Deep Teleportation: Quantum Simulation of Conscious Report in Attentional Blink

Fuente: arXiv
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Main Author: Sohrabi, Ahmad
Format: Preprint
Published: 2025
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author Sohrabi, Ahmad
author_facet Sohrabi, Ahmad
contents Recent quantum models of cognition have successfully simulated several interesting effects in human experimental data, from vision to reasoning and recently even consciousness. The latter case, consciousness has been a quite challenging phenomenon to model, and most efforts have been through abstract mathematical quantum methods, mainly focused on conceptual issues. Classical (non-quantum) models of consciousness-related experiments exist, but they generally fail to align well with human data. We developed a straightforward quantum model to simulate conscious reporting of seeing or missing competing stimuli within the famous attentional blink paradigm. In an attentional blink task, a target stimulus (T2) that appears after a previous one (T1) can be consciously reported if the delay between presenting them is short enough (called lag 1), otherwise it can be rendered invisible during the so-called refractory period of attention (lags 2 to 6 and even longer). For modeling this phenomenon, we employed a three-qubit entanglement ansatz circuit in the form of a deep teleportation channel instead of the well-known EPR channel. While reporting the competing stimuli was supposed to be the classical measurement outcomes, the effect of distractor stimuli (i.e., masks, if any) was encoded simply as random angle rotations. The simulation outcome for different states was measured, and the classical outcome probabilities were further used as inputs to a simple linear neural network. The result revealed a non-linear, alternating state pattern that closely mirrors human responses in conscious stimuli reporting. The main result was a successful simulation of Lag 1 sparing, lag 7 divergence, and masking effect through probabilistic outcome of measurement in different conditions.
format Preprint
id arxiv_https___arxiv_org_abs_2512_18585
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Deep Teleportation: Quantum Simulation of Conscious Report in Attentional Blink
Sohrabi, Ahmad
Neurons and Cognition
Recent quantum models of cognition have successfully simulated several interesting effects in human experimental data, from vision to reasoning and recently even consciousness. The latter case, consciousness has been a quite challenging phenomenon to model, and most efforts have been through abstract mathematical quantum methods, mainly focused on conceptual issues. Classical (non-quantum) models of consciousness-related experiments exist, but they generally fail to align well with human data. We developed a straightforward quantum model to simulate conscious reporting of seeing or missing competing stimuli within the famous attentional blink paradigm. In an attentional blink task, a target stimulus (T2) that appears after a previous one (T1) can be consciously reported if the delay between presenting them is short enough (called lag 1), otherwise it can be rendered invisible during the so-called refractory period of attention (lags 2 to 6 and even longer). For modeling this phenomenon, we employed a three-qubit entanglement ansatz circuit in the form of a deep teleportation channel instead of the well-known EPR channel. While reporting the competing stimuli was supposed to be the classical measurement outcomes, the effect of distractor stimuli (i.e., masks, if any) was encoded simply as random angle rotations. The simulation outcome for different states was measured, and the classical outcome probabilities were further used as inputs to a simple linear neural network. The result revealed a non-linear, alternating state pattern that closely mirrors human responses in conscious stimuli reporting. The main result was a successful simulation of Lag 1 sparing, lag 7 divergence, and masking effect through probabilistic outcome of measurement in different conditions.
title Deep Teleportation: Quantum Simulation of Conscious Report in Attentional Blink
topic Neurons and Cognition
url https://arxiv.org/abs/2512.18585