In this work, we use LR-QAOA protocol as an easy-to-implement scalable benchmarking methodology that assesses quantum processing units (QPUs) at different widths (number of qubits) and 2-qubit gate depths.

MIT-iQuHACK-2025-IonQ-Team7 by Mauro Risonho de Paula Assumpção

⚛ Quantum Computing, for Humans.

A client library for accessing IonQ Cloud Platform API

QuForce Project to implement asymmetric cloning to eavesdrop on the BB84 protocol.

Hardware-Aware Variational Quantum Algorithms under Noise (VQE / QAOA Benchmarking Across IBM & IonQ)

Qiskit provider for IonQ backends

Microsoft Azure Quantum is Microsoft's cloud quantum computing service — an open, multi-vendor platform that provides access to quantum hardware from IonQ, Quantinuum, Pasqal, and Rigetti alongside Microsoft's own Q# programming language, Quantum Development Kit (QDK), and post-layout fault-tolerant Resource Estimator. The Azure Quantum Workspace…

This project aims to implement Quantum Support Vector Machines (QSVM) on actual quantum devices and simulators using the Qiskit library in conjunction with Amazon Braket (AWS). The core objective is to evaluate and compare the performance efficiency of QSVM implementations across various quantum hardware and simulation environments.

Continuation of QuForce Innovation Fellows Project to implement asymmetric cloning to eavesdrop on the BB84 protocol.