CosmosVR – A Virtual Reality Exploration of a Cosmological Simulation

We made a Virtual Reality cosmology show!

This winter break, a friend took me to the Adler Planetarium in Chicago. This is one of the best space museums in the country, and had fascinating exhibits and movies about planets within and outside the Solar System, and the history of our attempts to explore them, going all the way back to Medieval timekeeping instruments. But when we got to the cosmology exhibit, my heart sank. The Big Bang! Dark matter! Dark energy! The fact that we can measure the how fast the Universe was expanding eight billion light years ago! How it looked thirteen billion years ago! Nothing. Some lame-ass screens full of text. None of the images, the mind-blowing technology, the methods we have to use to figure out what the Universe looks on the largest scales of space and time.

And Adler is not alone. Every museum cosmology exhibit I’ve been to has been woefully lacking.

So at the MIT VR Hackathon last month, I made a pitch to create a museum/planetarium show about extragalactic space. Self-driving car programmer Paul, computational biologist Diego, and the most impressive undergrad I have ever met, Beste, got on board. We loaded data from the Illustris simulation and visualised it in Unity (no small task). If you’re in the room with the VR headset and controller, you can fly around the space, toggle between views of the stars, gas and dark matter, and zoom in to see an individual galaxy in high resolution. For those of you further away, we recorded this demo, with a little spacey music and educational voiceover from yours truly. 

I was already over the moon (ha) because I had daydreamed of this for almost a year and it came together in two days. And because we were such a day dream, and working on it was so much fun. But then we won the Data Visualization prize (thanks Fidelity!). And a mentorship offer from _underscore VC. And support from Rus Gant of Harvard and Scott Greenwald of the MIT media lab to develop this further.

So now I’m really excited about all the places we’ll go! I still have to finish my PhD, hopefully in about a year. But in the meantime, you can experience the show at the Cambridge Science Festival on April 13 – just grab your free tickets.

We’re adding more features, like data sonification and more interaction and would love to bring the show to museums and planetariums around the country (heck, world, if you’re reading this abroad!). So if you have ideas and/or contacts, please do hit me up.

Primer: The Sunyaev-Zel’dovich Effect

 

Galaxy cluster RX J1347.5-1145 observed with ALMA (blue) and HST (background)

The Sunyaev-Zel’dovich effect is this really really awesome process that allows us to see clusters of galaxies at all distances. It is going to be vastly important with all the fancy new submillimeter telescopes astronomers have built lately, such as the Atacama Large Millimeter Array (ALMA), the Sub-Millimeter Array (SMA) and the Atacama Cosmology Telescope (ACT). At its core, it’s a beautifully simple phenomenon, so let’s break it down.

About 10% of the mass of galaxy clusters is intra-cluster gas, not attached to any individual galaxy. To counter the strong gravitational potential of the dark matter with thermal pressure, the gas needs high temperatures of 1-100 million Kelvin. Gas this hot is best observed with X-ray telescopes.

Light from the cosmic microwave background (CMB) is coming at us from all directions. Since these photons started out ~13 billion light years away from us, when light and matter separated for the first time, they pass through plenty of galaxy clusters on their way to us. And when they hit the very hot electrons in the ionized intra-cluster gas, they get “upscattered” – that is to say, they get more energy, while the electrons cool down a tiny bit. This is called inverse Compton scattering; in regular Compton scattering, the photon would have been hotter than the electron, so the energy transfer would have gone the opposite way.

A photon Compton scatters against an electron, gaining some energy and sending the electron into a slight recoil.

The magnitude of cooling due to the SZ effect is:

\frac{\Delta T}{T_{CMB}} = f(x)\int \sigma_T n_e \frac{kT_e}{m_ec^2}dl

where x = \frac{h\nu}{k_BT_{CMB}} describes how this cooling depends on the rest frame frequency \nu that you observe. In words, it is the integral along the line of sight of the thermal pressure of the electrons normalised by the rest energy of electrons, all multiplied by the Thomson cross-section, which sets the scale of the photon-electron interaction. This quantity is called the SZ decrement.

