Juneau, D. Kirkby, T. Kisner, A. Kremin, O. Lahav, A. Lambert, M. Landriau, M. E. Levi, M. Manera, R. Miquel, J. Moustakas, S. Nadathur, W. J. Percival, I. Pérez-Ràfols, G. Rossi, E. Sanchez, D. Schlegel, H. Seo, J. Silber, D. Sprayberry, G. Tarlé, B. A. Weaver, P. Zarrouk, R. Zhou2026-03-09🔭 astro-ph

PyBird-JAX: Accelerated inference in large-scale structure with model-independent emulation of one-loop galaxy power spectra

El artículo presenta PyBird-JAX\texttt{PyBird-JAX}, una implementación diferenciable basada en JAX\texttt{JAX} que utiliza emuladores de redes neuronales para acelerar drásticamente (en 3-4 órdenes de magnitud) el cálculo de espectros de potencia de galaxias de un bucle en la teoría efectiva de la estructura a gran escala, permitiendo inferencias cosmológicas de alta precisión y velocidad para futuros sondeos sin pérdida significativa de exactitud.

Alexander Reeves, Pierre Zhang, Henry Zheng2026-03-09🔭 astro-ph

Radiation GRMHD Models of Accretion onto Stellar-Mass Black Holes: II. Super-Eddington Accretion

Este estudio presenta simulaciones GRMHD radiativas de acreción super-Eddington en agujeros negros estelares que revelan que, aunque la acreción genera discos gruesos y vientos que reducen la eficiencia radiativa, la presencia de jets fuertes puede limpiar el embudo y permitir la emisión de radiación mediante haces geométricos, ofreciendo explicaciones para fuentes como las ULX y los "little red dots".

Lizhong Zhang, James M. Stone, Christopher J. White, Shane W. Davis, Yan-Fei Jiang, Patrick D. Mullen2026-03-09🔭 astro-ph

Rotating neutron stars within the macroscopic effective-surface approximation

Este artículo extiende el modelo macroscópico de estrellas de neutrones como gotas líquidas perfectas a sistemas rotatorios mediante una expansión de perturbación lineal en la métrica de Schwarzschild, derivando analíticamente expresiones para el momento de inercia adiabático que incorporan contribuciones de volumen y superficie, y revelando cómo las correlaciones espacio-temporales y la fuerte gravedad imponen restricciones adicionales sobre el radio de estas estrellas.

A. G. Magner, S. P. Maydanyuk, A. Bonasera, H. Zheng, S. N. Fedotkin, A. I. Levon, T. Depastas, U. V. Grygoriev, A. A. Uleiev2026-03-09🔭 astro-ph

Supernovae Exploding within Dense Extended Material: Early Emission Regimes and Degeneracies in Parameter Inference from Observations

Este estudio analiza analíticamente la emisión temprana de supernovas de colapso del núcleo al interactuar con material extendido denso, demostrando que las observaciones actuales presentan degeneraciones significativas en la inferencia de parámetros como el radio y la masa, las cuales pueden resolverse mediante coberturas multibanda tempranas en ultravioleta y rayos X, como las que proporcionará la misión ULTRASAT.

Tal Wasserman, Eli Waxman2026-03-09🔭 astro-ph

Excursion Set Approach to Primordial Black Holes: Cloud-in-Cloud and Mass Function Revisited

Este artículo reformula el enfoque del conjunto de excursión para los agujeros negros primordiales, demostrando que, a diferencia de la formación de halos, el proceso es no markoviano y que la aplicación del factor de corrección "2" es inválida, requiriendo en su lugar la inclusión consistente de ambas contribuciones estocásticas para obtener una función de masa positiva.

Ashu Kushwaha, Teruaki Suyama2026-03-09🔭 astro-ph

The trichotomy of primordial black holes initial conditions

Este artículo demuestra que el umbral de formación de agujeros negros primordiales no depende únicamente de la función de compacidad, sino también de la curvatura espacial en el núcleo, lo que permite clasificar las condiciones iniciales en tres tipos (abierto, cerrado y plano) con umbrales de formación distintos y diferentes implicaciones para la generación de agujeros negros de Tipo-I y Tipo-II.

Cristiano Germani, Laia Montellà2026-03-09🔭 astro-ph

Evidence of cosmic-ray acceleration up to sub-PeV energies in the supernova remnant IC 443

Este estudio presenta observaciones de LHAASO del remanente de supernova IC 443 que demuestran la aceleración eficiente de rayos cósmicos sub-PeV por sus ondas de choque, proporcionando evidencia crucial sobre el origen galáctico de estas partículas de alta energía.

