Non-ideal monitoring of a qubit state using a quantum tunnelling device

We propose a model for non-ideal monitoring of the state of a coupled quantum dot qubit by a quantum tunnelling device. The non-ideality is modelled using an equivalent measurement circuit. This allows realistically available measurement results to be related to the state of the quantum system (qubit). We present a quantum trajectory that describes the stochastic evolution of the qubit state conditioned by tunnelling events (i.e. current) through the device. We calculate and compare the noise power spectra of the current in an ideal and a non-ideal measurement. The results show that when the two qubit dots are strongly coupled the non-ideal measurement cannot detect the qubit state precisely. The limitation of the ideal model for describing a realistic system maybe estimated from the noise spectra.

Existence and embeddings of partial Steiner triple systems of order ten with cubic leaves

Denote the set of 21 non-isomorphic cubic graphs of order 10 by L. We first determine precisely which L is an element of L occur as the leave of a partial Steiner triple system, thus settling the existence problem for partial Steiner triple systems of order 10 with cubic leaves. Then we settle the embedding problem for partial Steiner triple systems with leaves L is an element of L. This second result is obtained as a corollary of a more general result which gives, for each integer v greater than or equal to 10 and each L is an element of L, necessary and sufficient conditions for the existence of a partial Steiner triple system of order v with leave consisting of the complement of L and v - 10 isolated vertices. (C) 2004 Elsevier B.V. All rights reserved.

Implicit stochastic Runge-Kutta methods for stochastic differential equations

In this paper we construct implicit stochastic Runge-Kutta (SRK) methods for solving stochastic differential equations of Stratonovich type. Instead of using the increment of a Wiener process, modified random variables are used. We give convergence conditions of the SRK methods with these modified random variables. In particular, the truncated random variable is used. We present a two-stage stiffly accurate diagonal implicit SRK (SADISRK2) method with strong order 1.0 which has better numerical behaviour than extant methods. We also construct a five-stage diagonal implicit SRK method and a six-stage stiffly accurate diagonal implicit SRK method with strong order 1.5. The mean-square and asymptotic stability properties of the trapezoidal method and the SADISRK2 method are analysed and compared with an explicit method and a semi-implicit method. Numerical results are reported for confirming convergence properties and for comparing the numerical behaviour of these methods.

Geodesics without differential equations: general relativistic calculations for introductory modern physics classes

Introductory courses covering modem physics sometimes introduce some elementary ideas from general relativity, though the idea of a geodesic is generally limited to shortest Euclidean length on a curved surface of two spatial dimensions rather than extremal aging in spacetime. It is shown that Epstein charts provide a simple geometric picture of geodesics in one space and one time dimension and that for a hypothetical uniform gravitational field, geodesics are straight lines on a planar diagram. This means that the properties of geodesics in a uniform field can be calculated with only a knowledge of elementary geometry and trigonometry, thus making the calculation of some basic results of general relativity accessible to students even in an algebra-based survey course on physics.

Non-linear principal components analysis: an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd.

Using urea dilution to standardise cellular and non-cellular components of pleural and bronchoalveolar lavage (BAL) fluids in the cat

A technique to standardise the analysis of cellular and non-cellular components in epithelial lining fluid (ELF) collected during saline lavage of pulmonary and pleural cavities was developed using the urea dilution method. Bronchoalveolar lavage (BAL) and pleural lavage (PL) fluids were collected from 12 clinically healthy cats. Total and differential cell counts in BAL fluid were within normal ranges for the cat, while cell Counts in PL fluid were assumed to be normal based on clinical health during examination, auscultation and lactate dehydrogenase (LDH) activities being comparable with other species. The major clinical implication of this study was that nucleated cell counts within feline ELF could not be predicted from analysis of lavage fluid which suggests that calculation of the proportion of ELF in lavage fluid by the urea dilution method may be necessary to avoid misdiagnosis of health or disease in pulmonary or pleural cavities. (C) 2005 ESFM and AAFP. Published by Elsevier Ltd. All rights reserved.

Bifurcations in the non-dissipative dynamics of ultra cold atoms

We present the first experimental observation of several bifurcations in a controllable non-linear Hamiltonian system. Dynamics of cold atoms are used to test predictions of non-linear, non-dissipative Hamiltonian dynamics.

EM optimization of latent-variable density models

There is currently considerable interest in developing general non-linear density models based on latent, or hidden, variables. Such models have the ability to discover the presence of a relatively small number of underlying `causes' which, acting in combination, give rise to the apparent complexity of the observed data set. Unfortunately, to train such models generally requires large computational effort. In this paper we introduce a novel latent variable algorithm which retains the general non-linear capabilities of previous models but which uses a training procedure based on the EM algorithm. We demonstrate the performance of the model on a toy problem and on data from flow diagnostics for a multi-phase oil pipeline.

