{"id":97979,"date":"2026-06-05T10:59:15","date_gmt":"2026-06-05T07:59:15","guid":{"rendered":"https:\/\/forklog.com\/en\/?p=97979"},"modified":"2026-06-05T11:01:36","modified_gmt":"2026-06-05T08:01:36","slug":"what-are-quantum-supremacy-utility-and-advantage","status":"publish","type":"post","link":"https:\/\/forklog.com\/en\/what-are-quantum-supremacy-utility-and-advantage\/","title":{"rendered":"What Are Quantum Supremacy, Utility and Advantage?"},"content":{"rendered":"
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What Is Quantum Supremacy and When Was It Achieved?<\/h2>\n

Theoretical physicist John Preskill coined the term \u201cquantum supremacy\u201d in 2012. In scientific terms, it marks a fundamental computational threshold: the point at which a quantum device solves a specific task in acceptable time while a classical supercomputer, though in principle capable, is so inefficient that the result would take years, centuries or even millennia.<\/p>\n

Early demonstrations were strictly laboratory exercises because devices were highly susceptible to computational noise (errors). To prove the technology\u2019s viability under such conditions, engineers turned to synthetic algorithms \u2014 for example, sampling from random quantum circuits (RCS<\/span>).<\/p>\n

These tests had no direct commercial value, but they served a critical purpose: they recorded quantum architecture\u2019s superiority over classical machines in a narrow niche and opened the industry\u2019s path toward useful applications.<\/p>\n

In 2019, Google\u2019s research team first claimed<\/a> quantum supremacy. Its 53-qubit superconducting Sycamore processor completed an RCS task in 200 seconds. The researchers said the then-most-powerful classical supercomputer, Summit, would have needed about 10,000 years.<\/p>\n

IBM disputed<\/a> the announcement. The company said Summit could handle the task in just two and a half days. By efficiently leveraging not only processors but also the supercomputer\u2019s vast RAM and disk storage, IBM argued, one could sidestep the apparent exponential complexity.<\/p>\n

Chinese research teams later reported crossing the threshold on two different physical architectures: the photonic quantum computer Jiuzhang<\/a>, which uses photons for boson sampling<\/span>, and updated superconducting systems with a QPU<\/span>, Zuchongzhi 3.0<\/a>. In March 2025, the system generated one million samples in just a few minutes. According to the Chinese team\u2019s estimates, exact simulation of this specific process would take Frontier, the world\u2019s most powerful classical supercomputer, about 6.4 billion years.<\/p>\n

While tasks like RCS lack practical or commercial utility, they play a vital role: they prove<\/a> that as the number of high-quality qubits grows, quantum power becomes insurmountable for the von Neumann classical architecture.<\/p>\n<\/div>\n

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What Is Quantum Utility?<\/h2>\n

At the stage of quantum utility, quantum computers stop being laboratory record-setters and become tools for scientific research. They don\u2019t yet outpace supercomputers across all metrics, but they can already probe physical problems at scales inaccessible to direct classical simulation.<\/p>\n

Quantum utility is the ceiling for the NISQ<\/span> era. For the next stage \u2014 FTQC<\/span> \u2014 engineers prioritize suppressing errors (error mitigation) over merely adding qubits. The method extracts accurate results from \u201cnoisy\u201d systems before they lose their quantum state.<\/p>\n

Error mitigation must be strictly distinguished from full-fledged hardware error correction, the hallmark of the next historical phase.<\/p>\n

The concept was proposed and demonstrated<\/a> by IBM in 2023, effectively launching the period of quantum utility, which continued in 2026. In the experiment, the 127-qubit Eagle processor modeled properties of complex magnetic materials. Using noise-mitigation techniques, the processor produced results that could not be computed exactly by classical methods.<\/p>\n

To realize quantum utility, teams often deploy hybrid architectures that use a QPU, a CPU<\/span> and a GPU<\/span> together \u2014 a balance that efficiently allocates workloads.<\/p>\n

In May 2026, IBM, Cleveland Clinic and Japan\u2019s RIKEN, using such heterogeneous computation, simulated<\/a> a giant protein\u2013ligand complex of 12,635 atoms. The task ran on two quantum computers and two classical supermachines.<\/p>\n<\/div>\n

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What Is Quantum Advantage?<\/h2>\n

The media often uses \u201cquantum supremacy\u201d and \u201cquantum advantage\u201d as synonyms, but in scientific and business contexts they mark different stages in the technology\u2019s evolution.<\/p>\n

Supremacy is a laboratory proof of quantum hardware\u2019s fundamental computational power. Advantage is broader: it is achieved when a device solves a concrete applied task faster, cheaper or more accurately than the best classical supercomputer.<\/p>\n

The key criterion is practical and economic viability. A business doesn\u2019t need a complex, expensive QPU if a conventional cluster can simulate a molecule for a new drug or calculate the properties of a super-strong alloy in comparable time and budget.<\/p>\n

Achieving quantum advantage, alongside FTQC, is a primary goal for leading technology companies and startups over the next three to four years.<\/p>\n

Examples from roadmaps:<\/p>\n