Efficient simulation of unitary operators by combining two numerical algorithms: An NMR simulation of the mirror-inversion propagator of an XY spin chain

Precise experimental implementation of unitary operators is one of the most important tasks for quantum information processing. Numerical optimization techniques are widely used to find optimized control fields to realize a desired unitary operator. However, finding high-fidelity control pulses to realize an arbitrary unitary operator in larger spin systems is still a difficult task. In this work, we demonstrate that a combination of the GRAPE algorithm, which is a numerical pulse optimization technique, and a unitary operator decomposition algorithm Ajoy et al., Phys. Rev. A 85, 030303 (2012)] can realize unitary operators with high experimental fidelity. This is illustrated by simulating the mirror-inversion propagator of an XY spin chain in a five-spin dipolar coupled nuclear spin system. Further, this simulation has been used to demonstrate the transfer of entangled states from one end of the spin chain to the other end.

Multimodal therapy for complete regression of malignant melanoma using constrained nonlinear optimal dynamic inversion

Using a realistic nonlinear mathematical model for melanoma dynamics and the technique of optimal dynamic inversion (exact feedback linearization with static optimization), a multimodal automatic drug dosage strategy is proposed in this paper for complete regression of melanoma cancer in humans. The proposed strategy computes different drug dosages and gives a nonlinear state feedback solution for driving the number of cancer cells to zero. However, it is observed that when tumor is regressed to certain value, then there is no need of external drug dosages as immune system and other therapeutic states are able to regress tumor at a sufficiently fast rate which is more than exponential rate. As model has three different drug dosages, after applying dynamic inversion philosophy, drug dosages can be selected in optimized manner without crossing their toxicity limits. The combination of drug dosages is decided by appropriately selecting the control design parameter values based on physical constraints. The process is automated for all possible combinations of the chemotherapy and immunotherapy drug dosages with preferential emphasis of having maximum possible variety of drug inputs at any given point of time. Simulation study with a standard patient model shows that tumor cells are regressed from 2 x 107 to order of 105 cells because of external drug dosages in 36.93 days. After this no external drug dosages are required as immune system and other therapeutic states are able to regress tumor at greater than exponential rate and hence, tumor goes to zero (less than 0.01) in 48.77 days and healthy immune system of the patient is restored. Study with different chemotherapy drug resistance value is also carried out. (C) 2014 Elsevier Ltd. All rights reserved.

Single network adaptive critic aided dynamic inversion for optimal regulation and command tracking with online adaptation for enhanced robustness

To combine the advantages of both stability and optimality-based designs, a single network adaptive critic (SNAC) aided nonlinear dynamic inversion approach is presented in this paper. Here, the gains of a dynamic inversion controller are selected in such a way that the resulting controller behaves very close to a pre-synthesized SNAC controller in the output regulation sense. Because SNAC is based on optimal control theory, it makes the dynamic inversion controller operate nearly optimal. More important, it retains the two major benefits of dynamic inversion, namely (i) a closed-form expression of the controller and (ii) easy scalability to command tracking applications without knowing the reference commands a priori. An extended architecture is also presented in this paper that adapts online to system modeling and inversion errors, as well as reduced control effectiveness, thereby leading to enhanced robustness. The strengths of this hybrid method of applying SNAC to optimize an nonlinear dynamic inversion controller is demonstrated by considering a benchmark problem in robotics, that is, a two-link robotic manipulator system. Copyright (C) 2013 John Wiley & Sons, Ltd.