Data visualisation with missing data: A non-linear approach

Exploratory analysis of data in all sciences seeks to find common patterns to gain insights into the structure and distribution of the data. Typically visualisation methods like principal components analysis are used but these methods are not easily able to deal with missing data nor can they capture non-linear structure in the data. One approach to discovering complex, non-linear structure in the data is through the use of linked plots, or brushing, while ignoring the missing data. In this technical report we discuss a complementary approach based on a non-linear probabilistic model. The generative topographic mapping enables the visualisation of the effects of very many variables on a single plot, which is able to incorporate far more structure than a two dimensional principal components plot could, and deal at the same time with missing data. We show that using the generative topographic mapping provides us with an optimal method to explore the data while being able to replace missing values in a dataset, particularly where a large proportion of the data is missing.

Interactions within heterogeneous systems of uncontrolled rectifiers for aircraft electrical power systems

There is an increase in the use of multi-pulse, rectifier-fed motor-drive equipment on board more-electric aircraft. Motor drives with feedback control appear as constant power loads to the rectifiers, which can cause instability of the DC filter capacitor voltage at the output of the rectifier. This problem can be exacerbated by interactions between rectifiers that share a common source impedance. In order that such a system can be analysed, there is a need for average, dynamic models of systems of rectifiers. In this study, an efficient, compact method for deriving the approximate, linear, large-signal, average models of two heterogeneous systems of rectifiers, which are fed from a common source impedance, is presented. The models give insight into significant interaction effects that occur between the converters, and that arise through the shared source impedance. First, a 6-pulse and doubly wound, transformer-fed, 12-pulse rectifier system is considered, followed by a 6-pulse and autotransformer-fed, 12-pulse rectifier system. The system models are validated against detailed simulations and laboratory prototypes, and key characteristics of the two system types are compared.

Neural network control of a gas turbine

In this paper we explore the practical use of neural networks for controlling complex non-linear systems. The system used to demonstrate this approach is a simulation of a gas turbine engine typical of those used to power commercial aircraft. The novelty of the work lies in the requirement for multiple controllers which are used to maintain system variables in safe operating regions as well as governing the engine thrust.

Ultra-long haul optical fibre transmission systems

This thesis examines experimentally options for optical fibre transmission over oceanic distances. Its format follows the chronological evolution of ultra-long haul optical systems, commencing with opto-electronic regenerators as repeaters, progressing to optically amplified NRZ systems and finally solitonic propagation. In each case recirculating loop techniques are deployed to simplify the transmission experiments. Advances in high speed electronics have allowed regenerators operating at 10 Gbit/s to become a practical reality. By augmenting such devices with optical amplifiers it is possible to greatly enhance the repeater spacing. Work detailed in this thesis has culminated in the propagation of 10 Gbit/s data over 400,000 km with a repeater spacing of 160 km. System reliability and robustness are enhanced by the use of a directly modulated DFB laser transmitter and total insensitivity of the system to the signal state of polarisation. Optically amplified ultra-long haul NRZ systems have taken on particular importance with the impending deployment of TAT 12/13 and TPC 5. The performance of these systems is demonstrated to be primarily limited by analogue impairments such as the accumulation of amplifier noise, polarisation effects and optical non-linearities. These degradations may be reduced by the use of appropriate dispersion maps and by scrambling the transmitted state of signal polarisation. A novel high speed optically passive polarisation scrambler is detailed for the first time. At bit rates in excess of 10 Gbit/s it is shown that these systems are severely limited and do not offer the advantages that might be expected over regenerated links. Propagation using solitons as the data bits appears particularly attractive since the dispersive and non-linear effects of the fibre allow distortion free transmission. However, the generation of pure solitons is difficult but must be achieved if the uncontrolled transmission distance is to be maximised. This thesis presents a new technique for the stabilisation of an erbium fibre ring laser that has aUowed propagation of 2.5 Gbit/s solitons to the theoretical limit of ~ 18,000 km. At higher bit rates temporal jitter becomes a significant impairment and to aUow an increase in the aggregate line rate multiplexing in both time and polarisation domains has been proposed. These techniques are shown to be of only limited benefit in practical systems and ultimately some form of soliton transmission control is required. The thesis demonstrates synchronous retiming by amplitude modulation that has allowed 20 Gbit/s data to propagate 125,000 km error free with an amplifier spacing approaching the soliton period. Ultimately the speed of operation of such systems is limited by the electronics used and, thus, a new form of soliton control is demonstrated using all optical techniques to achieve synchronous phase modulation.

Wave chaotic behaviour generated by linear systems

It is shown that regimes with dynamical chaos are inherent not only to nonlinear system but they can be generated by initially linear systems and the requirements for chaotic dynamics and characteristics need further elaboration. Three simplest physical models are considered as examples. In the first, dynamic chaos in the interaction of three linear oscillators is investigated. Analogous process is shown in the second model of electromagnetic wave scattering in a double periodical inhomogeneous medium occupying half-space. The third model is a linear parametric problem for the electromagnetic field in homogeneous dielectric medium which permittivity is modulated in time. © 2008 Springer Science+Business Media, LLC.

Statnote 19: non-linear regression: fitting an exponential curve to data

Non-linear relationships are common in microbiological research and often necessitate the use of the statistical techniques of non-linear regression or curve fitting. In some circumstances, the investigator may wish to fit an exponential model to the data, i.e., to test the hypothesis that a quantity Y either increases or decays exponentially with increasing X. This type of model is straight forward to fit as taking logarithms of the Y variable linearises the relationship which can then be treated by the methods of linear regression.