Okay now are you ready for the coolest (IMHO) bit? Consider how the value of the SZ decrement varies with redshift/distance. Since the Universe was (1+z) times smaller in each dimension at a redshift z, the number density of a cluster with a given total number of electrons goes as:

n_e = \frac{3 N_e}{4\pi r^3} =\frac{3 N_e}{4\pi r_0^3} (1+z)^3

Meanwhile, that line element dl that we’re integrating over can be written as:

dl = \frac{dr^3}{d_A^2} = \frac{dx^3}{d_L^2}\frac{ (1+z)^2}{(1+z)^3}

where, d_A is the angular diameter distance and d_L the luminosity distance. Following the same expansion argument as above, each of those dimensions was (1+z) times smaller, giving a total dependence of (1+z). So the intrinsic/rest frame SZ decrement increases with redshift as (1+z)^4.

Now the energy density from a source at redshift z decreases as (1+z)^3 due to cosmological expansion, plus a (1+z) fall-off in the frequency. This means that an object of a fixed luminosity L gets (1+z)^{-4} times fainter with redshift.

The redshift dependences of the SZ decrement and fading due to distance exactly cancel out!

This means that given a mass of a cluster (and thus N_e), we can detect it with the SZ effect at every redshift ever. It’s a redshift-independent tracer of mass. It means that we can study the assembly history of massive objects in the Universe to as far out as we freaking want, as long as the temperature measurements are precise enough! And currently, they are enough to see anything upwards of about 10^{14}M_\odot.

Making the most of twists and turns: Harvesting mechanical energy with carbon nanotube yarns

This article originally appeared in the Yale Scientific magazine.

Picture a bike ride along the seaside. Your T-shirt has a built-in heart rate monitor to track your activity. Floating up from the picturesque water are dozens, maybe hundreds of balloons that feed into a charging station on the beach, where you can recharge your phone to take a photo of the incredible scene. This is the future that Carter Haines, associate research professor at the University of Texas in Dallas, envisions. Haines and his collaborators have figured out a way to turn mechanical energy into electricity with the help of carbon nanotube yarns.

At the heart of the method is a capacitor. The archetypal capacitor is called a parallel-plate electrostatic capacitor, and it consists of a positive and a negative electrode with some dielectric medium in between. This dielectric is a material that stores charge well; the electrodes, by contrast, are conductors through which charge is quickly removed as a current. You can charge a capacitor to a high voltage and then harvest the energy inside it at a later time.

“You take a piece of rubber, coat carbon grease on both sides to get electrodes, and as you stretch and release this rubber you can change the capacitance and get energy out,” Haines said. However, the trouble with electrostatic capacitors is two-fold. First, of course, you have to charge them up with an electronic circuit to start with. Second, a human body, with its high conductivity, probably shouldn’t be near, let alone touching, high voltages.

This is the beauty of electrochemical capacitors. Virtually all electrochemical capacitors today have electrodes made of carbon allotropes—different forms of carbon with its atoms interacting in different ways—with high surface areas. Carbon nanotubes are one class of such allotropes. First discovered by Soviet scientists Radushkevich and Lukyanovich in 1952, they are incredibly strong and stiff, with length-to-diameter ratios of up to 100 million. They are grown upright in what is called a forest, then pulled out into fibers and twisted into yarns. “The nanotubes are no longer in the yarn axis, but are following helical paths, just as you’d have with any yarn that you twist,” Haines said. If you continue to twist the yarn under pressure, it will actually form coils; you’ve probably discovered this phenomenon while playing with your shoelaces. With the right amount of tension on the ends of the yarn during the twisting process, you can get neatly packed coils.

The dielectric in an electrochemical capacitor is an electrolyte, a solution of charged ions in a liquid. “Because there’s so much surface area on the surface of the nanotubes, the ions can just come and hang out on the surface,” Haines said. “When we compress the yarn, we’re actually getting rid of surface area.” By pulling one strand (one electrode) and tightening the twist, the ions on it pack closer together, increasing the voltage. Since the ions all have the same sign, they repel each other and are eager to escape. Even a small voltage on the surface area of the nanotubes will collect a large charge—much larger than the charge on their conventional parallel plate counterparts. Thus, electrochemical capacitors have earned the alternate name of “supercapacitors,” and their low voltage means no electrocuted humans.

