Discoveries: Information Science and Technology

Integrating Information, Science, and Technology for Prediction.

This pillar makes possible a discovery-to-prediction Laboratory, in which physical and information sciences come together to predict the behavior of complex, mission-critical systems.

Predictive science requires the ongoing anticipation and coupling of advanced analytics, modeling and simulation methods, algorithms and codes with a vibrant yet robust IS&T infrastructure capable of supporting dynamic interaction with data from many sources, including suites of experiments and observations. This pillar stimulates and leverages advances in physical theory, applied math, data science, algorithms, and diverse approaches to high-performance computing to accelerate predictive capability.

Nonlinear Dynamics

Nonlinear wave equations, ubiquitous in physics, were pioneered by discoveries of chaotic behavior in simple systems by Fermi, Pasta, Ulam, and Tsingou and by Feigenbaum.

In non-linear dynamics, a system can tend to evolve to a set of states, whatever its starting conditions. Image from wikimedia commons: https://commons.wikimedia.org/wiki/File:Poisson_saturne_revisited.jpg

Summary

Nonlinear wave equations are ubiquitous throughout physics, including the sine-Gordon equation (e.g., nonlinear pendulum, superconducting Josephson junctions), the nonlinear Schrodinger equation (e.g., light propagation in waveguides, Bose-Einstein condensates in a trap, Langmuir waves in hot plasmas) and the Korteweg-de Vries equation (shallow water waves, internal waves). Two watershed events at LANL laid their foundation.

In a groundbreaking computer simulation (1953), Fermi, Pasta, Ulam, and Tsingou discovered that a string comprising non-linear springs shows an unusual behavior, wandering from one pattern of motion to another, and from time to time piling all its energy into a single mode. Two decades later, Feigenbaum, with only a hand calculator, discovered a new universal constant in the behavior of non-linear systems. These discoveries opened applications in control systems, Earth systems such as ocean currents, aerodynamics, chaotic systems, economics, and more. For example, solitons occur both in optical fibers and as self-trapped excitations on biological molecules.

Contributing author

Avadh Saxena

References

The first simulation with nonlinear springs and its consequences are highlighted in: 

1. Fermi, Pasta, Ulam, and a mysterious lady, Dauxois, Thierry, Physics Today 61 (2008): 55.

The recursive relations exhibiting infinite bifurcation and universality were reported in: 

2. Quantitative universality for a class of nonlinear transformations, Feigenbaum, Mitchell, Journal of Statistical Physics 19 (1978): 25.  

On-line Archives

The rapid distribution of scientific results via electronic arXiv preprints posted to the internet was invented at Los Alamos. This changed scientific discourse forever.

Summary

To keep up with the rapid pace of discovery, scientists have for years distributed their papers in preprint form, sharing their preliminary results without waiting for the time-consuming steps needed to publish in a journal. While a journal carries out its due diligence, fresh results are already in the hands of colleagues. Before the internet, preprints were printed out and posted to a selected list, which was both slow and undemocratic, leaving out emerging researchers and institutions. Paul Ginsparg at Los Alamos changed everything in 1991, when he established a research-sharing platform that leveraged the internet to revolutionize the communication of scientific information worldwide. Originally called xxx.lanl.gov, the system was based at Los Alamos until migrating to Cornell in 2001. Renamed as arXiv, it now hosts over 2.5 million articles in 8 major subject areas. 

Contributing author

Bill Priedhorsky

References

Histories of arXiv and its impact can be found at:

1. Open Archives Initiative protocol development and implementation at arXiv. Warner, S. Expanded version of talk presented at Open Archives Initiative Open Meeting in Washington, DC, USA on 23 January 2001.
2. E-prints Intersect the Digital Library: Inside the Los Alamos arXiv. Luce, R. E. Issues in Science and Technology Librarianship, (Winter 2001).
3. Lessons from arXiv’s 30 years of information sharing. Ginsparg, P. Nature Reviews Physics 3 (2021): 602–603.

arXiv is a key data set for the science of scientific collaboration, as in:

4. Choosing Collaboration Partners. How Scientific Success in Physics Depends on Network Positions Heiberger, R. and O. Wieczorek. (2016). 

Computing and Algorithms

Progress in modeling complex systems requires both revolutionary algorithms and world-class computing power. Los Alamos has delivered both from the Manhattan project to today’s AI/ML breakthroughs.

Summary

The predictive modeling of complex systems for applications ranging from the nuclear deterrence to Earth systems to the Universe at its largest and smallest scales depends on efficient algorithms just as much as raw computing power. Los Alamos has led several algorithmic advances.

The Monte Carlo method, invented by Stanislaw Ulam, revolutionized the way complex systems involving neutrons are modeled. Today, LANL's MCNP (Monte Carlo N-Particle) and PARTISN (Parallel, Time-Dependent SN) codes are used globally for nuclear applications.

Groundbreaking techniques on early Lab computers solved fundamental fluid dynamics problems. Developed in the 1950s, Robert Richtmyer’s theory of shock instabilities and turbulence lies at the heart of modern simulations of systems such as inertial confinement fusion. Lagrangian and Arbitrary Lagrangian-Eulerian (ALE) techniques are essential to hydrodynamic modeling. Accelerated Molecular Dynamics was invented at Los Alamos to address materials processes at the atomic scale on time scales previously too long to model.

Contributing authors

Bill Priedhorsky and Mark Chadwick