The Hour is Blue

Hrishabh Srivastava: Probing Dark Matter with Nature’s Magnifying Glass

In this conversation, I speak with Hrishabh Srivastava, a PhD student in Astronomy at the University of British Columbia and a member of the Euclid Strong Lensing Science Working Group. His research uses gravitational lensing—the bending of light by massive objects in space—to investigate the distribution of dark matter in galaxies.

CiTR 101.9 FM / The Blue Hour

Recorded live on September 8, 2026

Listen: CiTR | Spotify | YouTube

The Blue Hour, hosted by Farha Guerrero, airs live every Tuesday at 2 p.m. PT on CiTR 101.9 FM at the University of British Columbia in Vancouver, Canada.

Hrishabh Srivastava is a PhD student in Astronomy at the University of British Columbia and a member of the Euclid Strong Lensing Science Working Group. Originally trained in materials engineering and data science at the Indian Institute of Technology Madras, his research now brings together astronomy, cosmology, statistics and computational methods.

His work focuses on strong gravitational lensing: a phenomenon predicted by Einstein’s theory of general relativity in which the gravity of a massive foreground object bends and distorts light travelling from a more distant galaxy. These rare alignments can create arcs, rings or multiple images—and allow astronomers to investigate matter that cannot be observed directly.

Hrishabh is developing methods for identifying these gravitational lenses within the enormous number of galaxy images being produced by the European Space Agency’s Euclid mission. Finding the lenses is only the beginning. By studying how light has been distorted, astronomers can reconstruct the distribution of dark matter within the galaxies doing the lensing.

Earlier this year, Hrishabh was a finalist in UBC’s Three Minute Thesis competition with Probing Dark Matter with Nature’s Magnifying Glass. During our conversation, he reads that three-minute presentation, before we explore some of the ideas behind it: Einstein and gravitational lensing, the Euclid Space Telescope, the search through billions of galaxies, and the much larger question driving his research—what is dark matter?

Transcript

Transcript lightly edited for clarity while preserving the natural rhythm of the live conversation.

Farha: Hrishabh, welcome to The Blue Hour.

Hrishabh: Hi Farha, thanks for having me.

Farha: I thought I would do something a little fun.

You did this remarkable Three Minute Thesis presentation recently, I thought, if you don't mind reading from the actual presentation, we can enjoy those three minutes and then talk about your research.

Hrishabh: Of course, let's do it.

Galaxies are pretty, and there are so many of them around us.

Now think about a situation when one galaxy lies right in front of the other. Would the background galaxy be visible to us? Certainly not.

Or so we thought, until a young Mr. Albert Einstein explained how gravity of the foreground galaxy will bend the light coming from the background galaxy, making the foreground one act like a lens, or as he called it, a gravitational lens.

Now, despite having so many galaxies out there, these gravitational lenses are incredibly rare, barely one in 15,000. To find them, you need to scan enormous areas of the sky with a powerful space telescope, like the Euclid Space Telescope.

In fact, with Euclid, for the first time ever, we are observing about 1.5 billion galaxies in just six years.

I am part of a team of over 150 members from more than 15 countries, going through millions of images from this telescope trying to find these rare lenses.

But what exactly am I doing?

I'm designing an algorithm to specifically look for these ring-like features in the images, thus finding lenses about 10 times faster than the currently used AI-based models, which end up wasting a lot of time, and fresh water as well, in just learning what features to look for.

But finding lenses is just the first step of my research.

Why am I doing so? Why are they even interesting? Hear me out.

About 80 years ago, we realized that all the galaxies out there, including ours, are held together by ghost particles.

We don't see them, but we feel their massive gravity.

They make up about 85% of the total matter in our universe, yet we know nothing about them. Isn't it concerning?

Imagine, everything you have seen, everything you will ever see, barely makes up 15% of what's actually out there.

And in fact, it's these ghost particles, aka the dark matter particles, in these galaxies that are bending the light.

So, just by looking at these images, I can figure out the distribution of dark matter particles in these galaxies.