The most interesting application is the potential for embedding the yarns into clothing. The group has already tracked breathing, which Haines says is just the beginning. “You can measure things like pulse, heart rate and all sorts of things about the way the body is moving just by having different yarns embedded in the textile,” Haines said. The biggest roadblock to a commercial-scale use of energy-harvesting yarns is the production cost of the carbon nanotubes. The search is on for cheaper alternatives that have the same ability to host ions from an electrolyte on an easily changeable surface area.

In the lab and in the fabrics, the electrolyte is some kind of synthetic gel. But it turns out that seawater, with its high salt concentration, also works well. Haines’ collaborators in South Korea did indeed attach a balloon to one end of the yarn and hold the other down to the seabed with a rock. “They can see the voltage coming out of the yarn as the waves are moving the balloon around,” Haines said. Harvesting the mechanical energy of ocean waves has been an open challenge, and one that these yarns may rise to meet—if scientists succeed in finding a way to affordably produce them on the industrial scale.

Bull’s Eye: Targeted Immunotherapy of Myasthenia Gravis

This article originally appeared in the Yale Scientific magazine.

Take a moment to appreciate how powerful your immune system is. Over millions of years, evolution has selected for specimens with the ability to identify an essentially infinite number of foreign objects, or antigens, in our bodies, and develop antibodies to attack them. This is why we are able to survive over 200 types of the common cold.

But with great power, notes Peter Parker’s Uncle Ben, comes great responsibility. To successfully attack our bodies, antigens must be relatively similar to our own cells. Your immune system has to carefully identify which agents in the body are foreign; sometimes, it can be too good. This is the basis of autoimmune disease:  when the body misidentifies its own cells as pathogens and attacks them.

“Myasthenia gravis” (MG) literally translates to grave muscle weakness. “For the longest time, it was thought to be like a muscular dystrophy, in that it was chronic, typically progressive and with no available disease-modifying treatment ” said Professor Richard J. Nowak, a physician-scientist, in the Department of Neurology at the Yale School of Medicine. In the 1970s, it was discovered to be an autoimmune disease.  This was a “major game changer” said Dr. Nowak.

Take another moment to appreciate your physical body. Each time you take a step or move your eye across a page to read a sentence, you make a decision. Your brain relays that decision to your muscles and induces their compliance. This communication occurs at a neuromuscular junction (NMJ).

The neuron contains neurotransmitters in synaptic vesicles, which are released at the NMJ and make their way to receptors on the surface of the muscle in question. In fact, there are so many of these receptors that the muscle surface is folded up into small villi to accommodate all of them. The neurotransmitter and receptor fit like pieces in a puzzle: something clicks, and the muscle knows to contract or release, causing motion.

In MG, the immune system mistakes one these critical components, the acetylcholine receptor, for a pathogen. B-cells, crucial agents of the immune system, flood the body with autoantibodies, which attach to the acetylcholine receptors on the muscle surface. The receptors no longer can bind the acetylcholine, and the neuromuscular communication fails. Movement becomes difficult and weakness results.

MG has traditionally been treated with immunosuppressants, like steroids. These treatments globally suppress the immune system, resulting in fewer life threatening attacks of the acetylcholine receptors. The sometimes chronic and continuous attack by the autoantibodies eventually takes its toll. “After a long period of active and unchecked autoimmunity, the architecture of the muscle surface is flattened,” said Nowak. The villi close up, leaving ever fewer receptors accessible to the neurotransmitter. “It was not uncommon for patients to die from [MG] in the past, because their respiratory muscles weaken, their diaphragm weakens and they can’t breathe on their own.”  Current immunosuppressive strategies are not targeted and can result in significant side effects when used chronically along with the fact that about 15% of patients do not respond to standard treatments.

But what if you could attack only the rogue B-cells, that ones that produce the autoantibodies and remove them completely? Nowak’s group is studying such a drug.

Rituximab was developed about twenty years ago in the treatment of non-Hodgkin’s lymphoma, which is a cancer of B-cells. One unfortunate patient also had MG and showed dramatic improvement in those symptoms. “Rituximab targets the CD20 antigen, which is expressed on B-cells that are antibody producing,” said Nowak. “It is administered intravenously once a week for four weeks.” The cycle is repeated six months later. The clinical benefits show several weeks to months later, so long-term follow-up is key.

