Sunday, April 27, 2014

Nature has it in for us: Supernovae from Massive Stars in 3D

[A version of this post has appeared in the Huffington Post. It is a more generally accessible discussion of our recent Astrophysical Journal Letters paper: Mösta, Richers, Ott et al., The Astrophysical Journal, 785, L29 (2014). ADS]

We don't know what precisely happens when a massive star -- about ten times the mass of our Sun or more -- first collapses and then goes supernova and leaves behind a neutron star or a black hole. The explosion expels the products of stellar evolution into the interstellar medium from which, ultimately, new stars and planets are made. These products, carbon, oxygen, silicon, calcium, magnesium, sodium, sulfur, and iron (among other elements), are the elements of life. It's arguably quite important to understand how this works, but we don't. At least we don't in detail.

The supernova problem is so complex and rich that computer simulations are crucial to even begin to formulate answers. This sure hasn't kept people from trying.  Los Alamos National Laboratory maverick Stirling Colgate (1925-2013; "I like things that explode: nukes, supernovae, and orgasms.") was one of the first to simulate a supernova in the 1960s (think: punch cards).  Over the following decades, computers got much faster, and simulations got better and better.

Today's supercomputers are more than 100 million times more powerful than the computers of the 1960s. Yet we are still struggling with this problem.

We are witnessing a revolution in dimensionality -- We are finally able to simulate stars in three dimensions:

For decades, it was possible to cram in all the complex physics of supernovae only into simulations that were spherically symmetric. Assuming that stars are spherical, the computer codes had to deal only with one spatial dimension, described by the radial coordinate inside the star. Turns out that this is a very bad approximation. Stars are not spherical cows. They rotate, the have regions that are convective (buoyant hot bubbles moving up, cold ones moving down) and turbulent, and they have magnetic fields, which are fundamentally nonspherical.

Two-dimensional (2D) simulations were the next step up from spherical symmetry. They became possible in the early to mid 1990s. In such a simulation, a 2D slice (think of the x-y plane in a graph) of the star is simulated and assumed to be symmetric under rotation about one of the axes. If a star's core is rotating rapidly and has a strong magnetic field, then 2D simulations show that such stars can explode in a "magnetorotational" explosion. Such an explosion is mediated by a combination of rapid rotation and a strong magnetic field that pushes out matter symmetrically along the rotation axis in jets that bore through the stellar envelope in the north and south directions.  This is called a bipolar explosion.  Such an explosion can be very energetic and could possibly explain some extremely energetic supernova explosions that make up about 1% of all supernovae and are referred to as hypernovae.

But not so fast. Nature tends to be 3D. And Nature has it in for us.

The current generation of supercomputers is the first to allow us to simulate supernovae in all three dimensions without the limiting assumption that there is some kind of symmetry. Studying supernovae in 2D was already quite exciting and we thought we'd already understood how things like rotation, magnetic fields, or convection affect a supernova.  So when we set out last year to simulate a magnetorotational supernova in 3D (read about the results in Mösta et al. 2014, ApJ 785, L29), we had an expectation bias: such explosions worked beautifully and robustly in 2D. We expected them to work quite similarly in 3D, perhaps with some slight, hopefully interesting variations about the general theme of a jet-driven explosion.

Colormap of a slice through the meridional plane of a rapidly rotating magnetized stellar core. The left panel shows the axisymmetric (2D) simulation, while the three slices to the right show the full 3D simulation without symmetry constraints at different times. The color coding is specific entropy. High values (indicated by red and yellow regions) of this quantity can be interpreted as "hot", "low-density", and "disordered". 2D and 3D yield fundamentally different results.

We were wrong. Nothing is perfect in nature. Even a quickly spinning star is not perfectly symmetric about its spin axis. There will always be small local variations and if there is some amplifying process around (an "instability"), they can grow. And that is precisely what we found in our 3D simulations. An instability grows from small variations from rotational symmetry. It distorts, twists, crumples, and ultimately destroys the jets that quickly and energetically blow up 2D stars. In 3D, we are left with something fundamentally different that we are only just beginning to understand. It's certainly not the runaway explosion we were looking for.

