# InTheLoop | 10.06.2014

## National Medal of Science Awarded to CRD's Chorin

President Barack Obama announced on Friday that **Alexandre J. Chorin**, a mathematician with the Computational Research Division, will be awarded the National Medal of Science. Chorin holds a joint appointment with the University of California, where he is professor emertis, and Berkeley Lab, where he is senior faculty scientist in the Mathematics Group.

Chorin is considered one of the great applied mathematicians of our time. He introduced powerful new computational methods for the solution of problems in fluid mechanics, covering the spectrum from practical software to rigorous error bounds. His methods are widely used to model airflow over aircraft wings and in turbines and engines, water flow in oceans and lakes, combustion in engines and blood flow in hearts and veins. His methods have also contributed to the theoretical understanding of turbulent flow.

In making the announcement President Obama said: “These scholars and innovators have expanded our understanding of the world, made invaluable contributions to their fields, and helped improve countless lives. Our nation has been enriched by their achievements, and by all the scientists and technologists across America dedicated to discovery, inquiry, and invention.” »Read more.

## Simulations Reveal Unusual Death for Ancient Stars

Certain primordial stars—those between 55,000 and 56,000 times the mass of our Sun—may have died unusually. In death, these objects—among the Universe’s first generation of stars—would have exploded as supernovae and burned completely, leaving no remnant black hole behind. Astrophysicists at the University of California, Santa Cruz (UCSC) and the University of Minnesota came to this conclusion after running a number of supercomputer simulations at the Department of Energy’s (DOE) National Energy Research Scientific Computing Center (NERSC) and Minnesota Supercomputing Institute at the University of Minnesota. They relied extensively on CASTRO, a compressible astrophysics code developed at the DOE’s Lawrence Berkeley National Laboratory’s Computational Research Division. Their findings were recently published in *Astrophysical Journal*. »Read more.

## Antypas to Present 'Big Idea' of Energy Efficient Supercomputing

**Katie Antypas** will be one of eight Berkeley Lab scientists presenting "8 Big Ideas" in only eight minutes each at this week's Science at the Theater. Antypas, who heads NERSC's Services Department, will address energy efficient supercomputing. The free program will take place at 7 p.m., on Wednesday, October 8 at Oakland's Kaiser Theater. »Learn more and register to attend.

## NPR's *SciFri* Notes NERSC, ESnet and CRD Collaboration with SLAC

The staff of National Public Radio's popular *Science Friday (SciFri) *show recently asked listeners to submit their observations of interesting science using the hashtag #ObserveEverthing. Their call netted dozens of replies. Among the handful of favorites the staff chose to highlight was an impressive collaboration between the Department of Energy's NERSC and ESnet and the SLAC National Accelerator Laboratory which has used SPOT Suite, a collection of software and data analysis tools developed by Berkeley Lab's Computational Research Division (CRD).

Berkeley Lab and SLAC researchers led a protein crystallography experiment at SLAC’s Linac Coherent Light Source (LCLS) to look at the different photoexcited states of photosystem II, an assembly of large protein molecules that play a crucial role in photosynthesis. Subsequent analysis of the data on supercomputers at NERSC helped explain how nature splits a water molecule during photosynthesis, a finding that could advance the development of artificial photosynthesis for clean, green and renewable energy. Thanks to a "photon speedway" created by ESnet, researchers saw data from the LCLS arrive at NERSC in real-time, allowing them to adjust the next day's experiments, a first for such instruments. In a follow-on experiment, the researchers added another twist: SPOT Suite. The set of CRD-developed software tools gave researcher access to analyses of experiments as they were being performed, rather than after hours of post-processing. »Read more.

## This Week's CS Seminars

### Simons Institute Open Lecture: The Revolution in Graph-Theoretic Optimization

**Monday, Oct. 6, 4 – 5 p.m. (Light refreshments at 3:30 p.m.)**

Banatao Auditorium (310 Sutardja Dai Hall) UC Berkeley Campus

Gary Miller, Carnegie Mellon University

Banatao Auditorium (310 Sutardja Dai Hall) UC Berkeley Campus

Gary Miller, Carnegie Mellon University

Graph theoretic optimization problems that have been dormant for fifty years are now seeing new and exciting algorithms. These advances have been made possible by Spectral Graph Theory, the interplay between linear algebra and combinatorial graph theory. One application of this interplay is a nearly linear time solver for Symmetric Diagonally Dominant systems (SDD). This seemingly restrictive class of linear systems has received substantial interest in the last fifteen years, and there is an ever growing list of problems that are amenable to SDD solvers, including image segmentation, image denoising, finding solutions to elliptic equations, computing maximum flow in a graph, and graph sparsification. All these examples can be viewed as special cases of convex optimization problems on graphs.

