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)
arXiv preprint PDF

Skier and loop the loop with friction

Field: Classical Mechanics
Main points: Developed analytical solutions to the extension of two ‘classic’ problems in classical mechanics.

D. Kufel, A. Sokal (2022)
American Journal of Physics 90, 573. PDF

Alternative quantisation condition for wavepacket dynamics in a hyperbolic double well

Field: Atomic Physics
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)
Journal of Physics A: Mathematical and Theoretical 54, 035304. PDF

Online Learning and matching for resource allocation problems

Field: Machine Learning
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)
SIAM Undergraduate Research Online Journal vol. 13. PDF

Analytical modelling of temperature effects on AMPA-type synapse

Field: Computational Neuroscience
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


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