2024-07-10 –, Function (4.1)
With a growing user-base, DMRjulia v1.0 is undergoing its inaugural release. This software package has been in development for a few years and has been used in previous academic publications for computations on tensor networks for strongly correlated quantum problems. We discuss new algorithms that have been developed in the software package and the interface of those access tools with hardware provided on the Digital Research Alliance of Canada. We will cover the documentation available.
Our talk will cover introductory material related to the use of the DMRjulia library that is pending its v1.0 release
https://github.com/bakerte/DMRJtensor.jl
and include an existing article for beginners:
T.E. Baker, S. Desrosiers, M. Tremblay, M.P. Thompson, Méthodes de calcul avec ré́seaux de tenseurs en physique Can. J. Phys. 99, 4 (2021) [(Basic tensor network computations in physics), arxiv: 1911.11566, p. 20]
We will debut a full software tutorial for the software and cases where DMRjulia has led to new developments in modelling of quantum systems, including some that will be released around March 2024. Basic design principles that are native to Julia will be discussed with lessons and recommendations. We also hope to contribute back to the core Julia codebase with some improvements that we have identified.
Our software was optimised around a specific hardware implementation on the Digital Research Alliance of Canada’s hardware infrastructure. We will debut public interfaces to use these tools and recap lessons learned on the specific implementation of the library on hardware. We used several packages in the Julia ecosystem to accomplish the best interface possible with the best performance. Our software has been optimized to run efficiently in shared memory environments, including high-performance computing clusters. We will demonstrate results and recap lessons learned in improving performance by utilizing parallelism in background libraries and tuning parameters for a given computing environment.
The core of the software package is available online under the DMRJtensor package, but the v1.0 release (scheduled for May) and some helper tools (scheduled for June) will be made available concurrent with some ongoing academic research. We will also cover any new developments with these new capabilities and ways in which DMRjulia can be used for scientific results at the cutting edge of research.
We are grateful to the US-UK Fulbright Commission for financial support and being hosted by the University of York. This research was undertaken in part thanks to funding from the Bureau of Education and Cultural Affairs from the United States Department of State.
T.E.B. graciously thanks funding provided by the postdoctoral fellowship from Institut quantique. This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund (CFREF).
This research was undertaken, in part, thanks to funding from the Canada Research Chairs Program. The Chair position in the area of Quantum Computing for Modelling of Molecules and Materials is hosted by the Departments of Physics & Astronomy and of Chemistry at the University of Victoria.
This work has been supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) under grants RGPIN-2023-05510 and DGECR-2023-00026.
This work is supported in part with support from the University of Victoria's start-up grant from the Faculty of Science.
This research was enabled in part by support provided by Research Computing Services at the University of Victoria as well as the Digital Research Alliance of Canada (alliancecan.ca).
Prof. Thomas E. Baker is the Canada Research Chair in Quantum Computing for Modelling of Molecules and Materials. He previously served as a Fulbright US Scholar in the United Kingdom at the University of York in 2021. He was the Prized Postdoctoral Researcher in Quantum Sciences and Technology at Institut quantique (Université de Sherbrooke, Québec). He has an active research interest in quantum computing, quantum algorithms, tensor network methods, and quantum chemistry. He is interested in working with people from all different backgrounds.