The algorithms course. Hidden subgroup problems, quantum walks, Hamiltonian simulation and query complexity, all treated properly. Dense, and worth every hour.
Quantum phase estimation
Given a unitary and one of its eigenvectors, extract the eigenvalue phase to n bits of precision using controlled applications of the unitary plus an inverse QFT.
Why it matters
QPE is the single most reused subroutine in quantum algorithms — Shor, HHL, and quantum chemistry energy estimation are all phase estimation wearing different hats.
After this you will be able to
- Draw and explain the QPE circuit
- Analyse the precision/qubit-count trade-off
- Identify QPE inside a larger algorithm
2 best places to start
Hand-picked and ordered. If you only have time for one, take the first.
Universally called "Mike & Ike" and still the field's reference text after two decades. Comprehensive rather than gentle — use it as the book you look things up in, not the one you read cover to cover first.
2 more resources
HHL, the source of most "exponential speedup for machine learning" claims. The caveats — state preparation, condition number, readout — matter more than the theorem, and are all in the paper.
A thorough, notebook-based curriculum built on the fast Qulacs simulator, strongest on quantum chemistry and variational methods. Under-known outside Japan and better than most English equivalents.
This unlocks
Topics that list Quantum phase estimation as a prerequisite.
Shor's algorithm
Factors large integers in polynomial time by reducing factoring to finding the period of a modular exponentiation function, which the QFT does efficiently.
IntermediateHamiltonian simulation
Simulating the time evolution of a quantum system — Feynman's original motivation — via Trotter-Suzuki product formulas, linear combination of unitaries, or qubitization.
Advanced