Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Quantum mechanics---the theory describing the fundamental workings of nature---is famously counterintuitive: it predicts that a particle can be in two places at the same time, and that two remote particles can be inextricably and instantaneously linked These predictions have been the topic of intense metaphysical debate ever since the theory's inception early last century However, supreme predictive power combined with direct experimental observation of some of these unusual phenomena leave little doubt as to its fundamental correctness In fact, without quantum mechanics we could not explain the workings of a laser, nor indeed how a fridge magnet operates Over the last several decades quantum information science has emerged to seek answers to the question: can we gain some advantage by storing, transmitting and processing information encoded in systems that exhibit these unique quantum properties? Today it is understood that the answer is yes Many research groups around the world are working towards one of the most ambitious goals humankind has ever embarked upon: a quantum computer that promises to exponentially improve computational power for particular tasks A number of physical systems, spanning much of modern physics, are being developed for this task---ranging from single particles of light to superconducting circuits---and it is not yet clear which, if any, will ultimately prove successful Here we describe the latest developments for each of the leading approaches and explain what the major challenges are for the future

Quantum Computing

Recent progress implies that a crossover between machine learning and quantum information processing benefits both fields. Traditional machine learning has dramatically improved the benchmarking an ...

Quantum machine learning

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

The control of individual quantum systems promises a new technology for the 21st century – quantum technology. This book is the first comprehensive treatment of modern quantum measurement and measurement-based quantum control, which are vital elements for realizing quantum technology. Readers are introduced to key experiments and technologies through dozens of recent experiments in cavity QED, quantum optics, mesoscopic electronics, and trapped particles several of which are analyzed in detail. Nearly 300 exercises help build understanding, and prepare readers for research in these exciting areas. This important book will interest graduate students and researchers in quantum information, quantum metrology, quantum control and related fields. Novel topics covered include adaptive measurement; realistic detector models; mesoscopic current detection; Markovian, state-based and optimal feedback; and applications to quantum information processing.

/pdf/quantum-measurement-and-control-1zwwhweisi.pdf

Quantum Measurement and Control

Optimized NMR spectroscopic method for the configurational analysis of chemically equivalent vicinal protons.

Quantum control plays a key role in quantum technology, e.g. for steering quantum hardware systems, spectrometers or superconducting solid-state devices. In terms of computation, quantum systems provide a unique potential for coherent parallelisation that may exponentially speed up algorithms as in Shor's prime factorisation. Translating quantum software into a sequence of classical controls steering the quantum hardware, viz. the quantum compilation task, lends itself to be tackled by optimal control. It is computationally demanding since the classical resources needed grow exponentially with the size of the quantum system. Here we show concepts of parallelisation tailored to run on high-end computer clusters speeding up matrix multiplication, exponentials, and trace evaluations used in numerical quantum control. In systems of 10 spin qubits, the time gain is beyond a factor of 500 on a 128-cpu cluster as compared to standard techniques on a single cpu.

/pdf/parallelising-matrix-operations-on-clusters-for-an-optimal-3744a3q5sv.pdf

Parallelising matrix operations on clusters for an optimal control-based quantum compiler

Nuclear magnetic resonance (NMR) microscopy allows to image and to quantify the distribution of NMR-active nuclei in living specimen. Using high-field NMR microscopy at 14.1 T magnetic field strength and strong gradients up to 3 T/m, we show in this study that separation of fat and water nuclear resonances in living insects can be achieved. Comparing it to destructive conventional photometric and weighing measurements, we demonstrate exemplarily in the European spruce bark beetle, that NMR can be efficiently used to quantify absolute fat and water content in living insects. Additionally, anatomic images with a spatial in-plane resolution up to 10 μm and with high soft tissue contrast were acquired. For the first time, we demonstrate, that fat distribution and fat consumption of living insects can be obtained by magnetic resonance imaging (MRI). This enables future research to address questions where single individuals have to be measured several times, which is not possible with conventional destructive methods.

/pdf/non-invasive-lipid-measurement-in-living-insects-using-nmr-4t9twv13mo.pdf

Non-invasive lipid measurement in living insects using NMR microscopy

We analyze the saturation of a nuclear magnetic resonance (NMR) signal using optimal magnetic fields. We consider both the problems of minimizing the duration of the control and its energy for a fixed duration. We solve the optimal control problems by using geometric methods and a purely numerical approach, the grape algorithm, the two methods being based on the application of the Pontryagin maximum principle. A very good agreement is obtained between the two results. The optimal solutions for the energy-minimization problem are finally implemented experimentally with available NMR techniques.

Steffen J. Glaser

Papers

Optimized NMR spectroscopic method for the configurational analysis of chemically equivalent vicinal protons.

Parallelising matrix operations on clusters for an optimal control-based quantum compiler

Non-invasive lipid measurement in living insects using NMR microscopy

Geometric versus numerical optimal control of a dissipative spin-(1/2) particle

"Kin " HEHAHA Sequences, Heteronuclear Hartmann-Hahn Transfer with Different Bandwidths for Spins I and S