🎛️ Parameterized Circuits
Master variational quantum algorithms with trainable circuit parameters
Your Progress
0 / 5 completed🎯 What are Parameterized Circuits?
Parameterized quantum circuits (PQCs) are quantum circuits containing gates with tunable parameters that can be optimized classically. They form the foundation of variational quantum algorithms, enabling hybrid quantum-classical computation on near-term quantum devices.
⚡ The Variational Principle
PQCs use a quantum processor to evaluate circuit outputs for given parameters, while a classical optimizer adjusts parameters to minimize a cost function. This hybrid approach maximizes the utility of noisy intermediate-scale quantum (NISQ) devices.
Tunable Parameters
Rotation angles θ in gates like RX(θ), RY(θ), RZ(θ) can be adjusted during optimization
Iterative Optimization
Parameters are updated iteratively to minimize cost function through gradient descent
Hybrid Workflow
Quantum circuit evaluates cost, classical optimizer proposes new parameters
Expressibility
Circuit architecture determines range of quantum states that can be represented
📝 Circuit Structure
💡 Key Insight
Parameterized circuits enable quantum machine learning and optimization on current hardware. By encoding problems into cost functions and optimizing circuit parameters, we can solve practical problems before fault-tolerant quantum computers become available.