Nowak’s team followed a group of 16 patients up to 8 years. After a year, most were able to reduce, or completely stop, their use of other immunosuppressants. The mean time until relapse was three years after treatment was completed. “This is the longest relapse time recorded in any treatment for MG,” remarked Nowak.

Affecting up to 100,000 individuals in the U.S., myasthenia gravis is considered a rare disease and as such there is a paucity of large interventional clinical trials.  Many treatments currently in use are based on small studies or anecdotal experience and do not have an FDA-approved indication.  Most health insurance companies are resistant to covering these treatments as a result.
Careful studies are necessary to ensure the treatment’s validity, notes Nowak and further explains that “everyone wants a prospective, placebo-controlled trial”. The team has already begun such a trial: BeatMG Study. “We anticipate results in late 2017.”

Rain on Black Holes

This article originally appeared in the Yale Scientific magazine.

Almost every observed galaxy has a giant black hole at its center. Clues lead us to believe that these monsters, weighing as much a billion suns, eat copious amounts of gas from their environment and occasionally send some of it back as powerful jets, bubbles or heat. How exactly they do this, however, has been a mystery.

For over half a century, said Grant Tremblay, postdoctoral researcher at Yale, “people have simplified supermassive black hole accretion as a smooth spherical inflow of very hot plasma.” And this wasn’t necessarily a bad idea: gas that falls into a gravitational field gets heated up—the stronger the gravity, the higher the temperature. For a dense region like a cluster of galaxies, this temperature is over a hundred million Kelvin, ten times the temperature of the Sun’s core. So far, warm accretion sounds like a credible explanation.

But then there is thermal bremsstrahlung, or braking radiation. In hot plasma, electrons zoom freely around until they come close to positively charged ions; then they change trajectories and lose energy. We observe this lost energy as X-ray emission. “The cluster had to lose energy to give us this photon,” said Tremblay. “Every X-ray observation of a galaxy cluster is actually a direct measurement of galaxy cooling.” If a gas is both hot and dense, in summary, it won’t stay hot for very long. There isn’t a long-term reservoir of warm gas to feed the black hole.

In fact, Professor Megan Donahue of Michigan State University, who is a co-author on the paper, explained that we now have the opposite problem. “The gas near the centers of galaxies is very dense, and the cooling rate of a gas goes as density squared”. The more gas there is at the center, the easier it should be for electrons to find positive ions to brake against, emitting X-ray radiation and cooling down. The cluster cores should be brimming with cold gas, which in turn should form lots of stars. Instead, astronomers found them warm and star-less. This discovery motivated theorists to propose a new model: central black holes are Active Galactic Nuclei (AGN), and spit energy back into their environment in what is known as feedback.

So if hot gas doesn’t feed the AGN, what does? Donahue says the key is realizing that the gas is not all the same: “it’s like this big rain cloud that can produce raindrops that cool very rapidly.” In this model, neither uniformly warm nor uniformly cold gas feeds the black hole; rather, cold clouds precipitate out of the warm gas, and these clouds can then rain down on the black hole. Just like raindrops, on their way to the Earth through the atmosphere, don’t heat up and evaporate, so the cold clouds can maintain their structure all the way from where they formed to the cluster core. Donahue’s team designed the model by observing galaxy clusters, but they could not detect the drops —until now.

In a paper published in Nature this June, the team reported observations of the elusive drops in the Atacama Large Millimeter Array (ALMA), a collection of telescopes located in the Atacama Desert. ALMA can accurately measure both positions and speeds of any object it sees, and has such great angular resolution that it could see a dime held up in New Haven from where it stands in Chile. The team was trying to observe the cold, star-forming gas in the galaxy cluster Abell 2597, which is a tad further – one billion light years away.

 

The central supermassive black hole (SMBH) is accreting a lot of matter – but a black hole can only eat so fast, and so the in-falling matter settles in a large accretion disk around it. Different layers of the rotating disk generate friction as they rub against each other, which they release as heat. The cluster center should have been bright as a light bulb. “But you also have, between the observer and the light bulb, something eclipsing the light bulb and creating a shadow,” said Tremblay. These shadows were the elusive cold gas clumps, absorbing the light in certain parts of the spectrum. “This is one of the first really big pieces of unambiguous evidence for cold molecular clouds that are falling towards a supermassive black hole,” says Tremblay.

