Eighteen quantum algorithms, each one proven, run, benchmarked, and priced. A colleague forwards a paper claiming a quantum advantage. A team asks which algorithm fits the problem on the table, and how much to trust the answer. The mathematics is settled enough to sort real speedups from hopeful ones, and this book puts that sorting skill in a reader's hands: *Quantum Computing Algorithms* is built to be checked, not just read.
Inside, eighteen algorithms get the treatment they have never gotten together in one book: the rigorous core (what each one actually does, why it works, and what speedup is genuinely proven), a working lab you can run yourself, and an honest verdict. Grover's search, amplitude estimation, quantum walks, phase estimation, Shor's factoring, quantum linear systems, Hamiltonian simulation and quantum chemistry, VQE, QAOA, annealing, quantum kernels, quantum reinforcement learning, and the deployed protocols of quantum key distribution and quantum randomness. Each one is placed on the **Speedup Ladder**, the book's organizing idea: four rungs of evidence, from *provable exponential* down to *heuristic*, so that the table of contents itself is a map of how much to trust each claim.
The rules never bend. Every number in the text was printed by a program that ships with the book, deterministic and checkable line for line. Every quantum result stands beside a tuned classical baseline that was actually trying to win, and in these pages the classical method often does. Every speedup names its evidence tier and its baseline. And where the honest answer today is *not yet*, the book says so and shows the arithmetic, including the one chapter that prices exactly what fault-tolerant quantum computing will cost.
Written for R&D engineers, technical architects, and graduate students who want the mathematics *and* need to know what it is for. Five recurring professionals, a safety lead, a dispatcher, a chemist, a security architect, and an operations engineer, carry the industrial stakes through the chapters and reconvene at the end as a decision board. A ten-question worksheet lets you run your own problem through the same discipline. Public labs run on nothing but pip-installable Python; the code companion is on GitHub.
By the author of *Quantum Computing Fundamentals* and *Quantum Computing in Finance*. No prior quantum background beyond the fundamentals is assumed.