Exactly how your eye doctor designs your lens just by knowing how blurry your vision is. Except for the fact that these lenses don't cost you your insurance money.

This is the ultimate goal of my research: to answer the century-old question, what is dark matter?

As it turns out, galaxies aren't just pretty, but are extremely useful as well.

In our case, they are nature's own magnifying glass to probe this fundamental ingredient of our universe.

If only we knew where to look.

Farha: That was really nice. I really enjoyed listening to you read it.

Did it feel like three minutes?

Hrishabh: I'm not sure.

Farha: I was saying to you earlier, that it seems very difficult, the idea that you are presenting a lot of research in a very short period of time.

How were you able to come up with that?

Hrishabh: It's certainly difficult, especially in the Three Minute Thesis competition. We have to describe this to a non-specialist audience. We can't use all the jargon that we use in our research.

Technically, we are presenting five years, or in my case two years, of our work in just three minutes.

So you think about what you want to say, you write it down, and then you present it in front of people. You ask your friends, your supervisor, others in your group, and more importantly, people who are not in your group.

You get their feedback and see if they are actually getting what you're trying to say.

That's what I did. I presented it in front of people from other departments, people from back home as well. It wasn't just me, it was a group effort.

Farha: And you were a finalist. You don't know how many people were competing because it starts at the department level, and then you got into the last group of 10.

You presented this at the Irving K. Barber Learning Centre, is that right?

Hrishabh: The final was at Irving K. Barber, yes.

Farha: Wonderful. I think that sums up everything. We now know everything about you!

Actually, there's still a lot to unpack from those three minutes, and that's what I'm hoping we can do. Maybe it can be a template for our discussion today.

You did say some words that, for someone who may have no idea about Einstein's theory of relativity, maybe doesn't remember much astronomy, or may not even know what a gravitational lens is, there needs some explanation.

Why don't you start with some basic definitions for us, and then we'll dig into what you're actually hoping to achieve?

Hrishabh: Let's start with what gravitational lenses actually are.

Imagine, as I was saying in my Three Minute Thesis, you have a galaxy in front of you, and then you have another galaxy which is right behind that galaxy.

If I ask you, should you be able to see the galaxy in the background if there's another galaxy right in front of you? You would say no, right? Because the light from the galaxy in the back is going to be blocked by the galaxy in front of it.

That's what we all thought until Albert Einstein came in.

Einstein explained gravity in a slightly different and a lot more interesting manner.

According to Newton, the thing we knew about gravity is that gravity is caused by particles with mass, and it affects particles with mass as well, because Newton's gravity is GMM by R squared. You have the mass of the particle causing gravity and then the mass of the particle that is being affected by gravity.

But Einstein said something very different. He challenged a 500-year-old belief. He said that gravity affects the curvature of space-time itself.

You need a massive object which causes gravity, and when I say it causes gravity, it distorts space-time itself.

If you want to imagine this, imagine a big piece of cloth made of spandex. It's huge and generally flat because you've spread it out.

Now, if you place a heavy ball on it, it's going to get distorted, right? That's what gravity is according to Einstein.

Light is massless. According to Newton, light should not be affected by gravity because it does not have mass.

But according to Einstein, if gravity affects the fabric of space-time itself, then light should be affected by it as well.

And that's what we observed.

Coming back to strong lensing, if I have a galaxy in front, the gravity of this galaxy will bend space-time. When light from the background galaxy approaches us, it's going to bend around the foreground galaxy because space-time itself is bent.

What we end up seeing is the galaxy which was in front of us, and then we see a ring of light around it, which is the image of the galaxy in the background.

This phenomenon is called gravitational lensing in general.

When there's one lens, which is the galaxy in the front, and one source, which is the galaxy in the back, it's called strong gravitational lensing.

That's what strong gravitational lenses are.

Farha: But it's not common, right? It's hard to find. They're rare.

Hrishabh: It is, and it's very easy to think about why it would be so uncommon.

We live in a universe full of galaxies, full of stars.

In order to observe a strong gravitational lens, as I was explaining in this example, you need to have three objects directly in line. You need to have yourself as an observer, a galaxy in front of you, and then another galaxy right behind it.

