Progress in quantum computing is typically measured using several key metrics. Here are some of the common ways to evaluate the advancement and performance of quantum computing systems:
Qubit Count: The number of qubits is a fundamental metric used to assess the size and capacity of a quantum computer. More qubits generally allow for more complex calculations and the potential to solve larger problem sizes.
Gate Error Rate: Quantum gates are the basic building blocks of quantum algorithms, similar to logic gates in classical computers. The gate error rate indicates the probability of an error occurring during the execution of a gate operation. Lower gate error rates are desirable for reliable computation.
Coherence Time: Coherence time refers to the duration during which quantum information can be maintained without significant loss or decoherence. Longer coherence times enable more complex computations and better error correction capabilities.
Quantum Volume: Quantum volume is a metric that combines various factors, including qubit count, gate error rate, and coherence time, to provide a single numerical value representing the overall computational capability of a quantum computer. It aims to capture the complexity of algorithms that can be executed on a given device.
Algorithmic Milestones: The successful demonstration of quantum algorithms that outperform classical algorithms on specific tasks is an essential measure of progress. For instance, achieving quantum advantage, also known as quantum supremacy, refers to solving a computational problem with a quantum computer faster than the best classical computer.
Error Correction: Quantum error correction is crucial for maintaining the accuracy and reliability of quantum computations. Progress in error correction techniques, such as achieving lower error rates or implementing larger code distances, is an indication of advancements in the field.
Scalability: The ability to scale quantum systems by adding more qubits, improving gate performance, and reducing error rates is a critical factor in measuring progress. Scalability is necessary to tackle more complex problems and achieve practical quantum computing applications.
It's important to note that these metrics are interconnected, and progress in one area often influences progress in others. Evaluating quantum computing progress involves considering these metrics collectively to understand the advancements made in building more powerful and reliable quantum systems.