What wavelengths of the light from the black hole the clouds absorbed depended on how fast they were moving with respect to it. Tremblay saw that they were moving inwards towards the SMBH at about 300 km/s, or 67,000 miles an hour. “These things are basically on ballistic trajectories falling towards the black hole.”

Perhaps the best part is that this Nature paper was just a by-product of asking a different question—how is the cold, star-forming gas distributed in galaxies, and clusters of galaxies, and how is that shaped by AGN? We saw above that it lives in little clouds, but there’s one last fascinating detail – the clouds themselves are arranged in extended filaments, as long as the cluster itself. Megan Donahue pictures it as “not like a squid… It’s got these little tentacles.”

Tremblay thinks pasta is a better way to understand the underlying physics. After the first round of cold gas falls into the black hole, the AGN releases jets and bubbles of energy. These ejecta, he says, “drag cold gas out of the center of the galaxy, like pulling spaghetti out of hot water.” Your best bet, then, is to imagine a perpetual fountain of pasta, jetting out of the cluster center towards its outskirts, dragging little bubbles of cold gas along with it.

And so, looking for the tiniest, coldest clumps of gas everywhere in a cluster of galaxies, astronomers confirmed a model for the how the largest, hot object at its very core feeds and responds to its environment.

#Sparknotes: AGN and Star Formation Feedback in Clusters

Cooling, AGN feedback and star formation in cool-core clusters

Li et al, 2015

This is an adaptive-mesh simulation of an idealized, isolated, cool-core cluster modeled after the observed Perseus cluster. It studies the interplay between ICM cooling, AGN feedback and star formation.

Firstly, it finds that all three quantities are tied to the ratio of the cooling time to free fall time, t_cool/t_ff. This is nice because that’s the quantity I’m studying in my simulations. Also because it is physically meaningful – if the gas can cool significantly before it can fall into the centre of the cluster, it will form filaments of cold clouds that rain onto the central black hole and build a reservoir of cold gas near the cluster centre.

screen-shot-2016-09-08-at-23-32-20

screen-shot-2016-09-08-at-23-31-38

 

 

 

 

 

 

 

 

 

 

Some of the cold gas is accreted onto the central SMBH, triggering mechanical outflows (modeled here are semi-thermalized bipolar jets). I don’t see mention of radiative feedback. In addition, the cold gas is also used for star formation. The three quantities (rows one, three and four above) are visibly correlated.

The two columns indicate runs with AGN feedback efficiencies of 1% and 0.1%, respectively. This was the only parameter in their model that significantly affected the qualitative results of a simulation. When AGN heating was lowered, there was little to pause star formation or accretion onto the central black hole; as a result, the AGN never “shuts off”, which is inconsistent with observations.

screen-shot-2016-09-08-at-23-31-00Another key point to note is that in the third column, which is the SMBH mass accretion rate, there is a large scatter corresponding to short-scale fluctuations. The black line instead shows the accretion rate averaged over a running window of 200Myr, and is much smoother. The average mass accretion rate is also much more tightly correlated with the star formation rate, as shown in this plot to the right. This emphasises the point that observations of AGN activity and star formation in a single galaxy can have a huge scatter because they measure only an instant in time.

screen-shot-2016-09-08-at-23-31-10screen-shot-2016-09-08-at-23-31-18

 

 

 

 

 

 

 

The star formation rates in the simulation, as well as its relation to the ratio t_cool/t_ff, are consistent with observations, too, as shown in the two plots above.  The key takeaway is that large sample of AGN galaxies is required to make a reasonable statement about the effect of AGN on star formation rates.

In summary, when you look at a cluster with a BCG, ICM with self-gravity, radiative cooling, AGN feedback in the form of jets, and star formation and feedback, you match observed measurements of star formation, t_cool/t_ff and the ratios between the two. I would like to also see a prediction for the X-ray surface brightness profile, and in particular how upcoming X-ray missions like E-Rosita could distinguish between different modes of accretion and feedback. Lastly, my simulation is looking at a zoom-in cluster from a cosmological box, with plenty of additional turbulence from the movement and mergers of galaxies within it. Since turbulence even in this simulation created filaments 15kpc long, I’d really like to see what happens when there’s more of it.

