Water resource problems of energy projects in the Colorado River Basin

The successful development of western coal and oil shale deposits is dependent, to a significant degree, on the availability of adequate water supplies. EQL is involved in a study of the aggregate effects of various energy activities in the upper Colorado River Basin on downstream water quantity and quality. These activities will tend to reduce the available water in the river, and could increase its salinity, which is already so high as to interfere with downstream domestic and agricultural use

Re-entrant magnetic field induced charge and spin gaps in the coupled dual-chain quasi-one dimensional organic conductor Perylene2_2[Pt(mnt)2_2]

An inductive method is used to follow the magnetic field-dependent susceptibility of the coupled charge density wave (CDW) and spin-Peierls (SP) ordered state behavior in the dual chain organic conductor Perylene$_2$[Pt(mnt)$_2$]. In addition to the coexisting SP-CDW state phase below 8 K and 20 T, the measurements show that a second spin-gapped phase appears above 20 T that coincides with a field-induced insulating phase. The results support a strong coupling of the CDW and SP order parameters even in high magnetic fields, and provide new insight into the nature of the magnetic susceptibility of dual-chain spin and charge systems.Comment: 6 pages, 6 figure

Modal expansions and non-perturbative quantum field theory in Minkowski space

We introduce a spectral approach to non-perturbative field theory within the periodic field formalism. As an example we calculate the real and imaginary parts of the propagator in 1+1 dimensional phi^4 theory, identifying both one-particle and multi-particle contributions. We discuss the computational limits of existing diagonalization algorithms and suggest new quasi-sparse eigenvector methods to handle very large Fock spaces and higher dimensional field theories.Comment: new material added, 12 pages, 6 figure

Transonic static and dynamic stability characteristics of a finned projectile configuration

Static and dynamic stability tests were made of a finned projectile configuration with the aft-mounted fins arranged in a cruciform pattern. The tests were made at free stream Mach numbers of 0.7, 0.9, 1.1, and 1.2 in the Langley 8-foot transonic pressure tunnel. Some of the parameters measured during the tests were lift, drag, pitching moment, pitch damping, and roll damping. Configurations tested included the body with undeflected fins, the body with various fin deflections for control, and the body with fins removed. Theoretical estimates of the stability derivatives were made for the fins on configuration

Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models

This paper extends our Real-Time Maude formalization of the semantics of flat Ptolemy II discrete-event (DE) models to hierarchical models, including modal models. This is a challenging task that requires combining synchronous fixed-point computations with hierarchical structure. The synthesis of a Real-Time Maude verification model from a Ptolemy II DE model, and the formal verification of the synthesized model in Real-Time Maude, have been integrated into Ptolemy II, enabling a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Efficient Cosmological Parameter Estimation with Hamiltonian Monte Carlo

Traditional Markov Chain Monte Carlo methods suffer from low acceptance rate, slow mixing and low efficiency in high dimensions. Hamiltonian Monte Carlo resolves this issue by avoiding the random walk. Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) technique built upon the basic principle of Hamiltonian mechanics. Hamiltonian dynamics allows the chain to move along trajectories of constant energy, taking large jumps in the parameter space with relatively inexpensive computations. This new technique improves the acceptance rate by a factor of 4 and boosts up the efficiency by at least a factor of D in a D-dimensional parameter space. Therefor shorter chains will be needed for a reliable parameter estimation comparing to a traditional MCMC chain yielding the same performance. Besides that, the HMC is well suited for sampling from non-Gaussian and curved distributions which are very hard to sample from using the traditional MCMC methods. The method is very simple to code and can be easily plugged into standard parameter estimation codes such as CosmoMC. In this paper we demonstrate how the HMC can be efficiently used in cosmological parameter estimation

Conjecturing-Based Computational Discovery of Patterns in Data

Modern machine learning methods are designed to exploit complex patterns in data regardless of their form, while not necessarily revealing them to the investigator. Here we demonstrate situations where modern machine learning methods are ill-equipped to reveal feature interaction effects and other nonlinear relationships. We propose the use of a conjecturing machine that generates feature relationships in the form of bounds for numerical features and boolean expressions for nominal features that are ignored by machine learning algorithms. The proposed framework is demonstrated for a classification problem with an interaction effect and a nonlinear regression problem. In both settings, true underlying relationships are revealed and generalization performance improves. The framework is then applied to patient-level data regarding COVID-19 outcomes to suggest possible risk factors.Comment: 25 pages, 6 figure

Low temperature structural phase transition and incommensurate lattice modulation in the spin gap compound BaCuSi2O6

Results of high resolution x-ray diffraction experiments are presented for single crystals of the spin gap compound BaCuSi$_2$O$_6$ in the temperature range from 16 to 300 K. The data show clear evidence of a transition from the room temperature tetragonal phase into an incommensurately modulated orthorhombic structure below $\sim$100 K. This lattice modulation is characterized by a resolution limited wave vector {\bf q}$_{IC}$=(0,$\sim$0.13,0) and its 2$^{nd}$ and 3$^{rd}$ harmonics. The phase transition is first order and exhibits considerable hysteresis. This observation implies that the spin Hamiltonian representing the system is more complex than originally thought.Comment: 4 pages, 4 figure