Quantitative estimation of density variation in high-speed flows through inversion of the measured wavefront distortion

A simple method employing an optical probe is presented to measure density variations in a hypersonic flow obstructed by a test model in a typical shock tunnel. The probe has a plane light wave trans-illuminating the flow and casting a shadow of a random dot pattern. Local slopes of the distorted wavefront are obtained from shifts of the dots in the pattern. Local shifts in the dots are accurately measured by cross-correlating local shifted shadows with the corresponding unshifted originals. The measured slopes are suitably unwrapped by using a discrete cosine transform based phase unwrapping procedure and also through iterative procedures. The unwrapped phase information is used in an iterative scheme for a full quantitative recovery of density distribution in the shock around the model through refraction tomographic inversion. Hypersonic flow field parameters around a missile shaped body at a free-stream Mach number of 5.8 measured using this technique are compared with the numerically estimated values. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

Adaptive Flight-Control Design Using Neural-Network-Aided Optimal Nonlinear Dynamic Inversion

A neural-network-aided nonlinear dynamic inversion-based hybrid technique of model reference adaptive control flight-control system design is presented in this paper. Here, the gains of the nonlinear dynamic inversion-based flight-control system are dynamically selected in such a manner that the resulting controller mimics a single network, adaptive control, optimal nonlinear controller for state regulation. Traditional model reference adaptive control methods use a linearized reference model, and the presented control design method employs a nonlinear reference model to compute the nonlinear dynamic inversion gains. This innovation of designing the gain elements after synthesizing the single network adaptive controller maintains the advantages that an optimal controller offers, yet it retains a simple closed-form control expression in state feedback form, which can easily be modified for tracking problems without demanding any a priori knowledge of the reference signals. The strength of the technique is demonstrated by considering the longitudinal motion of a nonlinear aircraft system. An extended single network adaptive control/nonlinear dynamic inversion adaptive control design architecture is also presented, which adapts online to three failure conditions, namely, a thrust failure, an elevator failure, and an inaccuracy in the estimation of C-M alpha. Simulation results demonstrate that the presented adaptive flight controller generates a near-optimal response when compared to a traditional nonlinear dynamic inversion controller.

Improved subject-independent acoustic-to-articulatory inversion

In subject-independent acoustic-to-articulatory inversion, the articulatory kinematics of a test subject are estimated assuming that the training corpus does not include data from the test subject. The training corpus in subject-independent inversion (SII) is formed with acoustic and articulatory kinematics data and the acoustic mismatch between training and test subjects is then estimated by an acoustic normalization using acoustic data drawn from a large pool of speakers called generic acoustic space (GAS). In this work, we focus on improving the SII performance through better acoustic normalization and adaptation. We propose unsupervised and several supervised ways of clustering GAS for acoustic normalization. We perform an adaptation of acoustic models of GAS using the acoustic data of the training and test subjects in SII. It is found that SII performance significantly improves (similar to 25% relative on average) over the subject-dependent inversion when the acoustic clusters in GAS correspond to phonetic units (or states of 3-state phonetic HMMs) and when the acoustic model built on GAS is adapted to training and test subjects while optimizing the inversion criterion. (C) 2014 Elsevier B.V. All rights reserved.

Comparative evaluation of inversion approaches of the radiative transfer model for estimation of crop biophysical parameters

The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

Phase Inversion of Agitated Liquid-Liquid Dispersions in the Presence of Micrometer-Sized Particles

We have investigated the impact of partially wetting particles of tens of micrometers on inversion instability of agitated liquid liquid dispersions. Particles of this size can be easily separated from the exit streams to avoid downstream processing-related issues. The results show that the presence of hydrophilic particles in small quantities (volume fraction range of 2 X 10(-4) to 1.25 x 10(-2)) significantly decreases the dispersed phase fraction at which water-in-oil (w/o) dispersions invert but leaves the inversion of oil-in-water (o/w) dispersions nearly unaffected. The addition of the same particles after they are hydrophobized decreases the dispersed phase fraction at which o/w dispersions invert but leaves the inversion of w/o dispersions unaffected. These findings suggest an increased rate of coalescence of drops when particles wet drops preferentially and a marginal decrease when they wet the continuous phase preferentially. High-speed conductivity measurements on w/o dispersion show transient conduction of a few hundred milliseconds duration through voltage pulses. Close to the inversion point, voltage pulses appear at high frequency for even 7 cm separation between the electrodes. The presence of hydrophilic particles produces a nearly identical signal at a significantly lower dispersed phase fraction itself, close to the new lowered inversion point in the presence of particles. We propose formation of elongated domains of the conducting dispersed phase through a rapid coalescence-deformation-breakup process to explain the new observations. The voltage signal appears as a forerunner of inversion instability.

