大学院
HOME 大学院 量子計算論
学内のオンライン授業の情報漏洩防止のため,URLやアカウント、教室の記載は削除しております。
最終更新日:2025年4月1日

授業計画や教室は変更となる可能性があるため、必ずUTASで最新の情報を確認して下さい。
UTASにアクセスできない方は、担当教員または部局教務へお問い合わせ下さい。

量子計算論

Introduction to Quantum Computing in the Utility-Era
The goal of this course is to learn how to implement utility-scale applications on a quantum computer. To achieve the goal, the course covers from the basics of quantum information to recent advances of quantum algorithms for noisy quantum devices as well as circuit optimization and error mitigation techniques to maximize results. The course also introduces how to implement quantum algorithms using open-source framework of quantum computing and real quantum devices with more than 100 qubits. The course is intended to help students understand the potential and limitations of currently available quantum devices.
MIMA Search
時間割/共通科目コード
コース名
教員
学期
時限
4810-1166
GIF-CS5044L3
量子計算論
小林 有里
S1 S2
金曜5限
マイリストに追加
マイリストから削除
講義使用言語
英語
単位
2
実務経験のある教員による授業科目
NO
他学部履修
開講所属
情報理工学系研究科
授業計画
1: Invitation to the Utility era/Basics of Quantum Information 2: Quantum Algorithms: Quantum Teleportation 3: Quantum Algorithms: Grover’s algorithm 4: Quantum Algorithms: Phase Estimation 5: Quantum Algorithms: Variational Quantum Algorithms (VQA) 6: Quantum Simulation, Time Evolution 7: Classical Simulation 8: Sample-based Quantum Diagonalization 9: Quantum Circuit Optimization 10: Quantum Noise Model and Quantum Error Mitigation 11: Creating Large Scale GHZ State based on Hardware Topology and Qubits Fidelity 12: Reproducing Nature paper – 2D Ising model simulation 13. Final Project
授業の方法
Weekly lectures in person. We will be using laptops, so please bring your own.
成績評価方法
No examinations. Grades will be based on two assignments and completing the final project.
教科書
None in particular
参考書
IBM Quantum Learning - Utility scale quantum computing: https://learning.quantum.ibm.com/***** Nielsen, Michael A., and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge, UK: Cambridge University Press, September 2000. ISBN: 9780521635035.
履修上の注意
Prior knowledge of linear algebra, classical algorithms, and programming are required. Understanding quantum mechanics is a plus but not required. Familiarity with programming tools is a plus because most assignments require students to write programs. All lectures will be held in person. Recording will also be available for reviewing.