Applications
Random Circuit Sampling
A computational task involving sampling outputs from a deliberately complex random quantum circuit, used to demonstrate quantum supremacy claims.
Definition
Random circuit sampling refers to the task of generating samples from the probability distribution produced by running a large, randomly generated quantum circuit, then measuring the result. This specific task was the basis of Google's 2019 quantum supremacy claim using its Sycamore processor.
Technical Definition
The task is believed to be exponentially hard for classical computers to simulate as circuit size grows, though the precise boundary of this hardness has shifted as classical simulation algorithms have improved, leading to ongoing debate about specific supremacy claims.
Visual Explanation: An Analogy
Think of random circuit sampling like a complex, randomly shuffled deck of cards — predicting the exact resulting order (the equivalent of classically simulating the circuit) becomes harder as the deck size grows, even though dealing the cards (running the actual circuit) stays straightforward.
Real-World Use Cases
- The specific task underlying Google's 2019 and subsequent quantum supremacy demonstrations
- Used as a benchmark task in independent verification studies, like those covered in our Research Papers section