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Rotating Black Holes: Continuum Failure Surfaces in Kerr Geometry
Michael Aaron Cody
Posted: 11 December 2025
Cosmological Microwave Background Without Expansion
Michael Aaron Cody
Posted: 09 December 2025
Impact of Atmospheric Delay on Equivalence Principle Tests Using Lunar Laser Ranging
Ze-Tian Jiang
,Cheng-Gang Qin
,Wei-Sheng Huang
,Jun Ke
,Yu-Jie Tan
,Cheng-Gang Shao
Posted: 02 December 2025
GEOmetric Laws of Tectonic Motion: The First Law
Anton Semashev
Posted: 27 November 2025
Thermodynamic Resolution of the Hubble Tension: The Dead Universe Theory (DUT) as a Cosmological Model Rooted in Irreversible Entropy
Joel Almeida
The Dead Universe Theory (DUT) proposes that the observable universe is not an isolated, ever-expanding system emerging from a primordial singularity, but a thermodynamically decaying domain embedded within the collapsed geometry of a prior cosmological phase. In this framework, the visible cosmos constitutes a localized photonic anomaly—a transient luminous fluctuation—formed inside a large-scale structural black hole generated by the exhaustion of a former universe. Rather than ending in a Big Rip, Big Freeze, or Big Crunch, DUT predicts an asymmetric thermodynamic retraction in which usable energy is progressively depleted, driving the cosmos toward structural infertility and thermodynamic death on a timescale of order 102 Gyr (≈ 166 billion years). Beyond this horizon, matter persists only in fossilized configurations such as planets, stellar remnants, black holes, and extinguished galaxies, forming a “dead universe”. This thesis develops the mathematical, thermodynamic, and computational foundations of DUT and tests its consequences against current observational data. The work combines (i) entropic retraction equations with time-dependent curvature and entropy-derived cosmological terms, (ii) the Cosmic Fossil Record Method for dating the exhaustion of cosmic energy, and (iii) numerical simulations of galactic evolution under finite-energy and high-entropy constraints. These simulations reproduce quenching histories, fossil signatures, and an entropic horizon consistent with a structurally dying universe. Remarkably, DUT-based simulations anticipated several deep-field results from the James Webb Space Telescope, including compact galaxies at z > 13 and a population of Small Red Dots (SRDs) at z ≈ 15–20. The theory yields falsifiable predictions, such as a measurable excess of compact high-redshift systems, a mildly negative curvature parameter (Ωₖ ≈ −0.07 ± 0.02), and a declining structural natality of galaxies with cosmic time. By providing reproducible codes, explicit equations, and clear observational tests, DUT is presented as a coherent and testable alternative to ΛCDM for modeling cosmic chronology, entropy dynamics, and large-scale gravitational architecture.
The Dead Universe Theory (DUT) proposes that the observable universe is not an isolated, ever-expanding system emerging from a primordial singularity, but a thermodynamically decaying domain embedded within the collapsed geometry of a prior cosmological phase. In this framework, the visible cosmos constitutes a localized photonic anomaly—a transient luminous fluctuation—formed inside a large-scale structural black hole generated by the exhaustion of a former universe. Rather than ending in a Big Rip, Big Freeze, or Big Crunch, DUT predicts an asymmetric thermodynamic retraction in which usable energy is progressively depleted, driving the cosmos toward structural infertility and thermodynamic death on a timescale of order 102 Gyr (≈ 166 billion years). Beyond this horizon, matter persists only in fossilized configurations such as planets, stellar remnants, black holes, and extinguished galaxies, forming a “dead universe”. This thesis develops the mathematical, thermodynamic, and computational foundations of DUT and tests its consequences against current observational data. The work combines (i) entropic retraction equations with time-dependent curvature and entropy-derived cosmological terms, (ii) the Cosmic Fossil Record Method for dating the exhaustion of cosmic energy, and (iii) numerical simulations of galactic evolution under finite-energy and high-entropy constraints. These simulations reproduce quenching histories, fossil signatures, and an entropic horizon consistent with a structurally dying universe. Remarkably, DUT-based simulations anticipated several deep-field results from the James Webb Space Telescope, including compact galaxies at z > 13 and a population of Small Red Dots (SRDs) at z ≈ 15–20. The theory yields falsifiable predictions, such as a measurable excess of compact high-redshift systems, a mildly negative curvature parameter (Ωₖ ≈ −0.07 ± 0.02), and a declining structural natality of galaxies with cosmic time. By providing reproducible codes, explicit equations, and clear observational tests, DUT is presented as a coherent and testable alternative to ΛCDM for modeling cosmic chronology, entropy dynamics, and large-scale gravitational architecture.
