7 citations · 10 across the 13 of their papers we have counts for
13 papers
Ternary-Valued Finite-Difference Time-Domain Method: Asymptotic Agreement with the Yee Scheme Through Noise-Shaped Quantisation
Ivan S. Maksymov
I show that finite-difference time-domain (FDTD) dynamics can be reproduced using field variables restricted to the ternary alphabet . The integration is carried out by…
Cognition in Superposition: Quantum Models in AI, Finance, Defence, Gaming and Collective Behaviour
Ivan S. Maksymov
At first glance, quantum mechanics and behavioural science seem worlds apart -- one rooted in equations and particles, the other in thoughts and choices. Yet, emerging research rev…
Resonant-Tunnelling Diode Reservoir Computing System for Image Recognition
A. H. Abbas, Hend Abdel-Ghani, Ivan S. Maksymov
As artificial intelligence continues to push into real-time, edge-based and resource-constrained environments, there is an urgent need for novel, hardware-efficient computational m…
Quantum-Cognitive Tunnelling Neural Networks for Military-Civilian Vehicle Classification and Sentiment Analysis
Milan Maksimovic, Anna Bohdanets, Immaculate Motsi-Omoijiade +2
Prior work has demonstrated that incorporating well-known quantum tunnelling (QT) probability into neural network models effectively captures important nuances of human perception,…
Reservoir Computing with a Single Oscillating Gas Bubble: Emphasizing the Chaotic Regime
Hend Abdel-Ghani, A. H. Abbas, Ivan S. Maksymov
The rising computational and energy demands of artificial intelligence systems urge the exploration of alternative software and hardware solutions that exploit physical effects for…
Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations
Milan Maksimovic, Ivan S. Maksymov
Modern machine learning (ML) systems excel in recognising and classifying images with remarkable accuracy. However, like many computer software systems, they can fail by generating…
Quantum-tunnelling deep neural network for optical illusion recognition
Ivan S. Maksymov
The discovery of the quantum tunnelling (QT) effect -- the transmission of particles through a high potential barrier -- was one of the most impressive achievements of quantum mech…
Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective
A. H. Abbas, Hend Abdel-Ghani, Ivan S. Maksymov
Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the…
Quantum Mechanics of Human Perception, Behaviour and Decision-Making: A Do-It-Yourself Model Kit for Modelling Optical Illusions and Opinion Formation in Social Networks
Ivan S. Maksymov
On the surface, behavioural science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely…
Reservoir Computing Using Measurement-Controlled Quantum Dynamics
A. H. Abbas, Ivan S. Maksymov
Physical reservoir computing (RC) is a machine learning algorithm that employs the dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this paper,…
Magnetism-Inspired Quantum-Mechanical Model of Gender Fluidity
Ivan S. Maksymov
Quantum-mechanical models of human cognition, opinion formation and decision-making have changed the way we understand and predict human behaviour in many practical situations, inc…
Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data
Ivan S. Maksymov
Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versat…
Continuous spatial field confocal thermometry using lanthanide doped tellurite glass
D. Stavrevski, E. Schartner, I. S. Maksymov +3
Quantifying temperature variations at the micron scale can provide new opportunities in optical sensing. In this paper, we present a novel approach using the temperature-dependent…