What You Shouldn't Know About Quantum Computers
Quantum computing’s promise of breaking RSA encryption and delivering “quantum supremacy” is questioned here on both physical and practical grounds. Commenters debate whether error correction, cooling, and scaling constraints will ultimately make large, fault-tolerant quantum computers infeasible, despite steady improvements in qubit quality and small-scale demonstrations. The conversation also critiques hype from industry and academia, arguing that while the underlying physics research is real, commercial usefulness and timelines remain highly uncertain.
Reception of the article
- Several readers find it a clear, accessible explanation of what quantum computers are and are not.
- Others criticize it for mixing abstraction layers (e.g., using transistors as an analogy) and for glossing over deep technical issues like scalable error correction.
Feasibility and Power of Quantum Computing
- One camp argues quantum computing may never be “usefully” realizable or significantly more powerful than classical computing in practice, especially at large scale.
- Another camp points to fault-tolerance threshold theorems and current experimental progress as strong evidence that large, useful machines are physically possible, though challenging.
- There is debate over whether skepticism implies new physics would be required, or merely that engineering might be impractically hard.
Cooling, Noise, and Scaling
- Long subthread on thermodynamics: whether cooling costs and thermal noise scale polynomially or worse with the number of qubits and volume.
- Some argue cooling difficulty grows sharply at very low temperatures and large scales; others emphasize geometry and error correction can mitigate this, and more qubits do not necessarily require lower temperatures.
- Several commenters distinguish between temperature limits and error-correction overhead.
State of Quantum Error Correction
- Question raised: has anyone demonstrated a single fully “usable” logical qubit?
- Linked experimental work shows substantial error reduction but only with heavy pre/post-selection; still far from target logical error rates (~10⁻⁸).
- Multiple comments repeat that the main milestone is crossing the error-rate threshold where overhead becomes finite and scalable.
Quantum Supremacy and Factoring Timelines
- Progress on factoring with Shor’s algorithm is seen as minimal; past demonstrations are criticized as “compiled” or non-robust.
- A co-author of a cited forecasting paper clarifies their predictions are conditional on smooth continuation of current trends and says more meaningful metrics than “largest integer factored” show steady progress.
- Some readers view predictions like “90% chance of factoring RSA‑2048 by ~2060” as overconfident or “delusional”; others stress that long-term probabilistic forecasts reflect present information, not certainty.
Cryptography and Complexity Perspective
- Discussion notes that quantum computers are expected to efficiently solve certain problems (e.g., discrete logarithms, factoring) but are not believed to solve arbitrary NP problems.
- Emphasis that quantum speedups come from interference patterns, not brute-force parallelism over 2ⁿ states.
Usefulness, Hype, and Industry Dynamics
- Multiple comments assert there are effectively no present-day, broadly useful quantum computing applications; current devices are mostly research or niche (e.g., annealers).
- Some call the investor-facing story around quantum computing a “con” in its expectations, while acknowledging the underlying science is real.
- Comparisons are drawn to hype in AI and blockchain, though AI is noted as already commercially useful.
Meta: arXiv Use and Popularization
- Brief debate over whether uploading a long popular-science-style PDF to arXiv is appropriate; others point out there is a dedicated “physics and society” category for such material.
- Short side discussion on children’s physics books and whether they emphasize superficial analogies versus core conceptual substance.