Parametrized tests of post-Newtonian theory using Advanced LIGO and Einstein Telescope

General relativity has very specific predictions for the gravitational waveforms from inspiralling compact binaries obtained using the post-Newtonian (PN) approximation. We investigate the extent to which the measurement of the PN coefficients, possible with the second generation gravitational-wave detectors such as the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) and the third generation gravitational-wave detectors such as the Einstein Telescope (ET), could be used to test post-Newtonian theory and to put bounds on a subclass of parametrized-post-Einstein theories which differ from general relativity in a parametrized sense. We demonstrate this possibility by employing the best inspiralling waveform model for nonspinning compact binaries which is 3.5PN accurate in phase and 3PN in amplitude. Within the class of theories considered, Advanced LIGO can test the theory at 1.5PN and thus the leading tail term. Future observations of stellar mass black hole binaries by ET can test the consistency between the various PN coefficients in the gravitational-wave phasing over the mass range of 11-44M(circle dot). The choice of the lower frequency cutoff is important for testing post-Newtonian theory using the ET. The bias in the test arising from the assumption of nonspinning binaries is indicated.

Performance study of high operating temperature HgCdTe mid wave infrared detector through numerical modeling

The design of present generation uncooled Hg1-xCdxTe infrared photon detectors relies on complex heterostructures with a basic unit cell of type (n) under bar (+)/pi/(p) under bar (+). We present an analysis of double barrier (n) under bar (+)/pi/(p) under bar (+) mid wave infrared (x = 0.3) HgCdTe detector for near room temperature operation using numerical computations. The present work proposes an accurate and generalized methodology in terms of the device design, material properties, and operation temperature to study the effects of position dependence of carrier concentration, electrostatic potential, and generation-recombination (g-r) rates on detector performance. Position dependent profiles of electrostatic potential, carrier concentration, and g-r rates were simulated numerically. Performance of detector was studied as function of doping concentration of absorber and contact layers, width of both layers and minority carrier lifetime. Responsivity similar to 0.38 A W-1, noise current similar to 6 x 10(-14) A/Hz(1/2) and D* similar to 3.1 x 10(10)cm Hz(1/2) W-1 at 0.1 V reverse bias have been calculated using optimized values of doping concentration, absorber width and carrier lifetime. The suitability of the method has been illustrated by demonstrating the feasibility of achieving the optimum device performance by carefully selecting the device design and other parameters. (C) 2010 American Institute of Physics. doi:10.1063/1.3463379]

BER Analysis of Weighted Interference Cancellation in Multicarrier DS-CDMA Systems

In this paper, we present the design and bit error performance analysis of weighted linear parallel interference cancellers (LPIC) for multicarrier (MC) DS-CDMA systems. We propose an LPIC scheme where we estimate (and cancel) the multiple access interference (MAI) based on the soft outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation; these weights are so chosen to maximize the signal-to-interference ratios at the individual subcarrier outputs. For this weighted LPIC scheme, using an approach involving the characteristic function of the decision variable, we derive exact bit error rate (BER) expressions for different cancellation stages. Using the same approach, we also derive exact BER expressions for the matched filter (MF) and decorrelating detectors for the considered MC DS-CDMA system. We show that the proposed weighted LPIC scheme performs better than the MF detector and the conventional LPIC (where the weights are taken to be unity), and close to the decorrelating detector.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Performance

Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space-time block codes (STBC) from Cyclic Division Algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32x32 STBC from CDA, which employs 32 transmit antennas and sends 32(2) = 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16x16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

Ultrasonic wave characteristics of a monolayer graphene on silicon substrate

The present work deals with an ultrasonic type of wave propagation characteristics of monolayer graphene on silicon (Si) substrate. An atomistic model of a hybrid lattice involving a hexagonal lattice of graphene and surface atoms of diamond lattice of Si is developed to identify the carbon-silicon bond stiffness. Properties of this hybrid lattice model is then mapped into a nonlocal continuum framework. Equivalent force constant due to Si substrate is obtained by minimizing the total potential energy of the system. For this equilibrium configuration, the nonlocal governing equations are derived to analyze the ultrasonic wave dispersion based on spectral analysis. From the present analysis we show that the silicon substrate affects only the flexural wave mode. The frequency band gap of flexural mode is also significantly affected by this substrate. The results also show that, the silicon substrate adds cushioning effect to the graphene and it makes the graphene more stable. The analysis also show that the frequency bang gap relations of in-plane (longitudinal and lateral) and out-of-plane (flexural) wave modes depends not only on the y-direction wavenumber but also on nonlocal scaling parameter. In the nonlocal analysis, at higher values of the y-directional wavenumber, a decrease in the frequency band gap is observed for all the three fundamental wave modes in the graphene-silicon system. The atoms movement in the graphene due to the wave propagation are also captured for all the tree fundamental wave modes. The results presented in this work are qualitatively different from those obtained based on the local analysis and thus, are important for the development of graphene based nanodevices such as strain sensor, mass and pressure sensors, atomic dust detectors and enhancer of surface image resolution that make use of the ultrasonic wave dispersion properties of graphene. (C) 2011 Elsevier Ltd. All rights reserved.

