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Classical phase-space analysis of vibronically coupled systems
Classical phase-space analysis of vibronically coupled systems

... On the other hand, one may be interested in the classical description of quantum systems which do not have an obvious classical analogon. For example, consider the well-known spin-boson problem, that is, an electronic two-state system (the spin) coupled to one or many vibrational degrees of freedom ...
Aggregation Operations from Quantum Computing
Aggregation Operations from Quantum Computing

... studies the uncertainty of the real world considering the principles of Quantum Mechanics (QM ). Many similarities between these two areas of research have been highlighted in several scientific papers [1], [2], [3], [4] and [5]. In this context, the logical structure describing the uncertainty asso ...
Real, Complex, and Binary Semantic Vectors
Real, Complex, and Binary Semantic Vectors

Stability of local quantum dissipative systems
Stability of local quantum dissipative systems

Shell Model Approach to Nuclear Reactions
Shell Model Approach to Nuclear Reactions

Magnetotransport in 2DEG
Magnetotransport in 2DEG

Quantum Computing
Quantum Computing

... Shannon’s theorem, error correcting codes, Turing machines and computational complexity. The principles of quantum mechanics are then outlined, and the EPR experiment described. The EPR-Bell correlations, and quantum entanglement in general, form the essential new ingredient which distinguishes quan ...
An Introduction to Deep Learning
An Introduction to Deep Learning

... feature space where input instances have desired properties for solving a particular problem. For example, in the context of supervised learning for binary classification, it is often required that the two classes are separable by an hyperplane. In the case where this property is not directly satisfie ...
Introduction to Quantum Error Correction and Fault Tolerance
Introduction to Quantum Error Correction and Fault Tolerance

... errors in a quantum memory. However, to perform quantum computing we must be able to correct errors which are happening while the computation proceeds, including errors in the gates and even the error correction procedures. The ability to use error correction so as to reduce the effect of errors on ...
talk
talk

... Consequences of a spatial limitation of entanglement Einstein et al. assume a limited interaction range of the 2 systems. Outside this range the 2 atoms have nothing to do with each other. We apply the EPR view in a very naive way (Einstein was not that naive!). Immediately after the disintegration ...
The Free Particle (PowerPoint)
The Free Particle (PowerPoint)

... The dual nature of matter (Quick Time movie 9 MB from Wilson group, *** ) Linear polarized light ( a wave function in 1-D would propagate in a similar way) (1 MB Quick time movie from the Wilson Group, *****) Circular polarized light ( ( a wave function could propagate in a similar way) (6 MB Quick ...
Applications of Artificial Intelligence in Machine Learning: Review
Applications of Artificial Intelligence in Machine Learning: Review

Chu Spaces: Automata with Quantum Aspects
Chu Spaces: Automata with Quantum Aspects

... bridge may ease the transitions of computer architecture to quantum devices, and of algorithms to quantum computing, by indicating how to relate concepts of quantum mechanics to a suitable blend of classical mechanics and automata theory, thereby capitalizing on familiar automata-theoretic intuition ...
Universal quantum simulation with prethreshold superconducting qubits: Single-excitation subspace method
Universal quantum simulation with prethreshold superconducting qubits: Single-excitation subspace method

Quantum mechanics as a representation of classical conditional
Quantum mechanics as a representation of classical conditional

Spin-valley lifetimes in a silicon quantum dot with tunable valley
Spin-valley lifetimes in a silicon quantum dot with tunable valley

Spontaneous symmetry breaking in quantum
Spontaneous symmetry breaking in quantum

The Parallel Development of Matrix and Wave Mechanics
The Parallel Development of Matrix and Wave Mechanics

Reflections on the deBroglie–Bohm Quantum Potential
Reflections on the deBroglie–Bohm Quantum Potential

... abandoning physical principles and ontological concepts that have been previously developed and have served physics successfully. Such well-established physical concepts and principles should not be given away until such time as they are clearly shown to be inappropriate, not applicable, or simply f ...
Good  Families  of  Quantum Low-Density
Good Families of Quantum Low-Density

Quantum Heat Engines and Refrigerators: Continuous Devices
Quantum Heat Engines and Refrigerators: Continuous Devices

... of hypothetical quantum heat engines and refrigerators to address these issues. Once understood, these models serve as a template for real devices. Gedanken heat engines are an integral part of thermodynamical theory. In 1824, Carnot (1) set the stage by analyzing an ideal engine. His analysis prece ...
pptx - Departamento de Matemáticas
pptx - Departamento de Matemáticas

... The Density Matrix Renormalization Group ($DMRG$) has become a powerful numerical method that can be applied to low-dimensional strongly correlated fermionic and bosonic systems. It allows for a very precise calculation of static, dynamical and thermodynamical properties. Its field of applicability ...
Ubiquitous Machine Learning
Ubiquitous Machine Learning

... Real-Time. They often have to take decisions or act upon their environment - analysis and inference has to be done in real-time. ...
Spin transport through nanostructures B. K ,
Spin transport through nanostructures B. K ,

... faster than any other time scale of the system, however, it is not possible to tunnel out of the quantum dot via such a state. In contrast, states with additional charge and/or spin are assumed to be stable. Therefore, the states of the dot that are relevant for transport can be labelled by the numb ...
Imaging electrostatically confined Dirac fermions in graphene
Imaging electrostatically confined Dirac fermions in graphene

... distribution (Fig. 4b) closely resembles the experimental eigenstate distribution (Fig. 4a). Both have a characteristic parabolic envelope due to the confinement potential, as well as a complex set of interior nodal patterns. The characteristic energy spacing seen experimentally is in good agreement ...
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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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