Tractable Simulation of Error Correction with Honest Approximations to Realistic Fault Models

In previous work, we proposed a method for leveraging efficient classical simulation algorithms to aid in the analysis of large-scale fault tolerant circuits implemented on hypothetical quantum information processors. Here, we extend those results by numerically studying the efficacy of this proposal as a tool for understanding the performance of an error-correction gadget implemented with fault models derived from physical simulations. Our approach is to approximate the arbitrary error maps that arise from realistic physical models with errors that are amenable to a particular classical simulation algorithm in an "honest" way; that is, such that we do not underestimate the faults introduced by our physical models. In all cases, our approximations provide an "honest representation" of the performance of the circuit composed of the original errors. This numerical evidence supports the use of our method as a way to understand the feasibility of an implementation of quantum information processing given a characterization of the underlying physical processes in experimentally accessible examples.Comment: 34 pages, 9 tables, 4 figure

Towards A Theory-Of-Mind-Inspired Generic Decision-Making Framework

Simulation is widely used to make model-based predictions, but few approaches have attempted this technique in dynamic physical environments of medium to high complexity or in general contexts. After an introduction to the cognitive science concepts from which this work is inspired and the current development in the use of simulation as a decision-making technique, we propose a generic framework based on theory of mind, which allows an agent to reason and perform actions using multiple simulations of automatically created or externally inputted models of the perceived environment. A description of a partial implementation is given, which aims to solve a popular game within the IJCAI2013 AIBirds contest. Results of our approach are presented, in comparison with the competition benchmark. Finally, future developments regarding the framework are discussed.Comment: 7 pages, 5 figures, IJCAI 2013 Symposium on AI in Angry Bird

On the Importance of Displacement History in Soft-Body Contact Models

Two approaches are commonly used for handling frictional contact within the framework of the discrete element method (DEM). One relies on the complementarity method (CM) to enforce a nonpenetration condition and the Coulomb dry-friction model at the interface between two bodies in mutual contact. The second approach, called the penalty method (PM), invokes an elasticity argument to produce a frictional contact force that factors in the local deformation and relative motion of the bodies in contact. We give a brief presentation of a DEM-PM contact model that includes multi-time-step tangential contact displacement history. We show that its implementation in an open-source simulation capability called Chrono is capable of accurately reproducing results from physical tests typical of the field of geomechanics, i.e., direct shear tests on a monodisperse material. Keeping track of the tangential contact displacement history emerges as a key element of the model. We show that identical simulations using contact models that include either no tangential contact displacement history or only single-time-step tangential contact displacement history are unable to accurately model the direct shear test

First-class models: on a noncausal language for higher-order and structurally dynamic modelling and simulation

The field of physical modelling and simulation plays a vital role in advancing numerous scientific and engineering disciplines. To cope with the increasing size and complexity of physical models, a number of modelling and simulation languages have been developed. These languages can be divided into two broad categories: causal and noncausal. Causal languages express a system model in terms of directed equations. In contrast, a noncausal model is formulated in terms of undirected equations. The fact that the causality can be left implicit makes noncausal languages more declarative and noncausal models more reusable. These are considered to be crucial advantages in many physical domains. Current, mainstream noncausal languages do not treat equational models as first-class values; that is, a model cannot be parametrised on other models or generated at simulation runtime. This results in very limited higher-order and structurally dynamic modelling capabilities, and limits the expressiveness and applicability of noncausal languages. This thesis is about a novel approach to the design and implementation of noncausal languages with first-class models supporting higher-order and structurally dynamic modelling. In particular, the thesis presents a language that enables: (1) higher-order modelling capabilities by embedding noncausal models as first-class entities into a functional programming language and (2) efficient simulation of noncausal models that are generated at simulation runtime by runtime symbolic processing and just-in-time compilation. These language design and implementation approaches can be applied to other noncausal languages. This thesis provides a self-contained reference for such an undertaking by defining the language semantics formally and providing an in-depth description of the implementation. The language provides noncausal modelling and simulation capabilities that go beyond the state of the art, as backed up by a range of examples presented in the thesis, and represents a significant progress in the field of physical modelling and simulation

Implementation by simulation; strategies for ultrasound screening for hip dysplasia in the Netherlands

Background: Implementation of medical interventions may vary with organization and available capacity. The influence of this source of variability on the cost-effectiveness can be evaluated by computer simulation following a carefully designed experimental design. We used this approach as part of a national implementation study of ultrasonographic infant screening for developmental dysplasia of the hip (DDH). Methods: First, workflow and performance of the current screening program (physical examination) was analyzed. Then, experimental variables, i.e., relevant entities in the workflow of screening, were defined with varying levels to describe alternative implementation models. To determine the relevant levels literature and interviews among professional stakeholders are used. Finally, cost-effectiveness ratios (inclusive of sensitivity analyses) for the range of implementation scenarios were calculated. Results: The four experimental variables for implementation were: 1) location of the consultation, 2) integrated with regular consultation or not, 3) number of ultrasound machines and 4) discipline of the screener. With respective numbers of levels of 3,2,3,4 in total 72 possible scenarios were identified. In our model experimental variables related to the number of available ultrasound machines and the necessity of an extra consultation influenced the cost-effectiveness most. Conclusions: Better information comes available for choosing optimised implementation strategies where organizational and capacity variables are important using the combination of simulation models and an experimental design. Information to determine the levels of experimental variables can be extracted from the literature or directly from experts

