As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers. While currently available quantum computers have less than 100 qubits, quantum computing hardware is widely expected to grow in terms of qubit count, quality, and connectivity. This review aims at explaining the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional. We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succinct and self-contained fashion. We show how these algorithms can be implemented on IBM’s quantum computer, and in each case, we discuss the results of the implementation with respect to differences between the simulator and the actual hardware runs. This article introduces computer scientists, physicists, and engineers to quantum algorithms and provides a blueprint for their implementations.

The goal of this work is to develop a new autonomous capability for remotely deploying precisely located sensor nodes without damaging the sensor nodes in the process. Over the course of the last decade there has been significant interest in research to deploy sensor networks. This research is driven by the fact that the costs associated with installing sensor networks can be very high. In order to rapidly deploy sensor networks consisting of large numbers of sensor nodes, alternative techniques must be developed to place the sensor nodes in the field.

The goal of this work is to develop a new autonomous capability for remotely deploying precisely located sensor nodes without damaging the sensor nodes in the process. Over the course of the last decade there has been significant interest in research to deploy sensor networks. This research is driven by the fact that the costs associated with installing sensor networks can be very high. In order to rapidly deploy sensor networks consisting of large numbers of sensor nodes, alternative techniques must be developed to place the sensor nodes in the field.

For the last 20 years the goal of the structural health monitoring community has been to endow man-made structures with a biologically-inspired nervous system in order to detect, localize, and quantify damage in structures. The effort has focused on collecting a wide array of measurements from sensor networks, extracting features from the data, comparing the data to models, and trying to use this information to determine the presence, extent and type of damage. Typically the Structural Health Monitoring community tries to make predictions of the remaining service life of the structure. It is generally assumed that there will be as little human intervention in this process as possible unless a high-consequence decision must be made. A number of advances have been made in structural health monitoring using this approach over the course of the last decade, but we are still struggling to build autonomous machines that can match the ability of a human to detect, localize and quantify damage in structures. This work aims to explore a new paradigm - cooperative human-machine structural health monitoring. The premise of this paradigm is the idea that a human cooperating with a machine will always significantly outperform a machine or human acting independently. There is no reason to not make full use of human resources that are available to us today. Furthermore, the regulatory and litigious environments that exist today for safety-critical structures are going to make it difficult to adopt health monitoring systems that effectively eliminate humans. Why not instead enhance the natural sensing and perception of human inspectors? During the course of this research effort a vibro-tactile haptic interface is under development that will in some sense allow a human to “feel” the pain of a structure when it is damaged. A number of different studies from the neuroscience community [1], [2], have indicated that it is possible to use “sensory substitution” to provide some restoration for lost senses such as sight. In this work we consider the possibility of extending the introception of a human to an external structure. This type of capability will help enable a wide variety of cyber-physical systems that must maintain reliability as well as interact with humans. For instance it may be possible to outfit a single human inspector with a haptic interface so they can single-handedly monitor a whole wind farm as if it were a natural extension of their own body. Alternatively, a single person with a haptic interface may be able to sense the state-of-health of a large ocean linear or an entire swarm of flying robots. These ideas will lead to creating a new class of high-performance, cyber-physical systems.