Glossary

quantum-like model

A computational model that represents normalized input sequences with quantum states and operations. In this project, a model encodes one qubit per input dimension over a fixed number of samples, applies an optional query transformation, and obtains an output by measuring the resulting circuit. The term describes the model’s mathematical and computational structure; it does not imply that the surrounding robot or simulator is a quantum physical system.

qUnit

A Redis-connected processing unit implemented by qrobot_qunits.QUnit. It periodically reads normalized values from upstream units, encodes them with a quantum-like model over a temporal window, applies a query, and publishes a normalized burst. A qUnit can serve a perceptual or cognitive role depending on its inputs and purpose in a qBrain.

qBrain

A network of sensorial units, qUnits, and actuators connected through their Redis inputs and outputs. A qBrain is an architectural concept rather than a single Python class: the application constructs and connects its constituent units for a particular robot or research scenario.

burst

A rule that converts a qUnit’s decoded measurement state into a normalized scalar output. The supplied qrobot.bursts.ZeroBurst and qrobot.bursts.OneBurst strategies express how strongly the measured bit string resembles the all-zero or all-one state, respectively.

query

A normalized target vector, with one value per model dimension, used to change the measurement basis after inputs have been encoded. An input matching the query is mapped toward the all-zero state before measurement. The selected burst strategy determines how that measured state becomes the qUnit output.

temporal window

The sequence of samples accumulated by a quantum-like model before it is queried, measured, and cleared. Its length is the model’s tau value; for a qUnit sampled every sampling_period seconds, the nominal window duration is tau * sampling_period seconds.

sensorial unit

A qrobot_qunits.SensorialUnit that periodically publishes one normalized sensor reading to Redis. It forms an input boundary between a sensor or simulated observation and the qBrain.

perceptual unit

A qUnit whose upstream inputs are sensorial units and whose burst represents a detected feature or perceptual condition over a temporal window. This is a functional role in a qBrain, not a separate Python class.

cognitive unit

A qUnit that integrates outputs from perceptual or other qUnits to represent a higher-level condition or decision. This is a functional role in a qBrain, not a separate Python class.

actuator

A qrobot_qunits.ActuatorUnit that reads the latest bursts from one or more qUnits, combines them into a normalized value, applies its activation rule, and publishes the result for robot or simulator behavior to consume. Actuators translate qBrain outputs into control signals; they do not directly model the mechanics of a physical device.