Singular perturbation of quantum stochastic differential equations with coupling through an oscillator mode

Gough, John; Van Handel, R., (2007) 'Singular perturbation of quantum stochastic differential equations with coupling through an oscillator mode', Journal of Statistical Physics 127(3) pp.575-607 RAE2008

An Ounce of Prevention is Worth a Pound of Cure: Towards Physically-Correct Specifications of Embedded Real-Time Systems

Predictability — the ability to foretell that an implementation will not violate a set of specified reliability and timeliness requirements - is a crucial, highly desirable property of responsive embedded systems. This paper overviews a development methodology for responsive systems, which enhances predictability by eliminating potential hazards resulting from physically-unsound specifications. The backbone of our methodology is a formalism that restricts expressiveness in a way that allows the specification of only reactive, spontaneous, and causal computation. Unrealistic systems — possessing properties such as clairvoyance, caprice, infinite capacity, or perfect timing — cannot even be specified. We argue that this "ounce of prevention" at the specification level is likely to spare a lot of time and energy in the development cycle of responsive systems - not to mention the elimination of potential hazards that would have gone, otherwise, unnoticed.

A simulator of real-time systems specified in et-lotos

info:eu-repo/semantics/published

No-Holdback allocation rules for continuous-time assemble-to-order systems

This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times. The inventory of each component is replenished following an independent base-stock policy. In contrast to the usually assumed first-come-first-served (FCFS) component allocation rule in the literature, an NHB rule allocates a component to a product demand only if it will yield immediate fulfillment of that demand. We identify metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules. For systems with certain product structures, we obtain key performance expressions and compare them to those under FCFS. For general product structures, we present performance bounds and approximations. Finally, we discuss the applicability of these results to more general ATO systems. © 2010 INFORMS.

Flexible and robust run-time configuration for self-managing systems

This paper describes a methodology for deploying flexible dynamic configuration into embedded systems whilst preserving the reliability advantages of static systems. The methodology is based on the concept of decision points (DP) which are strategically placed to achieve fine-grained distribution of self-management logic to meet application-specific requirements. DP logic can be changed easily, and independently of the host component, enabling self-management behavior to be deferred beyond the point of system deployment. A transparent Dynamic Wrapper mechanism (DW) automatically detects and handles problems arising from the evaluation of self-management logic within each DP and ensures that the dynamic aspects of the system collapse down to statically defined default behavior to ensure safety and correctness despite failures. Dynamic context management contributes to flexibility, and removes the need for design-time binding of context providers and consumers, thus facilitating run-time composition and incremental component upgrade.

A run-time configurable software architecture for self-managing systems

This paper describes a highly flexible component architecture, primarily designed for automotive control systems, that supports distributed dynamically- configurable context-aware behaviour. The architecture enforces a separation of design-time and run-time concerns, enabling almost all decisions concerning runtime composition and adaptation to be deferred beyond deployment. Dynamic context management contributes to flexibility. The architecture is extensible, and can embed potentially many different self-management decision technologies simultaneously. The mechanism that implements the run-time configuration has been designed to be very robust, automatically and silently handling problems arising from the evaluation of self- management logic and ensuring that in the worst case the dynamic aspects of the system collapse down to static behavior in totally predictable ways.

Organisational controls, typologies and time scales of paraglacial gravel-dominated coastal systems

The fundamental controls on the initiation and development of gravel-dominated deposits (beaches and barriers) on paraglacial coasts are particle size and shape, sediment supply, storm wave activity (primarily runup), relative sea-level (RSL) change, and terrestrial basement structure (primarily as it affects accommodation space). This paper examines the stochastic basis for barrier organisation as shown by variation in gravel barrier architecture. We recognise punctuated self-organisation of barrier development that is disrupted by short phases of barrier instability. The latter results from positive feedback causing barrier breakdown when sediment supply is exhausted. We examine published typologies for gravel barriers and advocate a consolidated perspective using rate of RSL change and sediment supply. We also consider the temporal variation in controls on barrier development. These are examined in terms of a simple behavioural model (BARCH) for prograding gravel barrier architecture and its sensitivity to such controls. The nature of macroscale (102–103 years) gravel barrier development, including inherited characteristics that influence barrier genesis, as well as forcing from changing RSL, sediment supply, headland control and barrier inertia, is examined in the context of long-surviving barriers along the southern England coastline.

Reuseable Silicon IP Cores for Discrete Wavelet Transform Applications

Architectures and methods for the rapid design of silicon cores for implementing discrete wavelet transforms over a wide range of specifications are described. These architectures are efficient, modular, scalable, and cover orthonormal and biorthogonal wavelet transform families. They offer efficient hardware utilization by exploiting a number of core wavelet filter properties and allow the creation of silicon designs that are highly parameterized, including in terms of wavelet type and wordlengths. Control circuitry is embedded within these systems allowing them to be cascaded for any desired level of decomposition without any interface glue logic. The time to produce chip designs for a specific wavelet application is typically less than a day and these are comparable in area and performance to handcrafted designs. They are also portable across a wide range of silicon foundries and suitable for field programmable gate array and programmable logic data implementation. The approach described has also been extended to wavelet packet transforms.

Correspondence between continuous-variable and discrete quantum systems of arbitrary dimensions

We establish a mapping between a continuous-variable (CV) quantum system and a discrete quantum system of arbitrary dimension. This opens up the general possibility to perform any quantum information task with a CV system as if it were a discrete system. The Einstein-Podolsky-Rosen state is mapped onto the maximally entangled state in any finite-dimensional Hilbert space and thus can be considered as a universal resource of entanglement. An explicit example of the map and a proposal for its experimental realization are discussed.

Time operators and shift representation of dynamical systems

We introduce and characterise time operators for unilateral shifts and exact endomorphisms. The associated shift representation of evolution is related to the spectral representation by a generalized Fourier transform. We illustrate the results for a simple exact system, namely the Renyi map.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.