6
Optimization Dynamics
Gradient Flow in Quantum Parameter Space
Gradient descent in VQA, quantum natural gradient, Adam and adaptive methods, stochastic optimization, convergence theory, optimal transport — plus population-based optimizers and HOPSO.
Lessons
6.1
Gradient Descent in VQA
6.2
Quantum Natural Gradient
6.3
Adam and Adaptive Methods
6.4
Stochastic Optimization
6.5
Convergence Theory
6.6
Optimal Transport and Optimization
6.7
Population-Based Optimizers
6.8
HOPSO: Hybrid Particle-Swarm Optimizer
Guided instruction and research mentorship are offered separately → hbar.work