Implementation of Physical Layer Key Distribution using Software Defined Radios

It was well known from Shannon’s days that characteristics of the physical channel like attenuation, fadingand noise can impair reliable communication. But it was more recently that the beneficial side effects of channelcharacteristics in ensuring secret communication started getting attention. Studies have been made to quantify theamount of secrecy that can be reaped by combining channel coding with security protocols. The Wiretap channelproposed by Wyner is arguably one of the oldest models of physical layer security protocols. In this paper, wepresent a brief tutorial introduction to the Wiretap channel, followed by an application of the physical layer modelto a class of Key Distribution protocols. We present results from an implementation of key distribution protocolsusing Software Defined Radio tools along with physical RF hardware peripherals. We believe this approach is muchmore tangible and informative than computer based simulation studies.Defence Science Journal, 2013, 63(1), pp.6-14, DOI:http://dx.doi.org/10.14429/dsj.63.375

Quantum-kinetic perspective on photovoltaic device operation in nanostructure-based solar cells

The implementation of a wide range of novel concepts for next-generation high-efficiency solar cells is based on nanostructures with configuration-tunable optoelectronic properties. On the other hand, effective nano-optical light-trapping concepts enable the use of ultra-thin absorber architectures. In both cases, the local density of electronic and optical states deviates strongly from that in a homogeneous bulk material. At the same time, non-local and coherent phenomena like tunneling or ballistic transport become increasingly relevant. As a consequence, the semi-classical, diffusive bulk picture conventionally assumed may no longer be appropriate to describe the physical processes of generation, transport, and recombination governing the photovoltaic operation of such devices. In this review, we provide a quantum-kinetic perspective on photovoltaic device operation that reaches beyond the limits of the standard simulation models for bulk solar cells. Deviations from bulk physics are assessed in ultra-thin film and nanostructure-based solar cell architectures by comparing the predictions of the semi-classical models for key physical quantities such as absorption coefficients, emission spectra, generation and recombination rates as well as potentials, densities and currents with the corresponding properties as given by a more fundamental description based on non-equilibrium quantum statistical mechanics. This advanced approach, while paving the way to a comprehensive quantum theory of photovoltaics, bridges simulations at microscopic material and macroscopic device levels by providing the charge carrier dynamics at the mesoscale.Comment: 22 pages, 8 figures; review article based on an invited talk at the MRS Spring Meeting 2017 in Phoeni

Patient-specific simulation environment for surgical planning and preoperative rehearsal

Surgical simulation is common practice in the fields of surgical education and training. Numerous surgical simulators are available from commercial and academic organisations for the generic modelling of surgical tasks. However, a simulation platform is still yet to be found that fulfils the key requirements expected for patient-specific surgical simulation of soft tissue, with an effective translation into clinical practice. Patient-specific modelling is possible, but to date has been time-consuming, and consequently costly, because data preparation can be technically demanding. This motivated the research developed herein, which addresses the main challenges of biomechanical modelling for patient-specific surgical simulation. A novel implementation of soft tissue deformation and estimation of the patient-specific intraoperative environment is achieved using a position-based dynamics approach. This modelling approach overcomes the limitations derived from traditional physically-based approaches, by providing a simulation for patient-specific models with visual and physical accuracy, stability and real-time interaction. As a geometrically- based method, a calibration of the simulation parameters is performed and the simulation framework is successfully validated through experimental studies. The capabilities of the simulation platform are demonstrated by the integration of different surgical planning applications that are found relevant in the context of kidney cancer surgery. The simulation of pneumoperitoneum facilitates trocar placement planning and intraoperative surgical navigation. The implementation of deformable ultrasound simulation can assist surgeons in improving their scanning technique and definition of an optimal procedural strategy. Furthermore, the simulation framework has the potential to support the development and assessment of hypotheses that cannot be tested in vivo. Specifically, the evaluation of feedback modalities, as a response to user-model interaction, demonstrates improved performance and justifies the need to integrate a feedback framework in the robot-assisted surgical setting.Open Acces

First-class models: on a noncausal language for higher-order and structurally dynamic modelling and simulation

The field of physical modelling and simulation plays a vital role in advancing numerous scientific and engineering disciplines. To cope with the increasing size and complexity of physical models, a number of modelling and simulation languages have been developed. These languages can be divided into two broad categories: causal and noncausal. Causal languages express a system model in terms of directed equations. In contrast, a noncausal model is formulated in terms of undirected equations. The fact that the causality can be left implicit makes noncausal languages more declarative and noncausal models more reusable. These are considered to be crucial advantages in many physical domains. Current, mainstream noncausal languages do not treat equational models as first-class values; that is, a model cannot be parametrised on other models or generated at simulation runtime. This results in very limited higher-order and structurally dynamic modelling capabilities, and limits the expressiveness and applicability of noncausal languages. This thesis is about a novel approach to the design and implementation of noncausal languages with first-class models supporting higher-order and structurally dynamic modelling. In particular, the thesis presents a language that enables: (1) higher-order modelling capabilities by embedding noncausal models as first-class entities into a functional programming language and (2) efficient simulation of noncausal models that are generated at simulation runtime by runtime symbolic processing and just-in-time compilation. These language design and implementation approaches can be applied to other noncausal languages. This thesis provides a self-contained reference for such an undertaking by defining the language semantics formally and providing an in-depth description of the implementation. The language provides noncausal modelling and simulation capabilities that go beyond the state of the art, as backed up by a range of examples presented in the thesis, and represents a significant progress in the field of physical modelling and simulation