The physics of angular momentum radio

Wireless communications, radio astronomy and other radio science applications are predominantly implemented with techniques built on top of the electromagnetic linear momentum (Poynting vector) physical layer. As a supplement and/or alternative to this conventional approach, techniques rooted in the electromagnetic angular momentum physical layer have been advocated, and promising results from proof-of-concept radio communication experiments using angular momentum were recently published. This sparingly exploited physical observable describes the rotational (spinning and orbiting) physical properties of the electromagnetic fields and the rotational dynamics of the pertinent charge and current densities. In order to facilitate the exploitation of angular momentum techniques in real-world implementations, we present a systematic, comprehensive theoretical review of the fundamental physical properties of electromagnetic angular momentum observable. Starting from an overview that puts it into its physical context among the other Poincar\'e invariants of the electromagnetic field, we describe the multi-mode quantized character and other physical properties that sets electromagnetic angular momentum apart from the electromagnetic linear momentum. These properties allow, among other things, a more flexible and efficient utilization of the radio frequency spectrum. Implementation aspects are discussed and illustrated by examples based on analytic and numerical solutions.Comment: Fixed LaTeX rendering errors due to inconsistencies between arXiv's LaTeX machine and texlive in OpenSuSE 13.

Angular and Polarization Response of Multimode Sensors with Resistive-Grid Absorbers

High sensitivity receiver systems with near ideal polarization sensitivity are highly desirable for development of millimeter and sub-millimeter radio astronomy. Multimoded bolometers provide a unique solution to achieve such sensitivity, for which hundreds of single-mode sensors would otherwise be required. The primary concern in employing such multimoded sensors for polarimetery is the control of the polarization systematics. In this paper, we examine the angular- and polarization- dependent absorption pattern of a thin resistive grid or membrane, which models an absorber used for a multimoded bolometer. The result shows that a freestanding thin resistive absorber with a surface resistivity of \eta/2, where \eta\ is the impedance of free space, attains a beam pattern with equal E- and H-plane responses, leading to zero cross polarization. For a resistive-grid absorber, the condition is met when a pair of grids is positioned orthogonal to each other and both have a resistivity of \eta/2. When a reflective backshort termination is employed to improve absorption efficiency, the cross-polar level can be suppressed below -30 dB if acceptance angle of the sensor is limited to <60degrees. The small cross-polar systematics have even-parity patterns and do not contaminate the measurements of odd-parity polarization patterns, for which many of recent instruments for cosmic microwave background are designed. Underlying symmetry that suppresses these cross-polar systematics is discussed in detail. The estimates and formalism provided in this paper offer key tools in the design consideration of the instruments using the multimoded polarimeters.Comment: 22 pages, 15 figure

Continuous-variable quantum neural networks

We introduce a general method for building neural networks on quantum computers. The quantum neural network is a variational quantum circuit built in the continuous-variable (CV) architecture, which encodes quantum information in continuous degrees of freedom such as the amplitudes of the electromagnetic field. This circuit contains a layered structure of continuously parameterized gates which is universal for CV quantum computation. Affine transformations and nonlinear activation functions, two key elements in neural networks, are enacted in the quantum network using Gaussian and non-Gaussian gates, respectively. The non-Gaussian gates provide both the nonlinearity and the universality of the model. Due to the structure of the CV model, the CV quantum neural network can encode highly nonlinear transformations while remaining completely unitary. We show how a classical network can be embedded into the quantum formalism and propose quantum versions of various specialized model such as convolutional, recurrent, and residual networks. Finally, we present numerous modeling experiments built with the Strawberry Fields software library. These experiments, including a classifier for fraud detection, a network which generates Tetris images, and a hybrid classical-quantum autoencoder, demonstrate the capability and adaptability of CV quantum neural networks

Analysis and Manipulation of Repetitive Structures of Varying Shape

Self-similarity and repetitions are ubiquitous in man-made and natural objects. Such structural regularities often relate to form, function, aesthetics, and design considerations. Discovering structural redundancies along with their dominant variations from 3D geometry not only allows us to better understand the underlying objects, but is also beneficial for several geometry processing tasks including compact representation, shape completion, and intuitive shape manipulation. To identify these repetitions, we present a novel detection algorithm based on analyzing a graph of surface features. We combine general feature detection schemes with a RANSAC-based randomized subgraph searching algorithm in order to reliably detect recurring patterns of locally unique structures. A subsequent segmentation step based on a simultaneous region growing is applied to verify that the actual data supports the patterns detected in the feature graphs. We introduce our graph based detection algorithm on the example of rigid repetitive structure detection. Then we extend the approach to allow more general deformations between the detected parts. We introduce subspace symmetries whereby we characterize similarity by requiring the set of repeating structures to form a low dimensional shape space. We discover these structures based on detecting linearly correlated correspondences among graphs of invariant features. The found symmetries along with the modeled variations are useful for a variety of applications including non-local and non-rigid denoising. Employing subspace symmetries for shape editing, we introduce a morphable part model for smart shape manipulation. The input geometry is converted to an assembly of deformable parts with appropriate boundary conditions. Our method uses self-similarities from a single model or corresponding parts of shape collections as training input and allows the user also to reassemble the identified parts in new configurations, thus exploiting both the discrete and continuous learned variations while ensuring appropriate boundary conditions across part boundaries. We obtain an interactive yet intuitive shape deformation framework producing realistic deformations on classes of objects that are difficult to edit using repetition-unaware deformation techniques