In a universe with galaxies spread all around, what are the odds that you will find three objects directly in your line of sight? It's very, very rare.

In fact, Albert Einstein, when he predicted this phenomenon, also made a statement. I'm not going to quote him because I don't know the exact statement he said, but he meant that we were never going to be able to observe this phenomenon in real life.

We did.

But again, he was not completely wrong, because these are rare. The odds of observing them are about one in 15,000.

Euclid is observing about 1.5 billion galaxies, and we are expecting to find only about 100,000 of these strong lenses.

Farha: That's amazing.

When you think about Einstein, do you think that if Einstein was alive today, he'd be pretty fascinated by this conversation?

He was doing a lot of predictions and ideas, and now, a century past, you've all come a long way with trying to really understand this even more.

Hrishabh: Einstein would technically be happy with the technology we have developed over time, that we can actually observe everything that he predicted.

We have observed gravitational waves that he predicted, strong lenses, gravitational lenses, as he predicted.

That would be interesting.

But theoretically, he was a lot smarter than any of us. He would probably be theorizing something else, something which we might again think, what is this? And then we find it 100 years later.

Farha: That Einstein. Wow.

One way that I was trying to understand this, and I don't know if this is a good analogy, is if you imagine a very thick glass, say a wine glass, and then you have a candle and you're looking through the glass and seeing that light bend.

Is that one analogy that might work if people want to visualize this ?

And can you also tell us about the eye doctor? In your three-minute talk, you mention this. How does that analogy fit in?

Hrishabh: Let's start with the wine glass. You gave a perfect example.

I was recently describing this to a group of kids, third to sixth grade, in one of the summer camps.

You can actually observe strong gravitational lensing yourself.

Take a wine glass. It's not the upper part of the wine glass, but the base of the wine glass which is perfect for this.

On a sheet of paper, draw a dot, a bigger dot, and then place the bottom of the wine glass over it. You will see a ring forming.

That's exactly how strong lensing works.

This is how we taught kids what gravitational lensing is.

What I meant by the eye doctor example was, it's a natural question to ask: sure, dark matter is causing lensing, but how can you describe dark matter just by observing a strong lens?

In the case of an eye doctor, if you have blurry vision, you go to your doctor and they give you a test where you have to look at a few pictures. Depending on how blurry they are, they design your optical lens.

Different people use different types of lenses. Some could be thicker in the middle and more tapered at the end. It varies.

My point was that just by looking at something, you know how bad your vision is.

If I'm looking at a strong gravitational lens, and I see a ring of a particular size, I have a decent idea of the lens through which I'm looking at this image, how cluttered that lens would be, how thick that lens would be.

That's what I meant by the eye doctor example.

Farha: I love both of those. That's great.

Let's talk about this ring of light, because it is called the Einstein ring, right?

Can you describe what it actually looks like when you see the images?

Hrishabh: It looks exactly like a ring.

Let me define a few names that I'm going to use.

We have two galaxies in the definition of strong gravitational lensing. The galaxy in front, we're going to call the lens. The galaxy in the back, we're going to call the source.

What you end up seeing is the lens right in front of you, which is a galaxy. You see that galaxy as a blob of light, and then you see a ring around it.

In the real world, you would see an exact ring when the background source is exactly behind this galaxy, but the odds of that occurring are even lower.

When the source galaxy is slightly moved towards the left or right, or wherever, you don't see a complete ring. There are times when you just see an arc, or two arcs.

Ideally you would expect to see a complete ring, and we have observed a lot of perfect gravitational lenses with a perfect ring-like structure.

Farha: And this is from a very, very big data set.

The curious question is, when you're actually seeing this, how do you find them? What's the process?

You mentioned the algorithm you're working on developing to make it easier to find them, but how does it come to you if you're part of this team around the world that's looking at these images?

Hrishabh: That's a very good question.

Since the paper is in progress, I can talk about that.

What used to happen is, when you see a strong lens, you have a fair idea that it looks like a strong lens.

