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Quantum Rotations: A Case Study in Static and Dynamic Machine
Quantum Rotations: A Case Study in Static and Dynamic Machine

... a qubit. The initial state s1 rotates θ radians about the Z-axis. The resultant state, s2 , maintains the same superposition but has a phase shifted by θ. act on a single qubit. An accessible example is the quantum NOT gate which performs a 180 degree rotation about the X- axis. When applied to a cl ...
Subjective Bayesian probabilities
Subjective Bayesian probabilities

Quantum information processing by nuclear magnetic resonance
Quantum information processing by nuclear magnetic resonance

... by taking advantage of the very ensemble nature of the system which gave rise to it in the first place. Namely, we define a ‘‘pseudopure’’ ensemble to be one in which the sum of the nuclear magnetic moments over all the molecules present in the sample yields a system of moments proportional to that ...
Quantum Computer Compilers - Computer Science, Columbia
Quantum Computer Compilers - Computer Science, Columbia

... The Future of Quantum Hardware • The future does not necessarily belong to the ion trappers: for example, electron spins in quantum dots, superconducting qubits, ultracold neutral atoms are all making impressive progress. • But ion traps have a head start, and some serious effort has been devoted t ...
Quantum Chaos
Quantum Chaos

... the energy levels and eigenstates of the (bound) system? For an open system, in  the decay rates, in the S­matrix, in the transport properties? (lectures 1 and 2) What kind of semiclassical approximations can be used? (lecture 2) What is the long­time behaviour of a quantum system? (lecture 3) For a ...
How Many Query Superpositions Are Needed to Learn?
How Many Query Superpositions Are Needed to Learn?

... corresponds a subset of Bn so-called consistent set and denoted by σqa . Functions in σqa are said to be consistent with tuple (q, a). In the learning game defined by protocol P , answer a to query q provides the information that the target function belongs to σqa . We also denote by Σq the set of ...
R14
R14

Quantum Communications in the Maritime Environment
Quantum Communications in the Maritime Environment

... of classical information processing systems. These efforts in quantum information science have produced a variety of promising theoretical and experimental results with a considerable impact on the development of perfectly secure quantum communications. In this regard, “perfectly secure” communicati ...
The presentation template
The presentation template

NeuroQuantology Journal
NeuroQuantology Journal

QUANTUM ERROR CORRECTING CODES FROM THE
QUANTUM ERROR CORRECTING CODES FROM THE

200 Beryllium Ions Entangled
200 Beryllium Ions Entangled

Solutions of the Equations of Motion in Classical and Quantum
Solutions of the Equations of Motion in Classical and Quantum

... a fixed time and it is best suited for the formulation of the quantum theory in the Schrodinger picture. The Heisenberg picture is obtained usually from the Schrodinger picture by applying the time-dependent unitary automorphism to the operator algebra. The Schrodinger picture description is not ver ...


... that depends explicitly on the time (see Sec. 3.1, below). The aim of this paper is to show that, with an appropriate definition of the invariance of a Hamiltonian [that generalizes Eq. (2)], any conserved operator is associated with a group of unitary transformations that leave the Hamiltonian inva ...
Quantum Transport Theory with Tight-Binding Hamiltonian Stefano Sanvito Department of Physics
Quantum Transport Theory with Tight-Binding Hamiltonian Stefano Sanvito Department of Physics

Does Quantum Mechanics Clash with the Equivalence Principle
Does Quantum Mechanics Clash with the Equivalence Principle

Introduction to Machine Learning
Introduction to Machine Learning

Quantum graphs and the integer quantum Hall effect
Quantum graphs and the integer quantum Hall effect

... Quantum graphs have been the focus of much interest during the last thirty years [1–3]. These models which describe the propagation of a quantum wave within an arbitrary complex object are extremely versatile allowing the study of various interesting quantum phenomena. Quantum graphs appear in vario ...
Ground State Structure in Supersymmetric Quantum Mechanics* Qv
Ground State Structure in Supersymmetric Quantum Mechanics* Qv

... A zero mode of Q is defined as an element of the kernel of Q, namely an eigenvector of H with energy zero. The index (1.8) is the number of linearly independent bosonic zero modes n + , minus the number of linearly independent fermionic zero modes n _ . Clearly i(Q + ) # 0 is a sufficient condition ...
Logic of Quantum Mechanics
Logic of Quantum Mechanics

A Quantum-Like Protectorate in the Brain
A Quantum-Like Protectorate in the Brain

Classification of Topologically ordered Phases
Classification of Topologically ordered Phases

... in finding and classifying the SPT phase via MPS/TPS. A key observation is that preserving symmetry in the QSRG allows us to study fix points of symmetry protected topological phases We have consider the 1- and 2-dimensional AKLT phases as the examples. ...
1 = A
1 = A

... J2 is the Casimir operator, which commutes with unit operator. In general case several Casimir operators may be constructed from group generators. Usually Casimir operators explicitly enter the Hamiltonian. In particular, one may use J2 instead of Δ . In some special cases Casimir operators do not e ...
Quantum Computer - Physics, Computer Science and Engineering
Quantum Computer - Physics, Computer Science and Engineering

... computation. i.e. we can perform any quantum computation by connecting just 1-qubit rotation gates and controlled-NOT gates (cf. any classical computation can be realized using just AND and ...
Quantum walk as a generalized measuring device
Quantum walk as a generalized measuring device

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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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