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Three Puzzles about Bohr`s Correspondence Principle
Three Puzzles about Bohr`s Correspondence Principle

... rejects this view that the correspondence principle can be thought of as an analogy between the two theories. He writes, In Q.o.L [Bohr 1918] this designation has not yet been used, but the substance of the principle is referred to there as a formal analogy between the quantum theory and the classic ...
Quantum process tomography of two-qubit controlled-Z
Quantum process tomography of two-qubit controlled-Z

... controlled-Z 共CZ兲 gates.3,5 Because the CZ gate is simple to implement, has high fidelity and can readily generate controlled-NOT 共CNOT兲 logic,6 it likely will be an important component in more complex algorithms such as quantum error correction. At present, however, the CZ gate functionality has on ...
Quantization of bi-Hamiltonian systems J.
Quantization of bi-Hamiltonian systems J.

The Tenth Rochester Conferences on Coherence Quantum Information and Measurement
The Tenth Rochester Conferences on Coherence Quantum Information and Measurement

Change Without Time - Publikationsserver der Universität Regensburg
Change Without Time - Publikationsserver der Universität Regensburg

... in general relativity), an internal notion of time becomes meaningful. This similarity between quantum mechanics and general relativity was recognized in the context of quantum gravity by Carlo Rovelli, who proposed a relational concept of quantum time in 1990. He showed in a two-oscillator model th ...
43-4.pdf
43-4.pdf

The Emergence and Interpretation of Probability
The Emergence and Interpretation of Probability

Monte Carlo Simulations of Quantum Spin Models - cond
Monte Carlo Simulations of Quantum Spin Models - cond

... in this volume. In devising QMC simulation methods, two major steps need to be taken: (i) The quantum partition function must be reformulated in a way as to allow stochastic sampling over a space of effective configurations, such that each contributing configuration has a positive statistical weight ...
Probability in Bohmian Mechanics[1]
Probability in Bohmian Mechanics[1]

arXiv:quant-ph/0202122 v1 21 Feb 2002
arXiv:quant-ph/0202122 v1 21 Feb 2002

Post-quantum Security of the CBC, CFB, OFB, CTR
Post-quantum Security of the CBC, CFB, OFB, CTR

Existential Contextuality and the Models of Meyer, Kent and Clifton
Existential Contextuality and the Models of Meyer, Kent and Clifton

Slide 1
Slide 1

... Sub-shot-noise sensitivities can be obtained using the sensitivity of the quantum state to displacements, which is related to the sub-Planck phase space structure extracted from its Wigner function. A number of proposals have been advanced for generating single particle cat and generalized states, s ...
Combining Rule Induction and Reinforcement Learning
Combining Rule Induction and Reinforcement Learning

Do You Need to Believe in Orbitals to Use Them - Philsci
Do You Need to Believe in Orbitals to Use Them - Philsci

Cavity dark states for quantum computing M.S. Shahriar , J.A. Bowers
Cavity dark states for quantum computing M.S. Shahriar , J.A. Bowers

A logico-conceptual analysis of the Einstein-Podolsky
A logico-conceptual analysis of the Einstein-Podolsky

... these magnitudes are positions and momenta; a much simpler version was later devised by David Bohm, in terms of spin components (Bohm 1951). The measurement of one of these quantities on one of the objects of the pair allows us to infer with certainty the measurement result of the same quantity for ...
Dynamical Aspects of Information Storage in Quantum
Dynamical Aspects of Information Storage in Quantum

... reliable discrimination between any two density operators with nonorthogonal supports), (b) practical constraints imposed by the specific experimental setting (e.g., impossibility of synthesizing any quantum state or any quantum operation with arbitrary precision), and (c) environment-induced noise. ...
Hubbard model description of silicon spin qubits: charge stability
Hubbard model description of silicon spin qubits: charge stability

Quantum Computation: Theory and Implementation
Quantum Computation: Theory and Implementation

REDUCED AND EXTENDED WEAK COUPLING LIMIT
REDUCED AND EXTENDED WEAK COUPLING LIMIT

... quantum Langevin dynamics equals i[Z, ·] where Z is a self-adjoint operator that does not look like a physically realistic Hamiltonian. In particular, it is unbounded from both below and above. Thus one can question the physical relevance of this construction. It turns out, however, that one can ext ...
Phys. Rev. B 94, 195305 (2016) - Petta Group
Phys. Rev. B 94, 195305 (2016) - Petta Group

Finite-temperature mutual information in a simple phase transition
Finite-temperature mutual information in a simple phase transition

Two Provers in Isolation
Two Provers in Isolation

... The starting point of this research is clearly the Bit Commitment scheme introduced by BenOr, Goldwasser, Kilian and Wigderson [BGKW88]. The security of a Two-Prover Bit Commitment scheme against quantum adversaries has been considered in the past in the work of Brassard, Crépeau, Mayers and Salvai ...
5.3 Atomic Emission Spectra and the Quantum Mechanical Model
5.3 Atomic Emission Spectra and the 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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