black holes as the dark matter

Today Cameron Norton (NYU) gave a great brown-bag talk on the possibility that the dark matter might be asteroid-mass-scale black holes. This is allowed by all constraints at present: If the masses are much smaller, the black holes evaporate or emit observably. If the black holes are much smaller, they would create observable microlensing or dynamical signatures.

She and Kleban (NYU) are working on methods for creating such black holes primordially, by modifying hte potential at inflation, creating opportunities for bubble nucleations in inflation that would subsequently collapse into small black holes after the Universe exits inflation. It's speculative obviously, but not ruled out at present!

An argument broke out during and after the talk whether you would be injured if you were intersected by a 10²⁰ g black hole! My position is that you would be totally fine! Everyone else in the room disagreed with me, for many different reasons. Time to get calculating.

Another great idea: Could we find stars that have captured low-mass black holes by looking for the radial-velocity signal? I got really interested in this one at the end.

extracting DNA

I spent the morning today at a conference for educators and education students at Queens College. It was great! I went to a session on classroom biology, in which we extracted DNA from a strawberry, using only household chemicals (detergent, salt, and alcohol). It was great, and I worked with two really cool lab partners, both Queens College first-year undergraduates.

water forces on bacteria

Today we had a really great colloquium by Ned Wingreen (Princeton), about water forces on bacteria and how communities of bacteria can be seen as an active material. He showed theory and data for simple experiments in which they can change the osmotic pressure on a wet surface where bacteria are moving. They can tune the water-driven forces on the bacteria and change their behaviors.

After that, at wine and cheese, David Grier (NYU) showed me (and lots of students) a home-built device that levitates (or really traps) tiny objects using acoustic waves. It was awesome.

coordinate-free reading?

The world is O(3) equivariant. Meaning: The laws of physics don't depend on the orientations of things, nor do they depend on the orientation of your coordinate system. But handwriting—and printed words—are not equivariant: Writing systems have a definite orientation and parity. Indeed, it can be hard to read things when they are reversed in a mirror or at an odd angle. Pick up a paper from your desk and read it. Before you start, you have to orient it. How do you do that?

My answer is: Context. I think you try different orientations until one seems to work for the reading. You can't always tell from a single letter (like an M or a W or an O), but you can tell once a string of a few letters or numbers are visible. Inspired by all this, Villar and I are making this data set (among others) for learning and reasoning tasks:

Dagstuhl, day 2

Today was day 2 of Machine Learning for Science: Bridging Data-driven and Mechanistic Modeling at Schloss Dagstuhl. Many great things happened. Here are two highlights:

Bernhard Schölkopf (MPI-IS), in a discussion session, asked what the key questions were for machine learning as a field. I love this question! Astronomy and physics do, I think, have key questions, which guide research and contextualize choices. Machine learning does not really, or if it does, the questions are implicit. I want to work on this.

Philipp Hennig (Tübingen) gave an energizing talk about the relationship between simulations of the world and observations of (or data about) the world. He argued (convincingly!) that we should not think of these as totally different things, and that learning from data and simulating a process could or even should always be integrated and done together. He demonstrated this with a simple model of infectious disease, but the point is extremely general.

Dagstuhl, day 1

Today was day 1 of Machine Learning for Science: Bridging Data-driven and Mechanistic Modeling at Schloss Dagstuhl. The first day was mainly about applications of machine learning, in Earth science, livestock management, astrophysics (dark matter), cells, and mechanical engineering. I had many thoughts and realizations. Here are a few random ones:

The problems that appear in Earth science, and the data types, are very similar to those that appear in astrophysics! But in Earth science, biology is a big driver of global processes, and there is no good mechanistic model for (say) how plants grow and take up carbon. The world is filled with mobile phones, with good cameras, and the methods we could could be employing to be doing science in a distributed way are way, way under-used. Cells are incredibly complicated. The mechanistic model involves literally thousands of individual processes. Like our model for the cell is as complicated as our model for the entire Earth system (which, by the way, depends on cells!), or even more complicated.

In the areas of the cell and the Earth, a theme was that the investigators want to preserve the causal structure we believe, and just use the machine learning to replace one tiny piece, with a data-driven model. Related: You can think of the machine learning as an effective theory for something (a sub-part of the problem) that doesn't work well from first principles. That's a good idea!

nothing

Teaching and life issues took out the day, I'm afraid.

infrared excesses for planet-hosting stars

Gaby Contardo (Flatiron) and I went to the Gaia EDR3 Archive to make use of its matched catalogs, matching up Gaia, 2MASS, and WISE. We are looking at very short-period planet hosts, which might show interesting photometric deviations. We took one host star, and then found many other stars with similar photometry in the visible. Do they agree in the infrared? It looks like maybe there is a tiny discrepancy? But the power will come from doing many, not just one.

modeling arid ecologies?

[This blog died for a few months. I apologize. I am back now, and hope to continue.]

