A recurrent quantum neural network model to describe eye tracking of moving targets
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A quantum model of visual pursuit dramatically outperforms comparable classical algorithms.
“This vague conjecture is realized in an impressive concrete form in a fascinating quantum model of visual pursuit—how our brain moves our eyes to follow a moving visual target (Behera et al. 2005). The quantum model dramatically outperforms comparable classical algorithms.”
From A quantum microtubule substrate of consciousness is experimentally supported and solves the binding and epiphenomenalism problems (2025) · cites this paper as Behera et al. 2005
The Simulation Results (pp. 3–4) report substantially lower tracking error for the RQNN than for a Kalman filter when tracking a fixed target in Gaussian noise. The Conclusion (p. 5) calls its stochastic filtering of a DC signal 1000 times more accurate. This supports a dramatic advantage in that comparison, but not the broader claim that the model outperforms comparable classical algorithms generally, including for moving-target pursuit. (LLM, conf=0.85)
Experimental — accuracy not yet measuredUnlike classical algorithms, the quantum model of visual pursuit predicts occasionally discontinuous jumps (saccades) in eye position, as is observed experimentally.
“Moreover, unlike the classical algorithms, the quantum model predicts occasionally discontinuous jumps (saccades) in eye position, as is observed experimentally.”
From A quantum microtubule substrate of consciousness is experimentally supported and solves the binding and epiphenomenalism problems (2025) · cites this paper as Behera et al. 2005
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- Authors
- Behera, L., Kar, I., & Elitzur, A. C.
- Affiliations
- Indian Institute of Technology Kanpur (IN)
- Corresponding author
- Elitzur, Avshalom C.
- Venue
- Foundations of Physics Letters
- Published
- 2005-07-25
- Volume
- 18
- Issue
- 4
- Pages
- 357-370
- ISSN
- 0894-9875 (ISSN-L)
- 1572-9524
- OpenAlex
- W1812431251
- Cited by
- 48
- References
- 32
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 1 · 2022: 1 · 2021: 1 · 2020: 4 · 2019: 3 · 2018: 2 · 2017: 1 · 2016: 2 · 2015: 3 · 2014: 2 · 2013: 2 · 2012: 1
- FWCI
- 0.82
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Foundations of Physics Letters (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Keywords
- eye tracking, moving targets, nonlinear Schrödinger equation, wave packets, saccades, smooth pursuit eye movements, Kalman filter comparison
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