麻豆传媒

EARLIER this month, science journalist Adam Mann reported a story for Science News that had one of my favourite headlines of 2021: 鈥淎stronomers may have seen a star gulp down a black hole and explode.鈥�

The article discusses a new , published in Science on 3 September, that describes observations of a supernova that were collected with the Very Large Array radio telescope in New Mexico. The strong radio signal observed in coordination with this event suggested to lead researcher using a different set of tools, this time through optical and X-ray observations.

When they took a holistic look at the data, they came to the conclusion that the most sensible model that matched the observational data is almost Shakespearean in nature. Two stars, both alike in their gravitational attraction to each other, were in a binary orbit. One went supernova, leaving behind a compact stellar remnant 鈥� a neutron star or a The binary, gravitational attraction continued until the compact remnant eventually sank into the remaining star, ultimately leading to yet another nova.

I enjoyed the Science News piece for a couple of reasons. First, what a stellar piece of headline writing that brings a deeply unfamiliar physical environment into a relatable context. Second, Mann鈥檚 writing succeeds at being both accessible and exciting.

Though I am a professional scientist, when it comes to reading outside my main topic of interest, I join the general public in being somewhat dependent on fellow science writers to keep me informed about new developments. Like people who don鈥檛 study astrophysics at all, I still stand to learn something from science in the media.

On the other hand, one of the best parts of being a professional physicist who reads popular science is that when I get really excited about an idea, I head right to the source and don鈥檛 rely solely on other people鈥檚 interpretations. This is exactly what I did after reading Mann鈥檚 excellent rundown.

In this particular case, I felt the urge to look at the Science paper because my training as a physicist has led me to always read these stories with a healthy scepticism. Exactly how sure are we that the model held up in this paper is the best one to fit the data?

鈥淓xactly how sure are we that this model best fits the data? That is the question every scientist has been trained to ask鈥�

That I am asking this question isn鈥檛 a knock against the team involved. This is always the key question that every scientist has been trained to ask, especially in a field like astronomy where experiments can鈥檛 exactly be replicated.

To give you a sense of the translation work required, the title of the actual paper is: 鈥淎 transient radio source consistent with a merger-triggered core collapse supernova.鈥� My first task is actually parsing this title. A transient is an astronomical phenomenon that occurs on human timescales 鈥� from seconds to years. A 鈥渞adio source鈥� means the paper is about radio observations. And 鈥渕erger-triggered core collapse supernova鈥� is a fancy way of saying that two stars collided and a supernova occurred.

All of the terms in the title are key, but the one that related to my question was 鈥渃onsistent鈥�. In other words, the paper isn鈥檛 actually claiming for certain that what the team observed was a merger-trigged core collapse supernova. What the researchers are saying is that the data can be explained by this model, giving merit to the model and providing a plausible explanation for the data.

You might find yourself wondering whether this careful non-commitment is a weakness, but to me as a scientist, it is a strength that makes me inclined to trust the authors. I know that the researchers involved probably aren鈥檛 making claims beyond what the data indicates.

Maybe this is disappointing to hear. After all, science is frequently discussed in public as if it is authoritative. 鈥淪cience鈥� becomes synonymous with 鈥渒nown鈥�. Indeed, there is much knowledge that we feel certain about, thanks to scientific work. But before we arrive at a place of certainty, there is the actual doing of science, which means operating at the boundary of what is known and unknown.

Science requires a flexible mindset: we may think we are right about something and turn out to be wrong. As we gather more data, our perspective may change. The public is getting a lesson in real time about what this looks like with the covid-19 pandemic.

Happily, these questions about supernovae are only a matter of life and death for distant stars, not people. Here, it is easier to get comfortable with a bit of uncertainty about what exactly we know and don鈥檛 know.