Zhen Cao (The LHAASO Collaboration), F. Aharonian (The LHAASO Collaboration), Y. X. Bai (The LHAASO Collaboration), Y. W. Bao (The LHAASO Collaboration), D. Bastieri (The LHAASO Collaboration), X. J. Bi (The LHAASO Collaboration), Y. J. Bi (The LHAASO Collaboration), W. Bian (The LHAASO Collaboration), A. V. Bukevich (The LHAASO Collaboration), C. M. Cai (The LHAASO Collaboration), W. Y. Cao (The LHAASO Collaboration), Zhe Cao (The LHAASO Collaboration), J. Chang (The LHAASO Collaboration), J. F. Chang (The LHAASO Collaboration), A. M. Chen (The LHAASO Collaboration), E. S. Chen (The LHAASO Collaboration), G. H. Chen (The LHAASO Collaboration), H. X. Chen (The LHAASO Collaboration), Liang Chen (The LHAASO Collaboration), Long Chen (The LHAASO Collaboration), M. J. Chen (The LHAASO Collaboration), M. L. Chen (The LHAASO Collaboration), Q. H. Chen (The LHAASO Collaboration), S. Chen (The LHAASO Collaboration), S. H. Chen (The LHAASO Collaboration), S. Z. Chen (The LHAASO Collaboration), T. L. Chen (The LHAASO Collaboration), X. B. Chen (The LHAASO Collaboration), X. J. Chen (The LHAASO Collaboration), Y. Chen (The LHAASO Collaboration), N. Cheng (The LHAASO Collaboration), Y. D. Cheng (The LHAASO Collaboration), M. C. Chu (The LHAASO Collaboration), M. Y. Cui (The LHAASO Collaboration), S. W. Cui (The LHAASO Collaboration), X. H. Cui (The LHAASO Collaboration), Y. D. Cui (The LHAASO Collaboration), B. Z. Dai (The LHAASO Collaboration), H. L. Dai (The LHAASO Collaboration), Z. G. Dai (The LHAASO Collaboration), Danzengluobu (The LHAASO Collaboration), Y. X. Diao (The LHAASO Collaboration), X. Q. Dong (The LHAASO Collaboration), K. K. Duan (The LHAASO Collaboration), J. H. Fan (The LHAASO Collaboration), Y. Z. Fan (The LHAASO Collaboration), J. Fang (The LHAASO Collaboration), J. H. Fang (The LHAASO Collaboration), K. Fang (The LHAASO Collaboration), C. F. Feng (The LHAASO Collaboration), H. Feng (The LHAASO Collaboration), L. Feng (The LHAASO Collaboration), S. H. Feng (The LHAASO Collaboration), X. T. Feng (The LHAASO Collaboration), Y. Feng (The LHAASO Collaboration), Y. L. Feng (The LHAASO Collaboration), S. Gabici (The LHAASO Collaboration), B. Gao (The LHAASO Collaboration), C. D. Gao (The LHAASO Collaboration), Q. Gao (The LHAASO Collaboration), W. Gao (The LHAASO Collaboration), W. K. Gao (The LHAASO Collaboration), M. M. Ge (The LHAASO Collaboration), T. T. Ge (The LHAASO Collaboration), L. S. Geng (The LHAASO Collaboration), G. Giacinti (The LHAASO Collaboration), G. H. Gong (The LHAASO Collaboration), Q. B. Gou (The LHAASO Collaboration), M. H. Gu (The LHAASO Collaboration), F. L. Guo (The LHAASO Collaboration), J. Guo (The LHAASO Collaboration), X. L. Guo (The LHAASO Collaboration), Y. Q. Guo (The LHAASO Collaboration), Y. Y. Guo (The LHAASO Collaboration), Y. A. Han (The LHAASO Collaboration), O. A. Hannuksela (The LHAASO Collaboration), M. Hasan (The LHAASO Collaboration), H. H. He (The LHAASO Collaboration), H. N. He (The LHAASO Collaboration), J. Y. He (The LHAASO Collaboration), X. Y. He (The LHAASO Collaboration), Y. He (The LHAASO Collaboration), S. Hernández-Cadena (The LHAASO Collaboration), B. W. Hou (The LHAASO Collaboration), C. Hou (The LHAASO Collaboration), X. Hou (The LHAASO Collaboration), H. B. Hu (The LHAASO Collaboration), S. C. Hu (The LHAASO Collaboration), C. Huang (The LHAASO Collaboration), D. H. Huang (The LHAASO Collaboration), J. J. Huang (The LHAASO Collaboration), T. Q. Huang (The LHAASO Collaboration), W. J. Huang (The LHAASO Collaboration), X. T. Huang (The LHAASO Collaboration), X. Y. Huang (The LHAASO Collaboration), Y. Huang (The LHAASO Collaboration), Y. Y. Huang (The LHAASO Collaboration), X. L. Ji (The LHAASO Collaboration), H. Y. Jia (The LHAASO Collaboration), K. Jia (The LHAASO Collaboration), H. B. Jiang (The LHAASO Collaboration), K. Jiang (The LHAASO Collaboration), X. W. Jiang (The LHAASO Collaboration), Z. J. Jiang (The LHAASO Collaboration), M. Jin (The LHAASO