GCRI · Quantum Technologies
Quantum computing
Quantum computers use qubits that can be in superpositions and become entangled, which in principle lets some problems be solved far faster than on classical computers. Current machines are noisy and small, and useful fault-tolerant computing requires error correction that is only beginning to be demonstrated. This page sets out how quantum computers work and fail, how progress is measured honestly, and what evidence serves the institutions deciding how to engage.
Quantum computing on the record.
Quantum computing: how the risk develops.
Hardware, algorithms and actual maturity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Qubits are fragile
Qubits lose their quantum state through interaction with their environment. Gate errors and decoherence limit how long a computation can run before results become noise.
Error correction needs overhead
Fault-tolerant computing encodes each logical qubit in many physical qubits and corrects errors continuously. It only helps once physical error rates fall below a threshold.
Advantage is problem-specific
Quantum algorithms speed up particular problems, such as simulating quantum systems or factoring. For many tasks classical computers remain as good or better.
Claims need classical comparison
Demonstrations of quantum advantage are often followed by improved classical methods. Honest comparison requires the best classical approach, not a convenient one.
Quantum testbed.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Quantum testbed
Quantum computing · Testbed lab · Device QD-28
Qubits
| Q0 | 121 | 49 | 0.03 | Drifting |
| Q1 | 118 | 24 | 0.03 | Drifting |
| Q2 | 94 | 41 | 0.03 | Drifting |
| Q3 | 73 | 93 | 0.05 | Drifting |
| Q4 | 50 | 48 | 0.02 | Drifting |
Device
- Topology
- heavy-hex, illustrative
- 2Q fidelity
- 0.994
- Access
- by committee
- Label
- OBSERVED
Quantum computing matters to the domains through simulation and through cryptography.
- EnergyCouplingSimulation of battery and catalyst chemistry is a proposed early use.What to watchDemonstrated against classical baselines
- HealthCouplingFuture cryptanalysis threatens long-lived health data.What to watchMigration of health systems
- FoodCouplingFertiliser catalysis is often cited as a target problem.What to watchClaims separated from results
Status reviews are designed for the Exponential Technology series, separating demonstrations from roadmaps. No date for a cryptographically relevant quantum computer is presented as known.
- Peer-reviewed results with classical comparisons.
- Corrections to over-stated claims.
How quantum computing is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in quantum computing: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Physical qubit count | qubits | per announcement | Published device results | REPORTED |
| Two-qubit gate fidelity | percent | per device | Benchmark results | REPORTED |
| Logical qubit error rate | errors per logical operation | per experiment | Peer-reviewed experiments | OBSERVED |
| Coherence time | microseconds | per device | Device characterisation | REPORTED |
| Quantum volume or similar holistic benchmark | benchmark score | per device | Published benchmarks | REPORTED |
| Demonstrations surviving classical challenge | count | per review | Literature review | ESTIMATED |
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| arXiv quant-ph and peer-reviewed journals | Primary experimental and theoretical results | Open access preprints; journal licence per article |
| Metriq benchmark platform (Unitary Foundation) | Community-submitted quantum benchmark results | Open, licence to check |
| Vendor technical documentation and roadmaps | Device specifications and stated targets | Public documents, terms per vendor |
| National academies and agency assessments of quantum computing | Independent assessments of progress and prospects | Public, terms per publisher |
| QED-C reports | Industry consortium analyses of use cases and benchmarks | Public reports, terms to check |
Who decides, and what the evidence serves.
Quantum Technologies prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Research funders and science ministries | How much to invest in quantum computing research and access | Progress summaries; independent assessments |
| Organisations exploring quantum use | Whether a problem is a plausible quantum use case | Use case assessments with classical baselines |
| Security agencies | How progress affects cryptographic migration timelines | Error correction and scale evidence |
Outputs this topic produces
- Progress summaries that separate peer-reviewed results from roadmaps
- Benchmark interpretation guides
- Use case assessments with classical baselines
- Evidence notes for research funders
What experts ask.
The central question is what has been demonstrated, not what has been promised.
- How many qubits does a device have, and how good are they: what are their error rates and coherence times?
- Can errors be corrected faster than they accumulate, and at what cost in physical qubits per logical qubit?
- Which algorithms offer a demonstrated advantage over the best classical methods, and for which problems?
- Are claims of quantum advantage robust to improved classical algorithms?
- Which hardware approaches are likely to scale, and what limits them?
Mechanisms and drivers.
Quantum computers gain their power from interference: algorithms are designed so that wrong answers cancel and right answers reinforce. That power is fragile. Qubits lose their quantum state through interaction with the environment, and every operation introduces some error. Quantum error correction encodes one reliable logical qubit in many physical qubits, but only works if physical error rates are below a threshold, and it multiplies the hardware required.
Known algorithms with large demonstrated speed-ups are few. Factoring and discrete logarithms, which underpin public-key cryptography, are the best-known examples; simulation of quantum systems in chemistry and physics is another. For many optimisation and machine-learning problems, a practical advantage has not been established, and improved classical algorithms have repeatedly narrowed claimed gaps.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Benchmarking of gate fidelity and coherence | Quality of physical qubits | Benchmarks can be chosen to flatter a device |
| Error-correction experiments | Whether logical qubits outperform physical ones | Early demonstrations are small and short-lived |
| Algorithm complexity analysis | Theoretical speed-up and resource estimates | Resource estimates depend on hardware assumptions |
| Classical simulation and verification | Whether results could be reproduced classically | Verification becomes harder as devices grow |
| Peer-reviewed literature versus announcements | What has been independently assessed | Announcements often precede, or replace, peer review |
How it is studied, and what the methods cannot say.
- 01Physics and quantum scienceCharacterising qubit noise · Metrology of quantum clocks · Verifying quantum effectsApplied here
- 02Quantum computing, sensing and communicationComparable benchmarking · Technology readiness assessment · Security implications trackingApplied here
- 03Probability and statisticsFidelity estimation · Testing advantage claims · Analysing patent and investment dataApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
What is a qubit?
What is quantum advantage?
What is fault-tolerant quantum computing?
Why does qubit count alone mislead?
Does the platform predict when large quantum computers will arrive?
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