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  • richardmitnick 4:06 pm on September 26, 2018 Permalink | Reply
    Tags: , , , , , , MIRA supercomputer   

    From ASCR Discovery: “Superstars’ secrets” 

    From ASCR Discovery
    ASCR – Advancing Science Through Computing

    September 2018

    Superstars’ secrets

    Supercomputing power and algorithms are helping astrophysicists untangle giant stars’ brightness, temperature and chemical variations.

    1
    A frame from an animated global radiation hydrodynamic simulation of an 80-solar-mass star envelope, performed on the Mira supercomputer at the Argonne Leadership Computing Facility (ALCF).

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    Seen here: turbulent structures resulting from convection around the iron opacity peak region. Density is highest near the star’s core (yellow). The other colors represent low-density winds launched near the surface. Simulation led by University of California at Santa Barbara. Visualization courtesy of Joseph A. Insley/ALCF.

    Since the Big Bang nearly 14 billion years ago, the universe has evolved and expanded, punctuated by supernova explosions and influenced by the massive stars that spawn them. These stars, many times the size and brightness of the sun, have relatively short lives and turbulent deaths that produce gamma ray bursts, neutron stars, black holes and nebulae, the colorful chemical incubators for new stars.

    Although massive stars are important to understanding astrophysics, the largest ones – at least 20 times the sun’s mass – are rare and highly variable. Their brightness changes by as much as 30 percent, notes Lars Bildsten of the Kavli Institute for Theoretical Physics (KITP) at University of California, Santa Barbara (UCSB). “It rattles around on a timescale of days to months, sometimes years.” Because of the complicated interactions between the escaping light and the gas within the star, scientists couldn’t explain or predict this stellar behavior.

    But with efficient algorithms and the power of the Mira IBM Blue Gene/Q supercomputer at the Argonne Leadership Computing Facility, a Department of Energy (DOE) Office of Science user facility, Bildsten and his colleagues have begun to model the variability in three dimensions across an entire massive star. With an allocation of 60 million processor hours from DOE’s INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program, the team aims to make predictions about these stars that observers can test. They’ve published the initial results from these large-scale simulations – linking brightness changes in massive stars with temperature fluctuations on their surfaces – in the Sept. 27 issue of the journal Nature.

    Yan-Fei Jiang, a KITP postdoctoral scholar, leads these large-scale stellar simulations. They’re so demanding that astrophysicists often must limit the models – either by focusing on part of a star or by using simplifications and approximations that allow them to get a broad yet general picture of a whole star.

    The team started with one-dimensional computational models of massive stars using the open-source code MESA (Modules for Experiments in Stellar Astrophysics). Astrophysicists have used such methods to examine normal convection in stars for decades. But with massive stars, the team hit limits. The bodies are so bright and emit so much radiation that the 1-D models couldn’t capture the violent instability in some regions of the star, Bildsten says.

    Matching 1-D models to observations required researchers to hand-tune various features, Jiang says. “They had no predictive power for these massive stars. And that’s exactly what good theory should do: explain existing data and predict new observations.”

    To calculate the extreme turbulence in these stars, Jiang’s team needed a more complex three-dimensional model and high-performance computers. As a Princeton University Ph.D. student, Jiang had worked with James Stone on a program that could handle these turbulent systems. Stone’s group had developed the Athena++ code to study the dynamics of magnetized plasma, a charged, flowing soup that occurs in stars and many other astronomical objects. While at Princeton, Jiang had added radiation transport algorithms.

    That allowed the team to study accretion disks – accumulated dust and other matter – around the edges of black holes, a project that received a 2016 INCITE allocation of 47 million processor hours. Athena++ has been used for hundreds of other projects, Stone says.

    Stone is part of the current INCITE team, which also includes UCSB’s Omer Blaes, Matteo Cantiello of the Flatiron Institute in New York and Eliot Quataert, University of California, Berkeley.

    In their Nature paper, the group has linked variations in a massive star’s brightness with changes in its surface temperature. Hotter blue stars show smaller fluctuations, Bildsten says. “As a star becomes redder (and cooler), it becomes more variable. That’s a pretty firm prediction from what we’ve found, and that’s going to be what’s exciting to test in detail.”

