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Companies / Google / Google Quantum Echoes: The first real proof that quantum computing actually works
AI futurologyCompaniesGoogleNewsResearch

Google Quantum Echoes: The first real proof that quantum computing actually works

Google’s Willow chip achieves verifiable Quantum advantage - A new era begins

Daniel Reed
ByDaniel Reed
AI Research, Safety & Ethics Analyst
Daniel Reed currently works as an AI Research, Safety & Ethics Analyst at Aiholics, writing about how changes in artificial intelligence are affecting and will affect...
- AI Research, Safety & Ethics Analyst
Published: October 24, 2025
6 Min Read
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Quantum computing has long promised to revolutionize how we solve some of the most complex problems in science and technology, yet actually proving its practical edge over classical supercomputers has remained elusive. Recently, I came across fascinating insights about a milestone that finally brings us closer to that promise. The Quantum Echoes algorithm, running on Google‘s Willow quantum chip, has accomplished the first-ever verifiable quantum advantage on actual hardware — not just simulations or theoretical proposals, but real devices.

This breakthrough means that a quantum computer has now done something an incredibly powerful classical supercomputer just can’t match, and it’s repeatable and checkable. The implications for fields like medicine, materials science, and chemistry could be huge.

What is quantum advantage, and why does verifiability matter?

Quantum advantage refers to a quantum computer solving a problem faster or more efficiently than any classical computer could. Back in 2019, the first evidence of such advantage was demonstrated, but those early successes were limited to contrived problems without clear real-world impact and lacked built-in verification. Fast forward to today, where the Quantum Echoes algorithm not only runs 13,000 times faster than top classical supercomputers but also produces verifiable results—meaning the output can be reliably reproduced and checked on other quantum systems of similar scale.

Image: Google

This is huge because reproducibility is the cornerstone of practical usefulness. If quantum results can’t be verified, their reliability and utility remain questionable. Now, with the ability to cross-check computations, we can trust that quantum computers have truly outpaced classical machines in meaningful ways, a vital step towards trustworthy real-world applications.

How Quantum Echoes works: the power of a quantum “echo”

The Quantum Echoes algorithm essentially uses a clever trick: it sends a quantum signal forward through a system of qubits, tweaks one qubit along the way, then runs the operations backward to catch an “echo” of that disturbance. This echo is amplified through constructive interference, making it exquisitely sensitive to how information and disturbances spread across the quantum chip.

The Willow Quantum chip. Image: Google

This four-step cycle—running operations forward, perturbing a qubit, running them backward, and measuring—is a sophisticated way to probe quantum dynamics with precision. Thanks to Willow’s 105-qubit array with ultra-low error rates and high-speed gates, this algorithm goes beyond previous quantum benchmarks focused just on complexity and steps toward precision calculations. It’s a new class of quantum challenge that mimics real physical experiments.

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From quantum advantage to real-world applications

Quantum computing isn’t just about speed; it’s about unlocking new ways to understand nature, especially at the atomic and molecular level. Nuclear Magnetic Resonance (NMR) spectroscopy is a key tool in chemistry and biology for revealing molecular structures, but it has limitations in sensitivity and range. The Quantum Echoes approach acts like a “molecular ruler” that can measure longer distances and extract richer information from NMR data.

In partnership with the University of California, Berkeley, this technique was tested on molecules with up to 28 atoms. Astonishingly, the quantum results matched traditional NMR while also providing new structural insights unavailable by conventional means. This hints at the potential for a “quantum-scope” capable of unveiling details of molecular and material structures that were previously hidden from us.

Such advances could dramatically impact drug discovery, where understanding how a drug binds to its target molecule is crucial, or materials science, for designing better batteries, polymers, or even new quantum hardware components themselves.

Key takeaways to keep in mind

  • Verifiable quantum advantage means that quantum results are reliably repeatable and checkable, a critical step for practical applications.
  • The Quantum Echoes algorithm leverages a quantum echo phenomenon to measure the spread of disturbances with unprecedented precision on a 105-qubit chip.
  • Applying quantum computing to enhance NMR spectroscopy opens a path toward new molecular and material insights with real-world implications for science and industry.

Looking forward, this breakthrough is more than just a technical feat. It signals the dawn of a new era where quantum computers start delivering tangible benefits beyond academic milestones. As quantum hardware improves toward long-lived, error-corrected qubits, we can expect more powerful algorithms that open new frontiers in medicine, chemistry, and materials science.

It’s exciting to witness how the once futuristic vision of quantum computing is steadily transforming into a practical tool that could redefine how we explore and harness the natural world.

TAGGED:Googlesupercomputer

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ByDaniel Reed
AI Research, Safety & Ethics Analyst
Daniel Reed currently works as an AI Research, Safety & Ethics Analyst at Aiholics, writing about how changes in artificial intelligence are affecting and will affect scholarship, society, and human civilization. He reports on breakthroughs in AI research, the development of safety frameworks, discussion of long-term risks, and ethical challenges; he also reports on global shifts in policy and governance. Daniel aims to make complex research papers and long-term thinking accessible to the everyday reader without sacrificing nuance. With his thoughtful and analytical style of writing, Daniel translates advanced topics into clear language. He targets questions that really matter: how safe are today's AI systems, what kind of ethical boundaries do we need, and how could exponential progress affect the way education, jobs, governance, and human values are shaped? His articles are often not just expert opinions but also balanced views and insight into emerging debates that define AI's place in the world. Daniel believes responsible AI development begins with awareness, transparency, and informed public conversation. In terms of his work with Aiholics, he encourages readers to look beyond headlines to understand the promise of artificial intelligence but also some of its consequences.
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