But as you said, this is a big data set. We are going to observe about 1.5 billion galaxies. You can't expect a human to go through all these 1.5 billion images to find these lenses.

What the Euclid team has done is develop a pipeline, a whole engine to find them, and it consists of three main steps.

The first step is using a machine-learning-based classifier. You train machine learning on how to identify lenses, and then you show it all of these galaxies. It finds all the possible lens candidates and ranks them based on how likely it thinks something is.

You take the top lens candidates that machine learning has identified and give them to citizen scientists.

This is something very interesting. What we have done in Euclid is a program called Space Warps, in which people, including young people who are interested in astronomy, can participate as citizen scientists.

They look at all these images, and the highly ranked machine-learning samples are classified and then ranked again based on what people think.

Once you have a catalogue of that, it goes to the third stage, which is expert inspection.

We have a team of Euclid strong-lensing scientists. We look at all the strong lenses that the citizen scientists told us are highly probable lenses, and then we start grading them.

We grade them A, B, C, X.

You might ask, what do you mean by grading something? Either something is a strong lens or it's not. What do you mean by grade A, grade B?

What happens is, there's no way to immediately confirm if the object you're seeing is a strong lens or not. It could very well be a ring galaxy, a galaxy which looks like a ring, or it could be anything which sort of looks like a ring.

There are many false positives that we have identified.

Based on our experience, we grade strong-lens candidates. Grade A means we are very confident that these are lenses. Then you have grade B, grade C, and grade X are non-lenses.

After that, we make a follow-up observation.

How do you confirm if something is a lens?

The only way to confirm it is to calculate the distance to the central galaxy and to the ring. We know that the source is supposed to be behind the lens.

The distances, or in astronomy we use the word redshift, to the central lens and to the ring are going to be different.

Once we find that to be the case, we know that something is a strong lens.

Euclid does not have very good spectroscopy capability as of now, so we use ground-based telescopes to make follow-up observations.

If you have a catalogue of five lens candidates, for example, and you know where each candidate is, you can use another telescope to look at that specific part of the sky, get a spectrum of it, and confirm if it is a lens or not.

Farha: Where does your algorithm fit into this process?

Hrishabh: In the very first part.

Ideally, what we would like to have is a classifier, machine-learning-based or whatever, that is able to find all the good strong lenses so that we do not need as many steps after this.

My algorithm is different from the machine-learning classifiers that we are using right now, which are CNNs or simple image classifiers that can identify any type of image.

What I am trying to develop instead comes from the fact that we are astronomers, we are physicists. We understand what strong lenses are. We understand the physical aspects of a strong lens.

Our idea was to extract a few features out of a strong-lensing image and use those features to train a classifier.

I am still using machine learning, but I am using a much simpler version of it.

That reduces training time. You can argue that once a machine-learning model is trained, testing does not need as much time, but it still needs computational resources when it's being applied.

For one lens or two lenses, it might not make a big difference, but Euclid is going to observe about 1.5 billion galaxies.

That is a lot.

So it makes a significant difference when you use a simpler classifier which uses far fewer resources.

If I have to summarize what I am doing, I am using my knowledge as a physicist to reduce the workload on a machine-learning-based classifier.

Farha: That's amazing.

If you think about that, you're trying to make AI work less in a way, right?

Hrishabh: Yes.

Farha: And that's something I want to talk about, but not just yet.

When you're looking at these, these are recognizable geometries that you are understanding, the arcs, rings, and they have a kind of symmetry.

How is this image-recognition problem different from what happens when you ask a computer to analyze an image? How is that different from the algorithm you're creating?

Hrishabh: While we are still learning about gravitational lenses, what's interesting is that we know a lot about optical lenses.

We all use glasses. An optical lens is made of glass, a gravitational lens uses gravity, two very different things, but the effect, the final image formation, is essentially the same.

That's why we call them gravitational lenses.

We are using the theory we already know about optical lenses and applying it to gravitational lenses.

I think it was in 1936 when a Dutch physicist called Fritz Zernike discovered a very interesting phenomenon called phase-contrast microscopy.

