There’s a lot of speculation about the potential for quantum computing, but to get a clearer vision of the future impact, we need to disentangle myth from reality. At this week’s virtual Q2B conference, we take a pragmatic perspective to cut through the hype and discuss the practicality of quantum computers, how to future-proof quantum software development, and the real value obtained today through quantum-inspired solutions on classical computers.
Achieving practical quantum advantage
Dr. Matthias Troyer, Distinguished Scientist with Microsoft Quantum, explains what will be needed for quantum computing to be better and faster than classical computing in his talk Disentangling Hype from Reality: Achieving Practical Quantum Advantage. People talk about many potential problems they hope quantum computers can help with, including fighting cancer, forecasting the weather, or countering climate change. Having a pragmatic approach to determining real speedups will enable us to focus the work on the areas that will deliver impact.
For example, quantum computers have limited I/O capability and will thus not be good at big data problems. However, the area where quantum does excel is large compute problems on small data. This includes chemistry and materials science, for game-changing solutions like designing better batteries, new catalysts, quantum materials, or countering climate change. But even for compute-intensive problems, we need to take a closer look. Troyer explains that each operation in a quantum algorithm is slower by more than 10 orders of magnitude compared to a classical computer. This means we need a large speedup advantage in the algorithm to overcome the slowdowns intrinsic to the quantum system; we need superquadratic speedups.
Troyer is optimistic about the potential for quantum computing but brings a realistic perspective to what is needed to get to practical quantum advantage: small data/big compute problems, superquadratic speedup, fault-tolerant quantum computers scaling to millions of qubits and beyond, and the tools and systems to develop the algorithms to run the quantum systems.
Future-proofing quantum development
Developers and researchers want to ensure they invest in languages and tools that will adapt to the capabilities of more powerful quantum systems in the future. Microsoft’s open-source Quantum Intermediate Representation (QIR) and the Q# programming language provide developers with a flexible foundation that protects their development investments.
QIR is a new Microsoft-developed intermediate representation for quantum programs that is hardware and language agnostic, so it can be a common interface between many languages and target quantum computation platforms. Based on the popular open-source LLVM intermediate language, QIR is designed to enable the development of a broad and flexible ecosystem of software tools for quantum development.
As quantum computing capabilities evolve, we expect large-scale quantum applications will take full advantage of both classical and quantum computing resources working together. QIR provides full capabilities for describing rich classical computation fully integrated with quantum computation. It’s a key layer in achieving a scaled quantum system that can be programmed and controlled for general algorithms.
In his presentation at the Q2B conference, Future-Proofing Your Quantum Development with Q# and QIR, Microsoft Senior Software Engineer Stefan Wernli explains to a technical audience why QIR and Q# are practical investments for long-term quantum development. Learn more about QIR in our recent Quantum Blog post.
Quantum-inspired optimization solutions today
At the same time, there are ways to get practical value today through “quantum-inspired” solutions that apply quantum principles for increased speed and accuracy to algorithms running on classical computers.
We are already seeing how quantum-inspired optimization solutions can solve complex transportation and logistics challenges. An example is Microsoft’s collaboration with Trimble Transportation to optimize its transportation supply chain, presented at the Q2B conference in Freight for the Future: Quantum-Inspired Optimization for Transportation by Anita Ramanan, Microsoft Quantum Software Engineer, and Scott Vanselous, VP Digital Supply Chain Solutions at Trimble.
Trimble’s Vanselous explains how today’s increased dependence on e-commerce and shipping has fundamentally raised expectations across the supply chain. However, there was friction in the supply chain because of siloed data between shippers, carriers, and brokers; limited visibility; and a focus on task optimization vs. system optimization. Trimble and Microsoft are designing quantum-inspired load matching algorithms for a platform that enables all supply chain members to increase efficiency, minimize costs, and take advantage of newly visible opportunities. You can learn more about our collaboration in this video:
Many industries—automotive, aerospace, healthcare, government, finance, manufacturing, and energy—have tough optimization problems where these quantum-inspired solutions can save time and money. And these solutions will only get more valuable when scaled quantum hardware becomes available and provides further acceleration.
How to get started
Explore Microsoft’s quantum-inspired optimization solutions, both pre-built Azure Quantum and custom solutions that run on classical and accelerated compute resources.
Learn how to write quantum code with Q# and the Quantum Development Kit. Write your first quantum program without having to worry about the underlying physics or hardware.
Azure Quantum will be available in preview early next year. Join us for our next Azure Quantum Developer Workshop on February 2, 2021, where you can learn more about our expanding partner ecosystem and the solutions available through the Azure Quantum service. Registration opens today.