QCCI 2013
2013 IEEE Symposium on Quantum Computing and Computational
Intelligence
Although quantum computing is still in its nascent days, there are
experiments that successfully perform quantum computation on a small number of
qubits. Recently, researchers at the NIST demonstrated continuous quantum
operations using a trapped-ion processor. Other researchers have discovered a
way to make quantum devices using technology common in our current chip-making
industry. Historically, classical computer concepts and underlying technologies
have been invented by mathematicians and physicists rather than engineers. It
was engineers, however, who took basic concepts and ideas and created the
practical powerful and inexpensive computers of today. We believe that the same
will happen in case of quantum computing.
As quantum information and computation research continues to develop, we will
see increasing interest in adapting the philosophy of quantum computing,
information theory and ideology into other, more traditional aspects of
computational research. Although the hardware technology to realize quantum
computing still yet to be materialized, research about the theoretical aspects
of quantum computing and its ideology has enjoyed some success with artificial
and computational intelligence.
This symposium focus on combining various aspects of quantum computing,
information theory, and other aspects with existing fields in computational
intelligence.
Topics
Some typical research areas that will be discussed in this special session
include (but are not limited to) the following:
- Quantum inspired evolutionary computation, quantum inspired genetic
algorithms.
- Quantum neural networks.
- Quantum and fuzzy computing systems.
- Evolutionary Techniques and Quantum Computing. Including: (a) use of
evolutionary paradigms to create quantum circuits, quantum algorithms,
quantum architectures and quantum games, (b) creation of new quantum
algorithms and architectures inspired by the concepts of evolution and other
biological ideas, (c) use of evolutionary algorithms to solve any practical
problems in designing quantum devices.
- Quantum implementation of Computational Intelligence: many machine
learning and problem-solving models known from Computational Intelligence
such as Neural Nets, Bayesian networks, Logic Networks, Fuzzy Logic, state
machines, evolvable hardware, etc., can be extended to those based on
quantum circuits and automata.
- Computational Intelligence interacting with various aspects of Quantum
information theory including error correction, teleportation,
encryption/decryption, security, etc.
- Quantum game theory, applications of quantum games.
- Using GA, GP and other evolutionary and biological paradigms in all
areas of quantum circuits, quantum information and quantum computing.
- Applications of quantum concepts in Computational Intelligence,
Multimedia and Robotics.
Keynote, Tutorial and Panel Sessions
Please forward your proposals with detailed abstract and bio-sketches of the
speakers to the Symposium Chair and Co-Chairs and SSCI Keynote-Tutorial Chair,
Dr S Das.
Special Sessions
Please forward your special session proposals to the Symposium Chair and
Co-Chairs.
Symposium Chair
William N. N. Hung, Synopsys Inc.,
USA
Symposium Co-chairs
Swagatam Das,
Indian Statistical
Institute, Kolkata, India
Marek Perkowski, Portland State
University, USA
Program Committee
-
Fabrizio Lombardi, Northeastern University, USA
- Faisal Shah Khan, Khalifa University, UAE
- Gerhard Dueck, University of
New Brunswick, Canada
- Guowu Yang, University of Electronic Science and Technology of China
- Hanwu Chen, Southeast University, China
- Jacob Biamonte,
National University of Singapore, Singapore
- Marek Perkowski, Portland
State University, USA
- Martin Lukac, Tohoku
University, Japan
- Mitch Thornton, Southern
Methodist University, USA
- Pawel Kerntopf, Warsaw University of Technology, Poland
- Rodney Van Meter, Keio
University, Japan
- Rolf
Drechsler, University of Bremen, Germany
- Swagatam Das,
Indian Statistical Institute, Kolkata, India
- William N. N. Hung, Synopsys
Inc., USA
- Xiaoyu Song, Portland State
University, USA
- Yun
Shang, Chinese Academy of Sciences, China
- Zairong Xi, Chinese Academy of Sciences, China