Collaboration), S. Kaci (The LHAASO Collaboration), M. M. Kang (The LHAASO Collaboration), I. Karpikov (The LHAASO Collaboration), D. Khangulyan (The LHAASO Collaboration), D. Kuleshov (The LHAASO Collaboration), K. Kurinov (The LHAASO Collaboration), B. B. Li (The LHAASO Collaboration), Cheng Li (The LHAASO Collaboration), Cong Li (The LHAASO Collaboration), D. Li (The LHAASO Collaboration), F. Li (The LHAASO Collaboration), H. B. Li (The LHAASO Collaboration), H. C. Li (The LHAASO Collaboration), Jian Li (The LHAASO Collaboration), Jie Li (The LHAASO Collaboration), K. Li (The LHAASO Collaboration), L. Li (The LHAASO Collaboration), R. L. Li (The LHAASO Collaboration), S. D. Li (The LHAASO Collaboration), T. Y. Li (The LHAASO Collaboration), W. L. Li (The LHAASO Collaboration), X. R. Li (The LHAASO Collaboration), Xin Li (The LHAASO Collaboration), Y. Li (The LHAASO Collaboration), Y. Z. Li (The LHAASO Collaboration), Zhe Li (The LHAASO Collaboration), Zhuo Li (The LHAASO Collaboration), E. W. Liang (The LHAASO Collaboration), Y. F. Liang (The LHAASO Collaboration), S. J. Lin (The LHAASO Collaboration), B. Liu (The LHAASO Collaboration), C. Liu (The LHAASO Collaboration), D. Liu (The LHAASO Collaboration), D. B. Liu (The LHAASO Collaboration), H. Liu (The LHAASO Collaboration), H. D. Liu (The LHAASO Collaboration), J. Liu (The LHAASO Collaboration), J. L. Liu (The LHAASO Collaboration), J. R. Liu (The LHAASO Collaboration), M. Y. Liu (The LHAASO Collaboration), R. Y. Liu (The LHAASO Collaboration), S. M. Liu (The LHAASO Collaboration), W. Liu (The LHAASO Collaboration), X. Liu (The LHAASO Collaboration), Y. Liu (The LHAASO Collaboration), Y. Liu (The LHAASO Collaboration), Y. N. Liu (The LHAASO Collaboration), Y. Q. Lou (The LHAASO Collaboration), Q. Luo (The LHAASO Collaboration), Y. Luo (The LHAASO Collaboration), H. K. Lv (The LHAASO Collaboration), B. Q. Ma (The LHAASO Collaboration), L. L. Ma (The LHAASO Collaboration), X. H. Ma (The LHAASO Collaboration), J. R. Mao (The LHAASO Collaboration), Z. Min (The LHAASO Collaboration), W. Mitthumsiri (The LHAASO Collaboration), G. B. Mou (The LHAASO Collaboration), H. J. Mu (The LHAASO Collaboration), A. Neronov (The LHAASO Collaboration), K. C. Y. Ng (The LHAASO Collaboration), M. Y. Ni (The LHAASO Collaboration), L. Nie (The LHAASO Collaboration), L. J. Ou (The LHAASO Collaboration), P. Pattarakijwanich (The LHAASO Collaboration), Z. Y. Pei (The LHAASO Collaboration), J. C. Qi (The LHAASO Collaboration), M. Y. Qi (The LHAASO Collaboration), J. J. Qin (The LHAASO Collaboration), A. Raza (The LHAASO Collaboration), C. Y. Ren (The LHAASO Collaboration), D. Ruffolo (The LHAASO Collaboration), A. Sáiz (The LHAASO Collaboration), D. Semikoz (The LHAASO Collaboration), L. Shao (The LHAASO Collaboration), O. Shchegolev (The LHAASO Collaboration), Y. Z. Shen (The LHAASO Collaboration), X. D. Sheng (The LHAASO Collaboration), Z. D. Shi (The LHAASO Collaboration), F. W. Shu (The LHAASO Collaboration), H. C. Song (The LHAASO Collaboration), Yu. V. Stenkin (The LHAASO Collaboration), V. Stepanov (The LHAASO Collaboration), Y. Su (The LHAASO Collaboration), D. X. Sun (The LHAASO Collaboration), H. Sun (The LHAASO Collaboration), Q. N. Sun (The LHAASO Collaboration), X. N. Sun (The LHAASO Collaboration), Z. B. Sun (The LHAASO Collaboration), N. H. Tabasam (The LHAASO Collaboration), J. Takata (The LHAASO Collaboration), P. H. T. Tam (The LHAASO Collaboration), H. B. Tan (The LHAASO Collaboration), Q. W. Tang (The LHAASO Collaboration), R. Tang (The LHAASO Collaboration), Z. B. Tang (The LHAASO Collaboration), W. W. Tian (The LHAASO Collaboration), C. N. Tong (The LHAASO Collaboration), L. H. Wan (The LHAASO Collaboration), C. Wang (The LHAASO Collaboration), G. W. Wang (The LHAASO Collaboration), H. G. Wang (The LHAASO Collaboration), J. C. Wang (The LHAASO Collaboration), K. Wang (The LHAASO Collaboration), Kai Wang (The LHAASO Collaboration), Kai Wang (The LHAASO Collaboration), L. P. Wang (The LHAASO Collaboration), L. Y. Wang (The LHAASO Collaboration), L. Y. Wang (The LHAASO Collaboration), R. Wang (The LHAASO Collaboration), W. Wang (The LHAASO Collaboration), X. G. Wang (The LHAASO Collaboration), X. J. Wang (The LHAASO Collaboration), X. Y. Wang (The LHAASO Collaboration), Y. Wang (The LHAASO Collaboration), Y. D. Wang (The LHAASO Collaboration), Z. H. Wang (The LHAASO Collaboration), Z. X. Wang (The LHAASO Collaboration), Zheng Wang (The LHAASO Collaboration), D. M. Wei (The LHAASO Collaboration), J. J. Wei (The LHAASO Collaboration), Y. J. Wei (The LHAASO Collaboration), T. Wen (The LHAASO Collaboration), S. S. Weng (The LHAASO Collaboration), C. Y. Wu (The LHAASO Collaboration), H. R. Wu (The LHAASO Collaboration), Q. W. Wu (The LHAASO Collaboration), S. Wu (The LHAASO Collaboration), X. F. Wu (The LHAASO Collaboration), Y. S. Wu (The LHAASO Collaboration), S. Q. Xi (The LHAASO Collaboration), J. Xia (The LHAASO Collaboration), J. J. Xia (The LHAASO Collaboration), G. M. Xiang (The LHAASO Collaboration), D. X. Xiao (The LHAASO Collaboration), G. Xiao (The LHAASO Collaboration), Y. L. Xin (The LHAASO Collaboration), Y. Xing (The LHAASO Collaboration), D. R. Xiong (The LHAASO Collaboration), Z. Xiong (The LHAASO Collaboration), D. L. Xu (The LHAASO Collaboration), R. F. Xu (The LHAASO Collaboration), R. X. Xu (The LHAASO Collaboration), W. L. Xu (The LHAASO Collaboration), L. Xue (The LHAASO Collaboration), D. H. Yan (The LHAASO Collaboration), T. Yan (The LHAASO Collaboration), C. W. Yang (The LHAASO Collaboration), C. Y. Yang (The LHAASO Collaboration), F. F. Yang (The LHAASO Collaboration), L. L. Yang (The LHAASO Collaboration), M. J. Yang (The LHAASO Collaboration), R. Z. Yang (The LHAASO Collaboration), W. X. Yang (The LHAASO Collaboration), Z. H. Yang (The LHAASO Collaboration), Z. G. Yao (The LHAASO Collaboration), X. A. Ye (The LHAASO Collaboration), L. Q. Yin (The LHAASO Collaboration), N. Yin (The LHAASO Collaboration), X. H. You (The LHAASO Collaboration), Z. Y. You (The LHAASO Collaboration), Q. Yuan (The LHAASO Collaboration), H. Yue (The LHAASO Collaboration), H. D. Zeng (The LHAASO Collaboration), T. X. Zeng (The LHAASO Collaboration), W. Zeng (The LHAASO Collaboration), X. T. Zeng (The LHAASO Collaboration), M. Zha (The LHAASO Collaboration), B. B. Zhang (The LHAASO Collaboration), B. T. Zhang (The LHAASO Collaboration), C. Zhang (The LHAASO Collaboration), F. Zhang (The LHAASO Collaboration), H. Zhang (The LHAASO Collaboration), H. M. Zhang (The LHAASO Collaboration), H. Y. Zhang (The LHAASO Collaboration), J. L. Zhang (The LHAASO Collaboration), Li Zhang (The LHAASO Collaboration), P. F. Zhang (The LHAASO Collaboration), P. P. Zhang (The LHAASO Collaboration), R. Zhang (The LHAASO Collaboration), S. R. Zhang (The LHAASO Collaboration), S. S. Zhang (The LHAASO Collaboration), W. Y. Zhang (The LHAASO Collaboration), X. Zhang (The LHAASO Collaboration), X. P. Zhang (The LHAASO Collaboration), Yi Zhang (The LHAASO Collaboration), Yong Zhang (The LHAASO Collaboration), Z. P. Zhang (The LHAASO Collaboration), J. Zhao (The LHAASO Collaboration), L. Zhao (The LHAASO Collaboration), L. Z. Zhao (The LHAASO Collaboration), S. P. Zhao (The LHAASO Collaboration), X. H. Zhao (The LHAASO Collaboration), Z. H. Zhao (The LHAASO Collaboration), F. Zheng (The LHAASO Collaboration), W. J. Zhong (The LHAASO Collaboration), B. Zhou (The LHAASO Collaboration), H. Zhou (The LHAASO Collaboration), J. N. Zhou (The LHAASO Collaboration), M. Zhou (The LHAASO Collaboration), P. Zhou (The LHAASO Collaboration), R. Zhou (The LHAASO Collaboration), X. X. Zhou (The LHAASO Collaboration), X. X. Zhou (The LHAASO Collaboration), B. Y. Zhu (The LHAASO Collaboration), C. G. Zhu (The LHAASO Collaboration), F. R. Zhu (The LHAASO Collaboration), H. Zhu (The LHAASO Collaboration), K. J. Zhu (The LHAASO Collaboration), Y. C. Zou (The LHAASO Collaboration), X. Zuo (The LHAASO Collaboration)2026-03-09🔭 astro-ph

