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“Quantum Computing: Dream or Nightmare”, Physics Today, 49, 51
“Quantum Computing: Dream or Nightmare”, Physics Today, 49, 51

Quantum Computing - Department of Physics and Astronomy
Quantum Computing - Department of Physics and Astronomy

... • When the number of transistors goes down, so does the overall dimensions • Transistor size will approach quantum dimensions in ~6-10 years! • We had better be ready to embrace a new approach. ...
Template of abstract for ICMNE-2005
Template of abstract for ICMNE-2005

... MOSFET performance. The ultra-thin (1-5nm) fully depleted silicon will be a structure to take an ultimate advantage of SOI wafers and to provide an advancement of silicon technology to the extreme channel length of about 5-10nm. The quantum simulation of such small devices becomes challenging [1, 2] ...
PHYS13071 Assessment 2012
PHYS13071 Assessment 2012

... seen years of great advances in quantum technology, especially in nanotechnology. According to the “Moore’s Law”, the number of transistors on computer chips, and hence their computational speed and memory capacity, doubles every eighteen months. If the “Moore’s Law” holds, in a very short time, the ...
Slide 1
Slide 1

... Joint Institute for Nuclear Research Dubna, Russia ...
Presentation (PowerPoint File)
Presentation (PowerPoint File)

... Hilbert-space dimension is determined by physics. The dimension available for a quantum computation is a physical quantity that costs physical resources. ...
Where is the Electron Located?
Where is the Electron Located?

Nonlincourse13
Nonlincourse13

CHM 421: Physical Chemistry 1 Quantum Mechanics
CHM 421: Physical Chemistry 1 Quantum Mechanics

... There is no prescribed book for this course. I prefer to make my notes after reading different books. There are many excellent books in Quantum Mechanics and you will be well-served by reading one or more of them. However, it is good to be a little cautious while going through any book. There are ma ...
the principle quantum number
the principle quantum number

... • Map to determine location of the electrons….. • (Methods for denoting earrangement for an atom: orbital notation) ...
PPT - Louisiana State University
PPT - Louisiana State University

Main Topic: T1 Density-Functional Theory beyond LDA
Main Topic: T1 Density-Functional Theory beyond LDA

Quantum Model of the Atom Power point
Quantum Model of the Atom Power point

Syllabus: Quantum computing - University of Hawaii Physics and
Syllabus: Quantum computing - University of Hawaii Physics and

... Topics in current theoretical research; e.g., quantum informational representations of field theories. This course is an introduction to quantum information theory (qubits, quantum gates, and qubit systems). It covers a few selected quantum algorithms, yet the emphasis of the course is on quantum si ...
Quantum Communication: A real Enigma
Quantum Communication: A real Enigma

Quantum Cryptography
Quantum Cryptography

... • A user can suggest a key by sending a stream of randomly polarized photons. • This sequence can be converted to a binary key. • If the key was intercepted it could be discarded and a new stream of randomly polarized photons sent. ...
Research Statement
Research Statement

... small systems to look for such a transition. It may be possible to extend such calculations to significantly larger systems using Chebyshev methods (following previous work by myself), which are natural for studying time evolution and spectral functions, and are billions of times more accurate than ...
On the Einstein-Podolsky-Rosen paradox
On the Einstein-Podolsky-Rosen paradox

WAVE MECHANICS (Schrödinger, 1926)
WAVE MECHANICS (Schrödinger, 1926)

... WAVE MECHANICS * The energy depends only on the principal quantum number, as in the Bohr model: En = -2.179 X 10-18J /n2 * The orbitals are named by giving the n value followed by a letter symbol for l: l= 0,1, 2, 3, 4, 5, ... s p d f g h ... * All orbitals with the same n are called a “shell”. All ...
Quantum Numbers
Quantum Numbers

... – Electron is knocked off metal surface only if struck by one photon with certain minimum energy. Mullis ...
Can computer science help physicists resolve the
Can computer science help physicists resolve the

... Wiesner 1969: Because of the No-Cloning Theorem, in principle it’s possible to have “quantum money,” where each bill includes qubits that are physically impossible to duplicate. Bennett et al. 1982: Can even combine with cryptography so the bank doesn’t need to remember stuff about every bill in cir ...
Slide 1
Slide 1

PPTX
PPTX

... If a deformed commutator applies to the coordinates of a fundamental constituent, then its effect on a macroscopic object (composed of N such constituents) should decrease as 1/N • what is a fundamental constituent? • geometrical properties of space-time  property of each particle ...
Another version - Scott Aaronson
Another version - Scott Aaronson

... minimum exponentially faster than simulated annealing (though maybe other classical algorithms do better) ...
Titles and Abstracts
Titles and Abstracts

< 1 ... 187 188 189 190 191 192 193 194 195 ... 212 >

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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