What molecule is discussed as an example of a problem quantum computers would need to tackle?

The video references the FIMO co-actor—a molecule important in nitrogen fixation in soil—as an example of a complex problem that quantum computers might one day simulate, illustrating the kinds of real-world chemistry challenges considered in this debate.

What is the traveling salesman problem and how is it used in the critique?

The traveling salesman problem (finding the shortest route to visit multiple locations) is highlighted as a benchmark where quantum approaches have struggled; a recent paper argues that purely quantum methods have little evidence of solving small instances better than classical or hybrid approaches.

Who is Olivier Rati and what did his estimate imply?

Olivier Rati is cited for estimating that error-correcting quantum computers, once large enough to perform useful tasks, would require as much power as entire supercomputer clusters, implying high energy costs even if quantum speedups existed for some tasks.

What does the video say about the 'transistor moment' and its relevance to quantum computing?

The video contrasts microchip success with transistors getting smaller and cheaper to produce against the quantum case, where cooling and noise buffering impose substantial, non-decreasing costs, challenging the parallel path to widespread practicality.

What is the conclusion about purely quantum versus hybrid quantum-classical approaches for optimization problems?

The video notes that reviews over two decades of attempts to force quantum advantages into problems like the TSP show little reason for optimism, suggesting that classical or hybrid quantum-classical methods may be more viable for many tasks.

Why is the FIMO co-actor used as an example, and what does it illustrate about quantum computing?

FIMO co-actor is used to illustrate that, although we can write equations for certain molecules, solving them with a quantum computer (and thus gaining practical advantage) remains challenging, as evidenced by a classical calculation achieving high precision on the molecule's ground state energy.

The Quantum Computer Dream is Falling Apart

Sabine Hossenfelder

Science & Technology3 min read8 min video

Feb 17, 2026|530,641 views|19,011|1,681

hossenfelder science with sabine science humour science news sabine science news science humor physics quantum physics quantum computing technology quantum physics news

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Key Moments

TL;DR

Quantum hype dims: real-world gains remain elusive amid cost and energy barriers.

Key Insights

The expected quantum advantage is much harder to realize in practice than early hype suggested.

Chemistry and materials problems have seen limited real-world gains; classical computation can outperform in some cases.

Error correction progress exists, but scaling quantum computers demands prohibitive cooling and noise-management costs.

Energy usage for large quantum systems could rival or exceed that of supercomputers, challenging long-term feasibility.

The traveling salesman problem is not a reliable pure-quantum showcase; hybrid classical-quantum approaches may be more practical.

Marketing narratives can outpace scientific reality, making cautious optimism with realism essential.

PROMISES AND HYPE AROUND QUANTUM COMPUTING

The transcript frames quantum computing as a once-gleaming story of promise and hype, where the allure of solving intractable problems with entanglement looks dazzling in theory but frays in practice. It emphasizes that entanglement is the engine of potential speedups, yet warns that turning that engine into reliable, scalable performance is far more complex than initial enthusiasm suggested. The narrative echoes a magic-show metaphor: first the rabbit of a guaranteed advantage vanishes, then the hack, and finally the audience—an apt image for the struggle to translate theoretical gains into real-world impact across science, industry, and finance.

MOLECULE TEST CASES AND PRACTICAL LIMITS

A central example discussed is the FIMO co-actor, a molecule important for nitrogen fixation and soil fertility. While the equations describing its properties exist, solving them on conventional computers proves impractical, which is why quantum proposals gained traction. However, a recent Caltech study shows that a conventional computer cluster can calculate the molecule’s ground-state energy with stunning precision. This doesn’t upend the field, but it illustrates a core message: finding a meaningful, scalable quantum advantage remains a narrow target rather than an all-encompassing solution.

TRAVELING SALESMAN PROBLEM: LIMITS OF PURELY QUANTUM SPEEDUPS

The traveling salesman problem, long touted as a canonical hard problem for quantum speedups, is scrutinized. In a new paper, researchers review two decades of attempts to recast TSP for quantum advantage and conclude there is little evidence that purely quantum approaches outperform classical or hybrid quantum-classical methods for small to moderate instances. The takeaway is pragmatic: many real-world tasks in logistics, finance, and manufacturing may benefit more from hybrid strategies or classical optimization, rather than expecting a broad, pure-quantum edge.

ERROR CORRECTION PROGRESS AND ITS LIMITS

On the research front, progress in error correction and qubit quality is acknowledged, with headlines suggesting a ‘transistor moment’ for quantum tech. But the comparison is imperfect: microchips achieved their success through dramatically smaller, cheaper transistors. Quantum hardware, in contrast, relies on cryogenic cooling and sophisticated noise buffering, which are costly to scale. The speaker emphasizes that while error-corrected qubits improve, these improvements come with mounting infrastructure and energy demands that temper the transformative potential of the technology.

COSTS, COOLING, AND ENERGY DEMANDS

A central economic reality is highlighted: large, useful quantum computers could require power comparable to entire supercomputer clusters, with some architectures demanding even more. Cryogenic cooling, vibration isolation, and error-correction overhead impose substantial energy costs. Even if quantum calculations are faster for certain tasks, repeated runs to achieve a target accuracy mean sustained high power draw. This energy footprint challenges the long-term cost-effectiveness and practicality of scaling quantum systems beyond niche demonstrations.

MARKETING, SPONSORSHIPS, AND A CAUTIONARY TONE

Beyond technical debates, the transcript notes how marketing narratives shape perception, sometimes presenting an overly optimistic view of readiness. A sponsorship segment follows, drawing attention to data-privacy services and illustrating how modern tech discourse blends skeptical science with monetized messaging. The host shares a personal anecdote about data-breach anxieties, tying the broader theme to practical concerns. The overarching message is to maintain cautious optimism tempered by realism about costs, ethics, and the limits of hype.

Mentioned in This Episode

●Studies Cited

●People Referenced

Common Questions

The video argues that practical quantum advantage is hard to achieve; several pieces of evidence are cited, including a Caltech preprint showing a ground-state calculation that a classical cluster could perform and reviews suggesting limited evidence for a purely quantum advantage. This casts doubt on rapid, broad real-world applicability.

Topics

Quantum Advantage Error Correction Cryogenic Cooling Noise Buffering Energy Consumption FIMO Co-actor Nitrogen Fixation Molecule Simulation Caltech Preprint Traveling Salesman Problem Hybrid Classical-quantum Optimization Transistor Moment Quantum Costs

Mentioned in this video

studyFIMO co-actor

A molecule described as playing a major role in bacteria that enrich soil with nitrogen; used in the video as the example molecule that quantum computers might one day simulate.

personOlivier Rati

Researcher quoted for an energy/power estimate about error-correcting quantum computers consuming power on par with entire supercomputer clusters when large enough to be useful.