We use the Max-Cut problem to demonstrate how to transition from a classical matrix formulation to a quantum operator without ever building the full dense matrix.
We cannot search the entire Hilbert space. We explore the n-local blueprint, why we prefer 2-local circuits, and use RealAmplitudes to find the answer with exponentially fewer parameters.
Why our previous circuit failed, how adding a CNOT gate fixes it, and why even that isn’t enough for every matrix.
Turning constants into variables: How to build a parameterized quantum circuit and use classical optimization to find the minimum eigenvalue and eigenvector.
How to translate classical linear algebra structures into quantum states and operators, and efficiently calculate expectation values using the Qiskit Estimator.
Exploring the linear algebra foundations of VQE and how finding the lowest eigenvalue translates to a quantum optimization problem.
Exploring how three particles can fit into two boxes without any two particles sharing a box—a journey through pre-selection, post-selection, and weak measurements.
Exploring the frontiers of Quantum Computing, the architecture of innovation, and how Generative AI is fundamentally altering professional workflows.