Possibly the best known graph theoretic optimization problem is computing the maximum flow in a graph. Again, using spectral graph theory, the maximum flow problem in undirected graphs can now be approximately solved in almost linear time. I claim that this is only the beginning of a new era in efficient algorithm design.

In this talk I will describe a world not too far in the future in which such optimization problems, which a priori seem to require at least quadratic work, will all be solvable by genuinely practical algorithms that are guaranteed to run in near linear time and are highly parallel.

### Atomistic Materials Modeling from a Commercial Point of View

**Tuesday, Oct. 7, 12 p.m. – 1 p.m, NERSC OSF Rm. 238**

**Paul Saxe, Materials Design**

There has been a dramatic growth of interest in integrated computational materials engineering (ICME) since the publication in 2008 of a report on the topic by the National Research Council and the announcement of the Materials Genome Initiative (MGI), announced three years later. ICME is considered to be vital to the continued viability of large swathes of industry since our technology is increasingly relying on sophisticated materials, yet the insertion of a new material into a product is a daunting, lengthy task. Clearly it will require a large cultural shift to successfully introduce and exploit ICME in industry. Materials Design is in a good position to understand the nature of the change needed. We have made our living for the last 16 years from integrating and selling atomistic computational materials tools to industry, and count among our customers many of the largest companies worldwide in the chemical, oil and gas, automotive and electronics industries. With a combined annual revenue exceeding $4 trillion, these companies are clearly heavily invested in materials. Using this perspective, I will comment on what industry needs and how some recent trends such as open-source software advance some interests but impede others. In addition I have some thoughts on what centers such as NERSC do exceedingly well, as well as areas that may need attention as the culture shifts in response to these initiatives, and to industry demand.

REMOTE ACCESS DETAILS

Join WebEx meeting https://nersc.webex.com/

Meeting number: 806 086 553

Meeting password: edison

### Hyper-QC: A method to coarse-grain space and accelerate time

**Mitchell Luskin, University of Minnesota**

Tuesday, Oct. 7, 2 p.m. – 3 p.m., 740 Evans Hall UC Berkeley

Tuesday, Oct. 7, 2 p.m. – 3 p.m., 740 Evans Hall UC Berkeley

Temporal and spatial multiscale challenges appear because the material response of crystalline solids is characterized by the nucleation and dynamics of defects such as point defects (vacancies, interstitials, impurities), line defects (dislocations), and surface defects (grain boundaries, surfaces, cracks, etc.). To overcome these challenges and reach mesoscopic scales, we have developed the Hyper-QC method to coarse-grain space by the finite temperature quasicontinuum method and accelerate time by the hyperdynamics method.

### CITRIS Research Exchange: Data Analytics in Energy

**Wednesday, Oct. 8, 12 p.m. – 1p.m., Banatao Auditorium (310 Sutardja Dai Hall) UC Berkeley**

**Ed Abbo, C3 Energy**

Analytics are becoming core business and essential to achieving the potential value of the digital power grid. In this session, C3 Energy’s President and Chief Technology Officer Ed Abbo will discuss the use of advanced analytics to realize the full promise of utility investments in smart grid. He will share thoughts on the evolution of IT systems over the last forty years, culminating in an opportunity today to build the data-driven utility.

### Stochastic Control and Trajectory Optimization: Information Theoretic Interpretations and Algorithms

**Wednesday, Oct. 8, 3:30 p.m. – 4:30 p.m., 939 Evans Hall UC Berkeley**

**Evangelos Theodorou, Georgia Tech**

While the topic of nonlinear stochastic control has been traditionally studied within control theory and applied mathematics, over the past 10-15 years there has been an increasing interest by researchers in the machine learning, statistical physics and robotics communities to expand nonlinear stochastic optimal control in terms of theoretical generalizations and algorithms. The main motivation for this increasing interest is the ability to solve stochastic optimal control problems with forward sampling of Stochastic Differential Equations (SDEs). There has been few approaches in the literature on this topic under the names of path integral control, Kullback-Leibler control or linearly solvable optimal control.

In this talk, in the first half I will present a unified view of the aforementioned approaches on stochastic control theory and show applications to autonomous systems and robotics. On the second half, I will present ongoing research on generalizations of stochastic control and show new algorithms for trajectory optimization based on non-parametric regression methods.