In its early days, the universe was a hot, dense soup of subtomatic particles, which included hydrogen and helium nuclei, alias barone. Small fluctuations created a sloping pattern through this early ionized plasma, which, with the spread of the universe and cooled, folded into a dimensional place. They are known as waves, or bubbles Barion Sound Osilations (Bao) It is possible to use BAOS as a kind of cosmic ruler to investigate the effects of dark energy on the history of the universe.
Desi is a sophisticated device that can get light from more than 5000 heavenly items simultaneously.
Designed to do this: Determine the galaxies and galaxies for more than 11 billion years and measure the precise size of these bubbles (both near and far). The data can then be cut into pieces to determine how rapidly the universe is spreading in the past, better than how much its expansion is being affected.
A top trend
The results of the previous year were based on a whole year -long data analysis taken from seven different pieces of cosmic time, and includes 450,000 kosar, which has been the largest accumulated so far, of which is the most remote period of 0.82 % (between 8 to 11 billion years ago). When the basic contract with the Lamba CDM model, when the first year’s results were mixed with other studies data (including the microwave background radiation and type IA Supernova), some subtle differences arose.
Basically, these differences suggested that the dark energy was weakening. In terms of confidence, the results were equal to 2.6 sigma levels for DESI data in conjunction with CMB Datases. When you add supernova’s data, this number increased to 2.5 sigma, 3.5 sigma, or 3.9 Sigma levels, depending on what special supernova datastate was used.
DSI data must be linked to other independent measurements because “we want consistency,” said Water Low University co -spacson. “All different experiments should give us the same answer as to how much the universe is, how fast the universe is spreading. It is not good if all the experiences agree with the Lambida-CDM model, but then give you different parameters. It is just to say that this is not enough for the Lambda-CDM.