Tutorials Program
Tutorials Scope and Goals
The shortage of skilled labor is one of the quantum computing sector’s greatest challenges. The week-long tutorials program, with tutorials by leading experts, is aimed squarely at workforce development and training considerations. The tutorials are ideally suited to develop quantum champions for industry, academia, government, and build expertise for emerging quantum ecosystems. IEEE Quantum Week will cover a broad range of topics in quantum computing and engineering including a lineup of fantastic hands-on tutorials on programming and applications.
Tutorials Co-Chairs and Contacts
- Prasanna Date, Oak Ridge National Laboratory (ORNL) — [email protected]
- Huiyang Zhou, NC State University — [email protected]
Tutorials Program
- Dates: Sunday – Friday, September 17-22, 2023
- Time: 10:00 – 16:30 Pacific Time (PDT) — UTC-7
- Duration: Each tutorial is 3 hours (2 sessions of 1.5 hours)
QCE23 Tutorials Program — Overview
Sunday, Sep 17, 2023 — Tutorials
Monday, Sep 18, 2023 — Tutorials
Tuesday, Sep 19, 2023 — Tutorials
TUT11 — QubiC: An Open-Source FPGA-based Quantum Controller
Abhi Rajagopala, Lawrence Berkeley National Laboratory (LBNL), USA
Neelay Fruitwala, Lawrence Berkeley National Laboratory (LBNL), USA
Yilun Xu, Lawrence Berkeley National Laboratory (LBNL), USA
Gang Huang, Lawrence Berkeley National Laboratory (LBNL), USA
Kasra Nowrouzi, Lawrence Berkeley National Laboratory (LBNL), USA
Wednesday, Sep 20, 2023 — Tutorials
TUT18 — Parameterized Quantum Pulse Circuit and its Application
Zhiding Liang, University of Notre Dame, USA
Hanrui Wang, MIT USA
Jinglei Cheng, University of Southern California, USA
Jiaqi Gu, University of Texas at Austin, USA
Zhixin Song, Georgia Institute of Technology, USA
Hang Ren, UC Berkeley, USA
Rui Yang, Peking University, China
David Pan, University of Texas at Austin, USA
Yongshan Ding, Yale University, USA
Fred Chong, University of Chicago, USA
Song Han, MIT, USA
Yiyu Shi, University of Notre Dame, USA
Thursday, Sep 21, 2023 — Tutorials
TUT24 — Quantum plus High-Performance Computing for Natural Language Processing
Eduardo Coello Perez, Oak Ridge National Laboratory (ORNL), USA
Prasanna Date, Oak Ridge National Laboratory (ORNL), USA
Mayanka Chandra Shekar, Oak Ridge National Laboratory (ORNL), USA
Kathleen Hamilton, Oak Ridge National Laboratory (ORNL), USA
John Gounley, Oak Ridge National Laboratory (ORNL), USA
Francisco Rios, Oak Ridge National Laboratory (ORNL), USA
In-Saeng Suh, Oak Ridge National Laboratory (ORNL), USA
Georgia Tourassi, Oak Ridge National Laboratory (ORNL), USA
TUT25 — Deep Dive into Classical Simulation of Quantum Circuits with QX-Simulator
Pablo le Henaff, Delft University of Technology, The Netherlands
Sebastian Feld, Delft University of Technology, The Netherlands
Medina Bandic´, Delft University of Technology, The Netherlands
Nikiforos Paraskevopoulos, Delft University of Technology, The Netherlands
Friday, Sep 22, 2023 — Tutorials
TUT30 — Introduction to SeQUeNCe, a Customizable Discrete-Event Simulator of Quantum Networks
Rajkumar Kettimuthu, Argonne National Lab (ANL) & The University of Chicago, USA
Alexander Kolar, University of Chicago, USA
Allen Zang, The University of Chicago, USA
Joaquin Chung, Argonne National Lab (ANL), USA
QCE23 Tutorials Program — Abstracts
Sunday, Sep 17, 2023 — Tutorials Abstracts
Date: Sun, Sep 17, 2023 — Part 1
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Date: Mon, Sep 18, 2023 — Part 2
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: From this tutorial, attendees will gain a basic understanding of quantum computing, from the underlying principles up through recent developments in the field. Attendees will learn how essential quantum algorithms operate and gain experience with approaches for programming radically different types of quantum computers.
Abstract: Quantum computing offers the potential to revolutionize high-performance computing by providing a means to solve certain computational problems asymptotically faster than any classical computer. Relatively recently, quantum computing has advanced from merely a theoretical possibility to engineered reality, including commercial entities offering early prototype quantum processors, both special-purpose quantum annealers and general-purpose gate-model processors. The media have been showcasing each new development and implicitly conveying the message that quantum-computing ubiquity is nigh. Here, we will respond to this hype and provide an overview of the exciting but still early state of the field.
In this tutorial, we introduce participants to the computational models that give quantum computing its immense computational power. We examine the thought processes that programmers need to map problems both to quantum annealers and gate-model quantum processors. And we discuss hardware and algorithmic challenges that must be overcome before quantum computing becomes a component of every software developer’s repertoire.
Keywords: Circuit-model, gate model, quantum annealing, quantum algorithms, QAOA
Contents Level: We expect the content level to be distributed as follows:
80% beginner
20% intermediate
0% advanced.
No prior knowledge of quantum computing or quantum mechanics is expected, but the final section of the tutorial goes
into some technical depth that requires that attendees have understood the preceding sections.
Target Audience: The tutorial targets a broad audience: essentially anyone who is curious about quantum computing and wants to learn how it works and what it can and cannot do. Those who know little to nothing about quantum computing will benefit more from the tutorial than those who have existing expertise in quantum mechanics or who already have had non-trivial exposure to quantum computing, but even professionals who have worked in the field will likely gain at least some knowledge.
Date: Sun, Sep 17, 2023
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: This tutorial will introduce the audience to the emerging field of quantum computer cybersecurity, which focuses on research on how to make quantum computing systems secure. With rapid advances in quantum computer technologies, as the number of qubits increases, and the fidelity of the qubits and operations improves, these computers will be able to generate novel drugs or material compounds. Once the computers are generating or processing sensitive or valuable information, they will become a target for security attacks. Moreover, many quantum computers are already cloud-based. Remote, on-demand cloud computing-like access to quantum computers makes them especially vulnerable to security attacks as anybody with a credit card can purchase access and run almost arbitrary quantum circuits on them. Even potential “virus” circuits. First, this tutorial will introduce audience to classical computer security ideas such as threat modeling, confidentiality, integrity, and availability, information leaks, side- and covert-channel attacks. Second, this tutorial will apply classical computer security mindset to quantum computers, and demonstrate examples of security attacks prototyped on real cloud-based NISQ quantum computers available today. Third, the tutorial will present designs for securing the cloud-based NISQ quantum computers from the security attacks. Lastly, the tutorial will present challenges and opportunities to build quantum computer security from the ground up now, rather than have to patch the quantum computers later once security attacks have occurred in the wild.
Keywords: Quantum computer security, Threat modeling, Security attacks, Security defenses, Fast and secure quantum computers
Contents Level: Quantum Computing: beginner; Compuer Security: beginner to intermediate.
Target Audience: Expected background and prerequisites of the tutorial attendees: Audience does not require computer security background. Expected background includes basic knowledge of computers, and interest in learning about cloud-based quantum computers and making them secure. What will target audience learn: Quantum computing engineers and researchers will learn how to make more secure quantum computers and how to protect the computing machines from vulnerabilities now that many of the quantum computers are connected to the internet (e.g., IBM Quantum, Amazon Braket, Microsoft Azure).
Date: Sun, Sep 17, 2023
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: The QICK is a standalone open-source controller for both superconducting and atomic qubits as well as various detectors. Over 20 times cheaper than commercial qubit control equipment, the QICK runs on publicly-available open-source firmware and software. The QICK is used in industry and academic labs throughout the world for controlling quantum systems, and by using the QICK anyone can learn the full quantum control stack from scratch. In this tutorial, we hope to engage those interested in quantum controls at any level of the stack, and teach them the QICK hardware, firmware and software. Attendees will leave this tutorial with a clear understanding of how QICK works under the hood, and with the ability to deploy and describe an experiment by using one of the supported boards. To make the tutorial easy to follow, attendees will access live demonstrations and use the boards themselves to send and receive signals.
