Quantum algorithms and benchmarks in plain language: what each family of algorithms does, which problems it addresses, how mature it is, which hardware platforms fit it and what it takes to run it, from a laptop simulation to a fault-tolerant machine.
22 algorithm families, 29 further algorithms from the Zoo index, 17 benchmarks, 11 resource estimates with 25 figures, each quoted with the assumptions and the publication it comes from.
Educational overview compiled by the portal from primary sources: papers (arXiv abstract pages and open-access articles), benchmark repositories and official pages, each read on the date shown. Resource estimates are quoted with the assumptions their authors state and change as methods improve; they are not forecasts, procurement guidance or investment advice. Summaries are in the portal’s own words. Owner-reviewed for demonstration, 28 October 2026. Compiled 2026-10-27.
6 algorithm families shown; 0 further algorithms shown.
A variational method for combinatorial optimisation, such as finding a large cut in a graph or scheduling, with circuits that alternate between the cost function and a mixing step.
Platforms: Superconducting qubits, Neutral atoms
0 sourced resource estimates · 1 documented demonstration
Details, requirements and sources Quantum approximate optimisation algorithm (QAOA)
Arrays of neutral atoms excited to Rydberg states cannot excite two close neighbours at once, which maps naturally onto the maximum independent set problem on unit-disk graphs.
Platforms: Neutral atoms, Analogue quantum simulators
0 sourced resource estimates · 1 documented demonstration
Parameterised quantum circuits trained like neural networks for classification, regression or generative modelling, often as one layer of a hybrid classical model.
Platforms: Neutral atoms, Superconducting qubits
0 sourced resource estimates · 1 documented demonstration
Details, requirements and sources Variational quantum neural networks
A controllable quantum system, such as atoms in optical tweezers or lattices or a chain of ions, is engineered to behave like a model of magnetism or of electrons in a solid, and is measured directly.
Platforms: Neutral atoms, Trapped ions, Analogue quantum simulators
0 sourced resource estimates · 4 documented demonstrations
Details, requirements and sources Analogue quantum simulation of spin and Hubbard models
The leading quantum error-correcting code for chips with nearest-neighbour connections: many physical qubits on a 2D grid encode one logical qubit, and repeated measurements detect errors that a classical decoder corrects in real time.
Platforms: Superconducting qubits, Neutral atoms
0 sourced resource estimates · 1 documented demonstration
Details, requirements and sources Surface code error correction
Codes that encode several logical qubits in one block with far fewer physical qubits than the surface code, at the price of more complex connections between qubits.
Platforms: Neutral atoms
1 sourced resource estimate · 1 documented demonstration
Details, requirements and sources Quantum low-density parity-check (qLDPC) codes
A dash means that no source for that platform was verified for this release, not that it cannot work. Any marks families that are platform-independent.
| Algorithm family | Superconducting qubits | Trapped ions | Neutral atoms | Analogue quantum simulators |
|---|---|---|---|---|
| Quantum approximate optimisation algorithm (QAOA) | Fits | Not listed | Fits | Not listed |
| Analogue optimisation on Rydberg atom arrays (maximum independent set) | Not listed | Not listed | Fits | Fits |
| Variational quantum neural networks | Fits | Not listed | Fits | Not listed |
| Analogue quantum simulation of spin and Hubbard models | Not listed | Fits | Fits | Fits |
| Surface code error correction | Fits | Not listed | Fits | Not listed |
| Quantum low-density parity-check (qLDPC) codes | Not listed | Not listed | Fits | Not listed |
Further notable quantum algorithms, found through the Quantum Algorithm Zoo and each checked against its original paper. They are mostly theoretical and need fault-tolerant machines; no resource estimate is given unless cited. Summaries and speedups are in the portal’s own words from the original papers; the Zoo category and speedup are given as the Zoo states them.
Index: the Quantum Algorithm Zoo by Stephen P. Jordan, last updated 2026-09-10, checked 2026-10-23. The portal links to it and copies no description from it. Browse the full Quantum Algorithm Zoo (external site)
These algorithms name no hardware platform, so the platform filter hides them.
Olivier Ezratty, Understanding Quantum Technologies (CC BY-NC-ND 4.0). Links only; no text of the book is reproduced on this portal.