A Large-Area Optical Time Projection Chamber for Hard X-ray Polarimetry with Directional Imaging of Low-Energy Electron Recoils

Este artículo presenta el desarrollo y las pruebas de un prototipo de cámara de proyección temporal óptica de gran área, originalmente diseñado para la búsqueda de materia oscura, que demuestra una capacidad robusta para realizar polarimetría de rayos X duros mediante el seguimiento direccional de electrones de retroceso en el rango de 10-60 keV con una resolución angular de hasta 15 grados.

Davide Fiorina, Elisabetta Baracchini, Giorgio Dho, Paolo Soffitta, Samuele Torelli, David J. M. Marques, Enrico Costa, Sergio Fabiani, Fabio Muleri, Giovanni Mazzitelli, Atul Prajapati2026-03-09🔭 astro-ph

The maximum offsets of binary neutron star mergers from host galaxies

Este artículo deriva analíticamente y demuestra mediante un modelo de síntesis poblacional que el desplazamiento máximo de las fusiones de estrellas de neutrones binarias fuera de sus galaxias anfitrionas es de aproximadamente 300 kpc, ajustado por la velocidad de escape de la galaxia, lo cual es crucial para identificar las galaxias anfitrionas de fusiones no coincidentes con galaxias y explorar posibles correlaciones con las masas del sistema y la duración de los estallidos de rayos gamma.

Ilya Mandel, Om Sharan Salafia, Andrew Levan, Paul Disberg2026-03-09🔭 astro-ph

Mass-to-Horizon Entropic Cosmology: A Unified Thermodynamic Pathway to Cosmic Acceleration

Este estudio presenta una cosmología entropica unificada basada en una relación masa-horizonte generalizada que, al ser validada mediante un análisis observacional exhaustivo que incluye supernovas, oscilaciones acústicas bariónicas y crecimiento de estructuras, se muestra estadísticamente preferida sobre el modelo Λ\LambdaCDM, sugiriendo que la aceleración cósmica es un fenómeno emergente de una fuerza entropica en lugar de una constante cosmológica fundamental.

Tomasz Denkiewicz, Hussain Gohar2026-03-09🔭 astro-ph