Laser pulse shape designer for direct-drive inertial confinement fusion

A pulse shape designer for direct drive inertial confinement fusion has been developed, it aims at high compression of the fusion fuel while keeping hydrodynamics instability within tolerable level. Fast linear analysis on implosion instability enables the designer to fully scan the vast pulse configuration space at a practical computational cost, machine learning helps to summarize pulse performance into an implicit scaling metric that promotes the pulse shape evolution. The designer improves its credibility by incorporating various datasets including extra high-precision simulations or experiments. When tested on the double-cone ignition scheme [J. Zhang et al, Phil. Trans. R. Soc. A. 378.2184 (2020)], optimized pulses reach the assembly requirements, show significant imprint mitigation and adiabatic shaping capability, and have the potential to achieve better implosion performance in real experiments. This designer serves as an efficient alternative to traditional empirical pulse shape tuning procedure, reduces workload and time consumption. The designer can be used to quickly explore the unknown parameter space for new direct-drive schemes, assists design iteration and reduces experiment risk

Compressive Mining: Fast and Optimal Data Mining in the Compressed Domain

Real-world data typically contain repeated and periodic patterns. This suggests that they can be effectively represented and compressed using only a few coefficients of an appropriate basis (e.g., Fourier, Wavelets, etc.). However, distance estimation when the data are represented using different sets of coefficients is still a largely unexplored area. This work studies the optimization problems related to obtaining the \emph{tightest} lower/upper bound on Euclidean distances when each data object is potentially compressed using a different set of orthonormal coefficients. Our technique leads to tighter distance estimates, which translates into more accurate search, learning and mining operations \textit{directly} in the compressed domain. We formulate the problem of estimating lower/upper distance bounds as an optimization problem. We establish the properties of optimal solutions, and leverage the theoretical analysis to develop a fast algorithm to obtain an \emph{exact} solution to the problem. The suggested solution provides the tightest estimation of the $L_2$-norm or the correlation. We show that typical data-analysis operations, such as k-NN search or k-Means clustering, can operate more accurately using the proposed compression and distance reconstruction technique. We compare it with many other prevalent compression and reconstruction techniques, including random projections and PCA-based techniques. We highlight a surprising result, namely that when the data are highly sparse in some basis, our technique may even outperform PCA-based compression. The contributions of this work are generic as our methodology is applicable to any sequential or high-dimensional data as well as to any orthogonal data transformation used for the underlying data compression scheme.Comment: 25 pages, 20 figures, accepted in VLD

Testing for delay defects utilizing test data compression techniques

textAs technology shrinks new types of defects are being discovered and new fault models are being created for those defects. Transition delay and path delay fault models are two such models that have been created, but they still fall short in that they are unable to obtain a high test coverage of smaller delay defects; these defects can cause functional behavior to fail and also indicate potential reliability issues. The first part of this dissertation addresses these problems by presenting an enhanced timing-based delay fault testing technique that incorporates the use of standard delay ATPG, along with timing information gathered from standard static timing analysis. Utilizing delay fault patterns typically increases the test data volume by 3-5X when compared to stuck-at patterns. Combined with the increase in test data volume associated with the increase in gate count that typically accompanies the miniaturization of technology, this adds up to a very large increase in test data volume that directly affect test time and thus the manufacturing cost. The second part of this dissertation presents a technique for improving test compression and reducing test data volume by using multiple expansion ratios while determining the configuration of the scan chains for each of the expansion ratios using a dependency analysis procedure that accounts for structural dependencies as well as free variable dependencies to improve the probability of detecting faults. Finally, this dissertation addresses the problem of unknown values (X’s) in the output response data corrupting the data and degrading the performance of the output response compactor and thus the overall amount of test compression. Four techniques are presented that focus on handling response data with large percentages of X’s. The first uses X-canceling MISR architecture that is based on deterministically observing scan cells, and the second is a hybrid approach that combines a simple X-masking scheme with the X-canceling MISR for further gains in test compression. The third and fourth techniques revolve around reiterative LFSR X-masking, which take advantage of LFSR-encoded masks that can be reused for multiple scan slices in novel ways.Electrical and Computer Engineerin

Image Processing Using FPGAs

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs

Optical sampling and metrology using a soliton-effect compression pulse source

A low jitter optical pulse source for applications including optical sampling and optical metrology was modelled and then experimentally implemented using photonic components. Dispersion and non-linear fibre effects were utilised to compress a periodic optical waveform to generate pulses of the order of 10 picoseconds duration, via soliton-effect compression. Attractive features of this pulse source include electronically tuneable repetition rates greater than 1.5 GHz, ultra-short pulse duration (10-15 ps), and low timing jitter as measured by both harmonic analysis and single-sideband (SSB) phase noise measurements. The experimental implementation of the modelled compression scheme is discussed, including the successful removal of stimulated Brillouin scattering (SBS) through linewidth broadening by injection dithering or phase modulation. Timing jitter analysis identifies many unwanted artefacts generated by the SBS suppression methods, hence an experimental arrangement is devised (and was subsequently patented) which ensures that there are no phase modulation spikes present on the SSB phase noise spectrum over the offset range of interest for optical sampling applications, 10Hz-Nyquist. It is believed that this is the first detailed timing jitter study of a soliton-effect compression scheme. The soliton-effect compression pulses are then used to perform what is believed to be the first demonstration of optical sampling using this type of pulse source. The pulse source was also optimised for use in a novel optical metrology (range finding) system, which is being developed and patented under European Space Agency funding as an enabling technology for formation flying satellite missions. This new approach to optical metrology, known as Scanning Interferometric Pulse Overlap Detection (SIPOD), is based on scanning the optical pulse repetition rate to find the specific frequencies which allow the return pulses from the outlying satellite, i.e. the measurement arm, to overlap exactly with a reference pulse set on the hub satellite. By superimposing a low frequency phase modulation onto the optical pulse train, it is possible to detect the pulse overlap condition using conventional heterodyne detection. By rapidly scanning the pulse repetition rate to find two frequencies which provide the overlapping pulse condition, high precision optical pulses can be used to provide high resolution unambiguous range information, using only relatively simple electronic detection circuitry. SIPOD’s maximum longitudinal range measurement is limited only by the coherence length of the laser, which can be many tens of kilometres. Range measurements have been made to better than 10 microns resolution over extended duration trial periods, at measurement update rates of up to 470 Hz. This system is currently scheduled to fly on ESA’s PROBA-3 mission in 2012 to measure the intersatellite spacing for a two satellite coronagraph instrument. In summary, this thesis is believed to present three novel areas of research: the first detailed jitter characterisation of a soliton-effect compression source, the first optical sampling using such a compression source, and a novel optical metrology range finding system, known as SIPOD, which utilises the tuneable repetition rate and highly stable nature of the compression source pulses