Instructor: Prof. Ted Pawlicki <pawlicki@cs.rochester.edu>
Office: 2101 Wegmans Hall instructor website
Lecture: Tuesday & Thursday 1230-1345.
Web: BlackBoard and https://learn.rochester.edu
Web: Blackboard
This course is a introduction to topics in Quantum Computing from a mathematical and algorithmic perspective. Topics covered include:
Students should expect to spend time outside of lecture in order to master this material.
Any introductory computer programming course is strictly required : CSC161, CSC171, ECE114.
Any course in Linear Algebra is strictly required.
The main text for the technical portion of this course will be online. Learn Quantum Computation using Qiskit . Many of the techincal exercises will be taken from this resource.
Six Impossible Things By Gribbin. There will be readings and homework (and maybe even small group discussions) based on this text.Quantum Algorithms via Linear Algebra By Lipton & Regan. If you love linear algebra.
Learn Quantum Computing with Python and IBM Quantum Experience: A hands-on introduction to quantum computing and writing your own quantum programs with Python By Loredo.Programming Quantum Computers: Essential Algorithms and Code Samples 1st Edition By Johnston, et.al. . Way cool simulator for small circuits.
< | Q | > A Course in Quantum Computing (for the Community College ) By Michael Loceff. A mighty tome; incredible detail.
Class meets twice per week.
There will be programming exercises using the online text.
Late assignments without suitable prearranged excuse will not be accepted. Missed or late homework will receive a grade of ZERO.
Final course grades will be based on the following components and weights:
| Written Homework & Programming Exercises | 80% |
| Reflective Essays (Gribbin text) & Guest Lecture Reviews (if any) | 20% |
There are no formal written exams.
There is no final exam during finals week.
This scheme is subject to change. Any changes will be announced in class.
Letter grades will follow the Official University of Rochester Grading Scheme. Note that the University scheme puts average
somewhere between C and B. The following table is an estimate of how the numeric grades will map onto the letter grades (subject to change):
| A: Excellent | >=90% |
| B: Above Average | >=80% |
| C: Minimum Satisfactory Grade | >=70% |
| D: Minimum Passing Grade | >=60% |
| E: Fail | <60% |
All appeals of grades for any component of the course (homework, project, quiz, exam, etc.) must be made within ONE WEEK of the grade being posted.
If you use your own computer, crashes, malfunctions, and catastrophic loss of files is NOT an excuse. Backup your files regularly to at least one external drive and/or cloud storage. You can always complete your assignments using the lab and IT Center computers.
Students with an appropriate excuse for late work must make arrangements in advance.
Students with an accommodation for any aspect of the course must make arrangements through the Center for Excellence in Teaching and Learning (CETL) IN ADVANCE. Then, as instructed by CETL, contact the instructor to confirm your arrangements. Do not leave this until the last minute either.
Students who are unable to attend or complete any part of the course due to illness should contact the instructor AS SOON AS POSSIBLE. Please note that the University Health Service (UHS) does not provide retroactive excuses for missed classes. Students who are seen at UHS for an illness or injury can ask for documentation that verifies the date of their visit(s) to UHS without mention of the reason for the visit. Students with extended or severe illness should contact the College Center for Advising Services (CCAS) for advice and assistance.
All assignments and activities associated with this course must be performed in accordance with the University of Rochester's Academic Honesty Policy. More information is available at: www.rochester.edu/college/honesty
Assignments including the final project are individual work and you must complete it individually. Your TAs are available in lab to help you with homework.
Collaboration on any assignment is permitted, subject to the following requirements:
Please note Section V.7 of the College's Academic Honesty policy regarding Unauthorized Recording, Distribution or Publication of Course-Related Materials.
CSUG is the Computer Science Undergraduate Council. These students graciously volunteer their time to help other students, especially students in introductory and core courses.
CSUG Tutoring Schedule: www.csug.rochester.edu/ugc/tutoring/
If you visit the CSUG tutors, please be respectful of their time and COME PREPARED. Try to solve the problem/question BEFORE going to CSUG Tutoring. Go to lab and work on the problem with the TAs BEFORE going to CSUG Tutoring. Go to workshop and discuss the problem with your colleagues BEFORE going to CSUG Tutoring. You MUST be able to show them what you have tried BEFORE you came to them.