I am currently studying quantum computers, but I compared the Python libraries for quantum computers "Qiskit" and "Blueqat" from a beginner's perspective. It has a lot of personal opinion, so please read it for reference only. By the way, Qiskit is made by IBM and Blueqat is made by MDR.
This time, we will compare with the following evaluation points.
――Is the explanation substantial? --Preparation of execution environment and ease of use --Usage (quite personal opinion)
This time I will evaluate it, but please tell me if there are any other good evaluation criteria.
From the conclusion, ** the explanation is easier to understand with "Blueqat" **. Below are the API documentation and tutorial links for Qiskit and Blueqat. ** · Qiskit Tutorial ** ** · Qiskit API documentation ** ** ・ Blueqat Tutorials ** ** ・ Blueqat Tutorial (Japanese) ** ** · Blueqat API documentation **
As you can see from the link, Qiskit has a difficult document system. It feels like various people have made parts and combined them. Also, Blueqat is a Japanese company, so the tutorials are available in Japanese.
In terms of ease of preparation / use of the execution environment, from my point of view, there is not much difference between the two. First of all, regarding "preparation of execution environment", when using Python, both "pip" commands are used to prepare the library. However, Qiskit can handle the jupyter notebook environment over the Internet at "IBM Q Experience". However, since the same environment is provided by "Google Colaboratory" provided by Google, I felt that it would not be a big advantage.
It's a little off the beaten track, but you can use IBM's Circuit Composer from IBM Q Experience to create quantum circuits by dragging and dropping. It may be good for those who want to feel free to try it.
Regarding the usability, if there are any points that I noticed in using it in the future, I will add / correct as appropriate. To be honest, there is a big part that is dragged by "1. Is the explanation substantial?", And it is Blueqat that can do what you want to do relatively quickly, and there are no scenes where you find it difficult to use. However, Qiskit can be easily implemented until the calculation result is displayed in a diagram, so I think the advantage is that the jupyter notebook is visually easy to understand. For now, I think Blueqat is for implementation speed, and Qiskit is for easy implementation of visually easy-to-understand things.
So, based on the evaluation so far, the overall evaluation is as follows!
| Qiskit | Blueqat | |
|---|---|---|
| Full explanation | △ | 〇 |
| Execution environment/Ease of use | 〇 | 〇 |
| Usability | 〇 | 〇 |
| Comprehensive evaluation | △ | 〇 |
I admit the objection! Because the evaluation of usability is loose (`・ ω ・ ´)
See you in the next post!
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