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2.5 The Schmidt decomposition and purifications
2.5 The Schmidt decomposition and purifications

... The goal of EPR was to show that quantum mechanics is incomplete, by demonstrating that quantum mechanics lacked some essential ‘element of reality’, by their criterion. They hoped to force a return to a more classical view of the world, one in which systems could be ascribed properties which existe ...
Simulation of Quantum Gates on a Novel GPU Architecture
Simulation of Quantum Gates on a Novel GPU Architecture

... basic building blocks of quantum computers. Recently, these GPUs are being used as general purpose multiprocessors, as they demonstrate to possess a floating point computing power larger than classic CPUs. In particular our implementation makes use of the new CUDA software/hardware architecture deve ...
University of Arizona - Materials Computation Center
University of Arizona - Materials Computation Center

Interpretive Themes in Quantum Physics: Curriculum Development and Outcomes
Interpretive Themes in Quantum Physics: Curriculum Development and Outcomes

Paper
Paper

... Abstract: The internal quantum state (IQS) is a kind of a pilot-wave (in the Bohmian sense) attached to a macroscopic system and representing its potential field continuously reduced during its exhibition to the external world. This state is maintained as decoherence-free by applying error-correctio ...
Semiconductor qubits for quantum computation
Semiconductor qubits for quantum computation

... There is a „Universal Turing machine“, that can efficiently simulate any other algorithm on any physical device ...
3D– Modern Physics
3D– Modern Physics

Semiconductor qubits for quantum computation
Semiconductor qubits for quantum computation

On the Utility of Entanglement in Quantum Neural Computing
On the Utility of Entanglement in Quantum Neural Computing

Q 18.1–18.7 - DPG
Q 18.1–18.7 - DPG

Multilinear Formulas and Skepticism of Quantum
Multilinear Formulas and Skepticism of Quantum

Feynman lectures on computation
Feynman lectures on computation

... of elementary quantum gates, single-, two-qubit... • The sequence of these quantum gates that are applied to the quantum input depends on the classical variables x and N complicatedly. • We need a classical computer processes the classical variables and produces an output that is a program for the q ...
Bohmian Mechanics
Bohmian Mechanics

Quantum law - Free Coursework for GCSE
Quantum law - Free Coursework for GCSE

Quantum Mechanical Foundations for 21st Century Business
Quantum Mechanical Foundations for 21st Century Business

... process then either accepts (actualizes) this conceptually characterized unit or rejects it, in accordance with a certain specified statistical rule. Then the process repeats, thereby repeatedly infusing conceptually characterized structure into the physically described world. Thus quantum mechanics ...
Neural Networks
Neural Networks

... • If function can be represented by perceptron, the learning algorithm is guaranteed to quickly converge to the hidden function! ...
Quantum Numbers, Spectra Calculations
Quantum Numbers, Spectra Calculations

ppt - ICTS
ppt - ICTS

slides - p-ADICS.2015
slides - p-ADICS.2015

... At this stage, the Universe was in a quantum state, which should be described by a wave function (complex valued and depends on some real parameters). But, QC is related to Planck scale phenomena - it is natural to reconsider its foundations. We maintain here the standard point of view that the wave ...
Zhang - Department of Computer Science and Engineering, CUHK
Zhang - Department of Computer Science and Engineering, CUHK

... polynomial threshold function thr(f) = O(n1/2)? • Recall that we have O(n1/2)-time quantum algorithm for any AND-OR-NOT formula • Now (roughly): thr(f) ≤ Q(f) ≤ n1/2 • This implies that formulas are learnable in time 2√n. (Matching the known lower bound.) *1: A. Klivans, R. Servedio, STOC’01; A. Kli ...
Quantum interference of large organic molecules
Quantum interference of large organic molecules

... their nominal masses. Although all samples were well characterized before the evaporation process, we can therefore not exclude some contamination with adducts or fragments in this high mass range. But even if there were a relative mass spread of 10%, this would only influence the wavelength distrib ...
Quantum interference of large organic molecules
Quantum interference of large organic molecules

New Evidence that Quantum Mechanics is Hard to Simulate on
New Evidence that Quantum Mechanics is Hard to Simulate on

... Boosters: Because it means we’ll build QCs! Skeptics: Because it means we won’t build QCs! Me: For reasons having nothing to do with building QCs! ...
Review by Robert Charman in Journal of the Society for Psychical
Review by Robert Charman in Journal of the Society for Psychical

... poets and mystics through their BL spiritual terminals. He takes as an example of shamanic communication with the BL the Dogon people’s apparent awareness that Sirius-A, the brightest star in the sky, had a Sirius-B companion as a binary star system (Sirius-B was discovered by telescope in 1862). It ...
Chapter 10 Entanglement of Quantum Systems
Chapter 10 Entanglement of Quantum Systems

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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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