Asymptotic adaptive bipartite entanglement distillation protocol

We present a new asymptotic bipartite entanglement distillation protocol that outperforms all existing asymptotic schemes. This protocol is based on the breeding protocol with the incorporation of two-way classical communication. Like breeding, the protocol starts with an infinite number of copies of a Bell-diagonal mixed state. Breeding can be carried out as successive stages of partial information extraction, yielding the same result: one bit of information is gained at the cost (measurement) of one pure Bell state pair (ebit). The basic principle of our protocol is at every stage to replace measurements on ebits by measurements on a finite number of copies, whenever there are two equiprobable outcomes. In that case, the entropy of the global state is reduced by more than one bit. Therefore, every such replacement results in an improvement of the protocol. We explain how our protocol is organized as to have as many replacements as possible. The yield is then calculated for Werner states.Comment: 11 pages, 5 figures, RevTeX

Hashing protocol for distilling multipartite CSS states

We present a hashing protocol for distilling multipartite CSS states by means of local Clifford operations, Pauli measurements and classical communication. It is shown that this hashing protocol outperforms previous versions by exploiting information theory to a full extent an not only applying CNOTs as local Clifford operations. Using the information-theoretical notion of a strongly typical set, we calculate the asymptotic yield of the protocol as the solution of a linear programming problem.Comment: 13 pages, 3 figures, RevTeX

A convolutional neural network aided physical model improvement for AC solenoid valves diagnosis

This paper focuses on the development of a physics-based diagnostic tool for alternating current (AC) solenoid valves which are categorized as critical components of many machines used in the process industry. Signal processing and machine learning based approaches have been proposed in the literature to diagnose the health state of solenoid valves. However, the approaches do not give a physical explanation of the failure modes. In this work, being capable of diagnosing failure modes while using a physically interpretable model is proposed. Feature attribution methods are applied to CNN on a large data set of the current signals acquired from accelerated life tests of several AC solenoid valves. The results reveal important regions of interest on current signals that guide the modeling of the main missing component of an existing physical model. Two model parameters, which are the shading ring and kinetic coulomb forces, are then identified using current measurements along the lifetime of valves. Consistent trends are found for both parameters allowing to diagnose the failure modes of the solenoid valves. Future work will consist of not only diagnosing the failure modes, but also of predicting the remaining useful life

Stabilizer states and Clifford operations for systems of arbitrary dimensions, and modular arithmetic

We describe generalizations of the Pauli group, the Clifford group and stabilizer states for qudits in a Hilbert space of arbitrary dimension d. We examine a link with modular arithmetic, which yields an efficient way of representing the Pauli group and the Clifford group with matrices over the integers modulo d. We further show how a Clifford operation can be efficiently decomposed into one and two-qudit operations. We also focus in detail on standard basis expansions of stabilizer states.Comment: 10 pages, RevTe

Stabilizer state breeding

We present a breeding protocol that distills pure copies of any stabilizer state from noisy copies and a pool of predistilled pure copies of the same state, by means of local Clifford operations, Pauli measurements and classical communication.Comment: RevTeX4, 9 pages, 1 figur

Quantitative evaluation of electric features for health monitoring and assessment of AC-powered solenoid operated valves

Quantitative assessment of feature performance for health monitoring is key to feature selection. This paper illustrates the application of well-established metrics in the research community - namely, monotonicity, robustness and prognosability - to the quantitative performance assessment of features for health monitoring of alternating-current (AC) powered solenoid operated valves (SOVs). These features are extracted from voltage and current signals measured on the valves and builds on previous work of the authors. Based on these metrics, the appropriate features are selected to be used as condition indicators. The selected features are inputs to a logistic regression model to predict a health index ranging from 0 to 1, which can be easily monitored and assessed by non-experts. We demonstrated the developed methodology on the experimental data acquired from accelerated life tests on 48 identical AC-powered SOVs.This research was supported by both Flanders Make, the strategic research center for the manufacturing industry, and VLAIO, Flanders Innovation and Entrepreneurship, within the framework of the MODA-ICON project

Neural Network Augmented Physics Models for Systems with Partially Unknown Dynamics: Application to Slider-Crank Mechanism

