Maneuvering strategies using CMGs

This paper considers control strategies for maneuvering spacecraft using Single-Gimbal Control Momentum Gyros (CMGs). A pyramid configuration using four gyros is utilized. Preferred initial gimbal angles for maximum utilization of CMG momentum are obtained for some known torque commands. Feedback control laws are derived from the stability point of view by using the Liapunov's Second Theorem. The gyro rates are obtained by the pseudo-inverse technique. The effect of gimbal rate bounds on controllability are studied for an example maneuver. Singularity avoidance is based on limiting the gyro rates depending on a singularity index

Hadronic B Decays to Charmless VT Final States

Charmless hadronic decays of B mesons to a vector meson (V) and a tensor meson (T) are analyzed in the frameworks of both flavor SU(3) symmetry and generalized factorization. We also make comments on B decays to two tensor mesons in the final states. Certain ways to test validity of the generalized factorization are proposed, using $B \to VT$ decays. We calculate the branching ratios and CP asymmetries using the full effective Hamiltonian including all the penguin operators and the form factors obtained in the non-relativistic quark model of Isgur, Scora, Grinstein and Wise.Comment: 27 pages, no figures, LaTe

Recent Neutrino Data and Type III Seesaw with Discrete Symmetry

In light of the recent neutrino experiment results from Daya Bay and RENO Collaborations, we study phenomenology of neutrino mixing angles in the Type III seesaw model with an discrete $A_4 \times Z_2$ symmetry, whose spontaneously breaking scale is much higher than the electroweak scale. At tree level, the tri-bimaximal (TBM) form of the lepton mixing matrix can be obtained from leptonic Yukawa interactions in a natural way. We introduce all possible effective dimension-5 operators, invariant under the Standard Model gauge group and $A_4 \times Z_2$, and explicitly show that they induce a deviation of the lepton mixing from the TBM mixing matrix, which can explain a large mixing angle $\theta_{13}$ together with small deviations of the solar and atmospheric mixing angles from the TBM. Two possible scenarios are investigated, by taking into account either negligible or sizable contributions from the light charged lepton sector to the lepton mixing matrix. Especially it is found in the latter scenario that all the neutrino experimental data, including the recent best-fit value of $\theta_{13} = 8.68^{\circ}$, can be accommodated. The leptonic CP violation characterized by the Jarlskog invariant $J_{CP}$ has a non-vanishing value, indicating a signal of maximal CP violation.Comment: 28 pages, 7 figures and references are adde

Prediction of airfoil stall using Navier-Stokes equations in streamline coordinates

A Navier-Stokes procedure to calculate the flow about an airfoil at incidence was developed. The parabolized equations are solved in the streamline coordinates generated for an arbitrary airfoil shape using conformal mapping. A modified k-epsilon turbulence model is applied in the entire domain, but the eddy viscosity in the laminar region is suppressed artificially to simulate the region correctly. The procedure was applied to airfoils at various angles of attack, and the results are quite satisfactory for both laminar and turbulent flows. It is shown that the present choice of the coordinate system reduces the error due to numerical diffusion, and that the lift is accurately predicted for a wide range of incidence

Higher and missing resonances in omega photoproduction

We study the role of the nucleon resonances ($N^*$) in $\omega$ photoproduction by using the quark model resonance parameters predicted by Capstick and Roberts. The employed $\gamma N \to N^*$ and $N^* \to \omega N$ amplitudes include the configuration mixing effects due to the residual quark-quark interactions. The contributions from the nucleon resonances are found to be important in the differential cross sections at large scattering angles and various spin observables. In particular, the parity asymmetry and beam-target double asymmetry at forward scattering angles are suggested for a crucial test of our predictions. The dominant contributions are found to be from $N\frac32^+ (1910)$, a missing resonance, and $N\frac32^- (1960)$ which is identified as the $D_{13}(2080)$ of the Particle Data Group.Comment: 8 pages, LaTeX with ws-p8-50x6-00.cls, 4 figures (5 eps files), Talk presented at the NSTAR2001 Workshop on the Physics of Excited Nucleons, Mainz, Germany, Mar. 7-10, 200

Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks

Deep networks consume a large amount of memory by their nature. A natural question arises can we reduce that memory requirement whilst maintaining performance. In particular, in this work we address the problem of memory efficient learning for multiple tasks. To this end, we propose a novel network architecture producing multiple networks of different configurations, termed deep virtual networks (DVNs), for different tasks. Each DVN is specialized for a single task and structured hierarchically. The hierarchical structure, which contains multiple levels of hierarchy corresponding to different numbers of parameters, enables multiple inference for different memory budgets. The building block of a deep virtual network is based on a disjoint collection of parameters of a network, which we call a unit. The lowest level of hierarchy in a deep virtual network is a unit, and higher levels of hierarchy contain lower levels' units and other additional units. Given a budget on the number of parameters, a different level of a deep virtual network can be chosen to perform the task. A unit can be shared by different DVNs, allowing multiple DVNs in a single network. In addition, shared units provide assistance to the target task with additional knowledge learned from another tasks. This cooperative configuration of DVNs makes it possible to handle different tasks in a memory-aware manner. Our experiments show that the proposed method outperforms existing approaches for multiple tasks. Notably, ours is more efficient than others as it allows memory-aware inference for all tasks.Comment: CVPR 201