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Quantum Error Mitigation: using Machine Learning This project demonstrates quantum error mitigation techniques using machine learning to improve the reliability of quantum computations in noisy quantum computers. The main goal is to mitigate measurement errors that occur during quantum computation.
Quantum Error Correction (QEC) is a critical step in implementing quantum computing at scale. We implement an algorithm and show it successfully reduces noise in various quantum circuits.
⚛️ 🚀 👽 A self-paced, game-based Quantum Computing learning program for students, researchers and enthusiasts. This program offers a general understanding of Quantum Computing, as well as some of its applications, such as Quantum Machine Learning and Quantum Optimization, and how to program real quantum computers.
Implementation of the paper Quantum Error Mitigation by Pauli Check Sandwiching. The scheme was first explored by the paper Extended flag gadgets for low-overhead circuit verification. Adds Pauli parity checks to the input quantum circuit.
libs_qrem is a python package written in C++/Cython that executes quantum readout error mitigation (QREM) efficiently even for large measurement results.
⚛️ 👨🏫 📚 A two-week intensive Summer School on Quantum Computing from IBM Quantum, using mostly the features of the IBM's Qiskit library. In this Summer School, were lectured topics on basics of Quantum Information, Quantum Entanglement, Quantum Algorithms, Quantum Error Mitigation, among many others.