Today I worked with Soledad Villar (JHU) on our project to execute regressions (and other machine-learning methods) that are constrained to be exactly symmetric (or equivariant) with respect to units and dimensions. Our target problem is a regression involving ecologies of arid regions. There are differential-equation models for this, and all the inputs to the equations have interesting units (such as water volume per area, and grams of vegitation, and so on). It was fun to do some real coding again, after days of grading final exams!

astrology: Yes, it's true

Today Paula Seraphim (NYU) and I extended our off-kilter research on the possibility that we live in a simulation to off-kilter research on whether astrology has some basis in empirical fact. It does! There are birth-season correlations with many things. The issue with astrology, oddly, is not the data! It is with the theory that it is all related to planets and constellations. And if you think about the causes of birth-season effects on personality and capability, most of them (but not all of them) would have been much stronger 2000 years ago than they are today!

aliens?

I have my student-project office hours on Tuesdays and Wednesdays. It was a pretty fun session this week, in part because two of my students (Abby Shaum and Avery Simon) got jobs (congratulations!) and in part because we had a wide-ranging conversation that went way beyond everyone's particular projects. In one part of it, we talked about looking for pairs of planets (around a common host star) that have a period ratio that is a known irrational number (like e or pi or tau). Anu Raghunathan and I are using this kind of model as a null test when we search for planets in resonances (that is, we should find small-integer rational period ratios, not irrational ratios (or rational numbers with very large denominators; don't at-me)). But then of course we realized that one way that alien civilizations might signal us is by creating “transit beacons” that are in a ratio like e or pi. Hahaha new project!

modeling the Milky Way disk

[Okay now I'm really trying to get back to blogging my research. If you out there are having trouble getting things done: I hear you. I have done very little in this time of quarantine, and I'm trying to be kind to myself about it (and not always succeeding). Take care of yourselves out there.]

The only research I did today was a couple of phone calls. The first was with Christina Eilers (MIT) about determining and implementing a selection function for the APOGEE spectroscopic survey, and using it to measure the scale length of the disk. This is a bit of a boring project! But it would lead to lots of follow-on projects. A good selection function makes you very powerful! For example, the spiral structure we see in kinematics would become abundantly clear in stellar density if we had a selection function and an azimuthally-averaged mean model for the disk.

The other phone call was with Jason Hunt (Flatiron). He has a medium-term goal of applying the made-to-measure method of modeling stellar systems to the entirety of the ESA Gaia data set. I love that goal! We discussed changes to M2M to let it be more responsible with noisy and incomplete data. We resolved that Hunt would teach me M2M in our next (remote) meeting.

nothing; recovery?

[I've been in and out for many weeks dealing with family crises. Hence the interruption in a blog that has gone essentially uninterrupted since January 2005. Indeed, the interruption made me miss this blog's 15th birthday party on 2020 January 27. I hope to re-start this week. But posting might be spotty, because I'm still in recovery from those crises. Take care of yourselves out there.]

ps. I got nothing done today. But I'm being kind to myself about it!

exciting stars

Stars and Exoplanets Meeting at Flatiron was a delight today. Lachlan Lancaster (Princeton) showed his results on a really interesting object he found in the ESA Gaia data. He was inspired by the idea that star clusters might have central black holes, which might retain a very dense, very luminous nuclear star cluster even after the cluster disrupts. But his search of the Gaia data was so simple: Look for things that are apparently bright but low in parallax (large in distance). Duh! And what he found is a very bright “star” that is variable, shows emission lines, and is above the top of the H–R diagram! The ideas from the room ranged from extremely young star to microquasar to technosignatures (who suggested that?). And the thing is incredibly variable.

But there was lots more! I won't do everything, but I will say that Thankful Cromartie (Virginia) showed data from pulsar monitoring (as part of a pulsar-timing project for gravitational waves). She showed that she can very clearly see the Shapiro time delay in the pulses when they pass by the neutron star that is in orbit around the pulsar. This lets them measure the mass of the neutron star accurately. It is very massive! i think it must be one of the most massive neutron stars known, which, in turn, will put pressure on the equations of state. Beautiful results from beautiful data.

Dr Taki

Today was a beautiful and accomplished PhD defense at NYU by Anna-Maria Taki (NYU). Taki is a particle phenomenologist who is looking at signatures of dark matter in the ESA Gaia data. She is concentrating on methods that relate to gravitational lensing: In addition to magnification changes, lensing can induce artificial proper motions and artificial accelerations in the stars. Indeed, Jupiter and Saturn have huge gravitational-lensing signatures at Gaia precision, and they are calibrated out. But if there are dark-matter substructures (say) between us and the SMC or LMC, we could see them in principle as anomalies in the Gaia data. Taki has developed matched filters and statistical techniques for finding the signatures. No detections yet! But there is a hope that an end-of-mission Gaia search could be very interesting.

In the discussion over champagne, I discussed with various people the idea that Taki's work could inspire a new small-explorer class NASA mission. If you could show that such a mission could definitively rule out the main predictions of lambda-CDM, that would be a competitive proposal, I think. And a beautiful experiment.

