Two PhD positions in theoretical and computational physics [closed]
Looking for new challenges in theoretical and computational physics that are closely linked to the latest experimental developments? Interested in applying machine learning to tackle so far unsolvable problems in physics? We have two PhD positions focused on theory and simulations of ultrafast dynamics of magnetism far out of equilibrium. Our main research interest is to understand the dynamics of magnetism at the shortest length (nm) and time scales (fs), for which existing methods fail to give an adequate description. We exploit and develop both phenomenological theory and new computational methods inspired from machine learning. We apply these methods to access otherwise inaccessible regimes of magnetism and provide explanations and predictions for state-of-the-art time-resolved optical and X-ray experiments.
IRP voucher towards disruptively green neuromorphic computational and datascience
We were awarded a voucher project to develop towards disruptively green computational and data science! Many thanks to our collaborators Sacha Caron (RU-IMAPP), Johan Kwisthout (RU-Donders), Theo Rasing (RU-IMM), Hans Hilgenkamp (Utwente), Sagar Dolas (SURF) and Heike Riel (IBM Zurich).
Preprint on Brownian Reservoir Computing with Skyrmions
The first preprint of our collaboration with the group of Prof. Kläui (Mainz, Germany) is online! This features the a demonstration of reservoir computing, one of the key paradigms in neuromorphic computing, using Brownian skyrmions.
Publication in Nano Letters
As a follow-up on our stimulating collaborative work on ultrafast skyrmion nucleation, we where invited by our colleagues in Berlin to support this nice study on "Deterministic Generation and Guided Motion of Magnetic Skyrmions by Focused He+-Ion Irradiation", which was published in Nano Letters. Great applause for our Rein Liefferink, who conducts this research as his Master thesis and already now has his first publication!
Publication in Applied Physics Letters
Our work on training and pattern recognition with optomagnetic neural networks is published in Applied Physics Letters.
Discovery of supermagnonic propagation in antiferromagnets
Like light waves, magnetic waves move through materials at a fixed maximum velocity. However, at the smallest possible length scale (nanometres) and the shortest possible time scale (femtoseconds), magnetism behaves differently. With simulations, we have discovered that magnetic waves with very short wavelengths can propagate up to 40% faster than previously thought. This supermagnonic propagation offers opportunities for even faster, smaller and more energy-efficient ways of data processing in future computers. The research is published in Physical Review Letters.
Press release available from RU.
Updated preprint online
We greatly extended our study of ultrafast entanglement dynamics in Heisenberg antiferromagnets. Check out our most recent preprint here.
New preprint online
A new preprint coauthored with Wojciech Rzadkowski and Misha Lemeshko from IST Austria is now online.
We are hiring: researcher neuromorphic scientific computing [FILLED]
Are you interested in a project at the interface of physics and machine learning? Do you thrive for societal impact of your research? We have a project (3-6 months) for you! Neuromorphic computing is a way to do computations with neural networks that mimic the architecture of the human brain. This project is a collaboration between Radboud University, IBM and SURF is aimed to benchmark the energy-efficiency of state-of-the-art neuromorphic hardware for concrete computational physics problems.
Interested? Send me an email.
GreenIT voucher for energy-efficient scientific computing
We were awarded a GreenIT voucher project to benchmark new neuromorphic computing hardware for more energy-efficient scientific computing! Many thanks to our collaborators Johan Kwisthout (RU-FSW, DCC), Sagar Dolas (SURF), Heike Riel (IBM Zurich), Theo Rasing (RU-IMM) and Sacha Caron (RU-IMAPP)
Alumni lecture "no energy for the computer of the future?"
I was asked to give an online lecture for physics-alumni on the energy cost of computing. In this lecture, the large contrast between the theoretically attainable and actual energy consumption of state-of-the-art computers are outlined. Reaching computing at the boundaries set be these laws is currently impossible - the knowledge to do so simply does not exist. Some of the most recent efforts to push the border of knowledge further are then discussed, focusing on fundamental research on magnetic materials. This research may ultimately lead to the smallest, fastest and most energy-efficient computers of the future.