Posted: 27 November 2025
A Natural Explanation of Dark Matter based upon Hawking’s Cosmology and an Improved Prediction Algorithm for Galaxy Rotation Curves and Cluster Velocity Dispersions
G.M. van Uffelen
Posted: 04 November 2025
Chrono-Quantum Field Theory: Time as a Fundamental Wave and Space as Quantum Amplitude
Furkan Rabee
Posted: 31 October 2025
Round-Trip Mars Missions in the 2031 Window: Feasible and Extreme Scenarios Derived from CA21-Anchored Trajectories
Marcelo de Oliveira Souza
Posted: 24 October 2025
Astrodynamics Innovation: Leveraging an Asteroid’s Early Data for Faster Mars Transits
Marcelo Souza
Posted: 15 October 2025
Ionospheric Corrections for Space Domain Awareness using HF Line-of-Sight Radar
Tristan Camilleri
,Manuel Cervera
Posted: 06 October 2025
Amplified Eastward SAPS Flows Observed in the Topside Ionosphere Near Magnetic Midnight
Ildiko Horvath
,Brian C. Lovell
Posted: 15 August 2025
Birth of an Isotropic and Homogeneous Universe with a Running Cosmological Constant
Alessandro Oliveira Castro Júnior
,Alan Corrêa Diniz
,Gil de Oliveira-Neto
,G.A. Monerat
Posted: 11 July 2025
Method of Determining Wind Shear Threshold by Using Historical Sounding Data in Experimental Area
Tingting Shu
,Qinglin Zhu
,Xiang Dong
,Houcai Chen
,Leke Lin
,Xuan Liu
Posted: 23 June 2025
Differences Research in Time Comparison and Positioning of BDS-3 PPP-B2b Signal Broadcast Through GEO
Hongjiao Ma
,Jinming Yang
,Xiaolong Guan
,Jianfeng Wu
,Huabing Wu
Posted: 21 May 2025
Quantum Harmonic Structuring of Filaments and Voids via Resonance-Suppression Fields
Simon Ashley Tomlinson
Posted: 09 April 2025
The Influence of Observation Media on Spacetime Effects and the Limitations of Special Relativity
Kaijun Dong
,Xiaoru Dong
Posted: 31 March 2025
Beyond the Magnetic Monopole: The Magnetic Metapole
Angelo De Santis
,Roberto Dini
Posted: 31 March 2025
Origin of Space Weather, Radiation, and Its Impact on Planetary Bodies in the Solar System
Sankha Debnath
Posted: 29 March 2025
Harang Discontinuity Observed by Multi-Instrument Satellites in the Topside Ionosphere During Substorms
Ildiko Horvath
,Brian C. Lovell
Posted: 25 March 2025
Using Machine Learning for Lunar Mineralogy-I: Hyperspectral Imaging of Volcanic Samples
Fatemeh Fazel Hesar
,Mojtaba Raouf
,Peyman Soltani
,Bernard Foing
,Michiel J.A. De Dood
,Fons J. Verbeek
This study examines the mineral composition of volcanic samples similar to lunar materials, focusing on olivine and pyroxene. Using hyperspectral imaging (HSI) from 400 to 1000 nm, we created data cubes to analyze reflectance characteristics of samples from Italy’s Vulcano region, categorizing them into nine regions of interest (ROIs) and analysing spectral data for each. We applied various unsupervised clustering algorithms, including K-Means, Hierarchical Clustering, Gaussian Mixture Models (GMM), and Spectral Clustering, to classify the spectral profiles. Principal Component Analysis (PCA) revealed distinct spectral signatures associated with specific minerals, facilitating precise identification. Clustering performance varied by region, with K-Means achieving the highest silhouette score of 0.47, whereas GMM performed poorly with a score of only 0.25. Non-negative Matrix Factorization (NMF) aided in identifying similarities among clusters across different methods and reference spectra for olivine and pyroxene. Hierarchical clustering emerged as the most reliable technique, achieving a 94% similarity with the olivine spectrum in one sample, whereas GMM exhibited notable variability. Overall, the analysis indicated that both Hierarchical and K-Means methods yielded lower errors in total measurements, with K-Means demonstrating superior performance in estimated dispersion and clustering. Additionally, GMM showed a higher root mean square error (RMSE) compared to the other models. The RMSE analysis confirmed K-Means as the most consistent algorithm across all samples, suggesting a predominance of olivine in the Vulcano region relative to pyroxene. This predominance is likely linked to historical formation conditions similar to volcanic processes on the Moon, where olivine-rich compositions are common in ancient lava flows and impact melt rocks. These findings provide a deeper context for mineral distribution and formation processes in volcanic landscapes.
This study examines the mineral composition of volcanic samples similar to lunar materials, focusing on olivine and pyroxene. Using hyperspectral imaging (HSI) from 400 to 1000 nm, we created data cubes to analyze reflectance characteristics of samples from Italy’s Vulcano region, categorizing them into nine regions of interest (ROIs) and analysing spectral data for each. We applied various unsupervised clustering algorithms, including K-Means, Hierarchical Clustering, Gaussian Mixture Models (GMM), and Spectral Clustering, to classify the spectral profiles. Principal Component Analysis (PCA) revealed distinct spectral signatures associated with specific minerals, facilitating precise identification. Clustering performance varied by region, with K-Means achieving the highest silhouette score of 0.47, whereas GMM performed poorly with a score of only 0.25. Non-negative Matrix Factorization (NMF) aided in identifying similarities among clusters across different methods and reference spectra for olivine and pyroxene. Hierarchical clustering emerged as the most reliable technique, achieving a 94% similarity with the olivine spectrum in one sample, whereas GMM exhibited notable variability. Overall, the analysis indicated that both Hierarchical and K-Means methods yielded lower errors in total measurements, with K-Means demonstrating superior performance in estimated dispersion and clustering. Additionally, GMM showed a higher root mean square error (RMSE) compared to the other models. The RMSE analysis confirmed K-Means as the most consistent algorithm across all samples, suggesting a predominance of olivine in the Vulcano region relative to pyroxene. This predominance is likely linked to historical formation conditions similar to volcanic processes on the Moon, where olivine-rich compositions are common in ancient lava flows and impact melt rocks. These findings provide a deeper context for mineral distribution and formation processes in volcanic landscapes.
Posted: 17 March 2025
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