New Fields of investigation

Equations On The Mind

HRL’S COMPUTATIONAL PHYSICS TEAM maintains world-class expertise in computational electromagnetics, computational materials and device physics, nonlinear science, and quantum information science. The team develops unique theory and modeling capabilities that are used throughout the four laboratories at HRL, as well as new concepts and designs for hardware developed by experimental groups within HRL. Because one of the primary values of theory and modeling is determining the limits of the physically possible before resources are committed to experimental investigations, the Computational Physics team is also leveraged in the exploration of new scientific areas that may potentially impact HRL and our LLC Members.

BEYOND FASTSCAT™

At HRL, computational electromagnetics is a mature area where we possess commanding knowledge and experience in frequency domain algorithms and their implementation. Our FastScat™ code has demonstrated unprecedented speed and accuracy for the calculation of electromagnetic scattering. It is also being used to design a new class of antennas that employ a variable impedance surface to shape surface currents in order to create any desired radiation pattern, independent of the actual shape of the surface. These impedance surface antennas are becoming integral to various LLC Member applications. Looking to the future, HRL is developing a time domain electromagnetics code with algorithmic performance advantages similar to FastScat™. We anticipate that this code will become a cornerstone for applications within HRL and for our LLC Members and customers.

THE QUANTUM APPROACH

In computational materials and device physics, state-of-the-art codes developed at HRL are being extensively applied to design layered semiconductor materials and devices for spintronics (which use a quantum property of electrons) and quantum information processing applications. Devices capable of trapping single electrons and manipulating their quantum mechanical properties, such as spin, have formed the foundation of several intriguing concepts for quantum information processing.

As individual devices are pushed to higher performances and systems become increasingly complicated, their limitations become obvious. To circumvent these barriers, we use the nonlinear sciences of dynamical systems, complexity, and networks to either mitigate the nonlinearities or create novel solutions. These solutions include disruptive self-organization approaches to highpower lasers and millimeter wave sources, novel NanoElectro-Mechanical System (NEMS) functionality, models for biological systems, and systems-of-systems design.

developing technologies