IBM: Three Demonstrations Prove Quantum Advantage Has Been Reached
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IBM: Three Demonstrations Prove Quantum Advantage Has Been Reached
Jeff Burt
Jeff<br>Burt
Published<br>fri 31 Jul 2026 // 23:48 UTC
There are a number of ways to measure the growing maturity of quantum computing, from qubit counts – both physical and logical – and fault tolerant thresholds to the speed in terms of CLOPS (circuit layer operations per second) and reliable operations executed with QuOps, or quantum operations.<br>Then there is quantum advantage. There are slight differences in the definition depending on who you’re talking to, but the gist is that quantum advantage occurs when a quantum system can solve a practical and real-world problem more quickly, cheaper, or more accurately than a classical supercomputer.
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Some vendors have claimed to have reached quantum advantage – from Google’s announcement last year of its Google Echoes Algorithm running on its Willow chip to quantum infrastructure software maker Q-CTRL in May saying it “achieved evidence of practical quantum advantage” in material science running its software on IBM’s Quantum Platform – but as seen here, there is plenty of debate within the scientific community whether quantum advantage actually has been reached just yet.<br>There also have been claims of quantum supremacy, including Google’s assertion in 2019 regarding its 53-qubit Sycamore quantum processor and D-Wave last year touting a version of its Advantage 2 quantum annealing system, which also has been challenged. The usefulness of the problem solved is the difference between advantage and supremacy. For quantum advantage, the problem needs to be practical and real-world; with supremacy, it’s any task that can be done faster by a quantum system than classical computer, even if the job itself is useless<br>IBM and quantum startup Pasqal last year laid out what they said are the requirements that need to be met to declare quantum advantage. Big Blue also has its Quantum Advantage Tracker, a platform-agnostic framework for collecting and validating results of quantum advantage claims.<br>This week, IBM and several partners in a series of research papers are detailing demonstrations run on the IT giant’s Heron quantum chip (below) where they say those requirements – that the work by the quantum systems is done with more accurately, cheaper, and more efficiently than classical systems, and that the output can be rigorously validated – were met.
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It’s an important step on the continuing trek toward fault-tolerant, practical, and commercial quantum computing, according to Jay Gambetta, IBM Fellow and director of IBM Research.<br>“These demonstrations prove that we can scale quantum computing forward with confidence,” Gambetta told journalists in a conference call. “First, they show that quantum computers can solve problems that go beyond the reach of classical methods that could run on the biggest classical computers. And second, they show a series of results of quantum computers that can be validated with confidence, even for problems where classical computers using current methods cannot solve these problems. To me, this marks a huge milestone for the field. We can now move quantum advantage beyond just demonstrating computational power – because we've established the trust in these methods – to looking at problems for science, business, and technology as we go forward in this technology.”<br>Algorithmiq is a startup that develops quantum software and algorithms for such industries as life sciences, chemistry, and material science. Eight months ago, the company submitted to the Quantum Advantage Tracker a demonstration where it simulated what co-founder and chief technology officer Sabrina Maniscalco called a “real-world disordered matter” and created a simulation framework to test it. The project addresses a challenge in some sciences in that materials like catalysts and batter electrolytes comes with irregular structures and variation to effect how they can move energy and particles through a system.<br>“Most of the physics that we are taught in school describe really something that is rather idealized: idealized materials, perfect crystals, clean symmetric structures,” Maniscalco said. “But the real world isn't like that. All materials that will power the next generation of clean energy and industry are messy, disordered, and irregular, and this messiness is exactly what makes them hard to simulate, and exactly why understanding the matters.”
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In the eight months since it was pulled into the Quantum Advantage Tracker, no classical system has been able to reliably reproduce the same results at scale, she said. IBM ran the same experiment on other quantum processors with different noise and calibrations, and Algorithmiq worked with classical simulation companies like the Flatiron Institute to challenge its findings.<br>The experiments...