Looking for an invisible Higgs signal at the LHC

While the recent discovery of a Higgs-like boson at the LHC is an extremely important and encouraging step towards the discovery of the complete Standard Model (SM), the current information on this state does not rule out possibility of beyond standard model (BSM) physics. In fact the current data can still accommodate reasonably large values of the branching fractions of the Higgs into a channel with `invisible' decay products, such a channel being also well motivated theoretically. In this study we revisit the possibility of detecting the Higgs in this invisible channel for both choices of the LHC energies, 8 and 14 TeV, for two production modes; vector boson fusion (VBF) and associated production (ZH). We perform a comprehensive collider analysis for all the above channels and project the reach of LHC to constrain the invisible decay branching fraction for both 8 and 14 TeV energies. For the ZH case we consider decays of the Z boson into a pair of leptons as well as a b (b) over bar pair. For the VBF channel the sensitivity is found to be more than 5 sigma for both the energies up to an invisible branching ratio (Br-inv) similar to 0.80, with luminosities similar to 20/30 fb(-1). The sensitivity is further extended to values of Br-inv similar to 0.25 for 300 fb(-1) at 14 TeV. However the reach is found to be more modest for the ZH mode with leptonic final state; with about 3.5 sigma for the planned luminosity at 8 TeV, reaching 8 sigma only for 14 TeV for 50 fb(-1). In spite of the much larger branching ratio (BR) of the Z into a b (b) over bar channel compared to the dilepton case, the former channel, can provide useful reach up to Br-inv greater than or similar to 0.75, only for the higher luminosity (300 fb(-1)) option using both jet-substructure and jet clustering methods. (C) 2013 Elsevier B.V. All rights reserved.

Photoacoustic and thermoacoustic signal characteristics study

Photoacoustic/thermoacoustic imaging is an emerging hybrid imaging modality combining optical/microwave imaging with ultrasound imaging. The photoacoustic/thermoacoustic signal generated are affected by the nature of excitation pulse waveform, pulse width, target object size, transducer size etc. In this study k-wave was used to simulate various configurations of excitation pulse, transducer types, and target object sizes and to see their effect on the photoacoustic/thermoacoustic signals. Numerical blood vessel phantom was also used to see the effect of various pulse waveform and excitation pulse width on the reconstructed images. This study will help in optimizing transducer design and reconstruction methods to obtain the superior reconstructed image.

Wide Voltage Input Receiver with Hysteresis Characteristic to Reduce Input Signal Noise Effect

In this paper, an input receiver with a hysteresis characteristic that can work at voltage levels between 0.9 V and 5 V is proposed. The input receiver can be used as a wide voltage range Schmitt trigger also. At the same time, reliable circuit operation is ensured. According to the research findings, this is the first time a wide voltage range Schmitt trigger is being reported. The proposed circuit is compared with previously reported input receivers, and it is shown that the circuit has better noise immunity. The proposed input receiver ends the need for a separate Schmitt trigger and input buffer. The frequency of operation is also higher than that of the previously reported receiver. The circuit is simulated using HSPICE at 035-mu m standard thin oxide technology. Monte Carlo analysis is conducted at different process conditions, showing that the proposed circuit works well for different process conditions at different voltage levels of operation. A noise impulse of (V-CC/2) magnitude is added to the input voltage to show that the receiver receives the correct logic level even in the presence of noise. Here, V-CC is the fixed voltage supply of 3.3 V.

On Computing Amplitude, Phase, and Frequency Modulations Using a Vector Interpretation of the Analytic Signal

The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.

Noncoherent Integration for Signal Detection: Analysis Under Model Uncertainties

The performance of postdetection integration (PDI) techniques for the detection of Global Navigation Satellite Systems (GNSS) signals in the presence of uncertainties in frequency offsets, noise variance, and unknown data-bits is studied. It is shown that the conventional PDI techniques are generally not robust to uncertainty in the data-bits and/or the noise variance. Two new modified PDI techniques are proposed, and they are shown to be robust to these uncertainties. The receiver operating characteristics (ROC) and sample complexity performance of the PDI techniques in the presence of model uncertainties are analytically derived. It is shown that the proposed methods significantly outperform existing methods, and hence they could become increasingly important as the GNSS receivers attempt to push the envelope on the minimum signal-to-noise ratio (SNR) for reliable detection.

