China

Continuous variable quantum key distribution (CV-QKD) has made great progress recent years. Throughput of error correction is one of the bottlenecks for CV-QKD. For typical distance of CV-QKD system, the signal-to-noise ratio is low, and a large number of iterations is needed for decoder. Since scheduling strategy is an important factor of the decoder’s convergence rate, in this paper, the performance of three different scheduling strategies (flooding scheduling, layered scheduling by row, layered scheduling by column) is compared. The algorithm complexity, adaptation to the parity check matrix, and throughput performance are studied. For the typical parity check matrix for CV-QKD system, the results show that layered scheduling by column is the best method. Throughput of more than 70 Mbits/s is achieved by this method, which surpasses the record in the literature and can improve the real-time processing capacity of CV-QKD system.

Quantum 2020

Study on error correction decoder scheduling strategies for continuous variable quantum key distribution system

quantum information

post-processing

AAPT® is a strong professional physics science society dedicated to the pursuit of excellence in physical science education.

Winter and Summer National Meetings:
These National Meetings, held each winter and summer, are opportunities for members, colleagues, and future physicists from around the world to:

- participate in physics workshops
- meet and greet other physics educators
- form networks nationally and locally
- engage exhibitors and learn about the latest physics resources
- discuss innovations in teaching methods
- share the results of research about teaching and learning.

If you're not able to log in, you're most likely using **incorrect login credentials**. Double-check that you are using the same email and password that you used to register for the conference, submit your abstract or access your AAPT membership. There may also be **an issue with your AAPT meeting registration**. Please email aapt2021@underline.io and programs@aapt.org and we will work quickly to resolve this issue.

AAPT WM 21

poster

The Institute of Physics and IOP Publishing, in partnership with the Chinese Physical Society (CPS) and the University of Science and Technology of China (USTC) are proud to have brought together the international quantum science community online for this inaugural conference.


Early career and leading researchers from universities, industry and government worldwide came together to share, learn and collaborate on the latest research and emerging areas of high interest across quantum science and technology. The broad themes covered by Quantum 2020 included:

Quantum communication;
Quantum computing and quantum simulation;
Quantum sensing, metrology and imaging;
Quantum information theory, software and algorithms;
Quantum foundations;
Quantum technology in industry.
The four-day event featured talks from world-renowned scientists, interactive poster sessions and two exciting panel discussions on the themes of Quantum Technology in Industry and Quantum Technology Programmes Around the World.


You will need to [register](https://www.iopconferences.org/iop/frontend/reg/tRegisterEmailNew.csp?pageID=978403&eventID=1552&tempPersonID=536224) to obtain a ticket. . If you have already registered you should have been sent an email from Underline (to the email address that you registered with) with the subject line ‘Welcome to Quantum 2020’. This email includes your ticket for the event. 

If you have a ticket and are experiencing problems in accessing the event, please contact us. 

The Institute of Physics and IOP Publishing, in partnership with the Chinese Physical Society (CPS) and the University of Science and Technology of China (USTC) are proud to have brought together the international quantum science community online for this inaugural conference.

Early career and leading researchers from universities, industry and government worldwide came together to share, learn and collaborate on the latest research and emerging areas of high interest across quantum science and technology. 

"HqHop: Hybrid Quantum Hopfield Neural Network for Portfolio Selection

RP Mahajan 
 
Faculty at Dept. of Computer Science & Engineering, SIRT, SAGE University, India
E-mail: rpmahajan.sage@gmail.com ; rpmahajan@yahoo.com

 
Abstract: Classical Hopfield neural networks (CHNN) are known for solving portfolio selection problem for asset management. A Hybrid Quantum Hopfield Neural Network (HqHop) is proposed to solve portfolio selection problem based on Markowitz mean variance approach. Due to the large number of portfolios, the CHNN requires huge memory and processing power. The inbuilt parallelism in CHNN makes it more suitable for quantum based system. This paper details an approach, perhaps the first time, for the solution of portfolio selection problem using the involved concept. The developed HqHop can be used for solving other optimization problems as well.

"

Next from Quantum 2020

HqHop: Hybrid Quantum Hopfield Neural Network for Portfolio Selection

Similar lecture

A Quantum Interactive Learning Tutorial on Quantum Key Distribution

Next from Quantum 2020

­­­­­­­­­­­­HqHop: Hybrid Quantum Hopfield Neural Network for Portfolio Selection

Similar lecture

A Quantum Interactive Learning Tutorial on Quantum Key Distribution

HqHop: Hybrid Quantum Hopfield Neural Network for Portfolio Selection