The day ended with a great and fun PhD candidacy exam by Paul McNulty (NYU). He is using data science and information theory to understand how neural activity relates to motor function in fruit-fly larvae. We discussed the sense in which such work is physics. It is, of course! But it's interesting how interdisciplinary physics has become.

free energy and life

One amusing conversation today was between Ben Pope (NYU) and myself about whether hot stars are more or less likely to host planets with live. We believe (it's not extremely well established yet) that there are more habitable planets around M-type stars than G-type (and there is probably a relatively smooth function of temperature). So why do we live around a G star? Is it because there is more free energy per photon? I have assumed that this is why. But we realized that we can make this argument quantitative. One question that I have is this: Is this argument anthropic? Or is it just the simple observation that Earth hosts life? I think it is anthropic, because it has something to do with whether our place is special.

phylogeny and nucleosynthesis

In Astronomical Data Group Meeting, Megan Bedell (Flatiron) talked about possible uses of phylogenetic methods for looking at the chemical evolution of stars in the Milky Way. That's an idea that has been tried a few times, but she has a new twist: There are methods that take explicit account of time, and there are now many stars for which we have precise ages. I'm not sure, in the end, that methods from biology will translate directly to astrophysics, but I bet the sandbox is worth digging in a little bit. This connects to my thoughts and hopes of building a data-driven model of nucleosynthesis.

Before that, in conversations (also) with Bedell, I down-selected my ideas for the NASA Exoplanets Research Program call. The stage-1 proposals are due next week, so this is about as late as I can leave it. My plan is to propose something about stellar spectral variability and the new NASA investments in extreme precision radial-velocity hardware. Watch my GitHub repos for details.

Ballard on exoplanets

Today was a great talk by Sarah Ballard (MIT) about the future of exoplanet research, with a concentration on the search for habitable planets. She made a strong argument for looking around low-mass stars. Of course I am suspicious that life can form around low-mass stars because the UV photons might be crucial!

She also emphasized a lot her results on two different populations of planets around M stars. I am not sure I like this description of her result: The fact that she gets a better fit with two simple populations than with one doesn't mean that there are two populations; there might just be one complex population not well described by a simple form! But it is a productive idea in the sense of generating and inspiring new projects.

And despite my criticisms and concerns, I loved this talk; it showed great vision for the future and she is taking great steps now towards that future. The methods and the process are good; my objections are all about subtle points of interpretation and discussion.

candidate Williamson

Today Marc Williamson (NYU) passed (beautifully, I might say) his PhD Candidacy exam. He is working on the progenitors of core-collapse supernovae, making inferences from post-peak-brightness spectroscopy. He has a number of absolutely excellent results. One is (duh!) that the supernovae types seem to form a continuum, which makes perfect sense, given that we think they come from a continuous process of envelope loss. Another is that the best time to type a supernova with spectroscopy is 10-15 days after maximum light. That's new! His work is based on the kind of machine-learning I love: Linear models and linear support vector machines. I love them because they are convex, (relatively) interpretable, and easy to visualize and check.

One amusing idea that came up is that if the stripped supernova types were not in a continuum, but really distinct types, then it might get really hard to explain. Like really hard. So I proposed that it could be a technosignature! That's a NASA neologism, but you can guess what it means. I discussed this more late in the day with Soledad Villar (NYU) and Adrian Price-Whelan (NYU), with whom we came up with ideas about wisdom signatures and foolishness signatures. See twitter for more.

Also with Villar I worked out a very simple toy problem to think about GANs: Have the data be two-d vectors drawn from a trivial distribution (like a 2-d Gaussian) and have the generator take a one-d gaussian draw and transform it into fake data. We were able to make a strong prediction about how the transform from the one-d to the two-d should look in the generator.

planets around hot stars

My research highlight for the day was a conversation with Ben Pope (NYU) about projects involving hot stars. We have been kicking around various projects and we realized in the call that they really assemble into a whole research program that is both deep and broad:

There are problems related to finding transiting planets around hot stars, which is maybe getting less attention than it should, in part because there are technical challenges (that I think we know how to overcome). And planets found around hot stars might have very good properties for follow-up observations (like transit spectroscopy, for example, and reflected light), and also good prospects for harboring life! (Okay I said it.)

There are problems related to getting stellar ages: Hot stars have lifetimes and evolutionary changes on the same timescales as we think exoplanetary systems evolve dynamically, so there should be great empirical results available here. And hot stars can have reasonable age determinations from rotation periods and post-main-sequence evolution. And we know how to make those age determinations.

And: The hot-star category includes large classes of time-variable, chemically peculiar stars. We now at Flatiron (thanks to Will Farr and Rodrigo Luger) have excellent technology for modeling spectral surface features and variability. These surface maps have the potential to be extremely interesting from a stellar model perspective.

Add to all this the fact that NASA TESS will deliver outrageous numbers of light curves, and spectroscopic facilities and surveys abound. We have a big, rich research program to execute.