Application of multi-core and cluster computing to the Transmission Line Matrix method

The Transmission Line Matrix (TLM) method is an existing and established mathematical method for conducting computational electromagnetic (CEM) simulations. TLM models Maxwell s equations by discretising the contiguous nature of an environment and its contents into individual small-scale elements and it is a computationally intensive process. This thesis focusses on parallel processing optimisations to the TLM method when considering the opposing ends of the contemporary computing hardware spectrum, namely large-scale computing systems versus small-scale mobile computing devices. Theoretical aspects covered in this thesis are: The historical development and derivation of the TLM method. A discrete random variable (DRV) for rain-drop diameter,allowing generation of a rain-field with raindrops adhering to a Gaussian size distribution, as a case study for a 3-D TLM implementation. Investigations into parallel computing strategies for accelerating TLM on large and small-scale computing platforms. Implementation aspects covered in this thesis are: A script for modelling rain-fields using free-to-use modelling software. The first known implementation of 2-D TLM on mobile computing devices. A 3-D TLM implementation designed for simulating the effects of rain-fields on extremely high frequency (EHF) band signals. By optimising both TLM solver implementations for their respective platforms, new opportunities present themselves. Rain-field simulations containing individual rain-drop geometry can be simulated, which was previously impractical due to the lengthy computation times required. Also, computationally time-intensive methods such as TLM were previously impractical on mobile computing devices. Contemporary hardware features on these devices now provide the opportunity for CEM simulations at speeds that are acceptable to end users, as well as providing a new avenue for educating relevant user cohorts via dynamic presentations of EM phenomena

Loss tolerant linear optical quantum memory by measurement-based quantum computing

We give a scheme for loss tolerantly building a linear optical quantum memory which itself is tolerant to qubit loss. We use the encoding recently introduced in Varnava et al 2006 Phys. Rev. Lett. 97 120501, and give a method for efficiently achieving this. The entire approach resides within the 'one-way' model for quantum computing (Raussendorf and Briegel 2001 Phys. Rev. Lett. 86 5188–91; Raussendorf et al 2003 Phys. Rev. A 68 022312). Our results suggest that it is possible to build a loss tolerant quantum memory, such that if the requirement is to keep the data stored over arbitrarily long times then this is possible with only polynomially increasing resources and logarithmically increasing individual photon life-times

The Loughborough wave lab - a mobile virtual electromagnetics laboratory for iOS devices

Modern mobile devices have now advanced to a point where they can execute computationally-intensive mathematical problems. The Transmission Line Matrix Modelling method (TLM) is a time-domain method allowing the computation of two and three dimensional electromagnetic fields and structures. TLM is able to model complex scenarios whilst utilising a computationally simple method to model structures in discrete spatial units. This paper presents an iOS App based around a TLM solver. The simulation output is presented on the screen as the simulation progresses. The performance of the iPhone is sufficient to visualise full-field simulations and to provide an interactive interface for the user. Discussion of relative performance on successive generations of iOS devices will be presented

A mobile virtual electromagnetics laboratory for iPhone

Modern mobile devices have now advanced to a point where they can execute computationally-intensive mathematical problems. The Transmission Line Matrix Modelling method (TLM) is a time-domain method allowing the computation of two and three dimensional electromagnetic fields and structures. TLM is able to model complex scenarios whilst utilising a computationally simple method to model structures in discrete spatial units. This paper presents an iPhone Application (App) containing a TLM solver. The simulation output is presented on the screen as the simulation progresses. The performance of the iPhone is sufficient to visualise full-field simulations and to provide an interactive interface for the user

What Fraction of Gravitational Lens Galaxies Lie in Groups?

