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Equilibrium and non-equilibrium dynamics in the quantum regime
Equilibrium and non-equilibrium dynamics in the quantum regime

Linear Circuit Analysis with Reactive Components
Linear Circuit Analysis with Reactive Components

... Solving the Schrödinger Equation on a 2D Lattice in Quantum Wave Interference (QWI) PhET Sam Reid Quantum Wave Interference allows the user to visualize the propagation of a wavefunction in the presence of potential barriers and detectors. We implement a 2D Richardson algorithm[1], a local propagati ...
Professor Jason Twamley
Professor Jason Twamley

e-the-quantum-numberssv-2
e-the-quantum-numberssv-2

Probing contextuality with superconducting quantum circuits Talk 27. Oct. 2015  ABSTRACT:
Probing contextuality with superconducting quantum circuits Talk 27. Oct. 2015 ABSTRACT:

... Contextuality is one of the most fundamental property which distinguishes quantum mechanics from classical theory. It has also been suggested to be the 'magical' resource responsible for an exponential speedup of a quantum computer. We will provide the first experimental evidence of this resource fo ...
HWU4-21 QUESTION: The principal quantum number, n, describes
HWU4-21 QUESTION: The principal quantum number, n, describes

Prof. Bertrand Reulet, Université de Sherbrooke, Canada  Talk: 23. May 2014
Prof. Bertrand Reulet, Université de Sherbrooke, Canada Talk: 23. May 2014

... Prof. Bertrand Reulet, Université de Sherbrooke, Canada Talk: 23. May 2014 ...
History and the State-of-art in Quantum Computation
History and the State-of-art in Quantum Computation

An Introduction to Quantum Computing
An Introduction to Quantum Computing

... Over the last 20 years, the field of quantum computing has been catapulted from a distant vision of celebrated physicist Richard Feynman into a rapidly expanding area of research intersecting computer science, mathematics, physics, and engineering. In this talk, we give a gentle introduction to the ...
Quantum mechanical model
Quantum mechanical model

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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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