Was LIGO’s Gravitational Wave Detection a False Alarm?

Initial results from the Alpha-CERN antihydrogen experiment indicate no discernible difference in the gravitational behavior between matter and antimatter, challenging CP violation models. Given that antimatter exhibits the same gravitational behavior as matter, distinguishing between a supermassive black hole (SMBH) composed of matter and an antimatter supermassive black hole (ASMBH) becomes challenging, as their gravitational effects are indistinguishable. This raises the question: Could the SMBH in the Milky Way, and all observed spiral galaxies, potentially be an ASMBH, with its event horizon concealing the equivalent number of antimatter particles, thereby preventing matter-antimatter destruction within a matter galaxy? This article assesses astronomical data comparing the mass of 100 SMBHs with their host galaxies. A theoretical value for the logarithmic mass relationship Log( MStellar /MSMBH ) is presented: 2.963 for ASMBHs situated in matter galaxies, and 2.285 for MSBHs in antimatter galaxies. This relationship, derived from the Ulianov Theory, is based on the premise of matter galaxy formation from protons and electrons expelled by ASMBHs during cosmic inflation. The same theory also posits antimatter galaxy formation from antiprotons and positrons released by matter SMBHs during this period. The database analysis (of 100 galaxies and their respective SMBHs) revealed that 77% of the SMBHs are composed of antimatter, resulting in a logarithmic relationship value of (2.945 ± 0.018) for the Log(MStellar/MASMBH ), while 23% are composed of matter, resulting in a value of (2.267 ± 0.036) for the Log( MAStellar/MSMBH). The congruence between these values and the theoretical prediction is likely not mere coincidence. A thorough examination of the results confirms the model's validity and underscores the precision of astronomers' mass measurements, with only 3 cases showing actual measurement errors beyond the predicted range. This discovery is pivotal, as it suggests the Ulianov Theory's potential to produce novel predictions, such as this model. Originating from a cold and empty universe, this model outlines the galaxy mass formation process, in which ASMBHs harness energy from cosmic inflation, converting it into matter and antimatter particles. This process is termed the "Small Bang" model by the author, reflecting its cold and gradual nature, contrasting the explosive nature of the "Big Bang".

Section: Discussionmentioning

confidence: 99%

Antimatter Enigma Solved: Astronomical Data Allows Identification of 77 Supermassive Antimatter Black Holes and 23 Antimatter Galaxies.

2024

“…The Ulianov Electron Distribution (UED) model has bases in the Ulianov Theory and Ulianov String Theory and Kepler Ulianov Proton Tree (KUPT) model [4][5][6]. UED introduces a different perspective in the electrons, assuming that exists a more basic distribution given by the protons distribution in the atomic nucleon defined by the KUPT model and so the electron follows orders from its related protons.…”

Section: The Ulianov Modelmentioning

confidence: 99%

Presenting the Ulianov Electron Distribution Model: A New Way to Define Electronic Orbitals

2024

This study presents a comprehensive comparison between the traditional Pauling electron distribution model and the innovative Ulianov model proposed by Dr. Policarpo Yoshin Ulianov. The Pauling model, which relies on the Aufbau principle, Hund’s rule, and the Pauli exclusion principle, has been a cornerstone in understanding electron configurations within atoms, organizing electrons into s, p, d, and f orbitals. In contrast, the Ulianov model introduces a novel linear progression for electron occupancy, proposing additional orbitals (g and h) to account for electron distribution in a manner that deviates from conventional methodologies. Through an analytical comparison, this paper evaluates both models in terms of functionality, energy levels, and methodology, highlighting the advantages and disadvantages inherent to each. The Pauling model is recognized for its empirical support and wide acceptance, offering a wellestablished framework for electron configuration. Meanwhile, the Ulianov model provides a fresh perspective that could potentially explain anomalies unaddressed by the Pauling model and predict new chemical properties, despite its current lack of empirical validation. Concluding, while the Pauling model remains the standard for electron configuration, the Ulianov model’s innovative approach challenges existing paradigms and invites further investigation into its validity and potential applications in the scientific community.

“…b) Ulianov String Theory (UST): Suggests that the collapse of imaginary time converts a 5D point-like particle (5D PUS) into a 4D string. These strings, visualized as sequences of small 4D spheres (4D PUSs), that can be wrapped in membranes and adopt various shapes (for example: circles, cylinders, spheres, shells and caps), reflecting the diverse properties and behaviors of particles within this theoretical framework [9]. UST can also explain that the proton changes its radii when form hydrogen and muonic hydrogen [10,11].…”

Section: Theoretical Bases 1the Ulianov Theorymentioning

confidence: 99%

Presented to Kepler Ulianov Proton Tree, A Way to Distribute Protons and Neutrons Within the Atomic Nucleus. First part: From Hydrogen to Krypton

2024

This work presents a novel approach to understanding the formation and structure of the 36 smallest known atomic isotopes, ranging from hydrogen to krypton, through the lens of the KUPT model. Focusing on the Small Known Isotope (SKI) of each atom, this study meticulously examines the distribution of protons across five nuclear layers (1E, 2T, 3T, 4E, and 4C), constructing a proton tree that spans from hydrogen to krypton atoms. With the aid of Artificial Intelligence, specifically Chat GPT-4, an in-depth analysis was conducted for each atom within the KUPT model framework. This process involved defining minimum stability rules for the nuclear structure, particularly regarding neutron inclusion, across the model’s first five layers. Remarkably, in 35 out of 36 cases, the KUPT model’s predictions aligned perfectly with the SKI data, underscoring the model’s accuracy and reliability. However, an intriguing discrepancy emerged in the case of the Gallium atom (62Ga), suggesting the possible existence of an unknown, lighter isotope with two or three fewer protons (59Ga or 60Ga). This discrepancy not only highlights the KUPT model’s predictive capability but also points to a fertile ground for further experimental investigation, aiming to uncover potentially undiscovered isotope forms of Gallium.