Dynamics of decoherence of an entangled pair of qubits locally connected to a one-dimensional disordered spin chain

We study the non-equilibrium evolution of concurrence of a Bell pair constituted of two qubits, through the measurement of Loschmidt echo (LE) under the scope of generalized central spin model. Having detected the Griffiths phase via derivative of LE in equilibrium, we show that in the non-equilibrium situation, the spin chain requires a temporal window to realize the effect of disorder. We show that within this timescale, LE falls off exponentially and this decay is maximally controlled by the initial states and coupling strength. Our detail investigation suggests that there actually exist three types of exponential decay, a Gaussian decay in ultra short time scale followed by two exponential decay in the intermediate time with two different decay exponents. The effect of the disorder starts appearing in the late time power law fall of LE where the power law exponent is strongly dependent on disorder strength and the final state but almost independent of initial states and coupling strength. This feature allows us to indicate the presence of Griffiths phase. To be precise, continuously varying critical exponent and wide distribution of relaxation time imprint their effect in LE in the late time limit where the power law fall is absent for quenching to a Griffiths phase. Here, LE vanishes following the fast exponential fall. Interestingly, for off-critical quenching LE attains a higher saturation value for increasing disorder strength, otherwise vanishes for a clean spin chain, referring to the fact that disorder prohibits the rapid decay of entanglement in long time limit. Moreover, we show that disorder is also able to destroy the light cone like nature of post quench quasi-particles as LE does not sense the singular time scales appearing for clean spin chain with qubits coupled at symmetric positions.Comment: 12 pages and 9 figure

Multilayered and Chemiresistive Thin and Thick Film Gas Sensors for Air Quality Monitoring

Selective detection of gases such as nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), and various volatile organic components (VOCs) is necessary for air quality monitoring. Detection of hydrogen (H2) is equally important as it is a flammable gas and poses serious threat of explosion when exposed to oxygen gas. We have studied the sensing characteristics of these gases using thin film deposited by chemical solution deposition as well as relatively thicker films deposited by atmospheric plasma spray (APS) process. The chapter starts with the sensing mechanism of chemiresistive sensors followed by the definition of gas sensing parameters. Subsequently, we have demonstrated selective NO2 sensing characteristics of zinc oxide-graphene (ZnO-G) multilayered thin film followed by CO and H2 sensing characteristics of ZnO thin film and SnO2 thick film. Cross-sensitivity among CO and H2 gases has been addressed through the analysis of conductance transients with the determination of activation energy, Ea, and heat of adsorption, Q. The concepts of reversible and irreversible sensing have also been discussed in relation to CO and H2 gases. CO2 sensing characteristics of LaFe0.8Co0.2O3 (LFCO)-ZnO thin film have been elucidated. Interference from CO has been addressed with principal component analyses and the ascertaining of Ea and Q values. Additionally, the variation of response with temperature for each gas was simulated to determine distinct parameters for the individual gases. Further, VOC sensing characteristics of copper oxide (CuO) thin film and WO3-SnO2 thick film were investigated. Principal component analysis was performed to discriminate the gases in CuO thin film. The interaction of WO3-SnO2 thick film with various VOCs was found to obey the Freundlich adsorption isotherm based on which Ea and Q values were determined

Diversity and Distribution of Archaea in the Mangrove Sediment of Sundarbans

Mangroves are among the most diverse and productive coastal ecosystems in the tropical and subtropical regions. Environmental conditions particular to this biome make mangroves hotspots for microbial diversity, and the resident microbial communities play essential roles in maintenance of the ecosystem. Recently, there has been increasing interest to understand the composition and contribution of microorganisms in mangroves. In the present study, we have analyzed the diversity and distribution of archaea in the tropical mangrove sediments of Sundarbans using 16S rRNA gene amplicon sequencing. The extraction of DNA from sediment samples and the direct application of 16S rRNA gene amplicon sequencing resulted in approximately 142 Mb of data from three distinct mangrove areas (Godkhali, Bonnie camp, and Dhulibhashani). The taxonomic analysis revealed the dominance of phyla Euryarchaeota and Thaumarchaeota (Marine Group I) within our dataset. The distribution of different archaeal taxa and respective statistical analysis (SIMPER, NMDS) revealed a clear community shift along the sampling stations. The sampling stations (Godkhali and Bonnie camp) with history of higher hydrocarbon/oil pollution showed different archaeal community pattern (dominated by haloarchaea) compared to station (Dhulibhashani) with nearly pristine environment (dominated by methanogens). It is indicated that sediment archaeal community patterns were influenced by environmental conditions

ASAP: A Transistor Sizing Tool for Speed, Area, and Power Optimization of Static CMOS Circuits

This paper introduces an automated transistor sizing tool (ASAP) that incorporates accurate gatelevel functio~nalm odels and can be used for delay, area, and power optimization of CMOS combinational logic circuits in a VLSI design environment. ASAP considers the performailce improvement of VLSI CMOS circuits by optimally sizing the transistors on the first N critical paths. The global picture of the circuit is considered by taking into account the effects that the transi.stor size changes of one path have on the others. The optimization technique in our sizing tool is based on simulated annealing and couples accurate delay modeling with power and area optimization. The combinatorial minimization of the objective function relies on analytical models that can accurately evaluate the delay, the power and the area of a gate. ASAP has been implemented in C on an Apollo 400 workstation with encouraging results

