Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Adenosine Triphosphate and Carbon Efficient Route to Second Generation Biofuel Isopentanol.

Climate change necessitates the development of CO2 neutral or negative routes to chemicals currently produced from fossil carbon. In this paper we demonstrate a pathway from the renewable resource glucose to next generation biofuel isopentanol by pairing the isovaleryl-CoA biosynthesis pathway from Myxococcus xanthus and a butyryl-CoA reductase from Clostridium acetobutylicum. The best plasmid and Escherichia coli strain combination makes 80.50 ± 8.08 (SD) mg/L of isopentanol after 36 h under microaerobic conditions with an oleyl alcohol overlay. In addition, the system also shows a strong preference for isopentanol production over prenol in microaerobic conditions. Finally, the pathway requires zero adenosine triphosphate and can be paired theoretically with nonoxidative glycolysis, the combination being redox balanced from glucose thus avoiding unnecessary carbon loss as CO2. These pathway properties make the isovaleryl-CoA pathway an attractive isopentanol production route for further optimization

Assessing New York City's Youth Gun Violence Crisis: Crews - Volume II - CompStat for Violence Prevention Programs: Collecting Program Specific Data to Manage Performance and Inform Policy

The success or failure of community strategies to address the youth gun violence crisis is often attributed in part to how well the problem is understood and diagnosed. With support from The New York Community Trust, the Crime Commission has undertaken an analysis of youth gun violence and crew activity -- violent turf rivalries among less-organized, smaller and normally younger groups than traditional gangs -- in select New York City communities. Our initial findings from available data, existing research and interviews with stakeholders are presented in a series of papers titled, "Assessing New York City's Youth Gun Violence Crisis: Crews.

Dynamics and Spatial Distribution of Global Nighttime Lights

Using open source data, we observe the fascinating dynamics of nighttime light. Following a global economic regime shift, the planetary center of light can be seen moving eastwards at a pace of about 60 km per year. Introducing spatial light Gini coefficients, we find a universal pattern of human settlements across different countries and see a global centralization of light. Observing 160 different countries we document the expansion of developing countries, the growth of new agglomerations, the regression in countries suffering from demographic decline and the success of light pollution abatement programs in western countries

NASA Cold Land Processes Experiment (CLPX 2002/03): ground-based and near-surface meteorological observations

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters include air temperature, relative humidity, wind speed and direction, barometric pressure, short- and long-wave radiation, leaf wetness, snow depth, snow water content, snow and surface temperatures, volumetric soil-moisture content, soil temperature, precipitation, water vapor flux, carbon dioxide flux, and soil heat flux. The CLPX weather stations include 10 main meteorological towers, 1 tower within each of the nine intensive study areas (ISA) and one near the local scale observation site (LSOS); and 36 simplified towers, with one tower at each of the four corners of each of the nine ISAs, which measured a reduced set of parameters. An eddy covariance system within the North Park mesocell study area (MSA) collected a variety of additional parameters beyond the 10 standard CLPX tower components. Additional meteorological observations come from a variety of existing networks maintained by the U.S. Forest Service, U.S. Geological Survey, Natural Resource Conservation Service, and the Institute of Arctic and Alpine Research. Temporal coverage varies from station to station, but it is most concentrated during the 2002/ 03 winter season. These data are useful in local meteorological energy balance research and for model development and testing. These data can be accessed through the National Snow and Ice Data Center Web site

Quantum annealing for systems of polynomial equations

Numerous scientific and engineering applications require numerically solving systems of equations. Classically solving a general set of polynomial equations requires iterative solvers, while linear equations may be solved either by direct matrix inversion or iteratively with judicious preconditioning. However, the convergence of iterative algorithms is highly variable and depends, in part, on the condition number. We present a direct method for solving general systems of polynomial equations based on quantum annealing, and we validate this method using a system of second-order polynomial equations solved on a commercially available quantum annealer. We then demonstrate applications for linear regression, and discuss in more detail the scaling behavior for general systems of linear equations with respect to problem size, condition number, and search precision. Finally, we define an iterative annealing process and demonstrate its efficacy in solving a linear system to a tolerance of $10^{-8}$.Comment: 11 pages, 4 figures. Added example for a system of quadratic equations. Supporting code is available at https://github.com/cchang5/quantum_poly_solver . This is a post-peer-review, pre-copyedit version of an article published in Scientific Reports. The final authenticated version is available online at: https://www.nature.com/articles/s41598-019-46729-