    Another factor in teasing out massive stars’ behaviors could be the quantity of heavy elements in their atmospheres. Fusion of the lightest hydrogen and helium atoms in massive stars produces heavier atoms, including carbon, oxygen, silicon and iron. When supernovae explode, these bulkier chemical elements are incorporated into new stars. The new elements are more opaque than hydrogen and helium, so they capture and scatter radiation rather than letting photons pass through. For its code to model massive stars, the team needed to add opacity data for these other elements. “The more opaque it is, the more violent these instabilities are likely to be,” Bildsten says. The team is just starting to explore how this chemistry influences the stars’ behavior.

    The scientists also are examining how the brightness variations connect to mass loss. Wolf-Rayet stars are an extreme example of this process, having lost their outer envelopes containing hydrogen and instead containing helium and heavier elements only. These short-lived objects burn for a mere 5 million years, compared with 10 billion years for the sun. Over that time, they shed mass and material before collapsing into a neutron star or a black hole. Jiang and his group are working with UC Berkeley postdoctoral scholar Stephen Ro to diagnose that mass-loss mechanism.

    These 3-D simulations are just the beginning. The group’s current model doesn’t include rotation or magnetic fields, Jiang notes, factors that can be important for studying properties of massive stars such as gamma ray burst-related jets, the brightest explosions in the universe.

    The team also hopes to use its 3-D modeling lessons to improve the faster, cheaper 1-D algorithms – codes Bildsten says helped the team choose which systems to model in 3-D and could point to systems for future investigations.

    Three-dimensional models, Bildsten notes, “are precious simulations, so you want to know that you’re doing the one you want.”

    See the full article here.


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    ASCRDiscovery is a publication of The U.S. Department of Energy

     
  • richardmitnick 3:15 pm on November 25, 2016 Permalink | Reply
    Tags: INCITE program, , MIRA supercomputer, Stellar mass loss,   

    From UC Santa Barbara’s Kavli Institute for Theoretical Physics (KITP): “Stellar Simulators” 

    UC Santa Barbara Name bloc

    UC Santa Barbara

    KavliFoundation

    The Kavli Foundation

    November 22, 2016
    Julie Cohen

    It’s an intricate process through which massive stars lose their gas as they evolve. And a more complete understanding could be just calculations away, if only those calculations didn’t take several millennia to run on normal computers.

    But astrophysicists Matteo Cantiello and Yan-Fei Jiang of UC Santa Barbara’s Kavli Institute for Theoretical Physics (KITP) may find a way around that problem.

    The pair have been awarded 120 million CPU hours over two years on the supercomputer Mira — the sixth-fastest computer in the world — through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program, an initiative of the U.S. Department of Energy Office of Science.

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    INCITE aims to accelerate scientific discoveries and technological innovations by awarding, on a competitive basis, time on supercomputers to researchers with large-scale, computationally intensive projects that address “grand challenges” in science and engineering.

    “Access to Mira means that we will be able to run calculations that otherwise would take about 150,000 years to run on our laptops,” said Cantiello, an associate specialist at KITP.

    Cantiello and Jiang will use their supercomputer time to run 3-D simulations of stellar interiors, in particular the outer envelopes of massive stars. Such calculations are an important tool to inform and improve the one-dimensional approximations used in stellar evolution modeling. The researchers aim to unravel the complex physics involved in the interplay among gas, radiation and magnetic fields in such stars — stellar bodies that later in life can explode to form black holes and neutron stars.

    The physicists use grid-based Athena++ code — which has been carefully extended and tested by Jiang — to solve equations for the gas flow in the presence of magnetic fields (magnetohydrodynamics) and for how photons move in such environments and interact with the gas flow (radiative transfer). The code divides the huge calculations into small pieces that are sent to many different CPUs and are solved in parallel. With a staggering number of CPUs — 786,432 to be precise — Mira speeds up the process tremendously.

    This research addresses an increasingly important problem: understanding the structure of massive stars and the nature of the process that makes them lose mass as they evolve. This includes both relatively steady winds and dramatic episodic mass loss eruptions.

