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Quantum entanglement in photosynthetic light harvesting complexes
Quantum entanglement in photosynthetic light harvesting complexes

The density-matrix renormalization group in the age of matrix
The density-matrix renormalization group in the age of matrix

Quantum Memory in Atomic Ensembles - Oxford Physics
Quantum Memory in Atomic Ensembles - Oxford Physics

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Ph.D. Thesis Chirag Dhara

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Cavity Induced Interfacing of Atoms and Light

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Some New Classical and Semiclassical Models for Describing

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Generating random density matrices

Development of a Silicon Semiconductor Quantum Dot Qubit with
Development of a Silicon Semiconductor Quantum Dot Qubit with

Development of a Silicon Semiconductor Quantum Dot Qubit with
Development of a Silicon Semiconductor Quantum Dot Qubit with

... Semiconductor quantum dots in silicon demonstrate exceptionally long spin lifetimes as qubits and are therefore promising candidates for quantum information processing. However, control and readout techniques for these devices have thus far employed low frequency electrons, in contrast to high speed ...
The Emperor`s New Mind by Roger Penrose
The Emperor`s New Mind by Roger Penrose

... Not only is the universe 'out there', but mathematical truth also has its own mysterious independence and timelessness. Like Newton and Einstein, Penrose has a profound sense of humility and awe toward both the physical world and the Platonic realm of pure mathematics. The distinguished number theor ...
The density-matrix renormalization group in the age of matrix
The density-matrix renormalization group in the age of matrix

Spin Foam Models of Quantum Spacetime
Spin Foam Models of Quantum Spacetime

... gravity. They aim to represent a formulation of quantum gravity which is fully background independent and non-perturbative, in that they do not rely on any pre-existing fixed geometric structure, and covariant, in the spirit of path integral formulations of quantum field theory. Many different appro ...
Completeness and the zx-calculus
Completeness and the zx-calculus

Entanglement Entropy in a Triangular Billiard
Entanglement Entropy in a Triangular Billiard

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- Philsci-Archive

... What I am doing is using history as a guide to a tentative clarification of some unclear aspects of the theory. Since I am not taking into account more recent contributions, a work that goes back to the early fifties of last century and before might seem dated. Here I must distinguish between the a ...
Quantum Control for Scientists and Engineers
Quantum Control for Scientists and Engineers

... processes themselves, but do not cover either practical algorithms for state estimation or filtering theory, which are essential for stochastic optimal control. Here, we address both topics. The necessary background on classical probability theory as well as classical filtering is provided. As in th ...
Entanglement in many body quantum systems Arnau Riera Graells
Entanglement in many body quantum systems Arnau Riera Graells

Springer Tracts in Modern Physics
Springer Tracts in Modern Physics

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University of Florida - University of Missouri

...   tij  aa ab vac    a j ai  HF ...
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QUANTUM COMPUTING

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In Search of Quantum Reality

... 1.4.1.4 Final Thoughts: What is It All About? . . . . . Into the Microworld . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5.1 Duality and The Double Slit . . . . . . . . . . . . . . . . . 1.5.1.1 A Short Digression: How Science Works . . . . . 1.5.1.2 Waves versus Particles . . . . . . . . ...
Full-Text PDF
Full-Text PDF

Nonlocality in multipartite correlation networks  LARS ERIK WÜRFLINGER
Nonlocality in multipartite correlation networks LARS ERIK WÜRFLINGER

Studies in plausibility theory, with applications to physics
Studies in plausibility theory, with applications to physics

Quasi Classical Trajectory Binning: A Systematic
Quasi Classical Trajectory Binning: A Systematic

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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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