The simulation meets observations in the first image of the supermassive black hole at the center of our galaxy.

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As countless scientific and general news outlets report today, the image of Sagittarius A*, the supermassive black hole at the center of our galaxy, is an incredible scientific achievement. But one aspect that has been overlooked is the central role of modeling and synthetic data in discovery.

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If you haven’t read about this amazing science news yet, Event Horizon Telescope’s own post this is a great place to get the gist. Based on years of observations from around the globe, a huge team of over a hundred institutions have managed to map out the black hole around which our galaxy revolves, despite its relative proximity and interference from dust, nebulae, etc. and other vagaries of the void.

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But it wasn’t just about pointing the telescope in the right direction at the right time. Black holes cannot be observed directly with something like Hubble or even a still-heating Webb. Instead, all sorts of other direct and indirect measurements of the object must be made – how radiation and gravity go around it, and so on.

This means that data from dozens of sources must be collected and reconciled, which is a huge task in itself and a big part of why the observations made in 2017 are only now being released as the final image you can see below. But since this project is truly without precedent (even the famous M87* image, although superficially similar, used different processes), it was essentially necessary to test several possibilities of how the same observations could have been made.

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For example, if it is “dark” in the middle, is it because something is in the way (and there is – about half of the galaxy) or because there is a hole in the hole itself (and it seems)? The lack of direct observational data makes it difficult to determine. (Note that the images here show not just an image based on visible light, but an inferred shape based on countless readings of radiation and other measurements.)

This is the first image of Sgr A*, the supermassive black hole at the center of our galaxy.

Image credits: ENT

Imagine that you are looking at an ordinary object from a distance. From the straight side, it looks like a circle – but does this mean that it is a ball? Plate? Is the cylinder visible at the end? Here on Earth, you can turn your head or take a few steps to the side to get a little more information – but try it on a cosmic scale! To get effective parallax on a black hole at 27,000 light-years away, you have to travel quite a distance, and likely break the laws of physics in the process. Thus, researchers had to use other methods to determine which forms and phenomena best explained the little that could observe.

To systematically explore and evaluate design options for imaging algorithms and their impact on the resulting image reconstructions, we created a series of synthetic datasets. The synthetic data has been carefully designed to match the properties of the Sgr A* EHT measurements. The use of synthetic data makes it possible to quantify the reconstruction of an image compared to known ground data. This, in turn, makes it possible to evaluate the choice of design and the performance of the visualization algorithms.

In other words, they generated oceans of data relating to various possible explanations for their observations and looked at how predictive those simulated black hole environments were.

Lisa Medeiros of the Institute for Advanced Study, in a very interesting Q&A worth watching in full if you have time, explained it a bit in regards to how and why the study looked at the rotation of a black hole and how that relates to the rotation of materials around it and to the galaxy as a whole.

“What was really exciting about this new result, compared to what we did in 2019 for the M87, is that in Article 5 we actually included some simulations where we explore this. [i.e. the spin relationships],” she said. “So there are simulations where the spin axis of the black hole is not the same as the spin axis of the matter orbiting the black hole, and this is a really new and exciting simulation that didn’t make it into the 2019 publication.”

Image credits: ENT

Naturally, these simulations are incredibly complex things that require supercomputers to process, and there is an art and science to figuring out how many of them make sense to do and how close they need to be to each other. In this case, the alignment issue at hand has inherent scientific value, but can also help interpret, for example, interference caused by gases and dust orbiting a black hole. If the rotation is like Thisits gravity would affect the dust like Thiswhich means that the readings should be read as This.

“Our simulations, when we look at simulations versus data, we tend to prefer models that are almost pointing at us — not pointing straight at us, but deviated by about 30 degrees or so,” Medeiros continued. “And that would mean that the black hole’s axis of rotation is not the same as the axis of rotation of the galaxy as a whole, and if you believe what I said earlier, the disk prefers to be aligned with the axis of rotation of the black hole. hole. The disk and black hole appear to be aligned, but neither is aligned with the galaxy.”

In addition to looking at specific aspects like this, there was the more general question of what shape (or “underlying original morphology”) would give the readings they got: essentially a “ball versus plate” question, but much, much more difficult. .

In one of the papers published today, the team describes the creation of seven different potential black hole morphologies, reflecting the different arrangements of its matter, from a ring to a disk and even some kind of binary black hole – why not, right? They modeled how these different shapes would produce different results on their instruments and compared them to the more computationally (and linguistically) complex “general relativistic magnetohydrodynamics” or GRMHD simulations.

You can see them in the combination of the two images from the article here:

Images of simulated black holes and how their data might be displayed to sensors on Earth.

Image credits: ENT

The idea was to find which of the simulations produced results most similar to what they actually saw, and although there was no runaway winner, the ring and GRMHD simulations (which, it must be said, were pretty ring-like) gave the most consistent results. how the data was interpreted for the final interpretation of the data and the resulting image (note that I am summarizing an extremely complex process here).

Given that these observations were made about five years ago and a lot has happened since then, there is still a lot to explore and run additional simulations. But at some point they had to hit print, and the image above is their most informative interpretation of the data. As observations and simulations accumulate, we can certainly expect even better results.

In fact, as Richard Anantua of the University of Texas at San Antonio said in a Q&A session, you can even try it yourself.

“If you are in sixth grade and can access some of the school computers, I think there is EHT visualization and we have all kinds of pipelines and tools that you can teach your class,” he said, seemingly only half. joke. “The data for some of them is public, so you can start working on it now, and by the time you go to college, you pretty much have an image.”


Credit: techcrunch.com /

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