    Called stellar mass loss, this process has a decisive effect on the final fate of these objects. The type of supernova explosion that these stars undergo, as well as the type of remnants they leave behind (neutron stars, black holes or even no remnant at all), are intimately tied to their mass loss.

    The study is particularly relevant in light of the recent detection of gravitational waves from LIGO (Laser Interferometer Gravitational-Wave Observatory). The discovery demonstrated the existence of stellar mass black holes orbiting so close to each other that eventually they can merge and produce the observed gravitational waves.

    “Understanding how these black hole binary systems formed in the first place requires a better understanding of the structure and mass loss of their stellar progenitors,” explained Jiang, a postdoctoral fellow at KITP.

    The implications of the work Cantiello and Jiang will perform on Mira also extend to broader fields of stellar evolution and galaxy formation, among others.

    See the full UCSB article here .
    See the full Kavli article here .

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    The Kavli Foundation, based in Oxnard, California, is dedicated to the goals of advancing science for the benefit of humanity and promoting increased public understanding and support for scientists and their work.

    The Foundation’s mission is implemented through an international program of research institutes, professorships, and symposia in the fields of astrophysics, nanoscience, neuroscience, and theoretical physics as well as prizes in the fields of astrophysics, nanoscience, and neuroscience.

    UC Santa Barbara Seal

    The University of California, Santa Barbara (commonly referred to as UC Santa Barbara or UCSB) is a public research university and one of the 10 general campuses of the University of California system. Founded in 1891 as an independent teachers’ college, UCSB joined the University of California system in 1944 and is the third-oldest general-education campus in the system. The university is a comprehensive doctoral university and is organized into five colleges offering 87 undergraduate degrees and 55 graduate degrees. In 2012, UCSB was ranked 41st among “National Universities” and 10th among public universities by U.S. News & World Report. UCSB houses twelve national research centers, including the renowned Kavli Institute for Theoretical Physics.

     
  • richardmitnick 1:12 pm on August 5, 2016 Permalink | Reply
    Tags: , , MIRA supercomputer, Self-Healing Diamond-Like Carbon   

    From ANL: “Argonne Discovery Yields Self-Healing Diamond-Like Carbon” 

    ANL Lab

    News from Argonne National Laboratory

    1

    Argonne Leadership Computing Facility

    August 5, 2016
    Katie Jones
    Greg Cunningham

    1
    Mira simulations also allowed researchers to look beyond the current study by virtually testing other potential catalysts (other metals and hydrocarbons in coatings and oils) for their “self-healing” properties in a high-temperature, high-pressure engine environment.
    Joseph Insley, Argonne National Laboratory

    Large-scale reactive molecular dynamics simulations carried out on the Mira supercomputer at the Argonne Leadership Computing Facility, along with experiments conducted by researchers in Argonne’s Energy Systems Division, enabled the design of a “self-healing,” anti-wear coating that dramatically reduces friction and related degradation in engines and moving machinery. Now, the computational work advanced for this purpose is being used to identify the friction-fighting potential of other catalysts.

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    Fans of Superman surely recall how the Man of Steel used immense heat and pressure generated by his bare hands to form a diamond out of a lump of coal.

    The tribologists – scientists who study friction, wear and lubrication – and computational materials scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory will probably never be mistaken for superheroes. However, they recently applied the same principles and discovered a revolutionary diamond-like film of their own that is generated by the heat and pressure typical of an automotive engine.

    The discovery of this ultra-durable, self-lubricating tribofilm – a film that forms between moving surfaces – was first reported today in the journal Nature. It could have profound implications for the efficiency and durability of future engines and other moving metal parts that can be made to develop self-healing, diamond-like carbon (DLC) tribofilms.

    “This is a very unique discovery, and one that was a little unexpected,” said Ali Erdemir, the Argonne Distinguished Fellow who leads the team. “We have developed many types of diamond-like carbon coatings of our own, but we’ve never found one that generates itself by breaking down the molecules of the lubricating oil and can actually regenerate the tribofilm as it is worn away.”

