Death of stars, black holes and loud explosions… Humans will now be able to hear the universe along with seeing it, scientists are converting data into sound

 Universe Sound: We often think of astronomy as a visual science, with beautiful pictures of the Universe. However, astronomers use a wide range of analysis tools beyond photographs to gain a deeper understanding of nature. Data sonification is the process of converting data into sound. It has powerful applications in research, education and other fields, and enables blind and visually impaired communities to understand plots, photographs and other data. Its use as a tool in science is still in its infancy, but groups working in the field of astronomy are making great strides with it.

A paper published in Nature Astronomy discusses the current state of data sonification in astronomy and other fields, provides an overview of 100 sonification-based projects, and explores its future directions.

cocktail party effect

Imagine the scene: You're at a crowded party where there's a lot of noise. You don't know anyone and they are all speaking a language you can't understand. Then you hear fragments of a conversation in your own language from a far off corner. You focus on it and move towards it to introduce yourself.

While you may have never experienced a party like this, the idea of ​​hearing an intelligible voice or language in a noisy room is familiar to all. The ability of the human ear and brain to filter out unwanted sounds and retrieve desired sounds is called the 'cocktail party effect'.

Likewise, science is always pushing the limits of what can be detected, which often requires extracting very faint signals from noisy data. In astronomy we often strive to find the weakest, most distant or most fleeting signals. Data sonification helps us push these boundaries further.

abundance of good things

When we explore the Universe with telescopes, we find that it is full of cataclysmic explosions, including supernova deaths of stars, black holes and neutron star mergers that create gravitational waves, and intense explosions.

These phenomena allow us to understand extreme physics at the highest known energies and densities. They help us measure the expansion rate of the Universe and how much matter it contains, and to determine where and how elements were created, among other things.

Upcoming facilities such as the Rubin Observatory and the Square Kilometer Array will detect millions of these events every night. We are using computers and artificial intelligence to deal with the large number of detections.

However, most of these events are very soft bursts, and only computers can detect them. If the computer is given the template of the 'desired' signal, it can detect a faint sound. But if signals deviate from this expected behavior, they are lost.

And often these events are the most interesting and provide the greatest insight into the nature of the Universe. It can be beneficial to use data sonification to verify and identify these signals.

more than meets the eye

Data sonification is useful for science interpretation because humans interpret audio information faster than visual information. Furthermore, the ear can perceive more pitch levels than the eye can perceive.

Another direction we are exploring for data sonification is multi-dimensional data analysis – which involves understanding the relationships between many different features or properties in a sound.

Plotting data in ten or more dimensions at once is very complex, and interpreting it can be very confusing. However, the same data can be more easily understood through sonification.

As it turns out, the human ear can quickly tell the difference between the sound of a trumpet and a flute, even when they play the same tone (frequency) at the same timbre and duration.

Why? Because every sound is comprised of higher-order harmonics, these help determine the quality, or timbre, of the sound. The different strengths of the higher-order harmonics enable the listener to quickly identify the instrument.

Now imagine having information - different properties of the data - in the form of different powers of higher-order harmonics. Each object studied will have a unique tone, or belong to a class of tones based on its overall properties.

With a little training, a person can almost immediately hear and recognize all the properties of an object, or its classification, from a single tone.