Keywords: Quantum computing, quantum sensing, real-time control, hands-on programming, field-programmable gate arrays (FPGAs), digital signal processing, superconducting qubit.
Contents Level: 20% beginner, 40% intermediate, 40% advanced. No prior knowledge of either quantum computing or QICK is required. Basic concepts are introduced to build up knowledge gradually.
Target Audience: The tutorial targets a broad audience that ranges from researchers to students with some engineering, math, computer science or physics background that are willing to get started using the QICK for quantum experimentation. Attendees will learn how the QICK works, and be given the tools to be able to describe for themselves single- or multi-qubit experiments using this system.
Date: Sun, Sep 17, 2023
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: In this tutorial we educate the participants about the physical or hardware layer in quantum network stacks. Through a combination of lectures and a hands-on simulation workshop, we discuss the requirements for this abstraction layer.
Abstract: Quantum networks will enhance our classical Internet by supplementing it with capabilities such as quantum secure communications, quantum sensing, secure quantum computing in the cloud, and distributed quantum computation. To develop this technology, several initiatives have recently started to create quantum network testbeds. In this tutorial we focus on one of the key challenges in creating such testbeds: the architecture of the hardware or physical layer, which is responsible for generating entanglement between two neighbouring nodes. In particular, we will focus on the quantum device control stacks which are responsible for sending control signals to the quantum hardware as well as the synchronisation and low-level communication between the nodes. In the first half of the tutorial, we will discuss the needs for the physical layer from both the state-of-the-art research perspective, i.e., what is needed to control the quantum hardware, as well as from the use-case perspective, i.e., what is needed for quantum network applications. In the second half of the tutorial the participants will develop a simulation of the physical layer of the quantum network stack using the NetSquid quantum network simulator. The goal is to learn about the building blocks necessary to build full-stack quantum network nodes and how to connect them. In a final interactive discussion the participants will get the chance to discuss what they have learned, both in terms of requirements of the quantum control stacks, as well as on how to use them for different quantum networking qubit platforms.
Keywords: Quantum Internet, Quantum Communication, Quantum Control Stack
Contents Level: 30% beginner, 60 % intermediate, 10% advance
Target Audience: The main goal of this tutorial is to educate the audience about the challenges of building a quantum
network from the bottom up. We aim to achieve this goal by teaching the audience about the
entanglement generation process at the physical layer for a single quantum link. To reach that, the main
goal is broken up into three subgoals: (1) discuss the requirements and limitations of the
hardware/physical layer from the use case perspective and (2) from a quantum hardware or qubit
perspective, and (3) providing the audience with a hands-on exercise to implement a simulation of a
quantum network physical layer protocol to consolidate the prior discussions.
With this tutorial we target participants with an interest in quantum communication and networks with
either a physics background or an engineering background as the physical layer is where these two meet.
All attendees will benefit by learning about the basic building blocks of quantum networks from hardware
to applications. The hands-on exercise in NetSquid will help the audience understand the fundamental
quantum processes and the hardware engineering that is required to build quantum networks. As the
details of the quantum hardware are abstracted away, this exercise is very suitable for engineers.
Attendees with a quantum computing background will benefit by learning about the physical requirements
of interconnecting quantum computers.
The audience will learn how to implement a physical layer protocol for entanglement creation between
nodes, and what the challenges and considerations are to be taken into account when doing this. These
considerations have implications for both the quantum hardware (physics) side as well as the use case
level.
Date: Sun, Sep 17, 2023
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: This tutorial explores the challenges of noise in quantum computing and introduces state-of-the-art error mitigation strategies for modern and near-term quantum computers. It also provides a hands-on case study using open-source quantum tools to demonstrate noise mitigation techniques in various stages of quantum computation.
Abstract: Using superposition and entanglement, one can develop an application accelerated by a quantum computer to solve some problem faster than a high-performance classical computer ever could. Although quantum computers capable of outperforming classical computers in solving real-world problems are not a reality yet, we expect them to be ready soon. Until then, we can get ready for this future, developing and testing quantum-accelerated solutions now. In this tutorial, we cover from the description of what is a quantum bit to the implementation and execution of quantum algorithms, presenting the basics of quantum computing and how to express them in a quantum program. The objective is to offer a gentle introduction to quantum computing, presenting a new quantum programming language, paving the way for those getting started in the field. We will be hands-on in the quantum programming language Ket, looking into the superposition to better understand the computation process without deepening into the math of quantum mechanics. We will introduce the concepts of quantum superposition, entanglement, quantum gates, and measurement, following a step-by-step evolution of the quantum state while applying quantum operations. In the end, we will present, implement, and execute two well-known quantum algorithms: Grover’s search algorithm and Shor’s factoring algorithm.
Keywords: Quantum Computing, Quantum Programming, Quantum Simulation, Quantum Algorithm, Grover’s Algorithm, Shor’s Algorithm, Ket
Contents Level: The content level of this tutorial is approximate 80% beginner, 20% intermediate, 0% advanced. No prior knowledge of quantum mechanics or quantum computing is required. The basics of linear algebra will help understand some of the content, but it is not required. We expect the attendees to have a basic understanding of Python and, optionally, Jupyter Notebook.
Target Audience: The target audience of this tutorial is students, researchers, and enthusiasts that are getting started with quantum computing and quantum programming. We will present the tutorial focusing on peculiarities, limitations, and features of the quantum computation model and not on the physical realization of quantum computers, a more appealing perspective to engineers, developers, and computer scientists. The attendees will learn how to program and execute quantum algorithms and applications in Ket, preparing them for future research and development of solutions powered by quantum computers.
Date: Sun, Sep 17, 2023
Time: 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Quantum hardware is experiencing a boon leading to more chip variety and configurations with higher fidelities. While ultimately, this will translate to a boon for the entire field of quantum computing, it presents two problems. First, algorithm designers and users must make more difficult choices between potential hardware vendors. Second, this places more of the overall burden of end-to-end quantum applications on the software stacks, specifically the quantum compiler. The Berkeley Quantum Synthesis Toolkit (BQSKit) is a powerful and portable compiler with a proven ability to alleviate these issues and translate recent hardware successes up to the algorithm level. In this tutorial, we first introduce the idea of numerical instantiation and BQSKit compilation, including workflows for transpiling circuits to any hardware, even ones with heterogeneous gate sets or higher-level qudits (qutrits). We then do a deep dive fine-tuning a compilation workflow for an end-to-end variational application equipping attendees with the knowledge and ability to better implement algorithms on NISQ devices and beyond.
Keywords: Circuit, Unitary, Synthesis, Gateset, Topology-aware, Mapping, Compilation, Transpilation
Contents Level: 20% beginner, 60% intermediate, 20% advanced.
Target Audience: This tutorial introduces the practical challenges when compiling quantum programs for NISQ-era devices and teaches how to use BQSKit to overcome these challenges. Beginners, who only need to be familiar with the quantum circuit model, basic linear algebra terms, and the Python programming language, will learn how to utilize circuit transpilation methods to pick and compile for NISQ-era hardware. Advanced quantum computing users with a target application in mind will additionally benefit when we teach how to fine-tune a compilation workflow for their specific application.
Monday, Sep 18, 2023 — Tutorials Abstracts
Date: Mon, Sep 18, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: The limited number of qubits poses a challenge for practical usage of near-term quantum computation. Circuit cutting is a technique to increase the size of circuits we can run on quantum hardware at the cost of an additional sampling overhead. A larger quantum circuit can be decomposed by cutting its gates and wires into smaller circuits which can be executed within the constraints of available quantum hardware. The results of these smaller circuits are combined to reconstruct the outcome of the original problem.
Attendees of this tutorial will learn: the theory behind the latest circuit cutting techniques, how to cut a quantum circuit using the Circuit Knitting Toolbox, how to optimize a hybrid workflow with Quantum Serverless, and how circuit cutting can leverage the next iterations of quantum hardware architectures.