    The phenomenon was first discovered several years ago by Erdemir and his colleague Osman Levent Eryilmaz in the Tribology and Thermal-Mechanics Department in Argonne’s Center for Transportation Research. But it took theoretical insight enhanced by the massive computing resources available at Argonne to fully understand what was happening at the molecular level in the experiments. The theoretical understanding was provided by lead theoretical researcher Subramanian Sankaranarayanan and postdoctoral researcher Badri Narayanan from the Center for Nanoscale Materials (CNM), while the computing power was provided by the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. CNM, ALCF and NERSC are all DOE Office of Science User Facilities.

    The original discovery occurred when Erdemir and Eryilmaz decided to see what would happen when a small steel ring was coated with a catalytically active nanocoating – tiny molecules of metals that promote chemical reactions to break down other materials – then subjected to high pressure and heat using a base oil without the complex additives of modern lubricants. When they looked at the ring after the endurance test, they didn’t see the expected rust and surface damage, but an intact ring with an odd blackish deposit on the contact area.

    “This test creates extreme contact pressure and temperatures, which are supposed to cause the ring to wear and eventually seize,” said Eryilmaz. “But this ring didn’t significantly wear and this blackish deposit was visible. We said ‘this material is strange. Maybe this is what is causing this unusual effect.’”

    Looking at the deposit using high-powered optical and laser Raman microscopes, the experimentalists realized the deposit was a tribofilm of diamond-like carbon, similar to several other DLCs developed at Argonne in the past. But it worked even better. Tests revealed the DLC tribofilm reduced friction by 25 to 40 percent and that wear was reduced to unmeasurable values.

    Further experiments, led by postdoctoral researcher Giovanni Ramirez, revealed that multiple types of catalytic coatings can yield DLC tribofilms. The experiments showed the coatings interact with the oil molecules to create the DLC film, which adheres to the metal surfaces. When the tribofilm is worn away, the catalyst in the coating is re-exposed to the oil, causing the catalysis to restart and develop new layers of tribofilm. The process is self-regulating, keeping the film at consistent thickness. The scientists realized the film was developing spontaneously between the sliding surfaces and was replenishing itself, but they needed to understand why and how.

    To provide the theoretical understanding of what the tribology team was seeing in its experiments, they turned to Sankaranarayanan and Narayanan, who used the immense computing power of ALCF’s 10-petaflop supercomputer, Mira. They ran large-scale simulations to understand what was happening at the atomic level, and determined that the catalyst metals in the nanocomposite coatings were stripping hydrogen atoms from the hydrocarbon chains of the lubricating oil, then breaking the chains down into smaller segments. The smaller chains joined together under pressure to create the highly durable DLC tribofilm.

    “This is an example of catalysis under extreme conditions created by friction. It is opening up a new field where you are merging catalysis and tribology, which has never been done before,” said Sankaranarayanan. “This new field of tribocatalysis has the potential to change the way we look at lubrication.”

    The theorists explored the origins of the catalytic activity to understand how catalysis operates under the extreme heat and pressure in an engine. By gaining this understanding, they were able to predict which catalysts would work, and which would create the most advantageous tribofilms.

    “Interestingly, we found several metals or composites that we didn’t think would be catalytically active, but under these circumstances, they performed quite well,” said Narayanan. “This opens up new pathways for scientists to use extreme conditions to enhance catalytic activity.”

    Using the LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) code, Sankaranarayanan and Narayanan modeled as many as two million atoms per simulation, making this one of the few atomistic studies of friction — of any kind, not just tribocatalysis — at this scale. Millions of time steps per simulation enabled researchers to identify the initial catalytic processes that occur within nanoseconds of machine operation and cannot be readily observed under experimental conditions.

    “Tribology has traditionally been an applied field, but the advent of supercomputers like Mira is now allowing us to gain fundamental insights into the complex reactions that are at play at the tribological interfaces,” Sankaranarayanan said.

    Mira simulations also allowed researchers to look beyond the current study by virtually testing other potential catalysts (other metals and hydrocarbons in coatings and oils) for their “self-healing” properties in a high-temperature, high-pressure engine environment.

    “This study has profound implications for pushing the frontiers of atomistic modeling towards rapid, predictive design and discovery of next-generation, anti-wear lubricants,” Narayanan said.

