Search for dissertations about: "physics computer"
Showing result 1 - 5 of 268 swedish dissertations containing the words physics computer.
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1. Development of theoretical approaches for post-silicon information processing
Abstract : Despite knowing the fundamental equations in most of the physics research areas, still there is an unceasing need for theoretical method development, thanks to the more and more challenging problems addressed by the research community. The investigation of post-silicon, non-classical information processing is one of the new and rapidly developing areas that requires tremendous amount of theoretical support, new understanding, and accurate theoretical predictions. READ MORE
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2. Characterisation and Modeling of Coupled-Core Optical Fibers
Abstract : The growth in data traffic coupled with trends in internet use will result in a requirement for interfaces of the network to reach Tb/s data rate in the future. Considering this, novel transmission techniques that can increase the data rate with orders of magnitude must be considered. READ MORE
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3. Exploring patterns of empirical networks
Abstract : We are constantly struggling to understand how nature works, trying to identify recurrent events and looking for analogies and relations between objects or individuals. Knowing patterns of behavior is powerful and fundamental for survival of any species. READ MORE
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4. On the control of virtual violins : Physical modelling and control of bowed string instruments
Abstract : This thesis treats the control of sound synthesis of bowed string instruments based on physical modelling. The work followed two approaches: (a) a systematic exploration of the influence of control parameters (bow force, bow velocity, and bow-bridge distance) on the output of a physical model of the violin, and (b) measurements and analyses of the bowing parameters in real violin playing in order to model and parameterize basic classes of bowing patterns for synthesis control. READ MORE
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5. Data Analysis in High-Energy Physics as a Differentiable Program
Abstract : Machine learning methods are now ubiquitous in physics, but often target objectives that are one or two steps removed from our physics goals. A prominent example of this is the discrimination between signal and background processes, which doesn’t account for the presence of systematic uncertainties – something crucial for the calculation of quantities such as the discovery significance and upper limits. READ MORE