blqs
qiskit
| blqs | qiskit | |
|---|---|---|
| 1 | 23 | |
| 34 | 4,643 | |
| - | 3.6% | |
| 3.2 | 9.8 | |
| 6 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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blqs
qiskit
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Library for Machine learning and quantum computing
Qiskit
- Reorientation vers metiers de l'informatique quantique
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Basic question about quantum operations
Hello, guys. I am a newbie to quantum computing. I got a question when reading the textbook on Qiskit.org.
- Calcul quantique
- Mio padre sta diventando un complottaro. Internet corrompe i boomer
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Meetup Announcement: Quantum Computing meets Data Science, 6th of June, 2023
Second talk: Gesture Classification on a Smartphone Web-App using a Quantum ComputerDavid Alber and Olaf Hahn will demonstrate that Quantum enhanced Support Vector Machines (QSVMs) can be utilized to classify gestures made by a conventional smartphone. They will showcase how developers can utilize the Qiskit Python framework and provision IBM Cloud and IBM Quantum resources to integrate such models in a traditional application environment seamlessly.Machine learning and quantum are promising technologies with the potential to address yet intractable problems. The hybrid nature of QSVMs makes it possible to deploy such models already today. We will show you how.
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p=np is a hardware problem maybe
Also, see Shor's algorithm for a quantum approach to prime factorization, and maybe have a play with qiskit
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Qiskit #0
Qiskit
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Which programming language is best to simulate a quantum computer?
I think Python would be a more mainstream choice and so you'll find modules like qiskit or [qutip(https://qutip.org/) already exist and will make life easier.
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How much would I benefit if I started working on my coding skills before uni?
If you want to be a bit more physics-focused in your coding, it might help to dig up a course or textbook on numerical methods in physics. Being able to numerically solve differential equations is probably the most generally applicable skill in physics. Machine learning methods are pretty ''hot right now'' and might be fun to have a look into. And for quantum technology in particular, you might enjoy having a look at some python packages like Kwant for quantum transport, QuTiP for quantum dynamics and Qiskit for quantum computing. You won't understand the physics for this for quite some time, they might help serve as a bit of inspiration and an indication as to what physicists can use programming for.
What are some alternatives?
quantumcat - quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort.
QuTiP - QuTiP: Quantum Toolbox in Python
cqasm_development_interface - Framework for writing and running cQASM files against any Quantum Inspire's emulator backend via their API
mitiq - Mitiq is an open source toolkit for implementing error mitigation techniques on most current intermediate-scale quantum computers.
pyquil - A Python library for quantum programming using Quil.
pyquirk - A simple python program to convert graphical circuits to quantikz figures.
qiskit-tutorials - A collection of Jupyter notebooks showing how to use the Qiskit SDK
beets - music library manager and MusicBrainz tagger
pyzx - Python library for quantum circuit rewriting and optimisation using the ZX-calculus
qiskit-symb - Python package for symbolic quantum computation in Qiskit
quantumlisp - Quantum computing simulation for Common Lisp