Part VII: Applications and Career
"The question is not whether quantum computers will be useful. It is which problem, on which machine, in which year — and whether you will be one of the people who can tell."
Everything before this part taught you to program quantum computers. This part is about what to point them at, and what that means for your career.
It is also where the book's honesty commitment is tested hardest, because these are the chapters where a less careful book would sell you something.
The four applications, honestly ranked
Quantum chemistry (Chapter 36) is the strongest near-term case, and it is not close. The reason is structural rather than promotional: molecules are quantum systems, so simulating them on a quantum computer is a natural encoding rather than a forced one, and the classical alternatives hit a genuine exponential wall for strongly correlated systems. Current hardware still cannot beat a good classical chemistry code on any molecule of industrial interest — Chapter 36 says so with numbers — but the gap is closing from both directions and the endpoint is not in doubt. This is also where the book's running project lands: a real molecular Hamiltonian, a real VQE run, a real energy within chemical accuracy of the exact answer.
Cryptography (Chapter 38) is the most consequential application and the furthest from realization. Shor's algorithm genuinely breaks RSA and elliptic-curve cryptography — but Chapter 23 already showed you the resource estimate, and it is millions of physical qubits. The practical content of this chapter is therefore not "how to break RSA." It is the migration problem: what harvest-now-decrypt-later means for data with a long confidentiality horizon, what the NIST post-quantum standards actually are, and what an organization should do this year. Plus BB84, which you will implement, because quantum key distribution is the one quantum cryptographic protocol that works on today's technology.
Optimization (Chapter 37) is the most heavily marketed and the weakest. QAOA is elegant and it runs, and for every problem small enough to fit on current hardware, a classical solver — often a solver from the 1990s — finds a better answer faster. Chapter 37 implements QAOA properly, on MaxCut, portfolio selection, and scheduling, and then benchmarks it against classical baselines and reports what happens. This is the chapter to read before your company signs a quantum optimization contract.
Machine learning was Part VI, and the verdict there was similar.
Then: the profession
Chapters 39 and 40 are about the working reality.
Chapter 39 compares the cloud platforms — IBM Quantum, Amazon Braket, Azure Quantum, Google — on the axes that matter operationally: what hardware you can reach, how access is priced and queued, what the SDK integration costs you, what error mitigation is available, and how you keep a quantum experiment reproducible when the machine's calibration changes daily.
Chapter 40 is about the career: who is hiring, what they interview on, which of your existing skills transfer (more than you think), whether you need a physics degree (usually no), what the compensation picture actually looks like, and how to get in. The book's running project is the centerpiece of that argument. "I built a variational quantum eigensolver from scratch, ran it on IBM hardware, mitigated the readout error, and got within chemical accuracy on H₂" is a specific, verifiable, unusual thing to be able to say, and it is worth more than any credential currently available in this field.
What You Will Learn
Chapter 36 — Quantum Chemistry. The electronic structure problem. Second quantization briefly, Jordan–Wigner and Bravyi–Kitaev mappings concretely. Building H₂'s qubit Hamiltonian from scratch. Active-space reduction. The full VQE run, on hardware, to −1.137 Hartree. LiH as the next step up. Quantum phase estimation as the fault-tolerant successor to VQE. And a clear statement of where the classical crossover actually sits.
Chapter 37 — Quantum Optimization. QUBO and Ising encodings. QAOA implemented for MaxCut, portfolio optimization, and scheduling. Depth $p$ and what increasing it buys. Warm starts. Classical baselines run head to head. The honest assessment.
Chapter 38 — Quantum Cryptography. BB84 implemented end to end, including eavesdropper detection, sifting, and error estimation. E91 in brief. The threat model for RSA and ECC. Grover against symmetric ciphers, and why AES-256 is fine. The NIST post-quantum standards. Harvest-now- decrypt-later. A migration checklist.
Chapter 39 — The Quantum Cloud Platforms. Four platforms compared on access, pricing shape, queueing, SDK integration, mitigation support, and hybrid workflow support. Quantum serverless. Reproducibility and provenance for quantum experiments. A decision table.
Chapter 40 — The Quantum Programming Career. The employers, the roles, the interview, the skills that transfer, the portfolio, open source as an on-ramp, the compensation picture, and the five-year view — with the uncertainty stated rather than hidden.
How This Part Fits
Chapter 36 depends on Chapter 24 and completes the project. Chapter 37 depends on Chapter 24. Chapter 38 depends on Chapters 4, 5, and 23. Chapters 39 and 40 depend on nothing in particular and can be read at any time — many readers should read Chapter 40 early, because it changes how you approach the rest of the book.
Time Investment
| Chapter | Title | Difficulty | Est. hours |
|---|---|---|---|
| 36 | Quantum Chemistry | Advanced | 9 |
| 37 | Quantum Optimization | Advanced | 7 |
| 38 | Quantum Cryptography | Intermediate | 7 |
| 39 | The Quantum Cloud Platforms | Intermediate | 5 |
| 40 | The Quantum Programming Career | Beginner | 4 |
| Part VII total | ~32 hours |
The Project Ends Here
Chapter 36 is the culmination. vqelab receives a real molecular Hamiltonian — built by mapping
the electronic structure of H₂ onto four qubits with a Jordan–Wigner transformation — runs the
optimization loop you assembled in Chapter 24, on the hardware path you built in Chapter 12, with
the mitigation from Chapter 13, using the layout selection from Chapter 29. Every piece was built
somewhere in this book.
The result is a ground-state energy. Compare it to the exact value, −1.137 Hartree. If the difference is under 1.6 mHa, you have used a quantum computer to compute a chemical property to chemical accuracy.
Then read Chapter 40 and go put it on your résumé.
Turn to Chapter 36.