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Actually, sometimes you feel its ecosystem does not attract you since this is really a new language, however, as a package developer, when we decide to use Juli
by rogerluo 8y ago
Actually, sometimes you feel its ecosystem does not attract you since this is really a new language, however, as a package developer, when we decide to use Julia or C++ to finish a performance sensitive simulator: https://github.com/QuantumBFS/Yao.jl https://github.com/QuantumBFS/Yao.jl we choose Julia, just because we only have two people and we still want something fast and easy to use in 3 month (since it is dynamic). Another thing is the multiple dispatch feature which is really natural to scientific projects (probably even some other area), cannot talk about much details, but just personal experience.
- ChrisRackauckas 8y agoYao.jl is a fantastic project and I hope to keep following it in the future. Maybe we can build differential equation solver algorithms which utilize quantum algorithms :)
- rogerluo 8y agoActually, since we are planning to integrate QASM and eQASM (a new kind of assembly from Delft), if you can use Yao.jl to run a quantum algorithm for solving differential equations (there has been several already), you will be able to run it on some real hardware. Still working on more features, and we do need more feedback to help us make this better, please feel free to give us any comments in the issue :)
- ChrisRackauckas 8y agoCool, I'm not familiar with quantum at all but I'll start looking into it. It will definitely be something we add to DifferentialEquations.jl common interface next year. I'll see about getting a Google Summer of Code project on this.