Autonomous spacecraft maintenance study group

A plan to incorporate autonomous spacecraft maintenance (ASM) capabilities into Air Force spacecraft by 1989 is outlined. It includes the successful operation of the spacecraft without ground operator intervention for extended periods of time. Mechanisms, along with a fault tolerant data processing system (including a nonvolatile backup memory) and an autonomous navigation capability, are needed to replace the routine servicing that is presently performed by the ground system. The state of the art fault handling capabilities of various spacecraft and computers are described, and a set conceptual design requirements needed to achieve ASM is established. Implementations for near term technology development needed for an ASM proof of concept demonstration by 1985, and a research agenda addressing long range academic research for an advanced ASM system for 1990s are established

Projective Representations of the Inhomogeneous Hamilton Group: Noninertial Symmetry in Quantum Mechanics

Symmetries in quantum mechanics are realized by the projective representations of the Lie group as physical states are defined only up to a phase. A cornerstone theorem shows that these representations are equivalent to the unitary representations of the central extension of the group. The formulation of the inertial states of special relativistic quantum mechanics as the projective representations of the inhomogeneous Lorentz group, and its nonrelativistic limit in terms of the Galilei group, are fundamental examples. Interestingly, neither of these symmetries includes the Weyl-Heisenberg group; the hermitian representations of its algebra are the Heisenberg commutation relations that are a foundation of quantum mechanics. The Weyl-Heisenberg group is a one dimensional central extension of the abelian group and its unitary representations are therefore a particular projective representation of the abelian group of translations on phase space. A theorem involving the automorphism group shows that the maximal symmetry that leaves invariant the Heisenberg commutation relations are essentially projective representations of the inhomogeneous symplectic group. In the nonrelativistic domain, we must also have invariance of Newtonian time. This reduces the symmetry group to the inhomogeneous Hamilton group that is a local noninertial symmetry of Hamilton's equations. The projective representations of these groups are calculated using the Mackey theorems for the general case of a nonabelian normal subgroup

Equivalence theory for density estimation, Poisson processes and Gaussian white noise with drift

This paper establishes the global asymptotic equivalence between a Poisson process with variable intensity and white noise with drift under sharp smoothness conditions on the unknown function. This equivalence is also extended to density estimation models by Poissonization. The asymptotic equivalences are established by constructing explicit equivalence mappings. The impact of such asymptotic equivalence results is that an investigation in one of these nonparametric models automatically yields asymptotically analogous results in the other models.Comment: Published at http://dx.doi.org/10.1214/009053604000000012 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A balloon-borne 1 meter telescope for far-infrared astronomy

The flight of a balloon-borne one-meter telescope for infrared astronomy in the wavelength interval of 40 to 240 microns is discussed. The gyro-stabilized telescope mapped the intensity of the far infrared radiation from NGC 7538, Mars, the Orion Nebula, and W3 with a resolution of one minute and from selected regions of these sources with a resolution of 30 seconds. The infrared detection is described and its capabilities are analyzed. The instrumentation, orientation system, and modes of observation of the telescope are defined

Asymptotic Equivalence of Nonparametric Regression and White Noise

The principal result is that, under conditions, to any nonparametric regression problem there corresponds an asymptotically equivalent sequence of white noise with drift problems, and conversely. This asymptotic equivalence is in a global and uniform sense. Any normalized risk function attainable in one problem is asymptotically attainable in the other, with the difference in normalized risks converging to zero uniformly over the entire parameter space. The results are constructive. A recipe is provided for producing these asymptotically equivalent procedures. Some implications and generalizations of the principal result are also discussed

Information Inequality Bounds on the Minimax Risk (With an Application to Nonparametric Regression)

This paper compares three methods for producing lower bounds on the minimax risk under quadratic loss. The first uses the bounds from Brown and Gajek. The second method also uses the information inequality and results in bounds which are always at least as good as those from the first method. The third method is the hardest-linear-family method described by Donoho and Liu. These methods are applied in four examples, the last of which relates to a frequently considered problem in nonparametric regression

A Constrained Risk Inequality With Applications to Nonparametric Functional Estimation

A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lower bound for the risk at the point θ given an upper bound for the risk at the point 0. The inequality sheds new light on superefficient estimators in the normal location problem and also on an adaptive estimation problem arising in nonparametric functional estimation

Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the previous version v5

Corrections to deuterium hyperfine structure due to deuteron excitations

We consider the corrections to deuterium hyperfine structure originating from the two-photon exchange between electron and deuteron, with the deuteron excitations in the intermediate states. In particular, the motion of the two intermediate nucleons as a whole is taken into account. The problem is solved in the zero-range approximation. The result is in good agreement with the experimental value of the deuterium hyperfine splitting.Comment: 7 pages, LaTe