He became interested in understanding the optical aberration of optical lenses much better.

What he did was develop a mathematical basis, a set of polynomials, in order to understand these optical aberrations.

These are called Zernike polynomials.

Essentially, each of the lower-order Zernike polynomials corresponds to a specific optical defect, like astigmatism, coma, myopia, hypermetropia, defocus, and others.

We are using these polynomials as a basis to extract features.

I've said a lot of big words, but what do I mean by that?

Think of my image as an image that I'm decomposing into different polynomials.

My image is going to be equal to A1 P1 plus A2 P2 plus A3 P3, and so on, because there are an infinite set of polynomials.

P1, P2, P3 are the polynomials that we know about. These A's, these coefficients of these polynomials, are what we are using as features.

Let's say polynomial P1 corresponds to hypermetropia, or P2 corresponds to astigmatism.

In an image of a strong lens, I can sort of tell that it consists of 50% of this polynomial, 20% of this polynomial, and so on.

Instead of using a lot more numbers, I can use five or six numbers to describe this whole image.

What is a CNN or a simple image-classification classifier doing? You're giving it the whole image as an input.

Imagine the image is made of 100 by 100 pixels. You're giving it around 10,000 numbers to find lenses.

What I am doing instead is finding five important numbers from that image and giving those to the classifier, making its job easier, reducing the load on computational resources, and in turn saving natural resources.

Because why do we have knowledge if we don't use it?

Farha: I think people like Einstein inspire you to think, because in the end, we human beings have extraordinary intelligence and can come up with a lot of things that we can, in turn, also teach AI.

Let's hit this idea now.

Data centres and AI are in the news a lot, and one of the reasons is because AI uses a lot of natural resources, which you've mentioned.

Why do you feel your research, or your approach, is going to be helpful in this regard?

Do you think scientists in the future will look to this kind of decision-making as a way to direct their research, knowing that it could have positive environmental impacts versus negative?

Hrishabh: Let's start with the fact that the future of the world is going to consist of a lot of AI.

As with everything else in the world, everything uses energy.

If I have a task at hand and I'm going to use AI to solve that task, but I can find an alternative that uses AI in a much simpler way and uses a lot fewer resources, that would be a small step.

My research is a small step towards choosing a sustainable path, using an alternative to more complex AI.

With time, because we have limited resources on our planet, as the use of AI increases we might have to pick and choose.

If there's a task for which we can use a simpler version, we would have to choose the simpler way of doing things.

That will certainly require a lot more from our side before we get AI to do its own thing, but I think that's worth it because ultimately the total amount of resources is limited.

At least until we find another resource for extracting energy, we have to choose a sustainable alternative to simply throwing everything into an AI classifier and asking it to do everything.

My research is a small step towards a broader goal because, in the future, with more complex space telescopes going into space, we are going to have a lot of data to work with.

If we can find ways to work with data and find cool stuff, but also minimize the use of resources, that would be ideal.

Farha: Even if it's a small idea at this stage, it could have larger implications in the future.

It's really nice to see a young person like yourself thinking about that because, in the end, everything is always about future generations.

Let's quickly go back to something you say in your three-minute lecture. It has so much in it that we can extract even more from it.

There's one thing you say: ghost particles.

I was curious about that because dark matter is still hard for us to imagine, and even to define.

I don't know if we'll ever be able to put something as clear as water in our minds when we think of dark matter. Even the name dark matter says something about it.

But you say ghost particles. What do you mean by that, and how can you define it?

Hrishabh: I'm calling dark matter ghost particles because we don't see them. Dark matter particles don't interact with our usual light particles or electromagnetic radiation.

That's why I've called them ghost particles.

The only way to know dark matter exists is through gravity.

In fact, that's how it was discovered, and the discovery was quite interesting.

Astronomers were observing galaxy rotation curves, how fast galaxies are rotating.

Think about it.

If I give you an ice cream in your hands and ask you to rotate it, there will be an optimal speed at which the ice cream is still an ice cream.

If you rotate it any faster, it will start splashing everywhere. It will start getting destroyed.