High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio

Four-dimensional fluorescence microscopy-which records 3D image information as a function of time-provides an unbiased way of tracking dynamic behavior of subcellular components in living samples and capturing key events in complex macromolecular processes. Unfortunately, the combination of phototoxicity and photobleaching can severely limit the density or duration of sampling, thereby limiting the biological information that can be obtained. Although widefield microscopy provides a very light-efficient way of imaging, obtaining high-quality reconstructions requires deconvolution to remove optical aberrations. Unfortunately, most deconvolution methods perform very poorly at low signal-to-noise ratios, thereby requiring moderate photon doses to obtain acceptable resolution. We present a unique deconvolution method that combines an entropy-based regularization function with kernels that can exploit general spatial characteristics of the fluorescence image to push the required dose to extreme low levels, resulting in an enabling technology for high-resolution in vivo biological imaging.

Signal Detection in Generalized Gaussian Noise by Nonlinear Wavelet Denoising

In this paper, a nonlinear suboptimal detector whose performance in heavy-tailed noise is significantly better than that of the matched filter is proposed. The detector consists of a nonlinear wavelet denoising filter to enhance the signal-to-noise ratio, followed by a replica correlator. Performance of the detector is investigated through an asymptotic theoretical analysis as well as Monte Carlo simulations. The proposed detector offers the following advantages over the optimal (in the Neyman-Pearson sense) detector: it is easier to implement, and it is more robust with respect to error in modeling the probability distribution of noise.

Fractional Hilbert transform extensions and associated analytic signal construction

The analytic signal (AS) was proposed by Gabor as a complex signal corresponding to a given real signal. The AS has a one-sided spectrum and gives rise to meaningful spectral averages. The Hilbert transform (HT) is a key component in Gabor's AS construction. We generalize the construction methodology by employing the fractional Hilbert transform (FrHT), without going through the standard fractional Fourier transform (FrFT) route. We discuss some properties of the fractional Hilbert operator and show how decomposition of the operator in terms of the identity and the standard Hilbert operators enables the construction of a family of analytic signals. We show that these analytic signals also satisfy Bedrosian-type properties and that their time-frequency localization properties are unaltered. We also propose a generalized-phase AS (GPAS) using a generalized-phase Hilbert transform (GPHT). We show that the GPHT shares many properties of the FrHT, in particular, selective highlighting of singularities, and a connection with Lie groups. We also investigate the duality between analyticity and causality concepts to arrive at a representation of causal signals in terms of the FrHT and GPHT. On the application front, we develop a secure multi-key single-sideband (SSB) modulation scheme and analyze its performance in noise and sensitivity to security key perturbations. (C) 2013 Elsevier B.V. All rights reserved.

Low-complexity near-optimal signal detection in underdetermined large-MIMO systems

In this paper, we consider signal detection in nt × nr underdetermined MIMO (UD-MIMO) systems, where i) nt >; nr with a overload factor α = nt over nr >; 1, ii) nt symbols are transmitted per channel use through spatial multiplexing, and iii) nt, nr are large (in the range of tens). A low-complexity detection algorithm based on reactive tabu search is considered. A variable threshold based stopping criterion is proposed which offers near-optimal performance in large UD-MIMO systems at low complexities. A lower bound on the maximum likelihood (ML) bit error performance of large UD-MIMO systems is also obtained for comparison. The proposed algorithm is shown to achieve BER performance close to the ML lower bound within 0.6 dB at an uncoded BER of 10-2 in 16 × 8 V-BLAST UD-MIMO system with 4-QAM (32 bps/Hz). Similar near-ML performance results are shown for 32 × 16, 32 × 24 V-BLAST UD-MIMO with 4-QAM/16-QAM as well. A performance and complexity comparison between the proposed algorithm and the λ-generalized sphere decoder (λ-GSD) algorithm for UD-MIMO shows that the proposed algorithm achieves almost the same performance of λ-GSD but at a significantly lesser complexity.

Synthesis, Characterization, and Nuclear Magnetic Resonance Study of Chitosan-Coated Mn1-xZnxFe2O4 Nanocrystals

Ultra-fine crystallites of Mn1-xZnxFe2O4 series (0 <= x <= 1) were synthesized through wet chemical co- precipitation method followed by calcination at 200 degrees C for 4 hours. Formation of ferrites was confirmed by X-ray diffraction, TEM selected area diffraction (SAD) and Fourier Transform Infra-red Spectroscopy (FTIR). Nanocrystallites of different compositions in the series were coated with biocompatible chitosan in order to investigate their possible application as contrast agent for magnetic resonance imaging (MRI). Chitosan coating examined by FTIR, revealed a strong bonding of chitosan molecules to the surface of the ferrite nanocrystallites. Spin-spin, tau(2) relaxivities of nuclear spins of hydrogen protons of the solutions for different ferrites were measured from concentration dependence of relaxation time by nuclear magnetic resonance (NMR). All the compositions of Mn1-xZnxFe2O4 series possess higher values of tau(2) relaxivity thus making them suitable as contrast agents for tau(2) weighted imaging by MRI.