    With the help of ALCF staff in 2015, a team of domain and computational scientists worked to improve LAMMPS performance. The improvements targeted several parts of the code, including the ReaxFF module, an add-on package used to model the chemical reactions occurring in the system.

    In collaboration with researchers from IBM, Lawrence Berkeley National Laboratory (LBNL), and Sandia National Laboratories, ALCF optimized LAMMPS by replacing Message Passing Interface (MPI) point-to-point communication with MPI collectives in key algorithms, making use of MPI I/O, and adding OpenMP threading to the ReaxFF module. These enhancements doubled the code’s performance.

    Contributors to the code optimization work included Paul Coffman, Wei Jiang, Chris Knight, and Nichols A. Romero from the ALCF; Hasan Metin Aktulga from LBNL (now at Michigan State University); and Tzu-Ray Shan from Sandia (now at Materials Design, Inc.).

    The implications of the new tribofilm for efficiency and reliability of engines are huge. Manufacturers already use many different types of coatings – some developed at Argonne – for metal parts in engines and other applications. The problem is those coatings are expensive and difficult to apply, and once they are in use, they only last until the coating wears through. The new catalyst allows the tribofilm to be continually renewed during operation.

    Additionally, because the tribofilm develops in the presence of base oil, it could allow manufacturers to reduce, or possibly eliminate, some of the modern anti-friction and anti-wear additives in oil. These additives can decrease the efficiency of vehicle catalytic converters and can be harmful to the environment because of their heavy metal content.

    The results are published in Nature in a study titled Carbon-based Tribofilms from Lubricating Oils. The research was funded by DOE’s Office of Energy Efficiency & Renewable Energy.

    The team also includes microscopy expert Yifeng Liao and computational scientist Ganesh Kamath.

    See the full article here .

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    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    The Advanced Photon Source at Argonne National Laboratory is one of five national synchrotron radiation light sources supported by the U.S. Department of Energy’s Office of Science to carry out applied and basic research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels, provide the foundations for new energy technologies, and support DOE missions in energy, environment, and national security. To learn more about the Office of Science X-ray user facilities, visit http://science.energy.gov/user-facilities/basic-energy-sciences/.

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
  • richardmitnick 10:48 am on June 15, 2016 Permalink | Reply
    Tags: 3-D simulations illuminate supernova explosions, , , , MIRA supercomputer,   

    From Argonne: “3-D simulations illuminate supernova explosions” 

    Argonne Lab

    News from Argonne National Laboratory

    June 2, 2016
    Jim Collins

    1

    2
    Magnetohydrodynamic turbulence powered by neutrino-driven convection behind the stalled shock of a core-collapse supernova simulation. This simulation shows that the presence of rotation and weak magnetic fields dramatically impacts the development of the supernova mechanism as compared to nonrotating, nonmagnetic stars. The nascent neutron star is just barely visible in the center below the turbulent convection. (Image credit: Sean M. Couch, Michigan State University)

    In the landmark television series “Cosmos,” astronomer Carl Sagan famously proclaimed, “We are made of star stuff.”

    Supernova in Messier 101
    Supernova in Messier 101 2011 Image credit: NASA / Swift.

    Supernova remnant Crab nebula. NASA/ESA Hubble
    Supernova remnant Crab nebula. NASA/ESA Hubble

    At the end of their life cycles, these massive stars explode in spectacular fashion, scattering their guts — which consist of carbon, iron and basically all other natural elements — across the cosmos. These elements go on to form new stars, solar systems and everything else in the universe — including the building blocks for life on Earth.

    Despite this fundamental role in cosmology, the mechanisms that drive supernova explosions are still not well understood.

    “If we want to understand the chemical evolution of the entire universe and how the stuff that we’re made of was processed and distributed throughout the universe, we have to understand the supernova mechanism,” said Sean Couch, assistant professor of physics and astronomy at Michigan State University.

    To shed light on this complex phenomenon, Couch is leading an effort to use Mira, the Argonne Leadership Computing Facility’s (ALCF’s) 10-petaflops supercomputer, to carry out some of the largest and most detailed three-dimensional (3-D) simulations ever performed of core-collapse supernovas.

