Despite numerous advances in the field and a seemingly ever-increasing amount of investment, we are still some years away from seeing a production quantum computer in action. However, it is possible to make some educated guesses about the operational difficulties and challenges that may be encountered in practice. We can be reasonably confident that the early machines will be hybrid, with the quantum devices used in an apparently similar way to current accelerators such as FPGAs or GPUs. Compilers, libraries and the other tools relied upon currently for development of software will have to evolve/be reinvented to support the new technology, and training courses will have to be rethought completely rather than ``just'' updated alongside them. The workloads we are likely to see making best use of these hybrid machines will initially be few, before rapidly increasing in diversity as we saw with the uptake of GPUs and other new technologies in the past. This will again be helped by the increase in the number of supporting libraries and development tools, and by the gradual re-development of existing software, to make use of the new quantum devices. Unfortunately, at present the problem of error correction is still largely unsolved, although there have been many advances. Quantum computation is very sensitive to noise, leading to frequent errors during execution. Quantum calculations, although asymptotically faster than their equivalents in ``traditional'' HPC, still take time, and while the profiling tools and programming approaches will have to change drastically, many of the skills honed in the current HPC industry will not suddenly become obsolete, but continue to be useful in the quantum era.

翻译：尽管该领域取得了诸多进展，且投资规模看似持续增长，但距离生产级量子计算机的实际应用仍相隔数年。然而，我们仍可对实践中可能遇到的运行困难与挑战做出合理推测。有充分依据表明，早期量子计算机将采用混合架构，其量子器件的使用方式与当前FPGA或GPU等加速器类似。当前软件开发所依赖的编译器、程序库及其他工具必须进化或重构以支持新技术，而培训课程也需要彻底重构，而非"仅仅"随之更新。此类混合机器的最佳应用场景最初将较为有限，但正如过去GPU及其他新技术的普及过程所示，其多样性将迅速增加。这一进程同样将受益于支持性程序库与开发工具数量的增长，以及现有软件为适配新型量子设备而进行的渐进式重构。令人遗憾地是，尽管纠错领域已取得诸多进展，但目前该问题仍基本未获解决。量子计算对噪声极为敏感，导致执行过程中频繁发生错误。虽然量子计算在渐近复杂度上优于传统高性能计算的等效计算，但仍需消耗计算时间。在此过程中，性能分析工具与编程范式虽需彻底变革，但当前高性能计算行业锤炼出的诸多技能并不会突然过时，仍将在量子时代持续发挥价值。