Intermittent search strategies

This review examines intermittent target search strategies, which combine phases of slow motion, allowing the searcher to detect the target, and phases of fast motion during which targets cannot be detected. We first show that intermittent search strategies are actually widely observed at various scales. At the macroscopic scale, this is for example the case of animals looking for food ; at the microscopic scale, intermittent transport patterns are involved in reaction pathway of DNA binding proteins as well as in intracellular transport. Second, we introduce generic stochastic models, which show that intermittent strategies are efficient strategies, which enable to minimize the search time. This suggests that the intrinsic efficiency of intermittent search strategies could justify their frequent observation in nature. Last, beyond these modeling aspects, we propose that intermittent strategies could be used also in a broader context to design and accelerate search processes.Comment: 72 pages, review articl

Partial and approximate symmetry detection for 3D geometry

"Symmetry is a complexity-reducing concept [...]; seek it every-where." - Alan J. Perlis Many natural and man-made objects exhibit significant symmetries or contain repeated substructures. This paper presents a new algorithm that processes geometric models and efficiently discovers and extracts a compact representation of their Euclidean symmetries. These symmetries can be partial, approximate, or both. The method is based on matching simple local shape signatures in pairs and using these matches to accumulate evidence for symmetries in an appropriate transformation space. A clustering stage extracts potential significant symmetries of the object, followed by a verification step. Based on a statistical sampling analysis, we provide theoretical guarantees on the success rate of our algorithm. The extracted symmetry graph representation captures important high-level information about the structure of a geometric model which in turn enables a large set of further processing operations, including shape compression, segmentation, consistent editing, symmetrization, indexing for retrieval, etc. Copyright &copy; 2006 by the Association for Computing Machinery, Inc

Geometric guides for interactive evolutionary design

This thesis describes the addition of novel Geometric Guides to a generative Computer-Aided Design (CAD) application that supports early-stage concept generation. The application generates and evolves abstract 3D shapes, used to inspire the form of new product concepts. It was previously a conventional Interactive Evolutionary system where users selected shapes from evolving populations. However, design industry users wanted more control over the shapes, for example by allowing the system to influence the proportions of evolving forms. The solution researched, developed, integrated and tested is a more cooperative human-machine system combining classic user interaction with innovative geometric analysis. In the literature review, different types of Interactive Evolutionary Computation (IEC), Pose Normalisation (PN), Shape Comparison, and Minimum-Volume Bounding Box approaches are compared, with some of these technologies identified as applicable for this research. Using its Application Programming Interface, add-ins for the Siemens NX CAD system have been developed and integrated with an existing Interactive Evolutionary CAD system. These add-ins allow users to create a Geometric Guide (GG) at the start of a shape exploration session. Before evolving shapes can be compared with the GG, they must be aligned and scaled (known as Pose Normalisation in the literature). Computationally-efficient PN has been achieved using geometric functions such as Bounding Box for translation and scaling, and Principle Axes for the orientation. A shape comparison algorithm has been developed that is based on the principle of non-intersecting volumes. This algorithm is also implemented with standard, readily available geometric functions, is conceptually simple, accessible to other researchers and also offers appropriate efficacy. Objective geometric testing showed that the PN and Shape Comparison methods developed are suitable for this guiding application and can be efficiently adapted to enhance an Interactive Evolutionary Design system. System performance with different population sizes was examined to indicate how best to use the new guiding capabilities to assist users in evolutionary shape searching. This was backed up by participant testing research into two user interaction strategies. A Large Background Population (LBP) approach where the GG is used to select a sub-set of shapes to show to the user was shown to be the most effective. The inclusion of Geometric Guides has taken the research from the existing aesthetic focused tool to a system capable of application to a wider range of engineering design problems. This system supports earlier design processes and ideation in conceptual design and allows a designer to experiment with ideas freely to interactively explore populations of evolving solutions. The design approach has been further improved, and expanded beyond the previous quite limited scope of form exploration

A figure of merit measuring picture resolution

Figure of merit measuring picture resolutio