#Sparknotes: Black Holes as Chaotic Eaters

Chaotic cold accretion onto black holes

Gaspari, Ruszowski and Oh, 2013

This paper describes a set of very high resolution, idealized simulations of a supermassive black hole (SMBH) in the central (cD) galaxy of a massive cluster. Since the goal is essentially to challenge the current near-universal use of the Bondi accretion model in simulations, let’s start with the key equation:

Screen Shot 2016-08-31 at 21.32.14

Setup Start with a simple NFW dark matter halo, a de Vaucouleurs stellar distribution, gas that traces the gravitational potential and a SMBH, all with masses similar to the observed galaxy group NGC 5044. All of these are modelled in an adaptive mesh grid overlaid on a box of side 52kpc for a total time of 40 Myr. With upto 44 levels of refinement, the simulation resolves sub-parsec scales around the central black hole.

Screen Shot 2016-08-31 at 21.25.24

Mass accretion onto the black hole, normalized by Bondi prediction.

Varying physics models 

The initial setup thus consists of an ideal gas contracting under gravity. This results in adiabatic, isotropic, smooth accretion of warm gas, identical to the analytic model of Bondi (1952). Indeed, the (numerically) observed accretion in this case exactly matches Bondi’s prediction, since the solid line in Fig 1b is essentially = 1 throughout. What is the dashed line, you ask? Well, that is the accretion rate you would measure if you evaluated the parameters in the Bondi equation as an average over a cluster-centric radius of 1-2 kpc, instead of at the Bondi radius (85pc in this case). In other words, computing gas density and sound speed as an average over large cells overestimates the accretion rate.

The simulations sequentially complicate the physics.

 

Screen Shot 2016-08-31 at 21.27.50First they add cooling, which occurs due to atomic transitions in the ICM. Observed cluster ICMs tend to be quite enriched in metals, mostly due to ejecta from supernovae. They assume the metallicity of the cluster gas to equal that of the sun, which I thought was generous but is actually supported by Chandra observations (e.g. Vikhlinin et al 2005). The accretion is now boosted by over two orders of magnitude. Of course, the simulation doesn’t model star formation; if it did, a lot of this centrally accreted gas could actually be converted into stars, so we would observe very large star formation rates in over very short time scales in the central galaxies of clusters. We d not.

Next, they add turbulence by “stirring” the gas on large scales (lol 4kpc; this is just about the resolution of our cosmological simulation. It’s so relieving to see that someone is actually probing the smaller regions so that our sub-grid models aren’t full of hot air.)(I’m sorry I can’t help these things.) In reality turbulence can be induced by galaxy motions through the viscous ICM, galaxy-galaxy mergers, AGN and stellar feedback, etc. And this is where things start to look really different.

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You now see a slice of the temperature profile of the gas. Adding the metal cooling, as mentioned above, decreases the temperature in the core by over 4 orders of magnitude, but retains the spherical symmetry and isotropy. Adding turbulence creates very cold filaments on very large scales. The accretion is on average as high as in the cooling-only scenario, but with more fluctuations.

Screen Shot 2016-08-31 at 21.54.39Lastly, they consider global heating. In a real cluster, this could come from cosmic rays, AGN feedback, massive stellar feedback, etc. This suppresses the star formation somewhat from the previous case, but the “boost factor” with respect to the Bondi prediction is just under 100 by the end of the simulation. The filaments induced by turbulence are not broken up or significantly heated up.

In summary: accretion of gas onto the supermassive black holes at the centres of galaxy clusters is cold, chaotic and filamentary. Averaged over tens of megayears, the boost factor with respect to the Bondi model is just under 100, compared to the prevalent norm of 100-400.

#Sparknotes: AGN

So excited about this fall! I get to implement a new subgrid model for accretion onto, and feedback from, active galactic nuclei (AGN) at the centres of clusters in a cosmological simulation we develop here at Yale.

Developing subgrid models (and numerical approximations in general) is an art as much as a science.  On the one hand, you need to reproduce large-scale, observable phenomena, like star formation histories, stellar masses, stellar and metallicities, and dark and visible substructure. On the other, you want your input parameters to be motivated by plausible underlying physics.