Seismic microzonation of a nuclear power plant site with detailed geotechnical, geophysical and site effect studies

This paper highlights the seismic microzonation carried out for a nuclear power plant site. Nuclear power plants are considered to be one of the most important and critical structures designed to withstand all natural disasters. Seismic microzonation is a process of demarcating a region into individual areas having different levels of various seismic hazards. This will help in identifying regions having high seismic hazard which is vital for engineering design and land-use planning. The main objective of this paper is to carry out the seismic microzonation of a nuclear power plant site situated in the east coast of South India, based on the spatial distribution of the hazard index value. The hazard index represents the consolidated effect of all major earthquake hazards and hazard influencing parameters. The present work will provide new directions for assessing the seismic hazards of new power plant sites in the country. Major seismic hazards considered for the evaluation of the hazard index are (1) intensity of ground shaking at bedrock, (2) site amplification, (3) liquefaction potential and (4) the predominant frequency of the earthquake motion at the surface. The intensity of ground shaking in terms of peak horizontal acceleration (PHA) was estimated for the study area using both deterministic and probabilistic approaches with logic tree methodology. The site characterization of the study area has been carried out using the multichannel analysis of surface waves test and available borehole data. One-dimensional ground response analysis was carried out at major locations within the study area for evaluating PHA and spectral accelerations at the ground surface. Based on the standard penetration test data, deterministic as well as probabilistic liquefaction hazard analysis has been carried out for the entire study area. Finally, all the major earthquake hazards estimated above, and other significant parameters representing local geology were integrated using the analytic hierarchy process and hazard index map for the study area was prepared. Maps showing the spatial variation of seismic hazards (intensity of ground shaking, liquefaction potential and predominant frequency) and hazard index are presented in this work.

Probing the flavor violating scalar top quark signal at the LHC

The Large Hadron Collider (LHC) has completed its run at 8 TeV with the experiments ATLAS and CMS having collected about 25 fb(-1) of data each. Discovery of a light Higgs boson coupled with lack of evidence for supersymmetry at the LHC so far, has motivated studies of supersymmetry in the context of naturalness with the principal focus being the third generation squarks. In this work, we analyze the prospects of the flavor violating decay mode (t) over tilde (1) -> c chi(0)(1) at 8 and 13 TeV center-of-mass energy at the LHC. This channel is also relevant in the dark matter context for the stop-coannihilation scenario, where the relic density depends on the mass difference between the lighter stop quark ((t) over tilde (1)) and the lightest neutralino (chi(0)(1)) states. This channel is extremely challenging to probe, especially for situations when the mass difference between the lighter stop quark and the lightest neutralino is small. Using certain kinematical properties of signal events we find that the level of backgrounds can be reduced substantially. We find that the prospect for this channel is limited due to the low production cross section for top squarks and limited luminosity at 8 TeV, but at the 13 TeV LHC with 100 fb(-1) luminosity, it is possible to probe top squarks with masses up to similar to 450 GeV. We also discuss how the sensitivity could be significantly improved by tagging charm jets.

A Committee Machine Approach for Compressed Sensing Signal Reconstruction

Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

A Communication-Theoretic Framework for 2-DMR Channel Modeling: Performance Evaluation of Coding and Signal Processing Methods

We develop a communication theoretic framework for modeling 2-D magnetic recording channels. Using the model, we define the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters. We analyze the problem of optimizing the bit aspect ratio for maximizing SNR. The read channel architecture comprises a novel 2-D joint self-iterating equalizer and detection system with noise prediction capability. We evaluate the system performance based on our channel model through simulations. The coded performance with the 2-D equalizer detector indicates similar to 5.5 dB of SNR gain over uncoded data.

Diffusion in an elastic medium: A model for macromolecule transport across the nuclear pore complex

Nuclear pore complexes (NPCs) are very selective filters that sit on the membrane of the nucleus and monitor the transport between the cytoplasm and the nucleoplasm. For the central plug of NPC two models have been suggested in the literature. The first suggests that the plug is a reversible hydrogel while the other suggests that it is a polymer brush. Here we propose a model for the transport of a protein through the plug, which is general enough to cover both the models. The protein stretches the plug and creates a local deformation, which together with the protein, we refer to as the bubble. We start with the free energy for creation of the bubble and consider its motion within the plug. The relevant coordinate is the center of the bubble which executes random walk. We find that for faster relaxation of the gel, the diffusion of the bubble is greater. (C) 2014 Elsevier-B.V. All rights reserved.