Quantum Computer Systems: Research for Noisy Intermediate-Scale Quantum Computers (Synthesis Lectures on Computer Architecture)

✍ Scribed by Yongshan Ding, Frederic T. Chong

• Publisher: Morgan & Claypool Publishers
• Year: 2020
• Tongue: English
• Leaves: 227
• Category: Library

✦ Synopsis

This book targets computer scientists and engineers who are familiar with concepts in classical computer systems but are curious to learn the general architecture of quantum computing systems. It gives a concise presentation of this new paradigm of computing from a computer systems' point of view without assuming any background in quantum mechanics. As such, it is divided into two parts. The first part of the book provides a gentle overview on the fundamental principles of the quantum theory and their implications for computing. The second part is devoted to state-of-the-art research in designing practical quantum programs, building a scalable software systems stack, and controlling quantum hardware components. Most chapters end with a summary and an outlook for future directions. This book celebrates the remarkable progress that scientists across disciplines have made in the past decades and reveals what roles computer scientists and engineers can play to enable practical-scale quantum computing.

✦ Table of Contents

Preface
Acknowledgments
List of Notations
Building Blocks
Introduction
The Birth of Quantum Computing
The Rise of a New Computing Paradigm
What Is a Quantum Computer?
Models of Quantum Computation
Analog Model
Gate-Based Model
Measurement-Based Model
A QPU for Classical Computing
Architectural Design of a QPU
Quantum Technologies
A Road Map for Quantum Computers
Computer Science Research Opportunities
Think Quantumly About Computing
Bits vs. Qubits
Computing with Bits: Boolean Circuits
Computing with Qubits: Quantum Circuits
Architectural Constraints of a Quantum Computer
Basic Principles of Quantum Computation
Quantum States
Composition of Quantum Systems
Measurements
Quantum Gates
Noisy Quantum Systems
Quantum Probability
Operator Sum Representation
Qubit Decoherence and Gate Noise
Qubit Technologies
Trapped Ion Qubits
Superconducting Qubits
Other Promising Implementations
Quantum Application Design
General Features
The Computing Process
The Query Model and Quantum Parallelism
Complexity, Fidelity, and Beyond
Gate-Based Quantum Algorithms
Deutsch–Josza Algorithm
Bernstein–Vazirani Algorithm
NISQ Quantum Algorithms
Variational Quantum Eigensolver (VQE)
Quantum Approximate Optimization Algorithm (QAOA)
Summary and Outlook
Quantum Computer Systems
Optimizing Quantum Systems–An Overview
Structure of Quantum Computer Systems
Quantum-Classical Co-Processing
Quantum Compiling
NISQ vs. FT Machines
Quantum Programming Languages
Low-Level Machine Languages
High-Level Programming Languages
Program Debugging and Verification
Tracing via Classical Simulation
Assertion via Quantum Property Testing
Proofs via Formal Verification
Summary and Outlook
Circuit Synthesis and Compilation
Synthesizing Quantum Circuits
Choice of Universal Instruction Set
Exact Synthesis
Approximate Synthesis
Higher-Dimensional Synthesis
Classical vs. Quantum Compiler Optimization
Gate Scheduling and Parallelism
Primary Constraints in Scheduling
Scheduling Strategies
Highlight: Gate Teleportation
Qubit Mapping and Reuse
Finding a Good Qubit Mapping
Strategically Reusing Qubits
Highlight: Uncomputation
Summary and Outlook
Microarchitecture and Pulse Compilation
From Gates to Pulses–An Overview
General Pulse Compilation Flow
Quantum Controls and Pulse Shaping
Open-Loop vs. Closed-Loop Control
Quantum Optimal Control
Highlight: Compilation for Variational Algorithms
Summary and Outlook
Noise Mitigation and Error Correction
Characterizing Realistic Noises
Measurements of Decoherence
Quantum-State Tomography
Randomized Benchmarking
Noise Mitigation Strategies
Randomized Compiling
Noise-Aware Mapping
Crosstalk-Aware Scheduling
Quantum Error Correction
Basic Principles of QEC
Stabilizer Codes
Transversality and Eastin–Knill Theorem
Knill's Error Correction Picture
Summary and Outlook
Classical Simulation of Quantum Computation
Strong vs. Weak Simulation: An Overview
Distance Measures
Density Matrices: The Schrödinger Picture
Stabilizer Formalism: The Heisenberg Picture
Graphical Models and Tensor Network
Summary and Outlook
Concluding Remarks
Bibliography
Authors' Biographies