Edmund R. Meyer

The unprecedented scale, speed, and scope of interconnectivity, ranging from the microsensors on the edge to the global networks, will be the prominent characteristics of the emerging computing environments. Our current cyber defense methods, designed for the computing environments we know, will be mainly rendered inadequate for these future environments. To meet the emerging cyber defense demands, we need a new approach. The poster presents our early work on the cognitive cyber concept, which attempts to meet some of these emerging challenges by promoting dynamic, adaptive, and largely autonomous defenses in dynamic networks and edge computing environments.

We present a study in the warm, dense matter regime of transport properties for a ternary mixture of the isotopes of hydrogen at 5 g/cm³ at temperatures between 50 and 400 eV as well as for a quaternary system with added carbon at 20 g/cm³ and 10 eV. We determine the properties from a series of orbital-free molecular dynamics simulations and calculate the diffusion coefficients in the Maxwell–Stefan (MS) formulation. The Darken approximation, which includes only time correlations between the same atom of the same species, gives reasonable agreement with the full MS results. However, we find that the reasons for this concurrence rest with more complex, and somewhat subtle, details within the MS prescription.

We have performed finite-temperature density functional theory molecular dynamics simulations on dense methane, ammonia, and water mixtures (CH₄:NH₃:H₂O) for various compositions and temperatures (2000 K ≤ T ≤ 10 000 K) that span a set of possible conditions in the interiors of ice-giant exoplanets. The equation-of-state, pair distribution functions, and bond autocorrelation functions (BACF) were used to probe the structure and dynamics of these complex fluids. In particular, an improvement to the choice of the cutoff in the BACF was developed that allowed analysis refinements for density and temperature effects. We note the relative changes in the nature of these systems engendered by variations in the concentration ratios. A basic tenet emerges from all these comparisons that varying the relative amounts of the three heavy components (C,N,O) can effect considerable changes in the nature of the fluid and may in turn have ramifications for the structure and composition of various planetary layers.

In the warm dense matter (WDM) regime, material properties like diffusion and viscosity can be obtained from lengthy quantum molecular dynamics simulations, where the quantum behavior of the electrons is represented using either Kohn-Sham or orbital-free density functional theory. To reduce the simulation duration, we fit the time dependence of the autocorrelation functions (ACFs) and then use the fit to find values of the diffusion and viscosity. This fitting procedure avoids noise in the long time behavior of the ACFs. We present a detailed analysis of the functional form used to fit the ACFs, which is always a more efficient means to obtain mass transport properties. We use the fits to estimate the statistical error of the transport properties. We apply this methodology to a dense correlated plasma of copper and a mixture of carbon and hydrogen. Both systems show structure in their ACFs and exhibit multiple time scales. The mixture contains different structural forms of the ACFs for each component in the mixture.

Toward a New Physics: The search for physics beyond the Standard Model is carried out at accelerator facilities such as the Large Hadron Collider but also on a smaller scale in atomic and molecular physics experiments. One of the signatures of this “new physics” would be a nonvanishing electric dipole moment of the electron, but experiments designed to look for it need to distinguish between the signal and many potential artifacts. Loh et al. (p. 1220 ) introduce a method based on the spectroscopy of polarized molecular ions that avoids some of the sources of systematic error.