Performance analysis of a suprathreshold, stochastic resonance based nonlinear detector

In this paper we introduce a nonlinear detector based on the phenomenon of suprathreshold stochastic resonance (SSR). We first present a model (an array of 1-bit quantizers) that demonstrates the SSR phenomenon. We then use this as a pre-processor to the conventional matched filter. We employ the Neyman-Pearson(NP) detection strategy and compare the performances of the matched filter, the SSR-based detector and the optimal detector. Although the proposed detector is non-optimal, for non-Gaussian noises with heavy tails (leptokurtic) it shows better performance than the matched filter. In situations where the noise is known to be leptokurtic without the availability of the exact knowledge of its distribution, the proposed detector turns out to be a better choice than the matched filter.

A suprathreshold stochastic resonance based pre-processor for direction-of-arrival estimation

In this paper we propose a nonlinear preprocessor for enhancing the performance of processors used for direction-of-arrival (DOA) estimation in heavy-tailed non-Gaussian noise. The preprocessor based on the phenomenon of suprathreshold stochastic resonance (SSR), provides SNR gain. The preprocessed data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented to show that the SSR preprocessor provides a significant improvement in the performance of MUSIC in heavy-tailed noise at low SNR.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

An electron paramagnetic resonance study of Pr0.6Ca0.4MnO3 across the charge-ordering transition

We report the first electron paramagnetic resonance studies of single crystals and powders of Pr0.6Ca0.4MnO3 in the 300-4.2 K range, covering the charge-ordering transition (Tco) at ~240 K and antiferromagnetic transition (TN) at ~170 K. The asymmetry parameter for the Dysonian single-crystal spectra shows an anomalous increase at Tco. Below Tco the g-value increases continuously, suggesting a gradual strengthening of the orbital ordering. The linewidth undergoes a sudden increase at Tco and continues to increase down to TN. The intensity increases as the temperature is decreased until Tco is reached, due to the renormalization of the magnetic susceptibility arising from the build-up of ferromagnetic correlations.

Chlorine-35 nuclear quadrupole resonance study of molecular torsional motion in some chloropyridine-N-oxides and chloroquinoline-N-oxides

Chlorine has been substituted at the 2- and 4-positions in the pyridine and quinoline rings of the corresponding N-oxides and 35Cl n.q.r. spectra have been studied in the temperature range 77–300 K. The change in the n.q.r. frequencies in N-oxides as compared to their parent compounds are interpreted in terms of the conjugative effect and the inductive effect of the N+—O– group. The negative temperature coefficients of the resonance frequencies in chloropyridine-N-oxides have been analysed using the Bayer, Kushida and Brown equations. The calculated torsional frequencies, which are in the range 52–78 cm–1, are found to be only slightly temperature dependent.

Neel order, quantum spin liquids, and quantum criticality in two dimensions

This paper is concerned with the possibility of a direct second-order transition out of a collinear Neel phase to a paramagnetic spin liquid in two-dimensional quantum antiferromagnets. Contrary to conventional wisdom, we show that such second-order quantum transitions can potentially occur to certain spin liquid states popular in theories of the cuprates. We provide a theory of this transition and study its universal properties in an epsilon expansion. The existence of such a transition has a number of interesting implications for spin-liquid-based approaches to the underdoped cuprates. In particular it considerably clarifies existing ideas for incorporating antiferromagnetic long range order into such a spin-liquid-based approach.

Ordering near the percolation threshold in models of two-dimensional interacting bosons with quenched dilution

Randomly diluted quantum boson and spin models in two dimensions combine the physics of classical percolation with the well-known dimensionality dependence of ordering in quantum lattice models. This combination is rather subtle for models that order in two dimensions but have no true order in one dimension, as the percolation cluster near threshold is a fractal of dimension between 1 and 2: two experimentally relevant examples are the O(2) quantum rotor and the Heisenberg antiferromagnet. We study two analytic descriptions of the O(2) quantum rotor near the percolation threshold. First a spin-wave expansion is shown to predict long-ranged order, but there are statistically rare points on the cluster that violate the standard assumptions of spin-wave theory. A real-space renormalization group (RSRG) approach is then used to understand how these rare points modify ordering of the O(2) rotor. A new class of fixed points of the RSRG equations for disordered one-dimensional bosons is identified and shown to support the existence of long-range order on the percolation backbone in two dimensions. These results are relevant to experiments on bosons in optical lattices and superconducting arrays, and also (qualitatively) for the diluted Heisenberg antiferromagnet La-2(Zn,Mg)(x)Cu1-xO4.

Geometric quantum computation using fictitious spin-1/2 subspaces of strongly dipolar coupled nuclear spins

Geometric phases have been used in NMR to implement controlled phase shift gates for quantum-information processing, only in weakly coupled systems in which the individual spins can be identified as qubits. In this work, we implement controlled phase shift gates in strongly coupled systems by using nonadiabatic geometric phases, obtained by evolving the magnetization of fictitious spin-1/2 subspaces, over a closed loop on the Bloch sphere. The dynamical phase accumulated during the evolution of the subspaces is refocused by a spin echo pulse sequence and by setting the delay of transition selective pulses such that the evolution under the homonuclear coupling makes a complete 2 pi rotation. A detailed theoretical explanation of nonadiabatic geometric phases in NMR is given by using single transition operators. Controlled phase shift gates, two qubit Deutsch-Jozsa algorithm, and parity algorithm in a qubit-qutrit system have been implemented in various strongly dipolar coupled systems obtained by orienting the molecules in liquid crystal media.

Memory effect in Dy0.5Sr0.5MnO3 single crystals

We have performed a series of magnetic aging experiments on single crystals of Dy0.5Sr0.5MnO3. The results demonstrate striking memory and chaos-like effects in this insulating half-doped perovskite manganite and suggest the existence of strong magnetic relaxation mechanisms of a clustered magnetic state. The spin-glass-like state established below a temperature T-sg approximate to 34 K originates from quenched disorder arising due to the ionic-radii mismatch at the rare earth site. However, deviations from the typical behavior seen in canonical spin glass materials are observed which indicate that the glassy magnetic properties are due to cooperative and frustrated dynamics in a heterogeneous or clustered magnetic state. In particular, the microscopic spin flip time obtained from dynamical scaling near the spin glass freezing temperature is four orders of magnitude larger than microscopic times found in atomic spin glasses. The magnetic viscosity deduced from the time dependence of the zero-field-cooled magnetization exhibits a peak at a temperature T < T-sg and displays a marked dependence on waiting time in zero field.