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Kondo, Fano and Dicke effects in side quantum dots
Kondo, Fano and Dicke effects in side quantum dots

... The transmission spectrum shows a structure with two antiresonances localized at the bonding and antibonding renormalized energies of the quantum-dot molecule, and one resonance at the renormalized site energy of the outside quantum-dot. The LDOS at each dot shows that when the Kondo correlations ar ...
Quantum Statistics - Ole Witt
Quantum Statistics - Ole Witt

... Analytical mechanics is characterized by describing a mechanical system in generalized coordinates usually denoted: q1, q2, q3,…,qn. Differentiating with respect to time is indicated with a bullet above the variable e.g. q  dq / dt , so that q1 , q 2 , q 3 ,..., q n represents the generalized ...
arXiv:1501.01373v2 [physics.hist
arXiv:1501.01373v2 [physics.hist

... theories are fundamentally different from classical theories. No-one should dare to compare a simple computer model such as a cellular automaton based on the integers, with a fully quantized field theory. Yet here we find a quantum field system and an automaton that are based on states that neatly c ...
Quantum one-time programs
Quantum one-time programs

Lecture 12: Holevo`s theorem and Nayak`s bound
Lecture 12: Holevo`s theorem and Nayak`s bound

... We will now consider a related, but nevertheless different setting from the one that Holevo’s theorem concerns. Suppose now that Alice has m bits, and she wants to encode them into fewer than n qubits in such a way that Bob can recover not the entire string of bits, but rather any single bit (or sma ...
The Zeno`s paradox in quantum theory
The Zeno`s paradox in quantum theory

Quantum NP - A Survey Dorit Aharonov and Tomer Naveh
Quantum NP - A Survey Dorit Aharonov and Tomer Naveh

Classical/Quantum Dynamics in a Uniform Gravitational Field: B
Classical/Quantum Dynamics in a Uniform Gravitational Field: B

Average-Case Quantum Query Complexity
Average-Case Quantum Query Complexity

... of these de nitions, however, is that the average-case performance of polynomially related algorithms can be superpolynomially apart (we will see this happen in Section 5). This seemingly paradoxical e ect makes these de nitions unsuitable for dealing with polynomial-time reducibilities and average- ...
H. Lee
H. Lee

... If the system is insulating, and if the filling factor = p/q, the ground state is q-fold degenerate. Usually the required degeneracy is achieved by long range order. Can a fractional filled insulator exist without symmetry breaking ? Oshikawa PRL 2000 ...
Quantum numbers for relative ground states of antiferromagnetic
Quantum numbers for relative ground states of antiferromagnetic

Simultaneous Measurement
Simultaneous Measurement

FPGA emulation of quantum circuits
FPGA emulation of quantum circuits

... There is an increased interest in quantum computing and algorithms [5]. Many quantum algorithms outperform their classical counterparts through parallelism that is impossible in classical computing. Such algorithms use physical effects like entanglement and super-position to achieve the speedup. The ...
Information measures of hydrogenic systems, Laguerre polynomials
Information measures of hydrogenic systems, Laguerre polynomials

File
File

... The ground state of a quantum mechanical system is its lowest-energy state; the energy of the ground state is known as the zero-point energy of the system. An excited state is any state with energy greater than the ground state. The ground state of a quantum field theory is usually called the vacuum ...
URL - StealthSkater
URL - StealthSkater

... idea is that various information molecules binding to receptors involved with bio-control (neurotransmitters, hormones, etc.) are involved with building the flux tube connections between cells. These biomolecules could carry the ends of flux tubes to special places for which receptors serve as addre ...
available here - Centre for High Energy Physics
available here - Centre for High Energy Physics

... N tmax . Amplitude amplification can be used when A is probabilistic, and search bound O a polylogarithmic overhead in T is required when ti are not known in advance. ...
Optical and Quantum Communications—J. H. Shapiro, N. C. Wong
Optical and Quantum Communications—J. H. Shapiro, N. C. Wong

... a CO2-laser trap in an ultra-high vacuum chamber with cryogenic walls within a high-finesse single-ended optical cavity. An abstract representation of the relevant hyperfine levels for such a memory is given in Fig. 2(a). A 795 nm photon in an arbitrary polarization can be absorbed, transferring the ...
Determinant formulas for the reflection equation algebra
Determinant formulas for the reflection equation algebra

Is Quantum Indeterminism Relevant to Free Will?
Is Quantum Indeterminism Relevant to Free Will?

Suppose now that a local hidden variable theory provides a full
Suppose now that a local hidden variable theory provides a full

Quantum Potential - Fondation Louis de Broglie
Quantum Potential - Fondation Louis de Broglie

... particle with a well-defined trajectory that coexists with the wave and interpreting ∇S and −∂S/∂t as momentum and energy of the particle that the Schrödinger wave function describes, we can consistently describe all known quantum phenomena. But, what he found was very powerful, specially in solvin ...
Pulsed field ionization of Rydberg atoms
Pulsed field ionization of Rydberg atoms

... compare fully quantum and classical trajectory Monte Carlo calculations to test the accuracy of the classical method. This will provide guidance as to what sort of accuracy needs to be obtained in order to measure the difference between classical and quantum mechanics in this system. The second purp ...
Theory of the topological Anderson insulator
Theory of the topological Anderson insulator

Lecture 1 , Jan - 14 - 2015
Lecture 1 , Jan - 14 - 2015

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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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