Now assume you have an iron ball in your hands and you're rotating it as well. You can keep rotating it faster and faster, but it still won't get destroyed because iron is a lot denser than an ice cream scoop.

What astronomers observed was something interesting.

The galaxies are rotating faster than the amount of matter present in them should allow.

With the speed at which these galaxies are rotating, and with the matter present in them, they should not have existed.

That's what made astronomers realize that there is something in these galaxies which we can't see, which is adding additional gravity.

That's how we discovered the existence of dark matter, a kind of matter that exerts gravity and is holding galaxies together.

But we don't see it. We detect it indirectly, through its gravitational effect.

That's why dark matter is cool.

And it's even more cool because we realized that about 85% of the total matter in our universe is actually dark matter.

Everything you see around us is just 15%.

Farha: So we're inferring it, but we can't actually see it.

That 85% was going to be my next question because that's a huge number.

It may come as a surprise because a lot of us think that when we look up at the night sky - my son took out his telescope late at night the other day, it was a clear sky - you feel you can see everything.

And yet you say 85% of the total matter is, dark matter.

Can you give us some more analogies about that?

Hrishabh: The way we find out the quantity of dark matter is, again, we can look at a galaxy rotation curve, how fast something is rotating.

In order to be stable, it needs to have a certain amount of gravity. Let's say it needs to have X amount of matter.

There's visible matter, which we can see. Then we realize, this is how much matter we're seeing, but we need this much matter for this galaxy to exist.

By virtue of these galaxies existing, we realize that the remaining amount of matter has to be dark matter.

When we found out the required remaining amount of matter, we found it to be almost 85%.

And this is not specific to one galaxy.

Eighty-five percent is the total dark matter content when we look around the universe. When we see all the visible matter, and then see all the gravitational structures present in our universe, it requires the presence of about five times more dark matter just to exist.

Otherwise, nothing would exist.

That's how we found that there's about five times more dark matter than visible matter in the universe.

Farha: How do you visualize dark matter in your head?

Hrishabh: It's difficult.

The way I think about dark matter is that these are particles which are present around us.

If I'm using my eyes, I can't see a lot of different types of matter particles around us. We can detect things using telescopes that we can't see with our naked eyes.

If I had to visualize dark matter, I just visualize it as a particle which could be going through me right now.

There could be a lot of them here in the studio which we just can't see.

Little particles flying around?

That's the thing, we don't know.

We don't know how dark matter interacts with itself. They could be going through themselves, or they might have a structure of their own.

We don't know that.

That's why dark matter is cool. It's difficult to visualize.

It's just matter. I don't know, there could be a book made of dark matter or something. I'm not sure.

Farha: It feels like you enter the science-fiction realm when you think about dark matter because it is so elusive, so strange, and we still don't know.

But that's what you're after. That's what you're looking for.

Maybe it's time to ask you about your own path because you started in engineering and then moved into physics and astronomy.

Why do you want to study what you're studying now?

Hrishabh: My path to astronomy was a bit unconventional.

I grew up in India. We have this nationwide entrance exam called the Joint Entrance Examination, which is one of the most difficult entrance exams.

You have to qualify for this exam to get into the good institutes in the country.

The unfortunate problem is that, if you don't have a very good rank, you don't get to choose what you're going to study.

I took this exam in 2019. I got a rank of around 5,000, and I got into materials engineering.

I started studying it, which was interesting, but while I was there I also became part of the institute's astronomy club.

That fascinated me.

Even before that, when I was still in high school, I attended a workshop which was a little coincidental, accidental, because I wasn't really keen on going to this workshop, but my teacher sent me to it.

Apparently it was a workshop in which we made an astronomical telescope of our own.

There were things that happened throughout the years that got me more and more fascinated with the sky and with the universe we are living in.

That's how it started.

Then, in my third year of undergrad, I got a Mitacs Globalink Research Internship, which gave me a chance to come to Canada and actually pursue whatever I wanted to.

Fortunately, I got matched with my current supervisor.

I came here and I loved Vancouver, I loved UBC, I loved studying astronomy, being part of this group, talking about galaxies, talking about the universe and being around all these great minds.