Keywords: Quantum algorithms, Circuit cutting, Circuit knitting, Quantum serverless
Contents Level: The content will be 60% beginner and 40% intermediate. We expect the typical attendee to have had exposure to programming in Python and some basic knowledge about quantum computing. Some familiarity with Qiskit would also help. Prior to attending the tutorial session, participants are expected to have both Python and Qiskit installed if they wish to follow along with the code examples.
Target Audience: This tutorial targets quantum researchers, quantum software developers, and quantum cloud developers who want to leverage quantum computing in their respective fields and are interested in learning how circuit cutting and other workflows containing heterogeneous compute can be configured with Quantum Serverless.
Date: Mon, Sep 18, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: In this tutorial, advanced methods for formulating problems as QUBO are presented. In a combination of lectures and a practical workshop, different methods and their influence on solution quality will be discussed.
Abstract: Real-world problems need first to be formalized such that one can choose or build an algorithm to solve them. There is a list called Karp’s 21 NP-complete problems, to which all problems can be reduced. Such a list helps to identify the general structure of a given problem and choose an already existing (type) of algorithm. Since relevant problems are in general hard to solve, one needs to choose from a variety of algorithms, solvers, and (meta-)heuristics, all of which have their pros and cons. Recently, quantum-assisted and quantum-based software- and hardware problem solvers have been proposed. Now, the well-known problem classes need to be reformulated such that they can be solved using these novel techniques. Quantum Annealing, for example, can solve problems formulated in the Ising model or as Quadratic Unconstrained Binary Optimization (QUBO) problems, while gate model algorithms like QAOA accept Polynomial Unconstrained Binary Optimization (PUBO) problems, and with this also those in QUBO form. It is known that the particular formulation of a certain problem has got an impact on the behavior of the solving algorithm and the resulting solution quality. Thus, the idea is now to step away from a manual formalization of a problem, towards an automated one. In this tutorial, we will present, explain, discuss and demonstrate several algorithmic approaches for finding QUBO formulations together with their impact on problem size and solution quality.
Keywords: QUBO, PUBO, Quantum Annealing, QAOA Problem Formulation Solution Quality
Contents Level: The approximate content level of this tutorial is 30% beginner, and 70% intermediate
Target Audience: This self-contained tutorial is intended to serve a broad audience. We basically address everyone who is interested in quantum-assisted (combinatorial) optimization and who would like to experience a well-prepared introduction to this topic. This includes researchers and students from the fields of electrical and computer engineering, computer science, applied physics, and other domains, with or without prior experience in optimization of QUBO problems [10]. We would also like to bring interested practitioners from the industry closer to this emerging field of research. An easy-to-use generic approach for finding better QUBO formulations may help increasing the dispersion of this emerging concept.
Date: Mon, Sep 18, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours
Summary: Near-term quantum computers are affected by a variety of noise sources, degrading the usefulness of the computation, but error mitigation techniques can reduce the effects of noise with minimal quantum resource overhead. In this tutorial we provide an interactive introduction to Mitiq, an open-source Python package for quantum error mitigation (QEM) on noisy quantum computers.
Abstract: We illustrate the use of Mitiq, an open-source Python package for quantum error mitigation (QEM) on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different QEM methods, including zero-noise extrapolation (ZNE), probabilistic error cancellation (PEC), digital dynamical decoupling (DDD), readout error mitigation (REM), and Clifford data regression (CDR). The library is compatible with different quantum software frameworks (Cirq, Qiskit, BraKet, PyQuil, QASM, PennyLane) and works with any backend (real or simulated).
Keywords: Quantum error mitigation, Python, Quantum algorithms, Qiskit, Cirq, Mitiq, NISQ
Contents Level: The tutorial aims to be as self-contained as possible. For this reason, no particular background knowledge is required. We will explain the necessary basic concepts to the participants and build up on this knowledge. However, a basic understanding of (combinatorial) optimization and the Python programming language is of advantage. The content will be distributed roughly as follows: 30% beginner, 50% intermediate, and 20% advanced.
Target Audience: The target audience is anyone who wishes to run quantum
programs and improve their results. The audience will be
expected to have some familiarity with quantum circuits but no
specific background in quantum error mitigation. The tutorial
will provide both the theoretical background and the handson demonstration of programming quantum circuits easily
applying quantum error mitigation techniques with Mitiq.
Previous experience on front-end toolkits such as any among
Cirq, Qiskit, PyQuil or PennyLane will be helpful. Interested
researchers will find information about quantum error mitigation techniques and their implementation. Expected outcomes
include:
- Learning the basics of quantum error mitigation (QEM)
and differences with respect to quantum error correction;
- Learn about most common quantum error mitigation
techniques, such as zero-noise extrapolation (ZNE), dynamical decoupling applied at the digital level (DDD),
and probabilistic error cancellation (PEC);
- Apply QEM techniques successfully on simulated backends, and learn how to apply them on real hardware;
- Implement optimization strategies with Mitiq’s automatic
calibration for QEM;
- Become acquainted with the Mitiq project (its documentation, online tutorials, installation requirements and
integrations, online community and support).
Tuesday, Sep 19, 2023 — Tutorials Abstracts
Date: Tue, Sep 19, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Many of the most promising quantum algorithms are hybrid quantum-classical solutions that combine the use of a quantum processor and a classical processor to arrive at a solution. Quantum circuits are parameterized, initialized with some values, and then run on the quantum processor. These parameters are then adjusted by performing a classical calculation that depends on the result of the quantum computation. Examples of such hybrid algorithms include the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE), algorithms that have important uses in performing quantum chemistry calculations and solving optimization problems on quantum computers. Hybrid algorithms rely on rapid iterative computations of the quantum and classical processors, typically requiring sharing data between the quantum and classical computer hundreds or thousands of times. This tutorial will teach the audience how to use Amazon’s Braket Hybrid Jobs capability to automate this task and reduce the overall execution time. Amazon Braket Hybrid Jobs simplifies the process of setting up, monitoring, and efficiently executing hybrid quantum-classical algorithms. Furthermore, the tutorial will introduce the paradigm of analog Hamiltonian simulation, as opposed to gate based quantum systems, which is based on neutral atoms. In the hands-on part of the tutorial, participants will set up their Braket Notebooks, run quantum circuits on quantum devices including gate based and analog Hamiltonian simulation device, and learn how to use the Hybrid Jobs feature. All attendees will leave with code examples that they can use as a foundation for their own projects.
Keywords: Quantum Computing, Quantum Optimization Algorithms, Analog Hamiltonian Simulation, Quantum Circuit, Quantum Classical Algorithms, Amazon Braket, Hands On Programming
Contents Level: 30% beginner, 50% intermediate, 20% advanced.
Target Audience: This tutorial is structured to appeal to diverse audiences that include researchers in quantum computing, attendees from industry, as well as students and general audience. The minimum requirements for attendees are an elementary knowledge of a modern programming language (such as Python) and Jupyter notebook, and familiarity with the basic concepts of quantum computing (quantum gates, quantum circuits, qubit measurement, analog Hamiltonian simulations). Industry participants will gain better understanding of the practical applications of quantum-classical algorithms in optimization, and students and the general audience will gain handson experience with running quantum workloads on quantum computers in the cloud.
Date: Tue, Sep 19, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: This tutorial introduces PennyLane, a quantum computing differentiable framework, and Covalent, an open-source Python tool for orchestrating quantum machine learning workflows. In the first session, we will introduce PennyLane and Covalent, highlighting PennyLane’s capabilities in developing quantum machine learning algorithms and Covalent’s role in managing and deploying these tasks across various compute backends. In the second session, we will dive into the Quantum Variational Rewinding (QVR) algorithm, a cutting-edge quantum machine learning technique for detecting anomalies in time series data. Participants will learn the principles behind QVR and engage in hands-on exercises using PennyLane and Covalent to implement and optimize the algorithm, demonstrating their seamless integration in a quantum machine learning workflow. Upon completing this tutorial, attendees will have a solid understanding of PennyLane’s differentiable quantum computing capabilities, Covalent’s orchestration features, and the practical application of the Quantum Variational Rewinding algorithm in time series anomaly detection.
