Videos and slides are now online at http://juliaquantum.github.io/news/2015/03/berkeley-meetup-videos-online/index.html
Feel free to spread over networks! On Monday, February 16, 2015 at 1:04:46 PM UTC-7, Xiaodong Qi wrote: > > Dear Julia users in the Bay area, > > I am glad to announce a meetup session in Berkeley, California, USA on Feb > 21. There are three invited speakers talking about their experiences on > using Julia for optimization, statistics, parallel computing and quantum > science applications. People from SQuInT (southwest quantum information > network) workshop, developers & researchers from Stanford and universities > nearby are also invited for discussions of developing related Julia > packages during the free interaction session starting from 9:25pm. > > Time: 7:30pm-10:00pm. > Place: Room Berkeley, DoubleTree Hilton Hotel, 200 Marina Blvd. Berkeley, > California 94710 USA > Register: http://goo.gl/forms/T5qnGPndSE > > Talks: > > Talk 1: Predictive Analysis in Julia - An overview of the > JuMP package for optimization > Speaker: Philip Thomas from StaffJoy > Content: This talk focuses on expressing problems including linear > programming and integer programming in the JuMP metalanguage. Possibly > with some introduction to general optimization problems. > > Talk 2: Convex.jl: Optimization for Everyone > Speakers: David Deng and Karanveer, possibly also with Jenny Hong > and Madeleine Udell from Stanford. > Content: This talk will start with a brief overview of how the > Convex.jl package works and the types of problems it can solve, and > really showcase how convenient it is to use. It will be clear that > Convex.jl is easily usable by just about anyone for their basic > optimization needs. One or two more involved applications of using > Convex.jl to solve real world problems will be demonstrated from a good > pool of examples. Hopefully there will be an example on quantum tomography. > > Talk 3: Quantum Statistical Simulations with Julia > Speaker: Katharine Hyatt from UCSB > Content: Using computers to probe quantum systems is becoming more > and more common in condensed matter physics research. Many of the > commonly used languages and techniques in this space are either > difficult to learn or not performant. Julia has allowed us to quickly > develop and test codes for a variety of commonly used algorithms, > including exact diagonalization and quantum Monte Carlo. Its parallel > features, including some MPI and GPGPU integration, make it particularly > attractive for many quantum simulation problems. I'll discuss what > features of Julia have been most useful for us when working on these > simulations and the developments we're most excited about. > > More details can be found here: > https://github.com/JuliaQuantum/JuliaQuantum.github.io/issues/15 > > Feel free to forward this message to anyone who might be interested. > Thanks. > > Contact: JuliaQuantum organization via quantumjulia AT gmail DoT com >
