When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a team has created an algorithm capable of optimizing multiple targets at once, effectively enabling a quantum machine to multitask.
When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a team has created an algorithm capable of optimizing multiple targets at once, effectively enabling a quantum machine to multitask.
Essentially, quantum compilation"programs" the quantum computer by converting a particular goal into an executable sequence. Just as the GPS app converts your desired destination into a sequence of actionable steps you can follow, quantum compilation translates a high-level goal into a precise sequence of quantum operations that the quantum computer can execute.
"By enabling a quantum computer to optimize multiple targets at once, this algorithm increases flexibility and maximizes performance," says Le. This leads to improvements in complex-system simulations or tasks that involve multiple variables in quantum machine learning, making it ideal for applications across various scientific disciplines.
Looking ahead, Le aims to study how this algorithm can adapt to various types of noise and identify ways to enhance its performance.A team has realized a key milestone in the quest for stable, scalable quantum computing. For the first time, the team has created a programmable, logical quantum processor, capable of encoding up to ...
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