Quantum Coherence, Coherent Information and Information Gain in Quantum Measurement

A measurement is deemed successful, if one can maximize the information gain by the measurement apparatus. Here, we ask if quantum coherence of the system imposes a limitation on the information gain during quantum measurement. First, we argue that the information gain in a quantum measurement is nothing but the coherent information or the distinct quantum information that one can send from the system to apparatus. We prove that the maximum information gain from a pure state, using a mixed apparatus is upper bounded by the initial coherence of the system. Further, we illustrate the measurement scenario in the presence of environment. We argue that the information gain is upper bounded by the entropy exchange between the system and the apparatus. Also, to maximize the information gain, both the initial coherence of the apparatus, and the final entanglement between the system and apparatus should be maximum. Moreover, we find that for a fixed amount of coherence in the final apparatus state the more robust apparatus is, the more will be the information gain.Comment: 6 Pages, Comments are welcom

Calibration for measurements of droplet size distributions of ground based clouds - a laboratory investigation

Water droplets of varying sizes, released through an atomizer, were collected on glass slides coated with uniform layers of magnesium oxide or carbon soot and silicone oil. Assuming that the droplets retain their original shapes in the oil film, calibrations were obtained for their spreading on oxide and soot layers of known thickness. The calibrations have been further applied to evaluate droplet size distributions of ground-based clouds

A relativistic model for Strange Quark Star

We propose a spherically symmetric and anisotropic model for strange quark stars within the framework of MIT Bag model. Though the model is found to comply with all the physical requirements of a realistic star satisfying a strange matter equation of state (EOS), the estimated values the Bag constant for different strange star candidates like Her X-1, SAX J 1808.4-3658 and 4U 1820-30, clearly indicate that the Bag constant need not necessarily lie within the range of 60-80 MeV fm$^{-3}$ as claimed in the literature.Comment: 12 pages, 6 figures. Major revision has been don

Application of artificial neural networks to weighted interval Kalman filtering

The interval Kalman filter is a variant of the traditional Kalman filter for systems with bounded parametric uncertainty. For such systems, modelled in terms of intervals, the interval Kalman filter provides estimates of the system state also in the form of intervals, guaranteed to contain the Kalman filter estimates of all point-valued systems contained in the interval model. However, for practical purposes, a single, point-valued estimate of the system state is often required. This point value can be seen as a weighted average of the interval bounds provided by the interval Kalman filter. This article proposes a methodology based on the application of artificial neural networks by which an adequate weight can be computed at each time step, whereby the weighted average of the interval bounds approximates the optimal estimate or estimate which would be obtained using a Kalman filter if no parametric uncertainty was present in the system model, even when this is not the case. The practical applicability and robustness of the method are demonstrated through its application to the navigation of an uninhabited surface vehicle. © IMechE 2014

An Alternative Method to Niskin Sampling for Molecular Analysis of the Marine Environment

The development of low-cost, open-source Remotely Operated Vehicle (ROV) systems has provided almost unrestricted access for researchers looking to monitor the marine environment in ever greater resolution. Sampling microbial communities from the marine environment, however, still usually relies on Niskin-bottle sampling (ROV or Conductivity-Temperature-Depth sampler (CTD) based), a method which introduces an inaccuracy and variability that is incompatible with metatranscriptomic analysis, for example. Here, we describe a versatile, easily-replicated platform which achieves in situ mRNA preservation, via the addition of RNAlater to filtered microbial cells, to enhance ROV or CTD functionality

Non-linear control algorithms for an unmanned surface vehicle

Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design. © 2014 IMechE

Subsea cable tracking in an uncertain environment using particle filters

Localization of subsea cables is a demanding and challenging task. Among the few methods reported in the literature, magnetic field detection is the most promising one, as the cable does not require to be seen visually. Magnetic noise and a quick attenuation of the magnetic field propagating in sea water often make available methods unreliable. The authors propose a novel method of using particle filters for estimating the position of a subsea cable in a highly uncertain environment. The method was tested on data collected from a buried cable in the Baltic Sea, Denmark and shown to have a close approximation to the true location of the subsea cable. The method can be used to localize a subsea cable in an offshore noisy and uncertain environment and provides an inexpensive alternative to the use of a diver or a remotely operated platform