scholarly journals Andrew Chi-Chih Yao: the future of quantum computing

2018 ◽  
Vol 5 (4) ◽  
pp. 598-602
Author(s):  
Mu-ming Poo ◽  
Ling Wang
Keyword(s):  
Quantum Computing ◽  
Academic Community ◽  
Quantum Computers ◽  
Quantum Properties ◽  
The Future ◽  
History Of ◽  
Founding Director ◽  
World Class ◽  
Properties Of Materials ◽  
Richard Feynman

ABSTRACT Quantum computing and quantum computers have attracted much attention from both the academic community and industry in recent years. By exploiting the quantum properties of materials, scientists are aiming to overcome Moore's law of miniaturization and develop novel quantum computers. The concept of quantum computing was first introduced by the distinguished physicist Richard Feynman in 1981. As one of the early pioneers in this field, Turing Award laureate Andrew Chi-Chih Yao made a seminal contribution in developing the theoretical basis for quantum computation in 1993. Since 2011, he has served as the founding director of Tsinghua University's Center for Quantum Information (CQI), which aims to become a world-class research center for quantum computing. In a recent interview with NSR, Yao recounted the history of quantum computing and expressed his view on the future of this field. He suggests that quantum computers could excel in many tasks such as the design of new materials and drugs as well as in the simulation of chemical reactions, but they may not supersede traditional computers in tasks for which traditional computers are already proven to be highly efficient.

scholarly journals Application of Quantum Computing to Biochemical Systems: A Look to the Future

2020 ◽  
Vol 8 ◽  
Author(s):  
Hai-Ping Cheng ◽  
Erik Deumens ◽  
James K. Freericks ◽  
Chenglong Li ◽  
Beverly A. Sanders
Keyword(s):  
Quantum Computing ◽  
Physical System ◽  
Quantum Computer ◽  
Quantum Algorithms ◽  
Active Regions ◽  
Quantum Computers ◽  
The Future ◽  
Biochemical Systems ◽  
Near Term ◽  
Different Levels

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

Quantum

2017 ◽  
Author(s):  
Lance Fortnow
Keyword(s):  
Quantum Mechanics ◽  
Quantum Computing ◽  
Quantum Cryptography ◽  
Nobel Prize ◽  
Quantum Computers ◽  
Physical Systems ◽  
Medium Scale ◽  
Computer Scientists ◽  
Working Together ◽  
Richard Feynman

This chapter examines the power of quantum computing, as well as the related concepts of quantum cryptography and teleportation. In 1982, the Nobel prize-winning physicist Richard Feynman noticed there was no simple way of simulating quantum physical systems using digital computers. He turned this problem into an opportunity—perhaps a computational device based on quantum mechanics could solve problems more efficiently than more traditional computers. In the decades that followed, computer scientists and physicists, often working together, showed in theory that quantum computers can solve certain problems, such as factoring numbers, much faster. Whether one can actually build large or even medium-scale working quantum computers and determine exactly what these computers can or cannot do still remain significant challenges.

Can Quantum Computers Solve Linear Algebra Problems to Advance Engineering Applications?

2018 ◽  
Author(s):  
Guanglei Xu ◽  
William S. Oates
Keyword(s):  
Quantum Computing ◽  
Linear Algebra ◽  
Quantum Algorithms ◽  
Finite Difference Methods ◽  
Engineering Application ◽  
Quantum Circuit ◽  
Quantum Computers ◽  
Measurement Methodology ◽  
Classical Computing ◽  
Richard Feynman

Since its inception by Richard Feynman in 1982, quantum computing has provided an intriguing opportunity to advance computational capabilities over classical computing. Classical computers use bits to process information in terms of zeros and ones. Quantum computers use the complex world of quantum mechanics to carry out calculations using qubits (the quantum analog of a classical bit). The qubit can be in a superposition of the zero and one state simultaneously unlike a classical bit. The true power of quantum computing comes from the complexity of entanglement between many qubits. When entanglement is realized, quantum algorithms for problems such as factoring numbers and solving linear algebra problems show exponential speed-up relative to any known classical algorithm. Linear algebra problems are of particular interest in engineering application for solving problems that use finite element and finite difference methods. Here, we explore quantum linear algebra problems where we design and implement a quantum circuit that can be tested on IBM’s quantum computing hardware. A set of quantum gates are assimilated into a circuit and implemented on the IBM Q system to demonstrate its algorithm capabilities and its measurement methodology.

NMR quantum computing - lessons for the future

2001 ◽  
Vol 1 (Special) ◽  
pp. 134-142
Author(s):  
L. Vandersypen ◽  
I. Chuang
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Quantum Computing ◽  
Magnetic Resonance ◽  
Large Scale ◽  
Experimental Methods ◽  
Quantum Systems ◽  
Quantum Computers ◽  
Physical Systems ◽  
The Future ◽  
Nuclear Magnetic

Future physical implementations of large-scale quantum computers will face significant practical challenges. Many useful lessons can be drawn from present results with Nuclear Magnetic Resonance realizations of controllable two, three, five, and seven qubit quantum systems. We summarize various experimental methods and theoretical procedures learned in this work which will be of considerable value in building and testing quantum processors with a wide variety of physical systems.

A History of the Future

2017 ◽  
Author(s):  
Peter J. Bowler
Keyword(s):  
The Future ◽  
History Of

A Dynamic Systems Approach to Personality

2001 ◽  
Vol 6 (3) ◽  
pp. 172-176 ◽  
Author(s):  
Lawrence A. Pervin
Keyword(s):  
Dynamic Systems ◽  
Systems Approach ◽  
Biological Processes ◽  
Recent Advances ◽  
Dynamic View ◽  
The Future ◽  
History Of

David Magnusson has been the most articulate spokesperson for a holistic, systems approach to personality. This paper considers three concepts relevant to a dynamic systems approach to personality: dynamics, systems, and levels. Some of the history of a dynamic view is traced, leading to an emphasis on the need for stressing the interplay among goals. Concepts such as multidetermination, equipotentiality, and equifinality are shown to be important aspects of a systems approach. Finally, attention is drawn to the question of levels of description, analysis, and explanation in a theory of personality. The importance of the issue is emphasized in relation to recent advances in our understanding of biological processes. Integrating such advances into a theory of personality while avoiding the danger of reductionism is a challenge for the future.

A Reflection on Crucial Periods in 50 Years of Social Psychology (in Germany)

2019 ◽  
Vol 50 (1) ◽  
pp. 1-6
Author(s):  
Katja Corcoran ◽  
Michael Häfner ◽  
Mathias Kauff ◽  
Stefan Stürmer
Keyword(s):  
Social Psychology ◽  
Early Development ◽  
West Germany ◽  
East And West Germany ◽  
The Future ◽  
History Of ◽  
East And West

Abstract. In this article, we reflect on 50 years of the journal Social Psychology. We interviewed colleagues who have witnessed the history of the journal. Based on these interviews, we identified three crucial periods in Social Psychology’s history, that are (a) the early development and further professionalization of the journal, (b) the reunification of East and West Germany, and (c) the internationalization of the journal and its transformation from the Zeitschrift für Sozialpsychologie to Social Psychology. We end our reflection with a discussion of changes that occurred during these periods and their implication for the future of our field.

The future of the history of psychology in Argentina and Brazil.

2016 ◽  
Vol 19 (3) ◽  
pp. 229-247 ◽  
Author(s):  
Hugo Klappenbach ◽  
Ana Maria Jacó-Vilela
Keyword(s):  
History Of Psychology ◽  
The Future ◽  
History Of
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