Keywords: Quantum machine learning, Workflow orchestration, Heterogeneous computing, High-performance computing, Quantum algorithms, Differentiable programming, Hybrid classical-quantum workflows, Time-series modelling, Anomaly detection
Contents Level: The content level is designed to accommodate a range of experience levels, with 30% of the material
tailored for beginners, 40% aimed at intermediate participants, and 30% for advanced users.
Target Audience: The target audience for this tutorial includes graduate/PhD students, postdocs, and early-career professionals in both quantum and classical machine learning fields who are interested in exploring practical applications of quantum machine learning techniques.
Participants should have a basic working knowledge of Python (functions, decorators, etc.), scientific computing (distributed/parallel programming), and experience with HPC environments. While a basic understanding of quantum computing and familiarity with PennyLane are beneficial, this tutorial is designed to cater to attendees with little or no prior experience in quantum machine learning. It is also suitable for those with a background in classical machine learning looking to expand their knowledge into the quantum domain. This tutorial will equip participants with the skills to use PennyLane for differentiable quantum computing and Covalent to orchestrate quantum machine learning workflows, specifically in the context of time series analysis using the Quantum Variational Rewinding algorithm. Advanced concepts and techniques will be introduced and explained during the workshop to ensure a comprehensive understanding for all attendees.
TUT11 — QubiC: An Open-Source FPGA-based Quantum Controller
Gang Huang, Lawrence Berkeley National Laboratory (LBNL), USA
Yilun Xu, Lawrence Berkeley National Laboratory (LBNL), USA
Neelay Fruitwala, Lawrence Berkeley National Laboratory (LBNL), USA
Abhi Rajagopala, Lawrence Berkeley National Laboratory (LBNL), USA
Kasra Nowrouzi, Lawrence Berkeley National Laboratory (LBNL), USA
Date: Tue, Sep 19, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: This tutorial aims to provide physicists, engineers, and quantum hobbyists insight into our open-source control system and empower the audience to utilize its capabilities to strengthen the quantum ecosystem.
Abstract: As quantum computing marches forward in the NISQ era, new qubit implementations enter the fray, and advanced quantum and hybrid algorithms are investigated, developments that place significant demands on classical control systems for quantum computing. Developed at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed as the first open-source system for control and readout of quantum processors, QubiC has recently undergone a system-wide upgrade, now positioned as the only open-source system capable of mid-circuit measurement and feedforward for superconducting quantum computing. In this tutorial, we introduce QubiC and provide a deep dive into its architecture, functionalities, and capabilities in quantum control and measurement. Specifically, we discuss advanced control requirements for superconducting qubits and QubiC’s approach to satisfying these requirements, including features such as fast parameter updates and real-time decision-making. We provide the audience access to our simulator and conduct pulse generation experiments. Finally, we demonstrate QubiC on multiple FPGA/SoC platforms controlling a Quantum processor.
Keywords: Quantum Computing, Quantum Control
Contents Level: The tutorial content divides into 50% beginner, 30% intermediate, and 20% advanced levels.
Target Audience: This tutorial targets a multi-disciplinary quantum community of experimentalists, hardware designers, and software engineers interested in using open-source control systems. QubiC being a cost-effective open-source controller for superconducting qubits, we expect interest from superconducting (and non-superconducting) qubit experimentalists requiring a flexible control system. The software infrastructure will also attract developers interested in transpilation and integration into the hardware.
Date: Tue, Sep 19, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: Learn about superconducting cat qubits. In this tutorial you will explore cat qubits’ implementation and noise-resistant properties, explore error correction and non-Clifford gates, and understand their potential for running algorithms such as Shor’s with 60-times less resources, on the road towards fault-tolerant, universal quantum computing.
Abstract: One of the biggest challenges in building a fault-tolerant quantum computer is the number of additional physicals qubits required to implement error correction. Cat qubits are a development focused on tackling this challenge by providing a “hardware-efficient” roadmap towards fault-tolerant, universal quantum computing. They form the basis of several Fault Tolerant roadmaps, most notably Amazon’s. Cat qubits are superconducting bosonic qubits which encode quantum information in two coherent states of a microwave resonator or cavity. They have demonstrated the capability to resist bit-flips, up to 2 minutes. This strong suppression of one type of quantum errors allows for a resource efficient road to fault-tolerant and universal gate-based quantum computing, in that it allows error correction to be performed with simpler schemes than a surface code. The hardware-efficiency of the cat qubit at the low levels of the architecture naturally results in a dramatic reduction of the final application-relevant size of the quantum processor: a recent study quantifies how this approach might reduce the number of qubits required to run Shor’s algorithm down to 350.000, where it was previously thought that millions of qubits were needed. This tutorial will go over the physics of cat qubits, using classical analogies as well as exposing the quantum equations of the hardware. It will then expose how they can be leveraged in a complete roadmap towards fault tolerance. It will also explore tools to simulate cat qubits behavior.
Keywords: Cat qubits, Superconducting qubits, Biased noise, Fault tolerant quantum computing
Contents Level: 30% beginner, 60% intermediate, 10% advanced.
Target Audience: The tutorial is aimed at anyone wanting to understand the cat qubit technology. It will not go over the basics of quantum computing. Concepts such as the Bloch Sphere, Schrödinger equation etc. are prerequisite for attendance. Additionally, passing knowledge of error correction scheme is expected. Some familiarity with quantum optics and of quantum development languages such as Qiskit will help.
Date: Tue, Sep 19, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: In this tutorial, we will review several important ideas for compiling quantum circuits to meet the constraints of real devices. For the first section we will begin by constructing quantum circuits using the higher-level primitives available in pytket, a quantum compiler framework developed by Quantinuum. We will also show several optimization techniques for reducing the gate count and circuit depth including circuit simplification with the ZX calculus. We will then show how these techniques can be applied in practice by using them in a variational experiment. Additionally, we will cover the tradeoffs of different devices (ion traps, superconductors etc.) and the challenges they present from a circuit compilation point of view. In the later part of our tutorial, we will focus on compilation of circuits involving both quantum and classical operations. Real time classical control is necessary for fault tolerance as errors need to be decoded and corrected during the computation. We will discuss executing quantum circuits with classical control on the H-Series devices through the pytket-Quantinuum extension. To this end, we will demonstrate how to compile classical functions using pytket and execute them alongside the quantum computation at runtime. Our first demonstration of a quantum-classical circuit will be a simple repeat-until-success example. We then will conclude by demonstrating a real quantum error correction protocol by using pytket.
Keywords: Quantum compilation, Classical control, Error correction, Circuit synthesis, ZX calculus
Contents Level: Approximate 30% beginner, 40% intermediate, 30% advanced.
Target Audience: We will assume that participants are familiar with quantum circuits and well as some basic python programming. Some knowledge of quantum error correction may be useful for the later part of the tutorial. We recommend that attendees install pytket before the tutorial and that participants are able to make use of jupyter notebooks. Instructions on installing pytket can be found in the pytket documentation
Wednesday, Sep 20, 2023 — Tutorials Abstracts
Date: Wed, Sep 20, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Variational quantum algorithms represent a highly promising category of quantum computing tasks that exhibit quantum benefits. In this interactive tutorial, we will introduce the Intel Quantum SDK for executing variational algorithms efficiently and delve into the comprehensive platform design. Moreover, we will demonstrate how users can develop their own quantum variational algorithms utilizing the Intel Quantum SDK. Participants will have the opportunity to access the Intel Quantum SDK and gain practical experience by running sample applications. Furthermore, we will showcase the process of writing, compiling, and executing a hybrid quantum-classical program on the platform.
