Introduction to Programming Quantum Algorithms in IBM’s Qiskit
In this course, you will learn the basics of modern quantum computing and gain exposure to software used to analyze and simulate quantum algorithms. Part 1 of the course will begin with an introduction to quantum gates and circuits after a brief refresher on quantum mechanics. We will then dive into modern quantum algorithms used in machine learning, molecular/material simulation, and combinatorial optimization. By the end of Part 1, you will be able to construct and analyze quantum circuits. Furthermore, you will be able to translate example quantum algorithms into quantum circuits.
The second part of the course will focus on gaining hands-on experience with implementing quantum circuits and algorithms using IBM’s Qiskit API. Through Qiskit, you will learn to construct, simulate, and analyze quantum circuits. This will include a discussion of noisy emulators used to mimic hardware dynamics. The course will finish with a brief introduction to executing quantum circuits on quantum hardware. By the end of Part 2, you will be able to leverage Qiskit to construct quantum algorithms and analyze their behavior in simulated and experimental environments.
A parking permit will be provided for registered attendees.
Date and Time
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- Starts 13 March 2026 04:00 AM UTC
- Ends 02 June 2026 04:00 AM UTC
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Speakers
Gregory Quiroz : Johns Hopkins University Applied Physics Laboratory & Department of Physics and Astronomy at Johns Hopkins University
Biography:
Gregory Quiroz is a principal scientist at the Johns Hopkins University Applied Physics Laboratory. In addition, he is an associate research professor in the Department of Physics and Astronomy at Johns Hopkins University. Dr. Quiroz received his PhD from the University of Southern California in 2013, where he studied quantum control and adiabatic quantum computation. Thereafter, he transitioned to a role as a staff scientist at the Aerospace Corporation in Los Angeles, CA. His research focused on quantum communication and quantum algorithm development for National Security Space applications. Since 2016, he has been a senior scientist at the Johns Hopkins University Applied Physics Laboratory, where he now also holds the role of supervisor for the Applied Quantum Sciences section within the R&D sector of the lab. His current research interests include quantum characterization and control, applications of quantum control to quantum algorithm design, and quantum sensing.
Agenda
The course will include the following:
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Part 1: Fundamentals of Quantum Computing and Quantum Algorithms
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Overview of Quantum Mechanics
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Introduction to Quantum Gates and Quantum Circuits
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Variational Quantum Algorithms
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Simulating Quantum Dynamics
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Part 2: Introduction to IBM’s Qiskit
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Building, Simulating, and Analyzing Quantum Circuits
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Leveraging Noisy Simulators
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Executing Circuits on Quantum Hardware
Attendee Requirements: Attendees will need to bring laptops with python, Qiskit, and Jupyter Lab or Jupyter Notebooks installed. Please download the python of your choice and create an environment to install the latest version of Qiskit and Jupyter (preferably Lab). Test the installation ahead of time by opening Jupyter and creating a notebook. Try to import Qiskit to check that the installation has completed correctly.
Qiskit - https://github.com/Qiskit/
Jupyter- Project Jupyter | Installing Jupyter