Performance and Wirability Driven Layout for Row-Based FPGAs

In FPGAs the routing resources are fixed and their usage is constrained by the location of antifuses. In addition, the antifuses affect the layout performance significantly, depending on the technology. Hence, simplistic placement level assumptions turn out to be grossly inadequate in predicting the timing and wirability behavior of a layout. There is a need, therefore, for a layout technique which changes the layout at placement level based on accurate post-layout timing analysis and net wirability. In this paper we consider such a wirability and performance driven layout flow for row-based FPGAs. Timing information from a post-layout timing analyzer and wirability information from global and channel routers are used by an incremental placer to effectively perturb the placement. A large improvement (up to 29%) in timing, has been obtained (compared to non-iterative FPGA layout) for a set of industrial designs and benchmark examples

Wireless e-jacket for multiparameter biophysical monitoring and telemedicine applications

A widespread requirement exists for a low cost and reliable health monitor in the clinical as well as home environment. The e-jacket presented here is an example of a smart clothing system with multiple bioparameter acquisition of electrocardiogram (ECG), pulse oximetry, body motion/tilt and skin temperature. The battery operated circuit has an integrated graphic liquid crystal display (LCD) screen and a 2.4 GHz wireless link. An RS232 interface provides a plug-in port for easy accessibility to remote telemedicine applications. The system incorporates an efficient ARM7 microcontroller to coordinate a list of software tasks with associated time stamp. Comfort analysis and reliability aspects have been carefully studied along with intelligent power conservation schemes. A low cost and reliable tele-medical network is proposed using an innovative e-textile solution.© IEE

Artificial neural networks in prediction of mechanical behavior of concrete at high temperature

The behavior of concrete structures that are exposed to extreme thermo-mechanical loading is an issue of great importance in nuclear engineering. The mechanical behavior of concrete at high temperature is non-linear. The properties that regulate its response are highly temperature dependent and extremely complex. In addition, the constituent materials, e.g. aggregates, influence the response significantly. Attempts have been made to trace the stress–strain curve through mathematical models and rheological models. However, it has been difficult to include all the contributing factors in the mathematical model. This paper examines a new programming paradigm, artificial neural networks, for the problem. Implementing a feedforward network and backpropagation algorithm the stress–strain relationship of the material is captured. The neural networks for the prediction of uniaxial behavior of concrete at high temperature has been presented here. The results of the present investigation are very encouraging.© Elsevie

Performance-Driven Simultaneous Placement and Routing for FPGA’s

Sequential place and route tools for FPGAs are inherently weak at addressing both wirability and timing optimizations. This is primarily due to the difficulty of accurately predicting wirability and delay during placement. A new performance-driven simultaneous placement / routing technique has been developed for island-style FPGA designs. On a set of industrial designs for Xilinx 4000-series FPGAs, our scheme produces 100 % routed designs with 8%-15 % improvement in delay when compared to the Xilinx XACT5.0 place and route system.

To Dope Mn2+ in a Semiconducting Nanocrystal

It has been an outstanding problem that a semiconducting host in the bulk form can be doped to a large extent, while the same host in the nanocrystal form is found to resist any appreciable level of doping rather stubbornly, this problem being more acute in the wurtzite form compared to the zinc blende one. In contrast, our results based on the lattice parameter tuning in a ZnxCd1−xS alloy nanocrystal system achieves 7.5% Mn2+ doping in a wurtzite nanocrystal, such a concentration being substantially higher compared to earlier reports even for nanocrystal hosts with the “favorable” zinc-blende structure. These results prove a consequence of local strains due to a size mismatch between the dopant and the host that can be avoided by optimizing the composition of the alloyed host. Additionally, the present approach opens up a new route to dope such nanocrystals to a macroscopic extent as required for many applications. Photophysical studies show that the quantum efficiency per Mn2+ ion decreases exponentially with the average number of Mn2+ ions per nanocrystal; en route, a high quantum efficiency of 25% is achieved for a range of compositions

3D Printed Sensors for Biomedical Applications: A Review

This paper showcases a substantial review on some of the significant work done on 3D printing of sensors for biomedical applications. The importance of 3D printing techniques has bloomed in the sensing world due to their essential advantages of quick fabrication, easy accessibility, processing of varied materials and sustainability. Along with the introduction of the necessity and influence of 3D printing techniques for the fabrication of sensors for different healthcare applications, the paper explains the individual methodologies used to develop sensing prototypes. Six different 3D printing techniques have been explained in the manuscript, followed by drawing a comparison between them in terms of their advantages, disadvantages, materials being processed, resolution, repeatability, accuracy and applications. Finally, a conclusion of the paper is provided with some of the challenges of the current 3D printing techniques about the developed sensing prototypes, their corresponding remedial solutions and a market survey determining the expenditure on 3D printing for biomedical sensing prototypes