MYSTIC: Michigan Young STar Imager at CHARA

We present the design for MYSTIC, the Michigan Young STar Imager at CHARA. MYSTIC will be a K-band, cryogenic, 6-beam combiner for the Georgia State University CHARA telescope array. The design follows the image-plane combination scheme of the MIRC instrument where single-mode fibers bring starlight into a non-redundant fringe pattern to feed a spectrograph. Beams will be injected in polarization-maintaining fibers outside the cryogenic dewar and then be transported through a vacuum feedthrough into the ~220K cold volume where combination is achieved and the light is dispersed. We will use a C-RED One camera (First Light Imaging) based on the eAPD SAPHIRA detector to allow for near-photon-counting performance. We also intend to support a 4-telescope mode using a leftover integrated optics component designed for the VLTI-GRAVITY experiment, allowing better sensitivity for the faintest targets. Our primary science driver motivation is to image disks around young stars in order to better understand planet formation and how forming planets might influence disk structures.Comment: Presented at the 2018 SPIE Astronomical Telescopes + Instrumentation, Austin, Texas, US

Programmable multiport optical circuits in opaque scattering materials

We propose and experimentally verify a method to program the effective transmission matrix of general multiport linear optical circuits in random multiple-scattering materials by phase modulation of incident wavefronts. We demonstrate the power of our method by programming linear optical circuits in white paint layers with 2 inputs and 2 outputs, and 2 inputs and 3 outputs. Using interferometric techniques we verify our ability to program any desired phase relation between the outputs. The method works in a deterministic manner and can be directly applied to existing wavefront-shaping setups without the need of measuring a transmission matrix or to rely on sensitive interference measurements.Comment: 14 pages, 7 figure

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Multi-View Video Packet Scheduling

In multiview applications, multiple cameras acquire the same scene from different viewpoints and generally produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this correlation during encoding and transmission of the multiview data. In this work, we propose a correlation-aware packet scheduling algorithm for multi-camera networks, where information from all cameras are transmitted over a bottleneck channel to clients that reconstruct the multiview images. The scheduling algorithm relies on a new rate-distortion model that captures the importance of each view in the scene reconstruction. We propose a problem formulation for the optimization of the packet scheduling policies, which adapt to variations in the scene content. Then, we design a low complexity scheduling algorithm based on a trellis search that selects the subset of candidate packets to be transmitted towards effective multiview reconstruction at clients. Extensive simulation results confirm the gain of our scheduling algorithm when inter-source correlation information is used in the scheduler, compared to scheduling policies with no information about the correlation or non-adaptive scheduling policies. We finally show that increasing the optimization horizon in the packet scheduling algorithm improves the transmission performance, especially in scenarios where the level of correlation rapidly varies with time

Comparison of fringe-tracking algorithms for single-mode near-infrared long-baseline interferometers

To enable optical long baseline interferometry toward faint objects, long integrations are necessary despite atmospheric turbulence. Fringe trackers are needed to stabilize the fringes and thus increase the fringe visibility and phase signal-to-noise ratio (SNR), with efficient controllers robust to instrumental vibrations, and to subsequent path fluctuations and flux drop-outs. We report on simulations, analysis and comparison of the performances of a classical integrator controller and of a Kalman controller, both optimized to track fringes under realistic observing conditions for different source magnitudes, disturbance conditions, and sampling frequencies. The key parameters of our simulations (instrument photometric performance, detection noise, turbulence and vibrations statistics) are based on typical observing conditions at the Very Large Telescope observatory and on the design of the GRAVITY instrument, a 4-telescope single-mode long baseline interferometer in the near-infrared, next in line to be installed at VLT Interferometer. We find that both controller performances follow a two-regime law with the star magnitude, a constant disturbance limited regime, and a diverging detector and photon noise limited regime. Moreover, we find that the Kalman controller is optimal in the high and medium SNR regime due to its predictive commands based on an accurate disturbance model. In the low SNR regime, the model is not accurate enough to be more robust than an integrator controller. Identifying the disturbances from high SNR measurements improves the Kalman performances in case of strong optical path difference disturbances.Comment: Accepted for publication in A&A. 17 pages 15 figure

Joint source channel coding for progressive image transmission

Recent wavelet-based image compression algorithms achieve best ever performances with fully embedded bit streams. However, those embedded bit streams are very sensitive to channel noise and protections from channel coding are necessary. Typical error correcting capability of channel codes varies according to different channel conditions. Thus, separate design leads to performance degradation relative to what could be achieved through joint design. In joint source-channel coding schemes, the choice of source coding parameters may vary over time and channel conditions. In this research, we proposed a general approach for the evaluation of such joint source-channel coding scheme. Instead of using the average peak signal to noise ratio (PSNR) or distortion as the performance metric, we represent the system performance by its average error-free source coding rate, which is further shown to be an equivalent metric in the optimization problems. The transmissions of embedded image bit streams over memory channels and binary symmetric channels (BSCs) are investigated in this dissertation. Mathematical models were obtained in closed-form by error sequence analysis (ESA). Not surprisingly, models for BSCs are just special cases for those of memory channels. It is also discovered that existing techniques for performance evaluation on memory channels are special cases of this new approach. We further extend the idea to the unequal error protection (UEP) of embedded images sources in BSCs. The optimization problems are completely defined and solved. Compared to the equal error protection (EEP) schemes, about 0.3 dB performance gain is achieved by UEP for typical BSCs. For some memory channel conditions, the performance improvements can be up to 3 dB. Transmission of embedded image bit streams in channels with feedback are also investigated based on the model for memory channels. Compared to the best possible performance achieved on feed forward transmission, feedback leads to about 1.7 dB performance improvement

Sparse Signal Processing Concepts for Efficient 5G System Design

As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces