In 2022, for the first time, NASA managed to convert and broadcast the sound waves emitted by a supermassive black hole io audible sounds for humans. This black hole is located in the ceer of the Perseus galaxy cluster and is located at a distance of about 250 million light years from Earth. The sound waves extracted from this black hole with an increase of 57 to 58 octaves have been transferred to the range of human hearing and have produced an eerie and unearthly sound that, according to NASA, has a frightening and even angry state.
Although there is a vacuum in space and sound cannot normally be transmitted, in 2003 (1382) astronomers managed to detect sound waves in the hot gases around this black hole. This discovery was made using X-ray data and spectral analysis, which is a turning poi in understanding the behavior of black holes in cluster environmes. These sound waves, which are emitted from the ceer of the Perseus galaxy cluster, include the lowest sound note recorded in the world; A note of the B flat type, which is 57 octaves lower than the middle two, and has a frequency equivale to once every 10 million years, which is much lower than the threshold of human hearing.
You can listen to the audio released by NASA below:
In NASA’s new project, these sound waves are extracted radially from the ceer of the black hole and reconstructed in a couerclockwise (clockwise) direction so that the listener can hear the sounds from all directions around the black hole. This reconstruction has been done using advanced audio generation algorithms that allow the conversion of astrophysical data io audible frequencies. The frequency of these sounds has increased up to 144 quadrillion and 288 quadrillion times to reach the range of human hearing. The end result is an eerie and mysterious sound that, like many other space sounds, conveys a sense of the unknown.
The importance of these sounds is not only limited to their scieific aspect, gases and dilute plasma flow between galaxies in galaxy clusters, which are called iracluster medium. These iercluster environmes are denser and much hotter than the iergalactic environme. This difference in density and temperature makes sound waves play a more effective role in energy transfer in these environmes. The sound waves that move in this environme have the ability to transfer energy through the plasma and cause the environme to heat up. Therefore, this heat plays an importa role in regulating the process of star formation, and as a result, sound waves can play a key role in the evolution of galaxy clusters over time.
The high temperature of the iercluster environme makes this region shine brightly in X-rays. These radiations have been recorded by advanced instrumes such as the Chandra X-ray Observatory, which have the ability to accurately image hot and energetic cosmic structures. Chandra observatory has played an importa role in the initial ideification of these sound waves as well as the implemeation of their sounding project.
In addition, another supermassive black hole named M87*, which was directly imaged for the first time, has also been subjected to the sounding project. This black hole has been observed by the Eve Horizon Telescope and instrumes such as Chandra, Hubble Space Telescope and Atacama Large Millimeter/submillimeter Array images. Images captured from the black hole show a massive outburst of matter escaping from the surrounding area at speeds that appear to exceed the speed of light in a vacuum, a phenomenon that is actually a visual error due to the high speed and viewing angle.
In the case of M87, the data used for acoustics consisted of light at differe frequencies, not actual sound waves. These data were first recorded in a visual form and then converted io audio frequencies using sounding techniques. In this voicing, radio data in the lowest frequencies produced a lower sound, optical data in the middle range, and X-ray data in the highest audio range.
Converting image data to sound not only provides a differe experience of cosmic phenomena, but can also help discover hidden details in data and provide a deeper understanding of the universe.
