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Fraunhofer IAO QC / SEQUOIA End-to-End / Sensitivity Analysis for Network Failure
Apache License 2.0Here we perform a hybrid, Grover based optimization to find the single network parameter change that leads to the largest reduction of the critical failure probability in a cascading network
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A web page for publishing process-specific hydrogen potentials, using GitLab pages.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Solving LamA Problem via MILP Model
Apache License 2.0In this demonstration, we present a Quantum Alternating Algorithm designed to address Mixed Integer Linear Problems (MILP). The algorithm's efficacy is showcased through the resolution of an energy use case, employing CPU and GPU quantum simulators, as well as the IBM Quantum System at Ehningen.
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Fraunhofer IAO QC / SEQUOIA End-to-End / PDEs Solutions with Quantum Convolutional Neural Networks
Apache License 2.0In this demostrator, we illustrate not only the general procedure of building a QNN via quantum circuit, but also showcase using QNN to predict 2D solution of Poisson equation. To accelerate the convergence, the physics informed NN is introduced. We also show the convergence comprison between QNN and PIQNN.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Error Mitigation by Zero Noise Extrapolation
Apache License 2.0Demonstrator for Zero-Noise Extrapolation (ZNE) and Inverted-Circuit ZNE
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Fraunhofer IAO QC / SEQUOIA End-to-End / Neural Networks with Quantum Deterministic Annealing
Apache License 2.0We propose a quantum version of the deterministic annealing algorithm to verify the input-output relations of a neural network. We apply the algorithm to traffic sign recognition, an important task for self-driving vehicles.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Automatic Feature Map Generation
Apache License 2.0The demonstration illustrates the generation of a quantum feature map for a simple regression problem. Reinforcement learning techniques are used, visualizing the decision process of the AI agent through a simple visualization of the quantum circuit creation. We show how to load, train and test the model. The results show a feature map design tailored to the problem.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Scenario-based Route Planning to Safeguard Automotive Driving Functions
Apache License 2.0A demonstrator for the Sequoia End-to-End project which shows how scenario-based route planning to safeguard automotive driving functions can be implemented to run on a quantum computer
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Fraunhofer IAO QC / SEQUOIA End-to-End / QC Network Resilience Analysis
Apache License 2.0The demonstrator shows the time evolution of a small network with failures.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Optimization EV Charging Schedules
Apache License 2.0End-to-end demonstrator for quantum optimization of charging schedules.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Configuration Selection and Prioritization using QAOA
Apache License 2.0This notebook illustrates using the Quantum Approximate Optimization Algorithm (QAOA) to find optimized configurations for feature models with attributed costs on a quantum computer.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Assembly Line Balancing Problem
Apache License 2.0Solving a combinatorial optimization problem with a hybrid quantum-classical algorithm.
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Fraunhofer IAO QC / SEQUOIA End-to-End / Accelerating TSP Approximation
Apache License 2.0An alternative problem encoding for QAOA is used to accelerate cost function computation
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Simulation env based on Brax / MuJoCo for robotic assembly tasks.
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