Internal

Parallel Algorithms for simulating the Fifth State of Matter

Condensed matter has been proven to be practically realisable in laboratory conditions. This work aims to perform simulation studies to analyse condensed matter properties and their potential applications.

Department: Computer Science, Systems Engineering

Supervised by: Dr. M. Manjunathaiah

The Placement Project

In 1924 a new form of matter, a condensed form, was predicted by Bose and Einstein. Condensation occurs in a super-cooled point just above absolute zero in which matter condenses into a wave form. The quest to realise this “fifth state of matter” culminated in 1995 by two research groups at Colarado and MIT who demonstrated the theoretical predictions in laboratory conditions. Since then research has concentrated on finding practical applications of this condensed matter with potential for wide ranging applications in medicine, in quantum computing and quantum information processing. The purpose of this research study is to investigate simulation techniques for understanding the Bose Hubbard Model. More specifically it requires the computation of matrix vector product over sparse matrices. Because of scalability issues (sequential computation running into days), parallel implementations of BH model have been proposed recently. The aim of this study is to specifically design a class of efficient parallel algorithms and compare it against the established results of recent research (Mary Ann Leung, Efficient parallel implementation of Bose Hubbard Model) for its effectiveness. The proposed research study will be carried out under the supervision of the principal investigator.

Tasks

As part of the research study, a student will be expected to: • Perform literature survey • Implement a class of parallel algorithms • Produce a technical report related to the findings from the research study

Skills, knowledge and experience required

It is essential that the student should : • Have strong background in algorithmic techniques and mathematical modelling. • Be proficient in programming • Have good technical report writing skills • Have strong motivation for research work

Skills which will be developed during the placement

• Experience in research methods of making comparative studies. • Knowledge of algorithmic approaches to problems in physics. • Introduction to parallel algorithm design which can benefit a student in producing a high quality part 3 project. • Technical report writing skills and a potential publication that can enhance a student’s CV.

Place of Work

UoR

Hours of Work

Approximate Start and End Dates (not fixed)

Unknown - Unknown

How to Apply

Applications in the form of a CV from suitable candidates with a covering letter stating why the student feels he/she is qualified for the research placement may be submitted to m.manjunathaiah@reading.ac.uk


Return to Placements List

Page navigation