Fig 1 from Urry and Padovani, 1995

Fig 1 from Urry and Padovani, 1995

AGN are a pesky beast. They consist of a supermassive black hole (SMBH) at the core, or nucleus, of a galaxy, surrounded by a hot disk of infalling matter. Since the material in the disk is unlikely to have falling in on a radial trajectory, it settles in a rotating disk around the black hole. Friction between layers of the disk heat it up to tens of millions of Kelvin, so that if you catch an AGN at the correct angle, it is bright in the X-ray. More often than not, due to geometric reasons, you’ll end up seeing dust-obscured AGN, which  are bright in the radio. That’s a two-line summary of the Unified Model of AGN.

This obscuration, combined with the final parsec problem, is the main reason AGN are so pesky. Stuff falls onto black hole, aggravates it, isothermal heat ejections and mechanical jets arise! But what sort of stuff can fall into the black hole? Why does that cause it to spit stuff out? How exactly does it eject this energy? How far does the energy travel, and how does it interact with gas on its way (more specifically, the Intra-Cluster Medium or the ICM)?

There has been a sea of observations and theoretical models on this topic in the last few decades, and I’m just starting to dip my toes in it. Here’s a summary of the papers I’ll review in the next months.

  1. How is energy transported within an accretion disk? How do the viscosity, density and temperature of the gas in the accretion disk determine whether energy transport is dominated by radiation, advection or convection? What does each of these processes look like? Advection-Dominated Accretion around Black Holes – Narayan, Mahadevan and Quataert, 1998
  2. How exactly does the gas fall onto the black hole? How cold does it have to be? Does this depend on whether the gas is in filaments or clouds, and how those may be oriented? Growing supermassive black holes by chaotic accretion – Gaspari et al, 2013
  3. The simulation I work with extracts clusters of galaxies from a cosmological box. This captures things idealized/isolated cluster simulations cannot, like smooth accretion of gas from filaments and mergers of clusters. Accretion during the merger of supermassive black holes – Armitage and Natarajan, 2002
  4. Several self-regulating mechanisms have resulted in tight relations between galaxies and the supermassive black holes that live in their centres. Accreting supermassive black holes in the COSMOS field and the connection to their host galaxies – Bongiorno et al, 2012.

 

Simulating the First Dwarf Galaxies and Globular Clusters

A Common Origin for Globular Clusters and Ultra-faint Dwarfs in Simulations of the First Galaxies

Massimo Ricotti, Owen H. Parry and Nickolay Y. Gnedin

This paper presents the results of simulations of four cosmological boxes, each 1 Mpc/h a side, using the Adaptive Refinement Tree (ART) technique. The adaptive refinement scheme creates finer spatial and temporal resolutions in regions of high density, where the physics is more interesting. In the highest-resolution run, the authors resolve individual star particles as small at 40M_\odot, at sub-parsec sizes. The numerical simulation ends at z ~ 9, sufficient to make predictions about what the James Webb Space Telescope would see. Afterwards, an analytical prescription extrapolates what the galaxies found at z=9 would look like today, and comparisons are made to dwarf galaxies and globular clusters in the Local Group.

The physics implementation here is very neatly explained and physically motivated. Stars form whenever a gas cell meets certain criteria of metallicity, number density and molecular hydrogen fraction. There are two sets of prescriptions, corresponding to metallicity requirements for Pop III and Pop II stars. Unless the gas cell is of the minimum mass, i.e. 40M_\odot, it is converted into a stellar particle, which is understood as a population of stars following the Chabrier IMF. Feedback occurs in the form of supernova (SNe) explosions 3 Myr after star formation has occurred in a given cell – this timescale corresponds to the main sequence lifetime of an 8M_\odot star. This releases 10^{51} ergs of thermal energy into the neighbouring cells, on time scales that range from 0 (for Pop III hypernovae) to 35 Myr (for Pop II supernovae). The feedback also serves to enrich the gas with metals.

