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Quantum effects in biology
Quantum effects in biology

On the interaction of mesoscopic quantum systems with gravity
On the interaction of mesoscopic quantum systems with gravity

Quantum critical states and phase transitions in the presence of non
Quantum critical states and phase transitions in the presence of non

Quantum effects in biology
Quantum effects in biology

Spectral Analysis of Nonrelativistic Quantum Electrodynamics
Spectral Analysis of Nonrelativistic Quantum Electrodynamics

PDF only - at www.arxiv.org.
PDF only - at www.arxiv.org.

Quantum Annealing with Markov Chain Monte Carlo Simulations
Quantum Annealing with Markov Chain Monte Carlo Simulations

... computation and processing information. It intends to develop quantum computing devices for solving certain tough computational problems faster and/or more efficient than classical computers. Any computers must utilize some states of physical systems to store digits. Classical computers use voltage ...
How Quantum Theory Helps us Explain - u.arizona.edu
How Quantum Theory Helps us Explain - u.arizona.edu

Topological Orders
Topological Orders

Mixed, pure, and entangled quantum states. Density matrix
Mixed, pure, and entangled quantum states. Density matrix

... diagonal in some basis. The qubit states then evolves from a pure state into a mixed state. On the Bloch sphere this is seen as the disappearance of the components rx and ry , if the environment makes the density matrix diagonal in the z-direction. ...
Classical analogy of Fano resonances
Classical analogy of Fano resonances

LEARNING FROM OBSERVATION: Introduction Observing a task
LEARNING FROM OBSERVATION: Introduction Observing a task

... Amongst other data mining methods, decision trees have various advantages: Simple to understand and interpret. People are able to understand decision tree models after a brief explanation. Requires little data preparation. Other techniques often require data normalisation, dummy variables need to be ...
Chapter 15
Chapter 15

Negative probability
Negative probability

... Negative and Complex Probability in Quantum Information Vasil Penchev1 Abstract: “Negative probability” in practice. Quantum Communication: Very small phase space regions turn out to be thermodynamically analogical to those of superconductors. Macro-bodies or signals might exist in coherent or entan ...
A Quantum Query Expansion Approach for Session Search
A Quantum Query Expansion Approach for Session Search

Stochastic semiclassical cosmological models
Stochastic semiclassical cosmological models

... initial value formulation. Thus when our equations are averaged with respect to the stochastic source they should not be directly compared with the equations in Ref. @28#, which were obtained using an in-out functional formalism. However, the analysis carried out by Hartle on the behavior of the cos ...
Some trends in the philosophy of physics - Philsci
Some trends in the philosophy of physics - Philsci

... along these lines may currently be happening with respect to physicist’s attempts to construct a quantum theory of gravity. A recent development in this regard is that (at least some) physicists think that philosophers could be helpful in the quest (see e.g. the quotes by Rovelli and Baez in Rickles ...
..............................................................
..............................................................

... and E J2 to be 41 meV. The superconducting energy gap is 209 meV. Probe junction tunnel resistance is equal to 48 MQ (left) and 33 MQ (right). b, Energy band diagram along two lines of n g1 ¼ n 0g1 and n g2 ¼ n 0g2 ; where n 0g1 and n 0g2 are constants. Here ðn 0g1 ; n 0g2 Þ ¼ ð0:24; 0:26Þ; correspo ...
Wigner functions for arbitrary quantum systems
Wigner functions for arbitrary quantum systems

... defined [27,49], the shapes of the functions are quantitatively different; however, these functions do visualize quantum interference in the states in a similar manner. The advantage of this approach is that the Wigner function can be obtained without a multipole expansion that can be problematic to ...
The Age of Entanglement  Quantum Computing the (Formerly) Uncomputable
The Age of Entanglement Quantum Computing the (Formerly) Uncomputable

... Quantum Computing the (Formerly) Uncomputable ...
Quantum mechanical computers | SpringerLink
Quantum mechanical computers | SpringerLink

... parts are to be made of atoms, there is no fundamental limit from these sources either. We are here considering ideal machines; the effects of small imperfections will be considered later. This study is one of principle; our aim is to exhibit some Hamiltonian for a system which could serve as a comp ...
RANDOM WORDS, QUANTUM STATISTICS, CENTRAL LIMITS
RANDOM WORDS, QUANTUM STATISTICS, CENTRAL LIMITS

Document
Document

Optimal Large-Scale Quantum State Tomography with Pauli
Optimal Large-Scale Quantum State Tomography with Pauli

... structure of the unknown matrix, these approaches can often be applied to estimate unknown matrices of high dimensions. Yet these methods do not fully account for the specific structure of quantum state tomography. As demonstrated in a pioneering article, Gross et al. (2010) argued that, when consid ...
Quantum computation of scattering in scalar quantum field theories
Quantum computation of scattering in scalar quantum field theories

... large amount of effort devoted to finding additional quantum algorithms offering exponential speedup. This turns out to be very difficult. At present, only relatively few problems have been discovered admitting exponential quantum speedup [7], including simulating nonrelativistic many-body quantum s ...
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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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