Publications
Approximately-symmetric neural networks for quantum spin liquids
Field: Quantum Many-Body Physics, AI
Main points: Constructed tailor-made, scalable and interpretable neural network architectures for studying quantum spin liquid problems.
D. Kufel, J. Kemp, S. Linsel, C. Laumann, N. Yao (2024) Field: Classical Mechanics
arXiv preprint PDF Skier and loop the loop with friction
Main points: Developed analytical solutions to the extension of two ‘classic’ problems in classical mechanics.
D. Kufel, A. Sokal (2022) Field: Atomic Physics
American Journal of Physics 90, 573. PDF Alternative quantisation condition for wavepacket dynamics in a hyperbolic double well
Main points: Proposed a new analytical way of finding allowed energies in the class of hyperbolic-double well potentials by connecting it to a problem of finding roots of some polynomial. Applied this approach to understanding the role of non-adiabatic effects during enhanced ionization.
D. Kufel, H. Chomet, C. Faria (2021) Field: Machine Learning
Journal of Physics A: Mathematical and Theoretical 54, 035304. PDF Online Learning and matching for resource allocation problems
Main points: Devised, provided performance guarantees, and implemented algorithms integrating dual problems in convex optimization with a subclass of reinforcement learning techniques. Applied these algorithms to the traffic-shaping problem.
A. Boskovic, Q. Chen, D. Kufel, Z. Zhou (2019) Field: Computational Neuroscience
SIAM Undergraduate Research Online Journal vol. 13. PDF Analytical modelling of temperature effects on AMPA-type synapse
Main Points: Used ODE-based modelling for understanding temperature effects on AMPA-type synapses in brain. Simplified the ODEs using some physically-motivated assumptions and shown how the obtained analytical solution faithfully reproduces the results of biological experiments.
D. Kufel, G. Wojcik (2018)
Journal of Computational Neuroscience 44, 379-391. PDF