This graduate elective bridges combinatorial optimization with the physics of quantum computing, focusing on how problems IE students already know how to model classically can be recast as Ising or QUBO formulations and attacked on actual quantum hardware. You'll work through three homeworks, a midterm and final, and a course project where you implement algorithms like quantum annealing, QAOA, and Grover search using Qiskit, D-Wave's Ocean SDK, and OpenJij on simulators and real devices. It sits at the edge of what's currently practical, so a big part of the course is honestly benchmarking quantum approaches against classical solvers and understanding why NISQ-era limitations still matter.
→ STARS müfredatı (resmi syllabus)
İzlencede 1 midterm var, ağırlığı %25. Final %35. Kalan %40 dersin öteki kalemlerinde. Tam dağılım aşağıda.
Bilkent kataloğunda bu ders için ön koşul yazılı değil.
İzlencede önerilen kitap: Quantum Algorithms for Optimizers, Giacomo Nannicini, 2025. İzlence toplam 4 kaynak sayıyor.
3 Bilkent kredisi, 5 AKTS.
| Kalem | Ağırlık | Notun (100 üzerinden) |
|---|---|---|
| Midterm Exam | %25 | |
| Final Exam | %35 | |
| Course Project | %25 | |
| Homework Assignment | %15 |
Ağırlıklar IE 558 izlencesinden. Hocanın bu dönemki dağılımı farklı olabilir; bağlayıcı olan ders izlencesidir. Harf notu sınırlarını hoca belirliyor, o yüzden hedefi sen giriyorsun. İzlencede FZ şartı var, sayfanın sonundaki kutuda.
Bilkent'in resmî syllabus'ünden. Sağdaki etiket o çıktının hangi değerlendirmeyle ölçüldüğünü söylüyor.
İlk dosyayı sen atarsan: not, slayt, geçmiş sınav, çözüm, cheat-sheet, ne varsa. defter ekibi öğrenci paylaşımlarından bu dersin notlarını yazar. Drive linki / PDF / ZIP, hepsi olur.
Course Learning Outcomes: Course Learning Outcome Assessment Explain the fundamental principles of quantum computation effectively applied to solving optimization problems. Midterm Exam Final Exam Homework Assignment Transform classical combinatorial optimization problems into quantum-compatible formulations, such as Ising and QUBO models. Midterm Exam Course Project Homework Assignment Demonstrate a strong understanding of leading NISQ-era algorithms, specifically Quantum Annealing and QAOA. Midterm Exam Final Exam Course Project Homework Assignment Construct and execute quantum algorithms using industry-standard Python toolkits like Qiskit, Ocean SDK, and OpenJij. Course Project Homework Assignment Critically evaluate quantum and quantum-inspired solutions against classical methods, considering the constraints of current quantum hardware. Final Exam Course Project