Keywords: Intel Quantum SDK, C++ Quantum Programming, LLVM-based Quantum Compiler, Variational Algorithm, Hybrid Quantum-Classical Application
Contents Level: No particular background knowledge of quantum computing is required. The fundamental concepts of quantum computing will be briefly introduced to the participants and the following session of the tutorial explains how to use the tool to write your own program. However, a basic understanding of programming languages in C++ is of advantage. The content will be distributed approximately 60% beginner and 40% intermediate
Target Audience: This tutorial is targeted for general quantum computing engineers/researchers/students who are interested in quantumclassical applications. We will have hands-on exercises to demonstrate variational algorithms on the platform step-bystep. Since the platform introduced in this tutorial leverages C++ to describe quantum circuits, participants are expected to be familiar with standard C++ programming
Date: Wed, Sep 20, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: Attendees will learn about Tangelo, an open-source, modular and extensible Python package for quantum chemistry workflows on current and future quantum computers. Its software design choices and approach to both accelerate R&D and design sensible experiments on quantum hardware can be reused across various fields.
Abstract: Significant advances in both hardware and algorithmic development are still necessary to meaningfully apply quantum computing to chemistry simulations. The current software landscape features open-source initiatives led by big players that resulted in frameworks that can feel a bit rigid for researchers, as well as efforts from quantum companies attempting to capitalize on black-box solutions or closed-source platforms despite the early stages of the technology. We present Tangelo, an open-source Python package for quantum chemistry workflows on gate-model quantum computers. It aims to accelerate quantum algorithm development in the field by facilitating the prototyping and integration of new research, and supporting users in benchmarking it against other state-of-the-art approaches or reproducing them. Tangelo provides a collection of reusable building blocks and backend-agnostic algorithms, with the flexibility to let users introduce their own. The toolboxes attempt to address the challenges occurring while modelling chemical systems and the various steps involved in designing / running feasible hardware experiments. In this tutorial, we familiarize attendees with Tangelo’s design, as well as its growing collection of features. The first session focuses on the backend-agnostic quantum circuit simulation / execution layer, and introduces the basics of chemical modeling on quantum computers before applying them through a modular and extensible framework for variational algorithms. The second session highlights toolboxes for quantum experiments and dives into fault-tolerant algorithms: how they differ from NISQ algorithms, their requirements, their building-blocks. The hands-on first cover the primitives of these algorithms, and then move on to applications such as state preparation, phase estimation of Hamiltonian simulation.
Keywords: Quantum, Chemistry, Workflows, Application, Research, Python, Open-source, NISQ, Fault-tolerant, R&D, Electronic solver
Contents Level: 40% beginner, 50% intermediate, 10% advanced [flexible, can accommodate heterogeneous audiences and advanced participants].
Target Audience: The target audience include researchers in computational chemistry or physics, quantum developers, and simply anyone interested in applications of quantum computing. Prerequisites include a basic understanding of the Python programming language, basic knowledge about quantum mechanics (schrodinger equation, wavefunction, eigenvalues, correlation energy. . . ) as well as the concept of quantum gates and circuits. The audience will further their understanding of the challenges of applying quantum computing to chemistry, and the different steps of end-to-end workflows aimed at leveraging current and future quantum devices. They will learn how to leverage the toolboxes and algorithms present in Tangelo, and how they can be used in conjunction with various frameworks developed by the community in order to facilitate their research.
Date: Wed, Sep 20, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: This tutorial will provide the audience with an introductory understanding of the ZX calculus, a diagrammatic language for quantum computing. By the end of the tutorial, attendees will have acquired familiarity with both the fundamental concepts of the ZX calculus and some of its most topical applications, making them ready to add diagrammatic methods to their toolbox.
Abstract: The ZX calculus is a graphical language that provides an intuitive and elegant way to reason about quantum computing, rigorously backed by over 200 research papers (cf. zxcalculus.com/publications). In this talk, we will introduce this calculus’s fundamental concepts and techniques in a manner accessible to quantum computing enthusiasts and professionals alike. The material will be of interest to both quantum researchers and practitioners of quantum software development.
ZX diagrams will initially look like quantum circuits, making them familiar to those already in this field. Unlike quantum circuits, however, these pictures are more than mere schematics: they are a new kind of sophisticated and rigorous mathematics, tailor-made to talk about the quantum world. Most importantly, they will shift your conception of quantum computations away from the rigid recipe used to implement them, instead focusing on the flow of information which ultimately powers them.
After introducing the basics, we will immediately apply the calculus to picturing advanced quantum applications such as Measurement-Based Quantum Computing, the Quantum Approximate Optimisation Algorithm, Quantum Error Correction, Lattice Surgery and Fusion-Based Quantum Computing. By the end of this tutorial, you will have the tools to understand quantum computing from a novel, if not revolutionary, perspective. You will be ready to add the ZX calculus to your toolbox, as used by a growing number of quantum businesses, universities, and research institutions.
Keywords: Quantum computing, ZX calculus, Diagrammatic languages, Quantum education
Contents Level: Part A of the tutorial is beginner-level, designed to provide an introduction to diagrammatic methods for gate-based quantum computing from the ground up. Part B of the tutorial is intermediate-level, covering applications such as Trotterization, error correction and MBQC.
Target Audience: The tutorial presumes familiarity with qubit states, quantum gates and the quantum circuit model.
Knowledge of linear algebra (Hilbert spaces, Dirac/bra-ket notation, etc) is not a pre-requisite. Mathematical
topics used throughout the tutorial are limited to angle addition and some binary arithmetic.
The tutorial introduces a new language for gate-based quantum computing: its target audience consists of all
practitioners and researchers, at any level, who are not yet familiar with the ZX calculus.
Date: Wed, Sep 20, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Hamiltonian simulation is one of the most promising applications of quantum computing. Recent experimental results suggest that continuous-time analog quantum simulation would be advantageous over gate-based digital quantum simulation in the Noisy Intermediate-Size Quantum (NISQ) machine era. However, programming such analog quantum simulators is much more challenging due to the lack of a unified interface between hardware and software, and the only few known examples are all hardware-specific.
In this tutorial, we will introduce SimuQ, the first domain-specific language for Hamiltonian simulation that supports pulse-level compilation to heterogeneous analog quantum simulators. Specifically, in SimuQ, front-end users will specify the target Hamiltonian evolution with a Hamiltonian modeling language, and the programmability of analog simulators is specified through a new abstraction called the abstract analog instruction set by hardware providers. Through a solver-based compilation, SimuQ will generate the pulse-level instruction schedule on the target analog simulator for the desired Hamiltonian evolution, which has been demonstrated on pulse-controlled superconducting (Qiskit Pulse) and neutral-atom (QuEra Bloqade) quantum systems, as well as on normal circuit-based digital quantum machines.
We will provide hands-on demonstrations of programming quantum simulation problems, illustrate commonly used quantum devices and their capability, and compile our programs to quantum devices.
Keywords: Quantum simulation, Analog quantum computing, Pulse-level programming
Contents Level: This tutorial will approximately contain 30% beginner-level content including basic background knowledge and easy cases of our tool, 40% intermediate-level content including the usage of our toolchain for complicated quantum simulation problems, and 30% advanced-level content including how to utilize SimuQ for your experimental devices.
Target Audience: This tutorial targets audiences ranging from students of quantum physics to researchers related to quantum simulation and quantum devices. We will include sufficient background knowledge from the very definition of the Schrodinger equation to ubiquitous architectures of quantum devices. and motivate quantum simulation with real scientific applications. This tutorial will also help hardware providers depict their devices’ capabilities of simulating other quantum
systems and program them in SimuQ as target platforms for compilation.
TUT18 — Parameterized Quantum Pulse Circuit and its Application
Zhiding Liang, University of Notre Dame, USA
Hanrui Wang, MIT USA
Jinglei Cheng, University of Southern California, USA
Jiaqi Gu, University of Texas at Austin, USA
Zhixin Song, Georgia Institute of Technology, USA
Hang Ren, UC Berkeley, USA
Rui Yang, Peking University, China
David Pan, University of Texas at Austin, USA
Yongshan Ding, Yale University, USA
Fred Chong, University of Chicago, USA
Song Han, MIT, USA
Yiyu Shi, University of Notre Dame, USA
Date: Wed, Sep 20, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: This tutorial aims to provide the audience with a comprehensive understanding of parameterized quantum pulse and its potential benefits in quantum computing research. Specifically, the audience will gain insights into fundamental concepts of calibration, optimal control, how to measure the metrics for parameterized pulse-based design space, and how to design pulse-level ansatz for Variational Quantum Algorithms.