That's when I decided this is what I want to do.

It was difficult to switch from materials engineering to astronomy, so I also did a master's in data science to make it more sensible.

Data science is used everywhere.

I did my master's in data science and then applied to graduate school.

Now I'm back here with my supervisor studying astronomy.

Farha: No regrets?

Hrishabh: No regrets. In fact, I'm quite happy.

Farha: I can feel you have a lot of positive energy.

Another thing I will say is that you come across as a teacher.

I was thinking about this while talking with you, because you are so young. I could see you as a professor one day, teaching.

Do you dream of that?

Hrishabh: I would love to be. If I get a job as a professor, that would be ideal.

But in the economy we're living in, it's quite difficult.

Farha: Don't give up on that dream.

We're here on the UBC campus. Let's not forget that. It's the first day of the semester and it's buzzing with energy.

So many students have come here, maybe for the first time, and it's that first lecture, their first interaction with their faculty members.

Those are really important.

Sometimes we forget how much a professor can change the life of a student.

It can be one teacher who inspires them...

There's something else I wanted to talk about. It was in the longer presentation that you sent me.

You use a phrase, "the language of the universe."

Why do you think of mathematics as a kind of language?

Hrishabh: Because mathematics is used to describe everything that happens in the universe.

What are languages? Languages are a means of communicating ideas, communicating information, and we use math to communicate ideas about how the natural world works.

I don't think it's just me. Physicists call maths the language of the universe because that's how we speak. We speak in numbers.

Farha: Do you feel it is that language that describes nature in a very powerful way?

Hrishabh: It does.

Maths describes nature.

More importantly, it's a language that everyone can understand and everyone can agree upon.

It's straightforward, it's experimental. You can test it and see the results.

Farha: Another thing we've talked about a little bit is that you have been giving presentations, and you told me you're going to be doing one very soon at the H.R. MacMillan Space Centre.

Why do you feel that public engagement, communicating science to high school students and to the general public, is important?

Hrishabh: I think it's my responsibility as a researcher.

I'm a privileged researcher. I can be in my lab working on the thing I have the whole day, thinking about ideas of how the universe is built, and I get paid for it.

That's my job.

So I also think it's my responsibility to communicate everything that I have learned to people who are as interested as I am, but might not be privileged enough to spend their whole time doing that.

I don't think there's a point in spending your life working on something and not sharing it with everyone.

It's about the growth of society as a whole when you learn something new.

Science communication is extremely important.

It also teaches people the art of scientific inquiry, which is ideally my goal.

I want to inculcate this culture where, even if you don't understand science, you can still ask questions in a scientific manner.

That's very important.

I feel that if everyone learns the art of scientific inquiry, it will solve a lot of problems in the world we're dealing with.

Farha: Absolutely.

For people on this campus right now who have just started getting involved in their departments, say grad students, how do they do this sort of research outreach where you can get off campus and engage with the general public?

Where do you create those opportunities? How do you find those connections?

Hrishabh: Fortunately, being at UBC, you get a lot of chances to do outreach.

Especially in our department, we have an outreach coordinator, and you just have to look out for opportunities.

She keeps sending emails about opportunities to speak to the public, and that helps a lot.

The Three Minute Thesis was also quite helpful because once you talk to people and participate in competitions like this, you explain your research in a general manner without using field-specific jargon.

That makes people interested in you.

They can come and talk to you.

This video of mine is out there on YouTube. When people look at it, they can reach out and ask questions.

That also helps.

Farha: Now that you're starting your PhD, do you feel that's going to be even more important, this engagement that you've been doing so far?

Do you think you'll have the time?

Hrishabh: It's going to be different, but as I said, I find science communication to be an equally important endeavour that I want to do.

You have 24 hours. You have to pick and choose what you're going to use those 24 hours for.

If you find something important enough, you can always find a way to do it.

Five years of a PhD, sitting in your lab, working in front of your computer on something specific, it's fun.

But it's also fun to describe it to people.

It helps you introspect about whatever you've learned.