We predict how the observed variations in galaxy populations with environment affect the number and properties of gravitational lenses in different environments. Two trends dominate: lensing strongly favors early-type galaxies, which tend to lie in dense environments, but dense environments tend to have a larger ratio of dwarf to giant galaxies than the field. The two effects nearly cancel, and the distribution of environments for lens and non-lens galaxies are not substantially different (lens galaxies are slightly less likely than non-lens galaxies to lie in groups and clusters). We predict that about 20% of lens galaxies are in bound groups (defined as systems with a line-of-sight velocity dispersion sigma in the range 200 < sigma < 500 km/s), and another roughly 3% are in rich clusters (sigma > 500 km/s). Therefore at least roughly 25% of lenses are likely to have environments that significantly perturb the lensing potential. If such perturbations do not significantly increase the image separation, we predict that lenses in groups have a mean image separation that is about 0.2'' smaller than that for lenses in the field and estimate that 20-40 lenses in groups are required to test this prediction with significance. The tail of the distribution of image separations is already illuminating. Although lensing by galactic potential wells should rarely produce lenses with image separations theta >~ 6'', two such lenses are seen among 49 known lenses, suggesting that environmental perturbations of the lensing potential can be significant. Further comparison of theory and data will offer a direct probe of the dark halos of galaxies and groups and reveal the extent to which they affect lensing estimates of cosmological parameters.Comment: 32 pages, 6 embedded figures; accepted for publication in Ap

Multiplex Microsphere PCR (mmPCR) Allows Simultaneous Gram Typing, Detection of Fungal DNA, and Antibiotic Resistance Genes

Objective: To show the high analytical specificity of our multiplex microsphere polymerase chain reaction (mmPCR) method, which offers the simultaneous detection of both general (eg, Gram type) and specific (eg, Pseudomonas species) clinically relevant genetic targets in a single modular multiplex reaction. Materials and Methods: Isolated gDNA of 16S/rRNA Sanger-sequenced and Basic Local Alignment Tool–identified bacterial and fungal isolates were selectively amplified in a custom 10-plex Luminex MagPlex-TAG microsphere-based mmPCR assay. The signal/noise ratio for each reaction was calculated from flow cytometry standard data collected on a BD LSR Fortessa II flow cytometer. Data were normalized to the no-template negative control and the signal maximum. The analytical specificity of the assay was compared to single-plex SYBR chemistry quantitative PCR. Results: Both general and specific primer sets were functional in the 10-plex mmPCR. The general Gram typing and pan-fungal primers correctly identified all bacterial and fungal isolates, respectively. The species-specific and antibiotic resistance–specific primers correctly identified the species- and resistance-carrying isolates, respectively. Low-level cross-reactive signals were present in some reactions with high signal/noise primer ratios. Conclusion: We found that mmPCR can simultaneously detect specific and general clinically relevant genetic targets in multiplex. These results serve as a proof-of-concept advance that highlights the potential of high multiplex mmPCR diagnostics in clinical practice. Further development of specimen-specific DNA extraction techniques is required for sensitivity testing

Brokered Graph State Quantum Computing

We describe a procedure for graph state quantum computing that is tailored to fully exploit the physics of optically active multi-level systems. Leveraging ideas from the literature on distributed computation together with the recent work on probabilistic cluster state synthesis, our model assigns to each physical system two logical qubits: the broker and the client. Groups of brokers negotiate new graph state fragments via a probabilistic optical protocol. Completed fragments are mapped from broker to clients via a simple state transition and measurement. The clients, whose role is to store the nascent graph state long term, remain entirely insulated from failures during the brokerage. We describe an implementation in terms of NV-centres in diamond, where brokers and clients are very naturally embodied as electron and nuclear spins.Comment: 5 pages, 3 figure

Generalized Flow and Determinism in Measurement-based Quantum Computation

We extend the notion of quantum information flow defined by Danos and Kashefi for the one-way model and present a necessary and sufficient condition for the deterministic computation in this model. The generalized flow also applied in the extended model with measurements in the X-Y, X-Z and Y-Z planes. We apply both measurement calculus and the stabiliser formalism to derive our main theorem which for the first time gives a full characterization of the deterministic computation in the one-way model. We present several examples to show how our result improves over the traditional notion of flow, such as geometries (entanglement graph with input and output) with no flow but having generalized flow and we discuss how they lead to an optimal implementation of the unitaries. More importantly one can also obtain a better quantum computation depth with the generalized flow rather than with flow. We believe our characterization result is particularly essential for the study of the algorithms and complexity in the one-way model.Comment: 16 pages, 10 figure

Draft Nuclear Genome Sequence of the Liquid Hydrocarbon-Accumulating Green Microalga Botryococcus braunii Race B (Showa).

Botryococcus braunii has long been known as a prodigious producer of liquid hydrocarbon oils that can be converted into combustion engine fuels. This draft genome for the B race of B. braunii will allow researchers to unravel important hydrocarbon biosynthetic pathways and identify possible regulatory networks controlling this unusual metabolism