Observable Effects and Peculiarities of the Low-Energy Quantum Gravity
Abstract
The existence of a background of ultra-strongly interacting gravitons is a key postulate of the author's low-energy gravity model. Side effects of the model due to photons interacting with this background may be important for cosmology, and their observation would be essential to support the model. The most important such effect is the quantum redshift mechanism, which may constitute an alternative to the generally accepted mechanism associated with the expansion of the universe. The model should have a weakening of the light flux due to a change in the number of photons, which replaces the influence of dark energy. Scattered photons may form a new background that can be detected by deep space missions. Some important predictions of the model are tested using observational data sets of Supernovae Ia (SNe Ia), compact quasars, and Lyman-alpha emitters. The article shows that the linear function H(z) of the model satisfactorily describes the results of measurements of the Hubble parameter. Using a trial function for the weakening parameter, the possibility of a different interpretation of the Hubble tension is illustrated. The increasing angular diameter distance of this model is fitted to a set of 120 measurements of the angular sizes of compact quasars with redshifts of 0.46–2.76 with independent calibration of their linear sizes. Attention is drawn to the possibility of a false interpretation of changes in the measured sizes of Lyman-alpha emitters observed by the James…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.