Dynamic models of mechatronic systems are abundantly used in the context of motion control and design of complex servo applications. In practice, these systems are often plagued by unknown interactions, which make the physics-based relations of the system dynamics only partially known. This paper presents a neural network augmented physics (NNAP) model as a combination of physics-inspired and neural layers. The neural layers are inserted in the model to compensate for the unmodeled interactions, without requiring direct measurements of these unknown phenomena. In contrast to traditional approaches, both the neural network and physical parameters are simultaneously optimized, solely by using state and control input measurements. The methodology is applied on experimental data of a slider-crank setup for which the state dependent load interactions are unknown. The NNAP model proves to be a stable and accurate modeling formalism for dynamic systems that ab initio can only be partially described by physical laws. Moreover, the results show that a recurrent implementation of the NNAP model enables improved robustness and accuracy of the system state predictions, compared to its feedforward counterpart. Besides capturing the system dynamics, the NNAP model provides a means to gain new insights by extracting the neural network from the converged NNAP model. In this way, we discovered accurate representations of the unknown spring force interaction and friction phenomena acting on the slider mechanism

An improved first-principle model of AC powered solenoid operated valves for maintenance applications

Solenoid operated valves (SOVs) are critical components in many industrial applications. There has been a continuing interest in the industry to have robust condition monitoring, prognostics and health management tools to support the condition based maintenance and predictive maintenance program for such valves. For critical assets like SOVs, it is of paramount interest to understand why a component might be declared as defective. In such a situation, a first principle-model based approach will always be preferred to a purely data-driven approach, because of its inherent interpretability. Furthermore, first principle-models typically have less free parameters than their data driven counterparts and will require less data to identify their parameters. In this paper, we present the improvement of a first-principle model of alternating current (AC) powered SOVs taking into account two important degradation effects. Using this model, we show that the state of degradation can be estimated from current and input voltage measurement signals on the solenoids. Our method is validated using data from an accelerated life test campaign on 48 identical AC-powered SOVs

Deliverable 3.6 zoning plan of case studies : evaluation of spatial management options for the case studies

Within MESMA, nine case studies (CS) represent discrete marine European spatial entities, at different spatial scales, where a spatial marine management framework is in place, under development or considered. These CS (described in more details below) are chosen in such a way (MESMA D. 3.1 ) that they encompass the complexity of accommodating the various user functions of the marine landscape in various regions of the European marine waters. While human activities at sea are competing for space, there is also growing awareness of the possible negative effects of these human activities on the marine ecosystem. As such, system specific management options are required, satisfying current and future sectoral needs, while safeguarding the marine ecosystem from further detoriation. This integrated management approach is embedded in the concept of ecosystem based management (EBM). The goal of marine EBM is to maintain marine ecosystems in a healthy, productive and resilient condition, making it possible that they sustain human use and provide the goods and services required by society (McLeod et al. 2005). Therefore EBM is an environmental mangagement approach that recognises the interactions within a marine ecosystem, including humans. Hence, EBM does not consider single issues, species or ecosystems good and services in isolation. Operationalisation of EBM can be done through place-based or spatial management approaches (Lackey 1998), such as marine spatial planning (MSP). MSP is a public process of analysing and allocating the spatial and temporal distribution of human activities aiming at achieving ecological, economic and social objectives. These objectives are usually formulated through political processes (Douvere et al. 2007, Douvere 2008). Within MESMA, a spatially managed area (SMA) is then defined as “a geographical area within which marine spatial planning initiatives exist in the real world”. Marine spatial planning initiatives refer to existing management measures actually in place within a defined area, or in any stage of a process of putting management in place, e.g. plans or recommendations for a particular area. Management can include management for marine protection (e.g. in MPAs), or management for sectoral objectives (e.g. building a wind farm to meet renewable energy objectives). Within MESMA, SMAs can have different spatial scales. A SMA can be a small, specific area that is managed/planned to be managed for one specific purpose, but it can also be a larger area within which lots of plans or ‘usage zones’ exist. This definition is different from the definition mentioned in the DoW (page 60). The original definition was adapted during a CS leader workshop (2-4 May 2012 in Gent, Belgium) and formally accepted by the MESMA ExB during the ExB meeting in Cork (29-30 May 2012). MSP should result in a marine spatial management plan that will produce the desired future trough explicit decisions about the location and timing of human activities. Ehler & Douvere (2009) consider this spatial management as a beginning toward the the implementation of desired goals and objectives. They describe the spatial management plan as a comprehensive, strategic document that provides the framework and direction for marine spatial management decisions. The plan should identify when, where and how goals and objectives will be met. Zoning (the development of zoning plans) is often an important management measure to implement spatial management plans. The purpose of a zoning plan (Ehler & Douvere 2009) is: To provide protection for biologically and ecologically important habitats, ecosystems, and ecological processes. To seperate conflicting human activities, or to combine compatible activities. To protect the natural values of the marine management area (in MESMA terminology: the SMA) while allowing reasonable human uses of the area. To allocate areas for reasonable human uses while minimising the effects of these human uses on each other, and nature. To preserve some areas of the SMA in their natural state undisturbed by humans except for scientific and educational purposes.peer-reviewe