Adding control to arbitrary unknown quantum operations

While quantum computers promise significant advantages, the complexity of quantum algorithms remains a major technological obstacle. We have developed and demonstrated an architecture-independent technique that simplifies adding control qubits to arbitrary quantum operations-a requirement in many quantum algorithms, simulations and metrology. The technique is independent of how the operation is done, does not require knowledge of what the operation is, and largely separates the problems of how to implement a quantum operation in the laboratory and how to add a control. We demonstrate an entanglement-based version in a photonic system, realizing a range of different two-qubit gates with high fidelity.Comment: 9 pages, 8 figure

Scalable laws for stable network congestion control

Discusses flow control in networks, in which sources control their rates based on feedback signals received from the network links, a feature present in current TCP protocols. We develop a congestion control system which is arbitrarily scalable, in the sense that its stability is maintained for arbitrary network topologies and arbitrary amounts of delay. Such a system can be implemented in a decentralized way with information currently available in networks plus a small amount of additional signaling

Two-dimensional Nanolithography Using Atom Interferometry

We propose a novel scheme for the lithography of arbitrary, two-dimensional nanostructures via matter-wave interference. The required quantum control is provided by a pi/2-pi-pi/2 atom interferometer with an integrated atom lens system. The lens system is developed such that it allows simultaneous control over atomic wave-packet spatial extent, trajectory, and phase signature. We demonstrate arbitrary pattern formations with two-dimensional 87Rb wavepackets through numerical simulations of the scheme in a practical parameter space. Prospects for experimental realizations of the lithography scheme are also discussed.Comment: 36 pages, 4 figure

Toward autonomous spacecraft

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented

Optimal Vaccine Allocation to Control Epidemic Outbreaks in Arbitrary Networks

We consider the problem of controlling the propagation of an epidemic outbreak in an arbitrary contact network by distributing vaccination resources throughout the network. We analyze a networked version of the Susceptible-Infected-Susceptible (SIS) epidemic model when individuals in the network present different levels of susceptibility to the epidemic. In this context, controlling the spread of an epidemic outbreak can be written as a spectral condition involving the eigenvalues of a matrix that depends on the network structure and the parameters of the model. We study the problem of finding the optimal distribution of vaccines throughout the network to control the spread of an epidemic outbreak. We propose a convex framework to find cost-optimal distribution of vaccination resources when different levels of vaccination are allowed. We also propose a greedy approach with quality guarantees for the case of all-or-nothing vaccination. We illustrate our approaches with numerical simulations in a real social network

Automatic visualization and control of arbitrary numerical simulations

Authors’ preprint version as submitted to ECCOMAS Congress 2016, Minisymposium 505 - Interactive Simulations in Computational Engineering. Abstract: Visualization of numerical simulation data has become a cornerstone for many industries and research areas today. There exists a large amount of software support, which is usually tied to specific problem domains or simulation platforms. However, numerical simulations have commonalities in the building blocks of their descriptions (e. g., dimensionality, range constraints, sample frequency). Instead of encoding these descriptions and their meaning into software architecures we propose to base their interpretation and evaluation on a data-centric model. This approach draws much inspiration from work of the IEEE Simulation Interoperability Standards Group as currently applied in distributed (military) training and simulation scenarios and seeks to extend those ideas. By using an extensible self-describing protocol format, simulation users as well as simulation-code providers would be able to express the meaning of their data even if no access to the underlying source code was available or if new and unforseen use cases emerge. A protocol definition will allow simulation-domain experts to describe constraints that can be used for automatically creating appropriate visualizations of simulation data and control interfaces. Potentially, this will enable leveraging innovations on both the simulation and visualization side of the problem continuum. We envision the design and development of algorithms and software tools for the automatic visualization of complex data from numerical simulations executed on a wide variety of platforms (e. g., remote HPC systems, local many-core or GPU-based systems). We also envisage using this automatically gathered information to control (or steer) the simulation while it is running, as well as providing the ability for fine-tuning representational aspects of the visualizations produced