Volume rendering of the specific entropy distribution in our 3D magnetorotational supernova simulation. Red and yellow regions indicate high entropy ("high disorder", "high temperature", "low density"). The flow structure is fundamentally aspherical. Two large-scale polar lobes have formed that slowly move outward, but are not yet running away in an explosion. This snapshot is from about 180 milliseconds after the proto-neutron star is made.
Here is a YouTube movie from our SXS collaboration YouTube Channel. It shows the dynamical 3D dynamics that drive the supernova towards the state shown in the above picture. The color coding is again specific entropy. Blue and green regions are "cold/ordered/high-density", yellow and red regions are "hot/disordered/low-density". (Viewing tip: Switch to HD and look at the movie full screen!)

Here is another movie, this time showing what is called the plasma β parameter encoding the ratio of gas pressure to the effective pressure exerted by the magnetic field. Small values of β mean that the magnetic field dominates the pressure (and thus drives the dynamics). Regions in which this is the case are color-coded in yellow in the below movie. Dark colors (black/blue) indicate dominance of fluid pressure and in red regions, the magnetic field plays a role, but does not dominate.

And we should have known!

When a spinning magnetized star collapses, it's magnetic field lines get wound up tightly about the star's spin axis, sort of like a tight coil or a phone cord. Plasma physics laboratory experiments have shown long ago that such magnetic fields are unstable to a "kink" instability. If one introduces a small kink that pushes the field lines further apart on one side, those on the other side are compressed, creating a stronger magnetic field there. This increases the force that is excerted on the stellar material, pushing it to the other side. As a result, the small kink is amplified into a bigger kink. In this way, a small microscopic deviation from symmetry will become macroscopic and globally change what is happening in the supernova. This instabilty is fundamentally 3D -- in 2D, there is no "other side," since everything is forced to be rotationally symmetric about the spin axis.

Now that we know what happens in 3D, we feel like we should have known.  We should have anticipated the magnetic field in our star to go kink unstable -- it's really textbook physics. In fact, it's the same problem that plasma physicists struggle with when trying to get thermonuclear fusion to work in Tokamak reactors!

The final word about what ultimately happens with our 3D magnetorotational supernova is not yet spoken. It could be that the explosion takes off eventually, blows up the entire star, leaving behind the central neutron star.  It's also possible that the explosion never gains traction and the stellar envelope falls onto the neutron star, which will then collapse to a black hole. We'll see.  We are pushing our simulations further and are ready for more surprises.

Meet the Team:

Science is a team sport; and this is true in particular for the kind of large-scale, massively-parallel simulations that our group at Caltech is pushing. The full author list of the Mösta et al. 2014, The Astrophysical Journal, 785, L29 (2014) includes Philipp Mösta, Sherwood Richers, Christian Ott, Roland Haas, Tony Piro, Kristen Boydstun, Ernazar Abdikamalov, Christian Reisswig, Erik Schnetter. 

Everybody on this team made important contributions to the paper, but I would like to highlight the roles of the first two people in the author list:

Philipp Mösta
Philipp Mösta is a postdoc in TAPIR at Caltech and part of our Simulating eXtreme Spacetimes program. He is funded primarily by a National Science Foundation Astronomy & Astrophysics research grant (NSF grant no. AST-1212170). Philipp received his PhD in 2012 from the Albert Einstein Institute (the Max Planck Institute for Gravitational Physics) in Potsdam, Germany. Philipp spent the past two years adding magnetic fields to our code and making the entire 3D simulation machinery work for these extremely demanding magnetorotational supernova simulations. His previous training was primarily in numerical relativity, but he picked up on supernova physics with an impressive pace. Philipp carried out all simulations that went into our new paper and he worked closely with grad student Sherwood Richers on analyzing them.

Sherwood Richers
Sherwood Richers is currently a second-year graduate student in physics at Caltech. Sherwood is independently funded by a Department of Energy Computational Science Graduate Fellowship (CSGF) and we are delighted that he has chosen to collaborate with us. Sherwood received his undergraduate degree from the University of Virginia, where he carried out research on magnetohydrodynamics (MHD) with John Hawley. Sherwood is a real expert in all things MHD and he and postdoc Tony Piro are the ones who pointed out that what we are seeing in our 3D magnetorotational supernova simulations is most likely an MHD kink instability. Sherwood also participated in visualizing our simulation output and he is the one responsible for the pretty pictures and movies that we were able to produce from our simulation data!

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