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Theoretical Physics (Mathematical and Computitional Physics
Theoretical Physics (Mathematical and Computitional Physics

... 3.3 McD93 E.W. McDaniel, J.B.A. Mitchell, M.E. Rudd, Atomic Collisions: Heavy Particle Projectiles, Wiley, New York, 1993. 3.3 Mos70 G.M. Mossop, Advanced Level Atomic Physics, University of London Press, 1970. 3.3 Sla60 J.C. Slater, Quantum Theory of Atomic Structure, Vol.1, McGraw-Hill, New York, ...
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... how to let machines to have intelligence. It is also a modern research area. We will mainly learn machine learning especially learning algorithms, applications. Machine learning, pattern recognition, vision based learning and the corresponding ...
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... Intensive laboratory research over much of the past decade at the Technical University of Eindhoven 1 and at Blacklight Power, see Ref. [3] for a review of the several publications in refereed journals, on what has come to be known as the “hydrino” state of hydrogen has sent theorists scurrying to e ...
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Do Global Virtual Axionic Gravitons Exist?

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... • The collection of coefficients in the expansion of a state function in any complete set is merely an alternate way to represent the state function. • These coefficients and the eigenfunctions contain the same information as the state function. • Expressing a state function in terms of eigenfunctio ...
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Quantum Mechanics in 3

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Chapter 7 Quantum Field Theory on Curved Spacetimes

... We decompose the field φ via a Fourier transform into a series of modes of spacial wave vector ~k, so that the amplitude of each mode satisfies the same equation as a classical harmonic oscillator and then treat each mode by the rules of ordinary quantum mechanics. It is convenient to imagine the fi ...
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Project Summary - Department of Electrical Engineering

... heterostructure quantum wells (inter- and intra-band transitions)” students will study properties of objects with dimensionality higher than quantum dots – quantum wells, which are two-dimensional objects. In this experiment the students will create a quasi-monochromatic light beam using the combina ...
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PPT - Fernando Brandao

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... overlap with the quantum dots will be explored. The first is to use quantum dots inside micro pillars that containing optical lensing through the use of tapered oxidation layer. The second is to develop a technique to position a single quantum dot in the center of an optical micro cavity. The second ...
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Particle control in a quantum world

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Statistical Physics

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... resolved by optical imaging. So Zwierlein and colleagues magnified the vortex cores and the whole vortex lattice by turning off the laser trap and releasing the system into free space, where it expanded. They also increased the size of the vortex cores, and thus their visibility, by changing the int ...
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Quantum machine learning

Quantum machine learning is a newly emerging interdisciplinary research area between quantum physics and computer science that summarises efforts to combine quantum mechanics with methods of machine learning. Quantum machine learning models or algorithms intend to use the advantages of quantum information in order to improve classical methods of machine learning, for example by developing efficient implementations of expensive classical algorithms on a quantum computer. However, quantum machine learning also includes the vice versa approach, namely applying classical methods of machine learning to quantum information theory.Although yet in its infancy, quantum machine learning is met with high expectations of providing a solution for big data analysis using the ‘parallel’ power of quantum computation. This trend is underlined by recent investments of companies such as Google and Microsoft into quantum computing hardware and research. However, quantum machine learning is still in its infancy and requires more theoretical foundations as well as solid scientific results in order to mature to a full academic discipline.
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