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When you think about how astronomy works, you probably think about observers pointing telescopes at objects, collecting data about their properties, and then analyzing that data to determine what those objects are truly like, and to infer what they can teach or show us about the Universe. But that's a rather old-fashioned way of doing things: one that's contingent on there being enough astronomers to examine all of that data manually. What do we do in this new era of big data in astronomy, where there aren't enough astronomers on Earth to even look at all of the data by hand?

The way we deal with it is fascinating, and involves a mix of statistics, classical analysis and categorization, and novel techniques like machine learning and simulating mock catalogues to "train" an artificial intelligence. Perhaps the most exciting aspect is how thoroughly the best of these applications continuously outperform, in both quality and speed, any of the manual techniques we've used previously. Here to walk us through this exciting and emerging field of machine learning in astronomy is Sankalp Gilda, PhD candidate and astronomer from the University of Florida. We've got a great 90 minutes here for you, so buckle up and enjoy the ride! 

(Image credit: VLT Survey Image / ESO; Acknowledgement: Aniello Grado & Luca Limatola)

Starts With A Bang #69 - Machine Learning In Astronomy

One of the most exciting possibilities for life beyond Earth doesn't require us going very far. While Mercury and the Moon have no atmosphere and Venus is an inferno-esque hellscape, Mars offers a tantalizing possibility for a new line of life, independent of Earth, here in our Solar System. With the same raw ingredients and more than a billion years of a watery, wet past, Mars could have had, or might even still have today, some form of life on its surface.

Part of the reason Mars is so exciting for us is that we've been there: at least, robotically, with a series of orbiters, landers, and even rovers. We've seen and learned so much about the red planet, including some tantalizing hints of what might be biological activity. But there's so much more to learn, and we're reaching the limits of what we can accomplish without having human beings walk on the Martian surface.

On this episode of the Starts With A Bang podcast, we're joined by Mars expert Dr. Tanya Harrison, who's worked on three generations of Mars Rovers and is a strong advocate for a variety of future missions to Mars. Join us for this fascinating conversation where she lays out what we know, what remains uncertain, and what we'll need to do if we want to take those next, critical steps. (And, as a bonus, she corrects one or two of my misconceptions along the way!)

(This image shows the Mars Perseverance rover in one of its "selfie-mode" images, where its own tracks and the Ingenuity rover are both visible in the background. Credit: NASA/JPL-Caltech/ASU/MSSS/Seán Doran)

Starts With A Bang #93 - Mars From The Ground

Happy new year, everyone, and with a new year comes a spectacular new podcast! We normally cover an intricate and underappreciated aspect of astrophysics on the podcast, but I had the opportunity to bring on a true expert in the field of quantum computing and just couldn't pass it up.

You've likely heard a lot of noise about quantum computers and the benefits that they're poised to bring, with buzzwords like "P=NP," "quantum supremacy," and "quantum advantage" tossed around, but a lot of what you're likely to hear is hype, not actual science. Good thing I was able to get Dr. Riccardo Manenti as a guest for our podcast!

Riccardo is the author of a state-of-the-art textbook on quantum computers, has his PhD from Oxford in Quantum Computing, and has been working for Quantum Computing startup Rigetti for several years now. Join us as he helps demystify some of the recent progress and problems right here on the cutting edge of this promising new arena of physics, right here on the Starts With A Bang podcast!

(This illustration show's Rigetti's widely-available quantum computer, Novera, with 9 superconducting physical cubits within it. The great hope is that by scaling up to greater numbers of physical qubits, quantum advantage will be an achievable milestone in the relatively near future. Credit: Rigetti/Novera)

Starts With A Bang #101 - Quantum Computing

Up until the early 1990s, we didn't know what sorts of planets lived around stars other than our Sun. Were they like our own Solar System, with inner, rocky planets close to our star and large, giant worlds farther away? It turned out that exoplanetary systems come in a great variety of configurations: with planets of all sizes, masses, and distances from their parent stars. But some configurations are more common than others.

There are lots of hot Earth-sized planets and lots of hot Jupiter-sized planets, but precious few "hot Neptune" worlds out there. Furthermore, there appear to be lots of Earth-sized and super-Earth-sized worlds at greater distances, as well as many Neptune-sized and mini-Neptune-sized worlds. However, there's a gap there, too: between the large super-Earths and the small mini-Neptunes. Where are these missing exoplanets? Or, rather, why are these classes of exoplanets so uncommon?

That's what we're exploring on this episode of the Starts With a Bang podcast, featuring Ph.D. candidate Dakotah Tyler as our guest this month. By looking at how a hot (but low-mass) Jupiter-sized planet is being photoevaporated by its parent star, we can learn so much about not only the classes of objects we see out there, but even the ones we don't!

(Around the star WASP-69, a "hot Jupiter" exoplanet has its outer layers of atmosphere photoevaporated away, creating a comet-like tail whose extent and mass were recently measured for the first time. Credit: W. M. Keck Observatory/Adam Makarenko)

Starts With A Bang #102 - The Missing Exoplanets

Right now, the Large Hadron Collider (LHC) is the most powerful particle accelerator/collider ever built. Accelerating protons up to 299,792,455 m/s, just 3 m/s shy of the speed of light, they smash together at energies of 14 TeV, creating all sorts of new particles (and antiparticles) from raw energy, leveraging Einstein's famous E = mc² in an innovative way. By building detectors around the collision points, we can uncover all sorts of properties about any known particles and potentially discover new particles as well, as the LHC did for the Higgs boson back in the early 2010s.

But the LHC has a limited lifetime, and by the 2030s, will complete its data-taking runs. If we want to go beyond the LHC, we need to start planning for a new particle collider now, and there are four great options that can take us beyond the current frontier: a linear lepton collider, a circular lepton collider, a circular hadron collider, and a potentially new innovation of a circular muon collider. In this episode of the Starts With A Bang podcast, Dr. Cari Cesarotti joins us to discuss all of these options and much more, as we look ahead to the future of particle physics.

The serious question isn't whether we should build one (we definitely should), but which approach will be most fruitful in pushing our suite of knowledge beyond the known frontiers. There's an entire Universe to explore at the subatomic level, and those of us curious about the Universe want to know what's out there better than ever before! Follow Cari's attempts to support the future of a muon collider on Twitter @muoncollider.

(This image shows the expected signature of a Higgs boson decaying to bottom-quark jets around the collision point inside a muon collider. The yellow lines represent the decaying background of muons, while the red lines represent the b-quark jets. Credit: D Lucchesi et al.)

Starts With A Bang #101 - Quantum Computing

Ethan Siegel