Role of feedback in mammalian vision: a new hypothesis and a computational model

This paper presents a novel hypothesis on the function of massive feedback pathways in mammalian visual systems. We propose that the cortical feature detectors compete not for the right to represent the output at a point, but for exclusive rights to abstract and represent part of the underlying input. Feedback can do this very naturally. A computational model that implements the above idea for the problem of line detection is presented and based on that we suggest a functional role for the thalamo-cortical loop during perception of lines. We show that the model successfully tackles the so called Cross problem. Based on some recent experimental results, we discuss the biological plausibility of our model. We also comment on the relevance of our hypothesis (on the role of feedback) to general sensory information processing and recognition. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

GNSS Signal Detection Under Noise Uncertainty

High sensitivity detection techniques are required for indoor navigation using Global Navigation Satellite System (GNSS) receivers, and typically, a combination of coherent and non- coherent integration is used as the test statistic for detection. The coherent integration exploits the deterministic part of the signal and is limited due to the residual frequency error, navigation data bits and user dynamics, which are not known apriori. So, non- coherent integration, which involves squaring of the coherent integration output, is used to improve the detection sensitivity. Due to this squaring, it is robust against the artifacts introduced due to data bits and/or frequency error. However, it is susceptible to uncertainty in the noise variance, and this can lead to fundamental sensitivity limits in detecting weak signals. In this work, the performance of the conventional non-coherent integration-based GNSS signal detection is studied in the presence of noise uncertainty. It is shown that the performance of the current state of the art GNSS receivers is close to the theoretical SNR limit for reliable detection at moderate levels of noise uncertainty. Alternate robust post-coherent detectors are also analyzed, and are shown to alleviate the noise uncertainty problem. Monte-Carlo simulations are used to confirm the theoretical predictions.

Temperature profiles of accretion discs around rapidly rotating strange stars in general relativity: A comparison with neutron stars

We compute the temperature profiles of accretion discs around rapidly rotating strange stars, using constant gravitational mass equilibrium sequences of these objects, considering the full effect of general relativity. Beyond a certain critical value of stellar angular momentum (J), we observe the radius ( $r_{\rm orb}$) of the innermost stable circular orbit (ISCO) to increase with J (a property seen neither in rotating black holes nor in rotating neutron stars). The reason for this is traced to the crucial dependence of ${\rm d}r_{\rm orb}/{\rm d}J$ on the rate of change of the radial gradient of the Keplerian angular velocity at $r_{\rm orb}$ with respect to J. The structure parameters and temperature profiles obtained are compared with those of neutron stars, as an attempt to provide signatures for distinguishing between the two. We show that when the full gamut of strange star equation of state models, with varying degrees of stiffness are considered, there exists a substantial overlap in properties of both neutron stars and strange stars. However, applying accretion disc model constraints to rule out stiff strange star equation of state models, we notice that neutron stars and strange stars exclusively occupy certain parameter spaces. This result implies the possibility of distinguishing these objects from each other by sensitive observations through future X-ray detectors.

Development and studies on microstrip detector

We report development of gas microstrip detectors using thin film and lithography techniques. The detectors were tested for their performance for X-rays (5.9 keV) and a maximum gas gain of similar to 13,000 and best resolution of similar to 12% was obtained. Factors affecting gain and resolution were investigated. The detectors were tested for their one-dimensional position sensitivity. Meandering resistive strips were used for charge division method. A position resolution of 0.48 mm was obtained.

Carbon based materials for low temperature detection

Resistance temperature detectors (RTDs) are being widely used to detect low temperature, while thermocouples (TCs) are being used to detect high temperature. The materials suitable for RTDs are platinum, germanium, carbon, carbon-glass, cernox, etc. Here, we have reported the possible application of another form of carbon i.e. carbon nanotubes in low temperature thermometry. It has been shown the resistance R and the sensitivity of carbon nanotube bundles can be tuned and made suitable for ultralow temperature detection. We report on the R-T measurement of carbon nanotube bundles from room temperature down to 1 K to felicitate the possible application of bundles in low temperature RTDs. ©2008 American Institute of Physics

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Solution processed reduced graphene oxide ultraviolet detector

Electronic properties of graphene have been studied more extensively than its photonic applications, in spite of its exciting optical properties. Recent results on solar cells, light emitting diodes and photodetectors show its true potential in photonics and optoelectronics. Here, we have explored the use of reduced graphene oxide as a candidate for solution processed ultraviolet photodetectors. UV detection is demonstrated by reduced graphene oxide in terms of time resolved photocurrent as well as photoresponse. The responsivity of the detectors is found to be 0.12 A/W with an external quantum efficiency of 40%. (C) 2011 American Institute of Physics. [doi:10.1063/1.3640222]

Time-Resolved Resonance Raman Spectroscopy: Exploring Reactive Intermediates

The study of reaction mechanisms involves systematic investigations of the correlation between structure, reactivity, and time. The challenge is to be able to observe the chemical changes undergone by reactants as they change into products via one or several intermediates such as electronic excited states (singlet and triplet), radicals, radical ions, carbocations, carbanions, carbenes, nitrenes, nitrinium ions, etc. The vast array of intermediates and timescales means there is no single ``do-it-all'' technique. The simultaneous advances in contemporary time-resolved Raman spectroscopic techniques and computational methods have done much towards visualizing molecular fingerprint snapshots of the reactive intermediates in the microsecond to femtosecond time domain. Raman spectroscopy and its sensitive counterpart resonance Raman spectroscopy have been well proven as means for determining molecular structure, chemical bonding, reactivity, and dynamics of short-lived intermediates in solution phase and are advantageous in comparison to commonly used time-resolved absorption and emission spectroscopy. Today time-resolved Raman spectroscopy is a mature technique; its development owes much to the advent of pulsed tunable lasers, highly efficient spectrometers, and high speed, highly sensitive multichannel detectors able to collect a complete spectrum. This review article will provide a brief chronological development of the experimental setup and demonstrate how experimentalists have conquered numerous challenges to obtain background-free (removing fluorescence), intense, and highly spectrally resolved Raman spectra in the nanosecond to microsecond (ns-mu s) and picosecond (ps) time domains and, perhaps surprisingly, laid the foundations for new techniques such as spatially offset Raman spectroscopy.

3D Image Reconstruction From Truncated Helical Cone Beam Projection Data - A Linear Prediction Approach

With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.