Quantum Computing
Quantum computing uses the principles of quantum mechanics — superposition, entanglement, and interference — to perform computations that would be intractable for classical computers on certain problem classes. Unlike classical bits (0 or 1), qubits can exist in superposition states representing both 0 and 1 simultaneously, enabling massively parallel exploration of solution spaces.
Why It Matters Now
Until recently, many researchers expected commercially relevant quantum computing to be decades away. That consensus is rapidly reversing. As scott-aaronson told Discover Magazine in 2026: “The last couple of years have been very, very exciting” — breakthroughs in hardware stability, error correction, and quantum advantage demonstrations have compressed the timeline significantly (cottier-2026-quantum-computing-breakthroughs).
Core Technical Challenges
Decoherence
Qubits are fragile. Temperature fluctuations, electromagnetic interference, and vibration collapse quantum states into classical behaviour — destroying the computation. This is called decoherence.
Quantum Error Correction
Because decoherence introduces errors, quantum computers need error correction. The challenge: error correction itself requires many qubits performing many operations, generating more errors. Until recently, adding more qubits made things worse, not better.
Google’s Willow chip (2024) crossed the critical threshold: error correction improves with increasing qubit count. This is the key enabler of fault-tolerant quantum computing (cottier-2026-quantum-computing-breakthroughs).
Hardware Platforms (2025–2026)
| Platform | Company | Approach | Strength |
|---|---|---|---|
| Superconducting | google-quantum-ai (Willow, 105 qubits) | Josephson junctions cooled near absolute zero | Speed; error threshold crossed |
| Trapped-ion | quantinuum (Helios, 98 qubits); ionq | Electrically suspended charged atoms | Very high accuracy (~99.99%) |
| Neutral-atom | QuEra | Laser-trapped atom arrays | Flexible connectivity |
| Superconducting | rigetti-computing (108 qubits) | Similar to Google | Scaling issues (99% fidelity vs 99.9% target) |
Key fidelity comparison:
- ionq: 99.99% 2-qubit-gate-fidelity (Oct 2025) — industry leading
- rigetti-computing: 99.9% (prototype only); 99% at 108-qubit scale (drury-2026-rigetti-2-qubit-fidelity)
Recent Breakthroughs (2024–2026)
1. Google Willow — Error Threshold Crossed
First demonstration that adding qubits improves rather than degrades accuracy. Published in Nature (“Quantum error correction below the surface code threshold”). Enables indefinite qubit stabilisation in theory (cottier-2026-quantum-computing-breakthroughs).
2. Quantinuum — Quantum Advantage (Nov 2025)
Simulated the Fermi-Hubbard model on trapped-ion hardware — a condensed-matter problem that is “near-impossible” classically, with implications for room-temperature superconductor research. Considered “verifiable quantum supremacy” on current devices (cottier-2026-quantum-computing-breakthroughs).
3. Caltech/Oratomic — Qubit Count Reduction
New fault-tolerant scheme reduces required qubits from millions to ~10,000 — two orders of magnitude — dramatically accelerating the commercial timeline (cottier-2026-quantum-computing-breakthroughs).
4. Google Quantum AI — Shor’s Algorithm Optimisation
Improved implementation of Shor’s algorithm for ECDLP-256 requires < 500,000 physical qubits (down ~20× from prior estimates). Combined with Caltech results, scott-aaronson estimates bitcoin could be vulnerable with only 25,000–30,000 qubits (babbush-neven-2026-quantum-vulnerabilities-cryptocurrency, cottier-2026-quantum-computing-breakthroughs).
Near-Term Applications
- Chemistry & drug discovery: Molecular simulation (already demonstrated by Quantinuum)
- Materials science: Room-temperature superconductors
- Optimisation: Logistics, finance, supply chains
- Cryptanalysis: Breaking ECC — the primary security concern for cryptocurrency and internet security
Cryptographic Implications
The most urgent near-term real-world consequence is the threat to public-key cryptography. bitcoin, most blockchain systems, and much of internet security rely on ECDLP-256. When cryptographically relevant quantum computers (CRQCs) arrive, this encryption will be broken. Migration to PQC is the solution — Google targets 2029 for its own infrastructure.
Sources
- cottier-2026-quantum-computing-breakthroughs — Primary survey of 2024–2026 breakthroughs
- babbush-neven-2026-quantum-vulnerabilities-cryptocurrency — Quantum threat to crypto; Google resource estimates
- drury-2026-rigetti-2-qubit-fidelity — Competitive landscape; fidelity metrics