Abstract: Quantum pulses and quantum gates are both important tools for manipulating the state of qubits in a quantum computer, but they have different advantages and disadvantages. Flexibility, high fidelity, scalability and real-time tuning are some potential advantages of using quantum pulses over quantum gates.
An example of the potential of quantum pulses can be seen with a single qubit, where one pulse and two parameters (amplitude and angle) can fully explore the Bloch Sphere. This illustrates the expressiblity of quantum pulses. However, it’s important to note that basis gates are still necessary for the well-defined gate-level abstraction layer currently used in quantum programming. These gates are carefully designed and regularly calibrated to maintain high fidelity. But in the case of variational quantum algorithms, we believe that the need for such calibration and resulting redundancy can be eliminated with the use of parameterized pulses. We believe the cost for consistent calibration and redundancy in compiling quantum gate instructions into the more fundamental pulse level can be reduced. With pulses, it’s possible to perform the variational algorithm without relying on basis gates.
At present, there isn’t a well-established framework for researchers to develop pulse-based quantum programs.
This tutorial showcases several methods that can serve as a framework for generating pulses for various variational quantum algorithms.
This tutorial is divided into three sessions. The first session will provide an introduction to quantum computing, quantum optimal control, and parameterized pulse circuits. In the second session, we will demonstrate the practical applications of parameterized pulse circuits and provide attendees the opportunity to run the programs themselves. Finally, in the third session, we will showcase the PAN framework and how it can be used to develop strategies for generating pulse ansatz for variational quantum algorithms.
Keywords: Parameterized Quantum Pulse, Quantum Control, Parameterized Quantum Circuits, Co-Design Optimization, Hands-On Programming
Contents Level: This tutorial is designed for a mix of attendees, with 60% being beginners and 40% being intermediate level in their knowledge of quantum computing and machine learning. However, the material presented will also be interesting and useful for advanced-level attendees. We expect typical participants to be beginners in quantum computing or machine learning who are interested in learning how to implement parameterized pulses and their applications, and who are familiar with Python and Qiski
Target Audience: This tutorial aims to take the audience from understanding the construction of parameterized pulses, to exploring their applications and advantages, as well as common research directions. It is suitable for both computer scientists and hobbyists interested in variational quantum algorithms, as well as hobbyists interested in quantum pulse control
Date: Wed, Sep 20, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: What is Quantum Ethics and why does it matter to me as a researcher? Quantum Ethics, like AI Ethics, is the academic study of the potential social, economic, and political implications of quantum technology. Unlike AI however, quantum technologies such as computing, sensing, and communication remain much more speculative in their eventual impact. We need to first understand the credibility of a given application before we can assess the social impact.
This workshop will explore case studies and real life examples such as hype in quantum technology, dual-use technologies, quantum nationalism and geopolitics, cybersecurity, workforce diversity, and limitations of the market in allocating quantum resources. Participants will have an opportunity to consider and discuss the various ethical dilemmas posed by these case studies. The ultimate goal of this workshop is for practitioners to be able to evaluate future ethical concerns that may arise in their own work that we cannot currently foresee.
The Quantum Ethics Project is an interdisciplinary research network of experts from around the globe with primary contributors and co-founders from the Institute for Quantum Computing at University of Waterloo, Harvard University, CU Boulder, the Center for Quantum Networks, and beyond. We hope you will join us to learn about how we can all shape our own research to the highest standard of ethics, equity, and the public good. Together we can ensure the quantum revolution works for everyone.
Keywords: Quantum ethics, Responsible innovation, Social impact
Contents Level: Our content is intentionally designed to promote a collaborative learning environment in which practitioners at different levels and stages in their career can learn alongside and from one another, advancing the conversation with their variety of perspectives. Material will be approximately 40% beginner and 60% intermediate with respect to the subject of quantum ethics, paced such that beginners can readily develop the skills they need to engage with more advanced material later in the tutorial. There will also be opportunities for deeper engagement interspersed throughout for those with greater experience or investment in the topic. Because the tutorial will be primarily discussion- and activity-based, the content level can also readily be adjusted in real time by the facilitators according to the needs and backgrounds of attendees.
Target Audience: The only prerequisite for tutorial participation is an open
mind and an eagerness to learn and share – anyone is welcome
from the complete beginner to seasoned expert! Basic (nontechnical) familiarity with quantum technologies may occasionally be helpful but is neither required nor expected; our
hope is that anyone who attends the QCE plenaries will have
sufficient background to engage.
Tutorial attendees will explore foundational ethical dilemmas in quantum technologies through the framework of Responsible Innovation. We will apply these theories to
issues such as cybersecurity, dual-use technologies and military applications, quantum hype, finance industry capture of
quantum technologies, and inclusive workforce development.
Tutorial participants will learn and practice skills for critically
and responsibly engaging with these issues throughout their
careers as quantum researchers or practitioners, enabling them
to become champions for an ethical and socially responsible
quantum revolution from within. While many of the tools we
introduce are broadly applicable beyond quantum technologies, our tutorial’s emphasis on quantum-specific applications
is key for the QCE audience: engineering ethics literature has
established the importance of domain-specific ethics education
in promoting ethical decision-making in one’s field.
Thursday, Sep 21, 2023 — Tutorials Abstracts
Date: Thu, Sep 21, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: The field of quantum computing is rapidly advancing, and one of the most pressing challenges is the mitigation of errors that can arise during the computation process. This tutorial delves into the concepts of error suppression and error mitigation in quantum computing using Qiskit Runtime Primivites. It begins with an overview of the various sources of errors that can impact quantum computations, followed by a detailed explanation of how to identify and mitigate these errors using proven techniques. The tutorial concludes by demonstrating the effectiveness of error mitigation and error suppression by using Qiskit Runtime Primitives in production. By the end of this tutorial, readers will have a foundational understanding of how to suppress and mitigate errors in order to extract the best results from today’s quantum hardware.
Keywords: Qiskit, Qiskit runtime, Quantum development kit, Quantum algorithms, Quantum-classical programming, Applications, Decoherence, Quantum noise, Error models, Error mitigation, Error suppression
Contents Level: 40% beginner, 40% intermediate, 20% advanced.
Target Audience: This tutorial targets developers and researchers who want to learn and leverage error mitigation and error suppression within their quantum programs in order to extract the best results from today’s quantum hardware. This tutorial is appropriate for a variety of audience including: Researchers and Practitioners who are looking to optimize the accuracy and reliability of their quantum computing experiments, students and educators who are interested in gaining a deeper understanding of quantum computing, and software engineers who want to learn about specific techniques for error suppression and mitigation in quantum computing. A background in Python and some basic knowledge of Quantum Computing will be useful but not necessary for attendees of this session.
Date: Thu, Sep 21, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: In this tutorial, the attendees will learn quantum computing from both algorithm and hardware perspectives by writing a simple Python simulator, using IBM quantum computers, and learning how classical microwave knowledge is used in quantum computer hardware design.
Abstract: There is a lack of tutorial that presents the beginning and intermediate learners of quantum computing with a holistic view from algorithm to hardware. Such a tutorial is useful for classical engineers who want to understand their roles in quantum computing. There are six sections in this tutorial to achieve this goal. In Section I, important concepts in quantum computing are introduced in a layman’s approach. The audiences will have an appreciation of the importance of superposition, entanglement, interference, no-cloning theorem, and error correction in quantum computing. In Section II, quantum gates will be introduced with hands-on exercises to create quantum gate simulators in Python. In Section III, the Deutsch algorithm will be studied and implemented on IBM Quantum Lab and Composer. The audiences will appreciate how a quantum circuit operates, the meaning of quantum oracles, and the power of quantum parallelism. In Section IV, Quantum Fourier Transform, which is a building block of many important quantum algorithms, will be introduced and implemented on IBM-Q so the audience can further appreciate the importance of interference in quantum computing. After learning algorithms, we will discuss the implementation of a quantum computer using superconducting qubits. We will emphasize this from an electrical engineer’s perspective. In Section V, we discuss how to implement qubit initialization, readout, and quantum gates in superconducting circuits and their relationship to electrical engineering. In Section VI, we further demonstrate how to use Qiskit-Metal and HFSS to optimize a quantum circuit in terms of the Energy Participation Ratio.
