Model atlas#
A block diagram for every model in Quantum Mind (48 diagrams): what goes in, what happens inside, what comes out, and which classical baselines it is compared with. Each entry links to the API, a tutorial where there is one, and a reference.
flowchart LR
accTitle: How the parts of Quantum Mind fit together
accDescr: Data from sensors and people feed the core fitting tools, the quantum-like families, the COBRA belief filter and perception, which all feed the robot decision layer; the families also feed circuits, back ends and the viewer; classical baselines are compared everywhere.
D[("data · sensors · people")]:::hum --> C["core: fit · compare"]:::op
C --> QL["quantum-like families"]:::op --> R["robot decision layer"]:::out
C --> BF["COBRA belief filter"]:::op --> R
P["perception and fusion"]:::op --> R
E["environments with simulated people"]:::op --> R
QL --> CI["circuits · back ends · viewer"]:::in
B["classical baselines everywhere"]:::base -.-> QL & BF & P
classDef in fill:#0b2a4a,stroke:#79c0ff,color:#e6edf3
classDef op fill:#2a1b3d,stroke:#d2a8ff,color:#e6edf3
classDef out fill:#0f2e1a,stroke:#7ee787,color:#e6edf3
classDef hum fill:#3d1414,stroke:#ff7b72,color:#e6edf3
classDef base fill:#262626,stroke:#8b949e,color:#e6edf3,stroke-dasharray:4 3
Where each model comes from#
Every entry carries one of four labels. Most models are published by other researchers and implemented here from their papers (the reference is on each entry). Quantum Mind’s own contributions are the COBRA belief filter, the robot decision layer, the environments, the circuits for the quantum-like families, and the tools that give every published people model uncertainty, per-person updating and informative-question selection.
Label |
Entries |
Meaning |
|---|---|---|
Unique to Quantum Mind |
15 |
designed in this library; it builds on the methods cited with it |
Published model, extended |
12 |
implements the cited model as published; Quantum Mind adds the capabilities listed |
Published method |
13 |
implements the cited method as published |
Software tool |
8 |
infrastructure rather than a model |
Every entry also carries a category, so the quantum-like models of people and the quantum circuits can be told apart; quantum-like models need no quantum computer.
Category |
Entries |
Meaning |
|---|---|---|
Quantum-like |
15 |
quantum probability used to model people; runs on an ordinary computer |
Quantum computing |
6 |
quantum circuits; run on the simulator or sent to quantum hardware |
Classical |
19 |
classical statistics, decision theory or baselines |
Mixed |
8 |
combines parts from more than one of these categories |
Unique to Quantum Mind: Uncertainty, online updating and informative questions, Context-rotated belief filter (COBRA), Online belief, Human-model ensemble, Ask or act, Intent resolution, Meta-calibrated gate, Question planner, Answer models, Trust-aware hand-over, Cue incompatibility, Clarification environment, Trust hand-over environment, Trust-aware task allocation, Circuits for the quantum-like families.
Published model, extended: Question order: quantum-like model, Question order: classical baselines, Quantum-like Bayesian network, Belief dynamics: quantum and Markov walks, Trust belief (open system), Bistable perception (quantum Zeno), Robot problems as QUBOs, Multi-rate Kalman dead reckoning, Conformal prediction sets, Personalised human models, Fusion rules, Dwell-time baselines.
The original paper of every model, for citing, is listed on references by model.
Pages#
The building blocks every model uses: linear algebra for states and projectors, the model base class, maximum-likelihood fitting, model comparison and recovery studies. (6 diagrams)
Models of human judgement, decision, memory and trust written in quantum probability, each with the classical baselines it must beat. (6 diagrams)
A robot’s belief about a person as a density matrix whose measurement basis is rotated by the previous sensor frame, so what a reading means depends on what came before it. (4 diagrams)
Robot problems as binary optimisation, the classical baselines a quantum result must be reported against, and a thin adapter to Qiskit’s QAOA. (4 diagrams)
Quantum limits, accelerometer models and a multi-rate Kalman filter that fuses a slow, almost drift-free quantum sensor with a fast, drifting classical one. (3 diagrams)
Components that turn models of people and uncertain perception into decisions: ask or act, calibrate, route, plan questions, personalise and hand over. (13 diagrams)
Adapters that turn perception outputs into likelihoods, three fusion rules, and the bistable-perception models. (4 diagrams)
Gymnasium environments in which a simulated person answers questions with order effects or trusts the robot according to the trust qubit. (2 diagrams)
The state-vector simulator, circuits for the quantum-like families, back ends, the allocation container and the Bloch-sphere viewer. (6 diagrams)