    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility
    MIRA IBM Blue Gene Q supercomputer at the Argonne Leadership Computing Facility

    The ALCF is a U.S. Department of Energy (DOE) Office of Science User Facility.

    After millions of years of burning ever-heavier elements, these super-giant stars (at least eight solar masses, or eight times the mass of the sun) eventually run out of nuclear fuel and develop an iron core. No longer able to support themselves against their own immense gravitational pull, they start to collapse. But a process, not yet fully understood, intervenes that reverses the collapse and causes the star to explode.

    “What theorists like me are trying to understand is that in-between step,” Couch said. “How do we go from this collapsing iron core to an explosion?”

    Through his work at the ALCF, Couch and his team are developing and demonstrating a high-fidelity 3-D simulation approach that is providing a more realistic look at this “in-between step” than previous supernova simulations.

    While this 3-D method is still in its infancy, Couch’s early results have been promising. In 2015, his team published a paper in the Astrophysical Journal Letters, detailing their 3-D simulations of the final three minutes of iron core growth in a 15 solar-mass star. They found that more accurate representations of the star’s structure and the motion generated by turbulent convection (measured at several hundred kilometers per second) play a substantial role at the point of collapse.

    “Not surprisingly, we’re showing that more realistic initial conditions have a significant impact on the results,” Couch said.

    Adding another dimension

    Despite the fact that stars rotate, have magnetic fields and are not perfect spheres, most one- and two-dimensional supernova simulations to date have modeled nonrotating, nonmagnetic, spherically symmetrical stars. Scientists were forced to take this simplified approach because modeling supernovas is an extremely computationally demanding task. Such simulations involve highly complex multiphysics calculations and extreme timescales: the stars evolve over millions of years, yet the supernova mechanism occurs in a second.

    According to Couch, working with unrealistic initial conditions has led to difficulties in triggering robust and consistent explosions in simulations — a long-standing challenge in computational astrophysics.

    However, thanks to recent advances in computing hardware and software, Couch and his peers are making significant strides toward more accurate supernova simulations by employing the 3-D approach.

    The emergence of petascale supercomputers like Mira has made it possible to include high-fidelity treatments of rotation, magnetic fields and other complex physics processes that were not feasible in the past.

    “Generally when we’ve done these kinds of simulations in the past, we’ve ignored the fact that magnetic fields exist in the universe because when you add them into a calculation, it increases the complexity by about a factor of two,” Couch said. “But with our simulations on Mira, we’re finding that magnetic fields can add a little extra kick at just the right time to help push the supernova toward explosion.”

    On the software side, Couch continues to collaborate with ALCF computational scientists to improve the open-source FLASH code and its ability to simulate supernovas.

    But even with today’s high-performance computing hardware and software, it is not yet feasible to include high-fidelity treatments of all the relevant physics in a single simulation; that would require a future exascale system, Couch said.

    “Our simulations are only a first step toward truly realistic 3-D simulations of supernova,” he said. “But they are already providing a proof-of-principle that the final minutes of a massive star evolution can and should be simulated in 3-D.”

    The team’s results were published in Astrophysical Journal Letters in a 2015 paper titled The Three-Dimensional Evolution to Core Collapse of a Massive Star. The study also used computing resources at the Texas Advanced Computing Center at the University of Texas at Austin.

    TACC bloc
    TACC

    Couch’s supernova research began at the ALCF with a Director’s Discretionary award and now continues with computing time awarded through DOE’s Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This work is being funded by the DOE Office of Science (Advanced Scientific Computing Research) and the National Science Foundation.

    See the full article here .

    Please help promote STEM in your local schools.
    STEM Icon
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    Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science. For more visit http://www.anl.gov.

    The Advanced Photon Source at Argonne National Laboratory is one of five national synchrotron radiation light sources supported by the U.S. Department of Energy’s Office of Science to carry out applied and basic research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels, provide the foundations for new energy technologies, and support DOE missions in energy, environment, and national security. To learn more about the Office of Science X-ray user facilities, visit http://science.energy.gov/user-facilities/basic-energy-sciences/.

    Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science

    Argonne Lab Campus

     
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