Gradient echo single scan inversion recovery: application to proton and fluorine relaxation studies

Single scan longitudinal relaxation measurement experiments enable rapid estimation of the spin-lattice relaxation time (T-1) as the time series of spin relaxation is encoded spatially in the sample at different slices resulting in an order of magnitude saving in time. We consider here a single scan inversion recovery pulse sequence that incorporates a gradient echo sequence. The proposed pulse sequence provides spectra with significantly enhanced signal to noise ratio leading to an accurate estimation of T-1 values. The method is applicable for measuring a range of T-1 values, thus indicating the possibility of routine use of the method for several systems. A comparative study of different single scan methods currently available is presented, and the advantage of the proposed sequence is highlighted. The possibility of the use of the method for the study of cross-correlation effects for the case of fluorine in a single shot is also demonstrated. Copyright (C) 2015 John Wiley & Sons, Ltd.

Gradient echo single scan inversion recovery: application to proton and fluorine relaxation studies

Single scan longitudinal relaxation measurement experiments enable rapid estimation of the spin-lattice relaxation time (T-1) as the time series of spin relaxation is encoded spatially in the sample at different slices resulting in an order of magnitude saving in time. We consider here a single scan inversion recovery pulse sequence that incorporates a gradient echo sequence. The proposed pulse sequence provides spectra with significantly enhanced signal to noise ratio leading to an accurate estimation of T-1 values. The method is applicable for measuring a range of T-1 values, thus indicating the possibility of routine use of the method for several systems. A comparative study of different single scan methods currently available is presented, and the advantage of the proposed sequence is highlighted. The possibility of the use of the method for the study of cross-correlation effects for the case of fluorine in a single shot is also demonstrated. Copyright (C) 2015 John Wiley & Sons, Ltd.

Parameters Inversion of Fluid-Saturated Porous Media Based on Neural Networks

The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

A Continuation Method of Parameter Inversion for Non-Equilibrium Convection-Dispersion Equation

Based on the homotopy mapping, a globally convergent method of parameter inversion for non-equilibrium convection-dispersion equations (CDEs) is developed. Moreover, in order to further improve the computational efficiency of the algorithm, a properly smooth function, which is derived from the sigmoid function, is employed to update the homotopy parameter during iteration. Numerical results show the feature of global convergence and high performance of this method. In addition, even the measurement quantities are heavily contaminated by noises, and a good solution can be found.

Abel Inversion of Axially-Symmetric Shock Wave Flows

Finite-fringe interferograms produced for axisymmetric shock wave flows are analyzed by Fourier transform fringe analysis and an Abel inversion method to produce density field data for the validation of numerical models. For the Abel inversion process, we use basis functions to model phase data from axially-symmetric shock wave structure. Steady and unsteady flow problems are studied, and compared with numerical simulations. Good agreement between theoretical and experimental results is obtained when one set of basis functions is used during the inversion process, but the shock front is smeared when another is used. This is because each function in the second set of basis functions is infinitely differentiable, making them poorly-suited to the modelling of a step function as is required in the representation of a shock wave.

Binary excitation of a high-Q bulk acoustic microresonator by actuation polarity inversion

We present a technique for independently exciting two resonant modes of vibration in a single-crystal silicon bulk mode microresonator using the same electrode configuration through control of the polarity of the DC actuation voltage. Applications of this technique may include built-in temperature compensation by the simultaneous selective excitation of two closely spaced modes that may have different temperature coefficients of resonant frequency. The technique is simple and requires minimum circuit overhead for implementation. The technique is implemented on square plate resonators with quality factors as high as 3.06 × 106. Copyright © 2008 by ASME.