ACM SIGPLAN Notices

Quantum Computing is Getting Real

Frederic T. Chong

Published Mar 19, 2018• 0 citations

Abstract

Quantum computing is at an inflection point, where 50-qubit (quantum bit) machines have been built, 100-qubit machines are just around the corner, and even 1000-qubit machines are perhaps only a few years away. These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation. Yet a significant resource gap remains between practical quantum algorithms and real machines. There is an urgent shortage of the necessary computer scientists to work on software and architectures to close this gap. I will outline several grand research challenges in closing this gap, including programming language design, software and hardware verification, defining and perforating abstraction boundaries, cross-layer optimization, managing parallelism and communication, mapping and scheduling computations, reducing control complexity, machine-specific optimizations, learning error patterns, and many more. I will also describe the resources and infrastructure available for starting research in quantum computing and for tackling these challenges.

DOI: 10.1145/3296957.3177152

Related papers

Closing the Gap between Quantum Algorithms and Machines with Hardware-Software Co-Design

Frederic T. Chong

Quantum computing is at an inflection point, where 127-qubit machines are deployed, and 1000-qubit machines are only a few years away. These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation.

ACM Great Lakes Symposium on VLSI (GLSVLSI)May 31, 20230 citations

Keynote 1

Quantum computing is at an inflection point, where 53-qubit (quantum bit) machines are deployed, 100qubit machines are just around the corner, and even 1000-qubit machines are perhaps only a few years away.These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation.Yet a significant resource gap remains between practical quantum algorithms and real machines.A promising approach to closing this gap is to selectively expose to programming languages and compilers some of the key physical properties of emerging quantum technologies.I will describe some of our recent work that focuses on compilation techniques that break traditional abstractions, including compiling directly to analog control pulses, compiling for machine variations, and compiling with ternary quantum bits.

IEEE International Conference on Rebooting Computing (ICRC)Nov 1, 20210 citations

Final Program

Quantum computing is at an inflection point, where 127-qubit (quantum bit) machines are deployed, and 1000-qubit machines are perhaps only a few years away.These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation.Yet a significant resource gap remains between practical quantum algorithms and real machines.A promising approach to closing this gap is to design architectural interfaces that selectively expose to programming languages and compilers some of the key physical properties of emerging quantum technologies.I will describe some of our recent work that focuses on techniques that break traditional abstractions, including compiling programs directly to analog control pulses, adapting programs for machine variations, computing with ternary quantum bits, efficient error correction using 2.5D structures, and designing just enough tunability in qubits to avoid crosstalk.

IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS)Apr 20, 20220 citations

Quantum Computing: bits to Q-bits, Applications, Challenges, Issues and Solutions

Priyanka, Piyush Dhuliya, Deepak Singh Rana +2 more

With high density and high performance applications, classical CMOS technology's drawbacks may be addressed via a method called quantum computing. This research is attracting more and more scholarly/technically focused on core area of QC and attention on its challenges because to its potential to revolutionize the current computing environment. This paper looks/finds at the many technologies that support quantum computing and provides a brief overview of its fundamental concepts. The resources, which include quantum programming languages, simulators, hardware platforms, and software development kits, have made it possible to conduct cutting-edge research and explore the seemingly endless potential of quantum computing. It also covers the most recent developments, challenges that persist, ongoing progress, and possible futures applications and challenges in this quickly changing field.

International Conference on Advances in Computing, Communication and Materials (ICACCM)Nov 22, 20240 citations

Quantum computing: foundations, algorithms, and emerging applications

V. Raseena

Quantum computing is an emerging paradigm that leverages the principles of quantum mechanics to solve computational problems beyond the reach of classical computers. This article provides an overview of the fundamental concepts of qubits, the distinctive features of quantum mechanics such as superposition and entanglement, and the challenges of building scalable, fault-tolerant systems. It surveys key quantum algorithms and their potential applications in fields including cryptography, optimization, finance, chemistry, and machine learning. Additionally, it highlights the importance of verification frameworks for ensuring the reliability of quantum programs. A literature review of significant contributions is presented, drawing insights from recent surveys on quantum algorithms, qubit technologies, and software verification approaches. The article concludes by discussing ongoing challenges, such as error correction overhead, hardware scalability, and verification complexity, and suggests directions for future research.

Frontiers in Quantum Science and TechnologyDec 29, 20257 citations

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

Masoud Mohseni, Artur Scherer, Katherine Grace Johnson +48 more

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits. Nevertheless, there are significant outstanding challenges in quantum hardware, fabrication, software architecture, and algorithms on the path towards a full-stack scalable quantum computing technology. Here, we provide a comprehensive review of these scaling challenges. We show how to facilitate scaling by adopting existing semiconductor technology to build much higher-quality qubits, employing systems engineering approaches, and performing distributed heterogeneous quantum-classical computing. We provide a detailed resource and sensitivity analysis for quantum applications on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. We provide comprehensive resource estimates for several utility-scale applications including quantum chemistry calculations, catalyst design, NMR spectroscopy, and Fermi-Hubbard simulation. We show that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration. Furthermore, we introduce high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical optimization, machine learning, and quantum simulation tasks in a cost-effective manner.

arXiv:2411.10406Nov 15, 20247 citations