If you can describe your research to someone in a simple manner so that they understand and appreciate the work you're doing, that also tells you a lot about how well you have understood your own work.

This is something attributed to Einstein again. I don't know if he actually said it, but I'm sure he did.

Farha: Finally, as you are about to embark on this new project of the PhD, what do you hope to achieve in the next five years?

Hrishabh: My research goal is to understand the dark matter distribution of the universe.

I'm going to use these gravitational lenses to find how dark matter is distributed in these galaxies.

If I do it for a catalogue of 100,000 galaxies, that's going to give me a fair idea of how dark matter is distributed everywhere.

That will tell me a lot about dark matter itself.

In a way, I'm hoping to add a bit of new knowledge to what we understand about dark matter in the upcoming five years.

That's the hope.

Farha: And the Euclid telescope, can you remind me, it was launched a few years ago?

When is the mission over?

Hrishabh: Interestingly, I'm quite lucky because the timeline of the Euclid mission is coinciding with my PhD timeline.

It was launched in 2023.

It started taking data in 2024, around when it had its first quick release. That's when I started my master's.

Euclid is going to have its first data release partly in November and partly next year.

I think it's going to keep taking data for the next five or six years, which is around the time I'm going to work on my PhD.

So that's ideal.

Farha: That's amazing.

There's some fate in that for sure.

I'm going to give you one last chance to say anything else that you would like to.

When we put a transcript of this interview online, we can link your research, and hopefully when that paper you've hinted at is published, when that comes out, tell me and I'll put it on this interview as well.

Is there anything else you want to share for someone who wants to be part of the research that you're doing?

Hrishabh: I want to give a broader message to people.

I started as an engineer, as someone with a passion for astronomy.

Given the world we're living in, you're always prompted to take up a corporate job and work on that because you feel, astronomy is a passion of mine, but is it even worth pursuing? Can I even do it?

I feel that if you are passionate enough about something, you always find a way to pursue that dream.

No matter what your background is, you can always find a way to work on the thing you want to work on because we've got one life.

You don't want to be on your deathbed thinking, I wish I could have done that.

That's a broader message.

But if you want to work on Euclid, that's a little more specific.

You have to be part of one of the countries involved in Euclid, which is primarily Europe, but Canada also has a stake in Euclid.

You have to be part of the group.

Fortunately, my supervisor was part of Euclid.

Farha: Who is your supervisor?

Hrishabh: Douglas Scott.

He's part of Euclid, so that's how I got my chance to work with a big collaboration.

It's always good to work with big collaborations because you keep discussing your updates with other people.

They also keep you on your feet because everyone is working hard to achieve a goal, so you also want to contribute.

You can't slack.

Farha: It's been such a pleasure.

I was really excited to have you because, when I watched your three-minute video, I knew that this is a man who's got big ambitions.

I wish you the best of luck as you start your PhD.

I have no doubt that when that mission ends, you'll maybe be starting another mission.

Hrishabh: That's the way to go.

Farha: As you said, if Einstein was alive, he would probably just do something else, invent a new theory.

You have been tuned in to an episode of The Blue Hour on CiTR, the broadcasting voice of the University of British Columbia.

CiTR began as a student club in 1937 and gained a place on the FM dial in 1982.

My name is Farha Guerrero. I'm the volunteer host and producer of The Blue Hour.

And thank you again, Hrishabh, for coming in today.

Hrishabh: Thank you for your time.

Further Reading & Viewing

More from UBC Physics & Astronomy on The Blue Hour

For further reading and listening, explore these conversations with other UBC physicists and astronomers:

Michelle Kunimoto — Reading Starlight
Exoplanets, the Kepler and TESS space telescopes, and how astronomers infer distant worlds from starlight.
Read / listen

Jaymie Matthews — Listening to the Stars
Stellar seismology, exoplanets, and MOST, Canada’s first space telescope.
Read / listen

Philip Stamp — Superfluid Helium and Quantum Vacuum Tunnelling
Quantum mechanics, the quantum vacuum, superfluid helium and the Schwinger effect.
Read / listen