US$25
weeklyor US$250 for 10 classes
包含什麼
10 現場會議
10 上課時間評分
Grades will be provided by request at the end of the course. They will be based on participation and project work.我們無法翻譯此文,請刷新頁面並再試一次。
課堂經歷
英語程度 - 未知
美國 9 - 12 年級
Beginner 等級
Quantum Computing for High School Students via Python Throughout history ideas taken from science fiction have evolved to become science fact and then gone on to transform our lives. This evolution takes time. One such example begins with the Wright brothers providing "proof of principle" for powered flight in 1903 and culminates with Boeing introducing the 747 "Jumbo Jet" in 1970. Quantum Computing promises to be another life altering idea and it is in its early stages. Maybe it's time to get in on the ground floor. Initially proposed by Richard Feynman in the early 1980s, but based on ideas from the science of quantum physics which date back to the 1920s, quantum computers have the potential to become one of the most important machines ever invented by mankind. When fully developed they will be capable of solving problems in minutes that would take even the world’s fastest supercomputer more than 10,000 years. Primitive versions of such machines have already been build by large corporations such as Google and IBM. Governments and universities around the world are also actively engaged in the field. This course is an opportunity for your student to be exposed early on to what promises to become one of the most important technologies of the twenty-first century. It is designed to provide students with a solid foundation in this emerging technology. In this course your student will learn how to code on a “classical” computer with the intent of simulating a “quantum computer”. Your student will learn a popular programming language (Python) and use it to write computer code for projects that will explore the basic ideas at the core of quantum computing. Along the way your student will become conversant with the fundamental unit of classical information (the bit), together with its quantum counterpart (the qubit). They will learn about gates and circuits and write programs that perform both mundane tasks, such as adding together two numbers, as well as extraordinary tasks such as quantum teleportation. By way of explanation, the term quantum teleportation refers to a laboratory procedure during which quantum information is transferred from a quantum particle or system at one location to a quantum particle or system some distance away. While not quite the same as what one might see in an episode of Star Trek, it is still an amazing feat to witness. By the end of the course your student will (i) have a working knowledge of a Python program that simulates the workings of an actual quantum computer; and (ii) be in a position to use this program to continue learning about a technology that promises to play an important role in their future. Week 1 Introduction to Quantum Computing Introduction to Python Classical Bits and Quantum Bits The NOT Gate The HADAMARD Gate Week 2 White Balls and Black Balls A Simple Arithmetic Model of Quantum Computing Quantum Circuits & the "Misty" Python code base An "experiment" with HADAMARD gates Week 3 Single qubits The "Rudolph" Grid The Z gate and the ROT gate Additional multi-qubit gates Week 4 Quantum Circuit Diagrams Python Code Lots of examples Week 5 Superposition Entanglement Measurement The "collapse" of Mist objects Week 6 Doing something useful with a quantum computer Quantum Arithmetic The Bernstein-Vazarani Algorithm Week 7 Quantum State Teleportation Week 8 The Classical "CHSH" Game Week 9 The Quantum "CHSH" Game Week 10 Wrap-Up The Current Quantum Playing Field During and after each class session students will work on a variety of practice coding scenarios related to quantum computing. These scenarios will assist students in acquiring a familiarity with the concepts being discussed. No prior knowledge of coding or quantum physics is required. Questions are both anticipated and encouraged — both during class and after class. Technology Requirements: Students will code with either Mu Editor (a small, simple editor for beginner Python programmers) or Processing, another free code editor. Both editors work with any Macintosh or Windows computer.
教學大綱
10 課程
超過 10 週課 1:
Introduction to Quantum Computing
This lesson serves as an introduction to quantum computing and contrasts it with classical computing. Both classical "bits" and quantum "qubits" are discussed, together with classical "not" gates and quantum "Hadamard" gates.
60 分鐘線上直播課
課 2:
Simple Arithmetical Model of Quantum Computing
This lesson describes a simple arithmetical model of what is going on inside a quantum circuit. The model is used to explain the strange behavior of quantum Hadamard gates. The "Misty" Python code base is introduced and the idea of "superposition" is explained.
60 分鐘線上直播課
課 3:
QuStates, Mists & the "Rudolph" Grid
This lesson involves a deeper understanding of single qubits and introduces the so-called "Rudolph" Grid. Two new single qubit quantum gates are introduced, together with a number of multi-qubit gates.
60 分鐘線上直播課
課 4:
Quantum Circuit Diagrams and Python Code
This lesson uses a number of examples of working with quantum circuit diagrams both via "pencil & paper" and the Python code.
60 分鐘線上直播課
其他詳情
父母的引導和規範
Students may use any programming environment that supports the Python programming language. Both Mu Editor and Processing will be used for demonstration purposes.
先決條件
There are no prerequisite requirements for this class. No programming experience is necessary and the only mathematics involved is simple arithmetic.
供應清單
Students will need access to either a Macintosh or Windows computer.
教學語言
英語
外部資源
學習者無需使用標準 Outschool 工具以外的任何應用程式或網站。
來源
Each class will accompanied by a set of class notes.
認識老師
教師專業知識和證書
Dr. Rosenberg holds a Ph.D. in theoretical physics from the City University of New York. Since 1995 he has taught at Edgemont High School in Scarsdale, NY and SAR High School in Riverdale, NY. He has taught Quantum Computing, AP Physics and AP Computer Science. In 2007 he was named the top AP Science Teacher in New York State by the Siemans Foundation. He was also cited twice (2006 and 2007) by the College Board for "best participation/performance" worldwide for AP Computer Science.
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