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Taming Quantum Computers with High-Level Software Stacks


Quantum computing promises to disrupt any industry that relies on heavy-duty computation. Use cases of this new technology range from chemistry and materials design to machine learning and optimization in finance, energy, mobility, logistics, and pharma. Over the past few years, first generation quantum computers have become available to end users. While these early-stage machines still need to overcome technical difficulties before they can outperform classical high-performance computing, they are an invaluable tool for exploring this new technology. Quantum computing requires new corporate structures and skills because classical algorithms and development methods cannot simply be reused or easily adapted. To be ready in time companies need to start this learning process today while the technology continues to mature.

Many of the largest industry players, governments and venture capitalists world-wide have ramped up heavily their investments in quantum computing. This has resulted in rapid progress of hardware and software. On the software side, development tools for quantum computer programming have emerged. On the hardware side, e.g. Google’s fully programmable quantum computer has demonstrated a computational advantage over the fastest supercomputer [1]. While the task they solved has no relevance for business use cases, these developments clearly demonstrate the prowess of even relatively small quantum computers.

The accelerating pace of the field means that some industry verticals could be affected sooner rather than later. It takes time and a deep understanding of the technology to acquire the skills necessary for an assessment and the implementation of potential use cases. First steps towards adoption are joining the growing quantum computing ecosystem and exploration with available early-stage quantum machines. We support you on this journey with our expertise in assessing potential use cases, building up skills, programming prototypes, and integration. For example, d-fine is a core member of PlanQK, a consortium of industry and academic partners developing a platform, ecosystem and use cases for quantum-assisted machine learning. This report provides you with an overview of quantum computing, the prevalent hardware access model, major quantum software frameworks, and concludes with a glimpse into programming quantum computers.