10,243 research outputs found
Thermoelastic analysis of solar cell arrays and their material properties
Announced report discusses experimental test program in which five different solar cell array designs were evaluated by subjecting them to 60 thermal cycles from minus 190 deg to 0.0 deg. Results indicate that solder-coated cells combined with Kovar n-interconnectors and p-interconnectors are more durable under thermal loading than other configurations
Flip-chip bonded stacked patch antenna for monolithic microwave integrated circuits
This paper presents the design and simulation of a stacked patch antenna with a proximity coupled feed realized via a flip-chip bonding process. The antenna uses high and low dielectric constant materials and is compatible to Monolithic Microwave Integrated Circuits. The antenna achieves a bandwidth of 23.8% (VSWR < 2) centered at frequency of 13 GHz and has a gain of 5.3 dBi
Reduction of computer usage costs in predicting unsteady aerodynamic loadings caused by control surface motions: Computer program description
A digital computer program was developed to calculate unsteady loadings caused by motions of lifting surfaces with leading edge and trailing edge controls based on the subsonic kernel function approach. The pressure singularities at hinge line and side edges were extracted analytically as a preliminary step to solving the integral equation of collocation. The program calculates generalized aerodynamic forces for user supplied deflection modes. Optional intermediate output includes pressure at an array of points, and sectional generalized forces. From one to six controls on the half span can be accomodated
Frequency multiplication in high-energy electron beams Semiannual progress report, Oct. 1, 1966 - Apr. 1, 1967
Frequency multiplication in high energy electron beam
Vector coherent state representations, induced representations, and geometric quantization: I. Scalar coherent state representations
Coherent state theory is shown to reproduce three categories of
representations of the spectrum generating algebra for an algebraic model: (i)
classical realizations which are the starting point for geometric quantization;
(ii) induced unitary representations corresponding to prequantization; and
(iii) irreducible unitary representations obtained in geometric quantization by
choice of a polarization. These representations establish an intimate relation
between coherent state theory and geometric quantization in the context of
induced representations.Comment: 29 pages, part 1 of two papers, published versio
Preparation of Dicke States in an Ion Chain
We have investigated theoretically and experimentally a method for preparing
Dicke states in trapped atomic ions. We consider a linear chain of ion
qubits that is prepared in a particular Fock state of motion, . The
phonons are removed by applying a laser pulse globally to the qubits, and
converting the motional excitation to flipped spins. The global nature of
this pulse ensures that the flipped spins are shared by all the target ions
in a state that is a close approximation to the Dicke state \D{N}{m}. We
calculate numerically the fidelity limits of the protocol and find small
deviations from the ideal state for and . We have demonstrated
the basic features of this protocol by preparing the state \D{2}{1} in two
Mg target ions trapped simultaneously with an Al
ancillary ion.Comment: 5 pages, 2 figure
An exactly solvable model of a superconducting to rotational phase transition
We consider a many-fermion model which exhibits a transition from a
superconducting to a rotational phase with variation of a parameter in its
Hamiltonian. The model has analytical solutions in its two limits due to the
presence of dynamical symmetries. However, the symmetries are basically
incompatible with one another; no simple solution exists in intermediate
situations. Exact (numerical) solutions are possible and enable one to study
the behavior of competing but incompatible symmetries and the phase transitions
that result in a semirealistic situation. The results are remarkably simple and
shed light on the nature of phase transitions.Comment: 11 pages including 1 figur
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems
The majority of model-based learned image reconstruction methods in medical imaging have been limited to
uniform domains, such as pixelated images. If the underlying
model is solved on nonuniform meshes, arising from a finite
element method typical for nonlinear inverse problems, interpolation and embeddings are needed. To overcome this, we
present a flexible framework to extend model-based learning
directly to nonuniform meshes, by interpreting the mesh as a
graph and formulating our network architectures using graph
convolutional neural networks. This gives rise to the proposed
iterative Graph Convolutional Newton-type Method (GCNM),
which includes the forward model in the solution of the inverse
problem, while all updates are directly computed by the network
on the problem specific mesh. We present results for Electrical
Impedance Tomography, a severely ill-posed nonlinear inverse
problem that is frequently solved via optimization-based methods,
where the forward problem is solved by finite element methods.
Results for absolute EIT imaging are compared to standard
iterative methods as well as a graph residual network. We
show that the GCNM has strong generalizability to different
domain shapes and meshes, out of distribution data as well
as experimental data, from purely simulated training data and
without transfer training
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