Finally, substructure is identified at every time step using the friend-of-friends (FoF) algorithm and refined using SubFind. The high-res simulation produced galaxies as small as 2.8\times 10^5 M_\odot, comparable to ultra-faint dwarfs today! Btw, I was elated that someone finally explained linking length, which is key to FoF! Particles are considered linked if their separation is less than

 (linking length)*(mean separation between particles in the box)

The group catalogues are then used to construct merger trees.

At z = 9, they find that many galaxies have gas disks, but stars still form spheroids –

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This makes sense if a spheroidal gas cloud was cool enough for star formation before dissipative processes turned it into a disk.

Screen Shot 2016-07-20 at 14.42.53What do the orbits of the stars look like? Defining circularity as the angular momentum of a star particle in the direction of the mean angular momentum of the galaxy, divided by that of a particle of that mass moving on a circular orbit. The star particles in the simulated galaxies are consistent with non-rotating spheroids, i.e. symmetric distributions of circularity peaking at zero. In some galaxies, the mean circularity is positive, indicating that at least some stars are undergoing some rotation. No difference between metal rich and metal poor stars, divided at [Fe/H] = -1.5.

Screen Shot 2016-07-20 at 14.51.27How big are the galaxies? Half-light radius r_h computed at 100 different viewing angles, error bars represent range between 10th and 90th percentile of measured values for each. Unlike observations in Local Group, where r_h scales with luminosity/stellar mass, in the simulation there is a large spread inr_h at fixed stellar mass. That said, a lot can happen between z = 9 and the present day. If tidal stripping, for example, occurs at a rate inversely proportional to the density of the dwarf galaxy, more extended low-mass galaxies at high z would be smaller by z=0. Patience – this comes a couple sections later!

Screen Shot 2016-07-20 at 15.27.13Of the ten most compact objects, 5 are DM dominated and 5 baryon-dominated. In fig 6, this is seen as a wide range in pseudo mass-to-light ratios at a fixed dynamical mass. There is, nevertheless, an apparently bimodal distribution – one where mass/light hovers around 10, and another around 10,000.

The money plot: 

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The three panels correspond to three different values adopted for star formation efficiency, ranging from 1-100%. To quote the authors, “luminosity of dwarfs increases by about a factor of two whenis increased by a factor of 100”; i.e. the qualitative results are depend very weakly on the assumed \eta (which is excellent, since this quantity is still poorly constrained by observations)! The grayscale is the log of the stellar mass to dark matter mass.

Takeaway: the simulation self-consistently forms several objects with half-light radii ranging from 1-150 pc and stellar-to-dark matter ratios ranging from 1:1,000 to 10,000:1! The latter systems live in the top left corner of each plot, and are consistent with the mass-to-light ratios observed in globular clusters today. The more dark-matter dominated systems, on the other hand, would be the progenitors of dwarf galaxies.

[The plots in this paper are so damn nice. Like, they really know the physics point they’re trying to get across.]

Finally, the paper analytically calculates what these high-redshift compact objects would look like in the Local Universe, and compare it to observations. Screen Shot 2016-07-20 at 15.46.55

Overall, it seems to me that the dwarf galaxies in the simulation don’t fit observations nearly as well as the globular clusters do – the simulation+analytic evolution produce dwarfs that are more compact, have smaller velocity dispersions, and with a smaller range of masses than observed. That said, the 13 billion years between the end of the simulation and the present day are very complex to model, and the fact that the predictions are so close to the observations is pretty impressive!

Ultimately the conclusion is that globular clusters and dwarf galaxies form through the same processes in the very early universe. How do you form very compact, baryon-dominated systems at high redshifts, though? I might have to re-read the paper to get this one.

Gravitational Waves are HERE!

If everyone spent their time thinking about how black holes collide and send out bunches of energy as ripples in the fabric of spacetime that can change the shape of things in their way just enough that one billion light years away four kilometres of metal on Earth could get stretched by one thousandth the width of a proton, which means a packet of light (that is also a wave) traveling along that piece of metal takes just a little longer to get back to where it started and collides with another wave that was not expecting it to take that much longer and therefore produces a signal on a photographic plate that HUMANS CAN SEE
we’d have a lot less time for bigotry and war and other ways of being mean.

ligo_bhs

Also a bunch of LIGo data is publicly accessible at  http://havewedetectedgravitationalwavesyet.com. Yes yes that is the official website name.

Good day for science!!