Keywords: Introduction to Quantum Computing, Quantum Algorithm, Quantum Computing Architectures, Quantum Education
Contents Level: 70% beginner, 30% intermediate.
Target Audience: This tutorial is suitable for students and engineers who have basic knowledge of matrix operations and Python coding and
who want to understand the nuts and bolts of quantum computing from algorithm to hardware implementation. Besides learning the basics of quantum algorithms (appreciate the important concepts, able to perform basic gate calculations, and implement quantum circuits on IBM-Q), they will also understand how a quantum computer is realized in hardware (with superconducting qubit as an example). They will realize the importance of controlling electronics (cryogenic, RF, and high-speed circuits) in a quantum computer and how they play the roles of creating quantum gates and performing qubit initialization and readout. They will also be ready to contribute to quantum circuit optimization after learning the Qiskit-Metal and HFSS framework which is purely classical. I need to emphasize that the teaching methodology will be based on my 3-year experience in teaching underrepresented minorities and socially disadvantaged students at SJSU with about 70 students. The materials will be made very accessible to less prepared students but are rigorous enough for them to pursue to the next step.
Date: Thu, Sep 21, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: In this hand-on tutorial, typical qubit tune-up experiments and qubit calibrations from the bottom up will be covered by employing Qblox’s hardware and software platforms; Q1ASM and Quantify.
Abstract: To create quantum computers that solve useful problems, the number of qubits and complexity of the computations must increase. This poses challenges for the control stack that governs both the qubit calibration as well as the algorithm execution. In this tutorial we will demonstrate the real-time agile sequencing solutions of the Qblox control stack through two different software abstraction layers. For both levels we have chosen a uniquely open approach: opening up the Q1ASM assembly layer and making the higher-level Quantify package open source. After introducing distributed sequencing, efficient signal generation and processing and real-time feedback, we move to a hands-on tutorial of both control software implementations, Q1ASM and Quantify. First we use the fine-grained control of the Q1ASM assembly language to operate the sequencers in the quantum control stack directly, and build qubit calibrations from the bottom up. Then, we move to Quantify, a higher-level software package, where we will define qubit algorithms and execute them. In both tutorials we program the control hardware and execute the pulse sequences and quantum algorithms on the hardware. Finally, we curate an open discussion on improvements for both the Q1ASM and Quantify software layers.
Keywords: Quantum Control Stack, Quantum Software, Quantum Computing
Contents Level: 30% beginner, 50% intermediate, 20% advanced.
Target Audience: This tutorial targets quantum researchers and experts with either experimental or theoretical quantum physics, quantum computation, computer science background both from academia and industry. The target audience will learn how to communicate with qubits using Qblox’s control/readout hardware and a dedicated software platform.
Date: Thu, Sep 21, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours
Abstract: Recently, QuEra’s 256 neutral atom quantum simulator “Aquila” was put online for public access through Amazon BraKet. Aquila works in a powerful “analog mode” of computation, which allows for efficient and flexible utilization of its quantum behavior. Unlike other contemporary platforms, neutral atom quantum computers offer many qubits—up to 256 on Aquila—and large effective gate depths—with order 50 coherent Rabi oscillations. The large breadth and depth of QuEra’s hardware enable real potential for near-term NISQ-era algorithms and applications that can solve real-world problems, from optimization to simulation. In two parts, this tutorial will be a hands-on demonstration of working with QuEra’s cloud-accessible analog mode neutral atom quantum simulators. The first part will introduce neutral atom quantum computing, including both analog mode and near-term digital mode operation. This will include an outline of the advantages and disadvantages of the platform, as well as an outlook for error correction and scalability. The second part will be a hands-on tutorial programming Aquila using Bloqade, which will provide jupyter notebooks with examples to all participants. These examples will scale from simple “hello world” programs all the way to prototypical application solutions such as geographic combinatorial optimization and quantum phases.
Keywords: Neutral atoms, Quantum computing, Cloud computing, Noisy intermediate scale quantum
Contents Level: This tutorial is geared towards beginners with a minimal understanding of quantum mechanics. An undergraduate 1- semester course is the expected level, with a clear requirement set by the understanding of what is a “quantum Hamiltonian”.
Target Audience: The contents of this tutorial will be most appreciated by researchers and students from academia, as well as researchers and developers from industry. It will be key to enable individual contributors to start deploying solutions on available quantum resources right away.
TUT24 — Quantum plus High-Performance Computing for Natural Language Processing
Eduardo Coello Perez, Oak Ridge National Laboratory (ORNL), USA
Prasanna Date, Oak Ridge National Laboratory (ORNL), USA
Mayanka Chandra Shekar, Oak Ridge National Laboratory (ORNL), USA
Kathleen Hamilton, Oak Ridge National Laboratory (ORNL), USA
John Gounley, Oak Ridge National Laboratory (ORNL), USA
Francisco Rios, Oak Ridge National Laboratory (ORNL), USA
In-Saeng Suh, Oak Ridge National Laboratory (ORNL), USA
Georgia Tourassi, Oak Ridge National Laboratory (ORNL), USA
Date: Thu, Sep 21, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: This tutorial provides an overview of Quantum Natural Language Processing (QNLP), a cutting-edge application of quantum computing dedicated to the execution of Natural Language Processing (NLP) tasks with the aid of quantum computers. We will provide a theoretical overview of NLP and QNLP. Then, we will construct two workflow examples used to train QNLP models. First, using single-threaded quantum-classical simulation. Second, as distributed computing workflows that could incorporate High-Performance Computing (HPC) resources. Finally we will present metrics that can be used to benchmark and compare QNLP performance against that of classical NLP models. Attendees will participate in hands-on activities demonstrating and testing these workflows using numerical simulators and examples of real-world applications. This tutorial will help attendees train Quantum Long Short-Term Memory (QLSTM) and Compositional Distributional Categorical (DisCoCat) models for respectively tagging the words in a small dataset with their parts of speech (POS) and classifying the meaning of the sentences they form. They will also explore the Quantum Support Vector Machine (QSVM) and Quantum Discriminator (QD) models for classification tasks. Moreover, the tutorial will delve into quantum binary and multi-class classification of more complex datasets by benchmarking the performance of quantum classifiers with different quantum embeddings and loss functions against Convolutional Neural Networks (CNN) trained on the Frontier supercomputer at ORNL, and the other hybrid models.
Keywords: Natural Language Processing, Quantum Machine Learning, High-Performance Computing
Contents Level: 67% intermediate, 33% beginner.
Target Audience: The tutorial targets a broad audience. It is geared towards individuals interested in exploring the capabilities of QNLP on quantum plus HPC systems. Attendees with no previous knowledge of QNLP will benefit the most from this tutorial, as it will ground the concepts and workflow required to simulate the execution of these tasks, and showcase simple applications by training some QNLP models. While seasoned professionals on the field may find some of the content familiar, they can expect to gain new insights about quantum classification of complex datasets in the intermediate portion of the tutorial.
TUT25 — Deep Dive into Classical Simulation of Quantum Circuits with QX-Simulator
Pablo le Henaff, Delft University of Technology, The Netherlands
Sebastian Feld, Delft University of Technology, The Netherlands
Medina Bandic´, Delft University of Technology, The Netherlands
Nikiforos Paraskevopoulos, Delft University of Technology, The Netherlands
Date: Thu, Sep 21, 2023
Time: Between 13:00-16:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Quantum computing is a paradigm of computation that promises to efficiently solve some problems which are inaccessible to classical computers. Nowadays’ quantum computers are, however, noisy and limited in size, being mostly used as research objects or proofs of concept. In this context, the classical simulation of quantum computers allows researchers to check the execution of their algorithms on a cheap and reliable platform. In addition, those simulations are an efficient pedagogical tool for the classroom. Simulation of a quantum computer poses serious challenges for a classical computer, notably in terms of memory usage. It requires advanced algorithms to efficiently implement the mathematical models described in physics textbooks. QX-simulator is a generic simulator for quantum circuits developed at QuTech and TU Delft in the Netherlands with a focus on performance and code quality. An idea fundamental to modern high-performance software development is the utmost importance of memory locality, which can be improved, in particular, by reducing the memory footprint of the program. QX-simulator does this by leveraging the mostly-sparse nature of the quantum states arising from meaningful algorithms. This tutorial covers bits of quantum computation theory (e.g., quantum operations) together with some practical software development tricks (e.g., sorted maps in C++). Basic knowledge of linear algebra is required. In the practical part, participants will get familiar with QX-simulator and push it to its limits. By the end of this tutorial, participants should be able to understand the challenges arising from the simulation of quantum circuits and how QX-simulator attempts to overcome those.-
Keywords: Quantum computing simulation, Software engineering, High performance computing
Contents Level: 20% beginner, 40% intermediate, 40% advanced.
