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I have been using the Python version of qulacs for simulations of variational quantum algorithms, and I wanted to try out qulacs-qpu to speedup my optimisations. After swapping out all instances of Qu…
ghost updated
3 years ago
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# Description
In the last few years, many Quantum Machine Learning (QML) algorithms have been proposed in the literature, promising several theoretical advantages with respect to their classical coun…
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### Team Name:
Hooked on Photonics
### Project Description:
One of the most promising applications of variational quantum algorithms is the study of condensed matter phenomena, such as quantu…
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### Team Name:
Giglampshare
### Project Description:
There are various proposals to apply quantum computing to reinforcement learning. This experiment serves as a proof-of-concept demonstra…
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### Informations
- **Qiskit Aer version**: 0.6.1
- **Python version**: 3.8.5
- **Operating system**: Manjaro
### What is the current behavior?
I'm trying to reproduce [this](https://q…
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# Description
The variational quantum eigensolver (VQE) is maybe one of the famous quantum algorithms: provided with a Hamiltonian describing a quantum system and a parameterized ansatz state, it fin…
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### Team Name:
Penn Ave Fish Company
### Project Description:
A prerequisite for quantum algorithms to outperform their classical counterparts lies in the ability to efficiently load the cl…
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Add code to automatically add contributors in index.html
There should be a javscript that adds an iframe or something
with the list of contributors to quantumalgorithms.org
https://github.com/Sci…
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# VQE Ansatz Generator
A **Variational Quantum Eigensolver** is a very powerful tool when creating algorithms for NISQ-era hardware. With applications from 💹 Finance, 🧪 Chemistry, 🔢 Optimization, 🧠 M…
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### Team Name:
CCH
### Project Description:
The emerging field of hybrid quantum-classical algorithms joins CPUs and QPUs to speed-up/improve specific calculations within a classical algori…