Target Audience: The sessions are accessible to people with some background knowledge in the mathematics of quantum computing theory: it will be assumed that participants fully understand complex numbers, vector spaces and linear maps. Attendees should know basic quantum unitary gates and be somewhat familiar with the expression of a quantum circuit in a quantum programming language like OpenQASM. On the other hand, some experience with a low-level programming language, like C or C++, is desirable.
Friday, Sep 22, 2023 — Tutorials Abstracts
Date: Fri, Sep 22, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: This tutorial gives an overview of how and why real quantum devices are characterized and calibrated with a hands-on demonstration using the open source Qiskit Experiments package. Participants will gain an understanding of the different types of benchmarks and calibrations in the field today and important design considerations for quantum software that runs these protocols on quantum processors.
Abstract: State-of-the-art quantum processors require increasingly complex software to calibrate and characterize. IBM’s Qiskit is a powerful open-source framework for building and running quantum programs from the ground up, but to implement a large-scale benchmark from fundamental quantum circuit building blocks is a complex task. In this tutorial, we will introduce the Qiskit Experiments package, which allows users to run and analyze benchmarking, characterization, and calibration experiments on top of Qiskit. We will motivate why such a package is necessary and useful by discussing the requirements of modern quantum processor upkeep and evaluation, as well as the large array of existing algorithms for this purpose. Using Qiskit Experiments, we will show users how to set up benchmarking and calibration experiments, run them on IBM systems, and analyze the results of these experiments. We will break down technical details of what the package is doing behind the scenes so that participants can learn not only how to run existing experiments in the library but also how to implement their own experiments using the Qiskit Experiments framework. By the end, participants should come away with an overview of current benchmarking algorithms used to measure the performance of quantum processors, how to calibrate gates on these processors, and how to use Qiskit Experiments to execute efficient workflows.
Keywords: Qiskit, Qquantum algorithms, Quantum benchmarking, Quantum calibration, Device characterization
Contents Level: 50% beginner, 50% intermediate.
Target Audience: The tutorial is for those interested in running characterization and calibration experiments on physical quantum devices and simulators, which may include quantum engineers, developers, and researchers. The audience is expected to be familiar with Python programming and the basics of quantum computing. Knowledge of Qiskit basics will also help, but we will keep the level of the tutorial beginner-friendly otherwise. Attendees will learn about the current state of device benchmarks and calibration procedures, how to evaluate algorithms for specific use cases, and the challenges of benchmarking and characterizing modern devices. In the hands-on portion, they will learn how Qiskit Experiments is designed to meet these challenges by running and writing experiments using this framework under the guidance of the instructor.
Date: Fri, Sep 22, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Abstract: Many important systems in nature are described by the space-time evolution of physical quantities using partial differential equations (PDEs), which can range from the microscale, such as the Schrödinger equation in quantum systems, to the macroscale, such as the Navier–Stokes equations of fluid dynamics. Thus, efficient PDE solvers are critical to understanding and solving many science and engineering problems. Quantum algorithms have been proposed to solve PDEs and verified on small-scale simulators. For long-term PDE solvers, the Harrow-Hassidim-Lloyd (HHL) algorithm could bring an exponential speedup over classical methods. For the near-term quantum hardware, variational quantum algorithms such as the Variational Quantum Linear Solver (VQLS) are applied to solve PDEs. In this tutorial, we will introduce users to QPDE-Benchmark, a new programming toolkit, powered by a set of quantum PDE solvers, that enable a user to more seamlessly test and improve quantum solvers for various PDEs. More specifically, we will show users how to solve the Schrödinger, Wave, and Poisson equation on near-term quantum computers using Hamiltonian simulation, VQLS and Variational Quantum Eigensolver (VQE). Additionally, we will discuss how to apply error suppression/mitigation techniques such as measurement error mitigation, pulse-efficient transpilation, and dynamical decoupling to enhance PDE solver’s performance on IBM’s quantum hardware.
Keywords: Variational Quantum Algorithms, Partial Differential Equations, Quantum Error Suppression, Hands-On Programming
Contents Level: This tutorial is designed for a mix of attendees, with 40% being beginners, 40% being intermediate level, and 20% being advanced level in their knowledge of quantum computing and scientific computing. We expect typical participants to be beginners in quantum computing or scientific computing who are interested in quantum algorithms for solving differential equations, and who are familiar with Python and Qiskit.
Target Audience: This tutorial aims to take the audience from understanding the construction of quantum linear solvers, to exploring their applications on solving linear PDEs with NISQ quantum hardware. It is suitable for both computer scientists and hobbyists interested in quantum PDE solvers, as well as hobbyists interested in quantum error suppression methods.
Date: Fri, Sep 22, 2023
Time: Between 10:00-14:30 Pacific Time (PDT) — UTC-7
Duration: 3 hours (2 x 1.5 hours)
Summary: Attendees will learn how to use qBraid’s platform to accelerate quantum research and development by accessing many tools and hardware providers in one location. Attendees will also be taken through a short tutorial on variational quantum algorithms (VQAs) that demonstrates qBraid’s capabilities while teaching about VQAs.
Abstract: Discover the power of qBraid, an innovative cloud platform designed to revolutionize quantum software development by offering seamless integration of compute resources, programming packages, and quantum hardware access. This comprehensive tutorial showcases qBraid as the ultimate all-in-one platform for learning, research, and collaboration in the quantum computing community. qBraid currently supports interactive and shareable Jupyter Notebook environments with customizable CPU/GPU options. This feature enables access to an extensive range of pre-packaged and tested quantum computing environments, encompassing Python packages such as Qiskit, Braket, and Cirq, as well as Julia packages like Bloqade. Users can effortlessly submit their quantum circuits to hardware providers, such as Amazon Braket and IBMQ, without the hassle of managing additional accounts. The integrated qBraid SDK simplifies circuit transpilation across various packages and backend submission. In this tutorial, participants will first explore the core functionality of qBraid and then use this functionality to participate in an introduction to variational quantum algorithms. Attendees will be taught the significance of these algorithms for tackling complex computational problems, while gaining practical experience developing code using diverse quantum hardware architectures, such as trapped ion, superconducting, and neutral atom systems. Join us to acquire essential knowledge on leveraging qBraid for accelerated quantum development and harnessing the platform for the efficient design of quantum variational algorithms. This tutorial promises an exciting and professional learning experience, making it a must-attend event for conference participants.
Keywords: Quantum computing, Development environment, Quantum software, Quantum variational algorithms, QAOA, VQE
Contents Level: 50% beginner, 40% intermediate, 10% advanced.
Target Audience: This tutorial is intended for quantum computing researchers, practitioners, and developers with a basic understanding of quantum computing concepts and familiarity with Python. Attendees who are not well-versed in quantum computing and/or Python should still be able to get a high-level picture of how qBraid enables the quantum development process. Attendees will be walked through how to set up a qBraid account that will be used to follow along with the tutorial.
TUT30 — Introduction to SeQUeNCe, a Customizable Discrete-Event Simulator of Quantum Networks
Rajkumar Kettimuthu, Argonne National Lab (ANL) & The University of Chicago, USA
Alexander Kolar, University of Chicago, USA
Allen Zang, The University of Chicago, USA
Joaquin Chung, Argonne National Lab (ANL), USA