The lecture (in Dutch) can be viewed online here.
New preprint online
New shortcut enables faster creation of spin pattern in magnet
In a collaborative effort led by groups at the Max Born Institute (Berlin, Germany) and at MIT (Boston, USA), we have discovered a much faster approach to create a pattern of spins in a magnet. This 'shortcut' may open a new chapter in topology research. This discovery relies on the observation of a transient topological fluctuating state, in which topological spin patterns, i.e. skyrmions and antiskyrmions, rapidly appear and disappear. Interestingly, this discovery also offers an additional method to achieve more efficient magnetic data storage, that is not only fast but also small. The research was published in Nature Materials.
Snapshot of a simulation of the topological fluctuation phase, where (anti)skyrmions are highlighted with coloured spheres. Picture by Bastian Pfau.
New preprint online
Laser-driven quantum magnonics
In a joint experimental-theoretical effort, published as Editor's Suggestion in Physical Review B, we study the dynamics of antiferromagnetic magnons triggered by ultrashort laser pulses. We demonstrate that the observed dynamics cannot be captured by the classical Landau-Lifshitz approach and develop a new quantum description in terms of magnon pair operators and coherent states. Interestingly, this analysis shows that the laser-triggered dynamics is a manifestation of magnon entanglement of dominantly nanometer magnons that oscillate with frequencies as high as 22 THz.
Picture by Helen Gomonay, illustrating the excitation of magnon pairs in antiferromagnets by optical perturbation of exchange interactions.
Simulating ultrafast quantum magnetism with machine learning
In a paper in the open access journal SciPost physics, we assess the efficiency of the recently proposed neural quantum states for studying the static properties and quantum spin dynamics in the paradigmatic two-dimensional Heisenberg model. For static properties we find close agreement with numerically exact Quantum Monte Carlo results in the thermodynamical limit. For dynamics and small systems, we find excellent agreement with exact diagonalization, while for systems up to N=256 spins close consistency with interacting spin-wave theory is obtained. In all cases the accuracy converges fast with the number of neural network parameters. This suggests great potential to investigate the quantum many-body dynamics of large scale spin systems relevant for the description of magnetic materials strongly out of equilibrium.
Picture by Ashim Chakravarty illustrating a neural network representation of the quantum many-body wave function.
Open source code ULTRAFAST released
An open source version of our implementation of the neural quantum states for the two-dimensional quantum spin systems can be found here. It is written in the easy-to-use yet fast Julia language and enables simulating dynamics of much larger spin systems than feasible before.
Ultrafast magnets that can learn
The power consumption of information storage and processing around the world is increasing. This creates a high demand for new technologies that could lead to more energy-efficient computers. The human brain can solve certain problems like pattern recognition with only 20W, while a supercomputer would need 10MW for the same task. Therefore, many researchers world-wide now try to realize brain-inspired computing principle in materials. In a new study, we experimentally demonstrate that it is possible to create artificial synapses by using ultrashort laser pulses in combination with materials that are nowadays used in magnetic hard disc drives. Moreover, we show that by combining such synapses, supervised learning can be achieved. These results suggest that there is high potential for realizing artificial neural networks using optically controlled magnetization in technologically relevant materials, which can learn not only fast but also energy-efficient.
Multi-orbital effects on the ultrafast control of exchange interactions
Optical control of exchange interactions is a promising way to achieve ultrafast control of magnetic order. However, theoretical modeling is so far restricted to models that ignore the role of the orbital degrees of freedom. In this paper by my PhD student Marion Barbeau, published in the new open access journal Sci Post physics, analytical methods are developed and applied that show that besides the already known control of Heisenberg exchange interaction, an additional biquadratic exchange interaction can be enhanced, reduced and even change sign depending on the electric field. Moreover, a qualitatively new spin-charge coupling phenomenon is found, which enables coherent transfer between spin and charge degrees of freedom of doubly ionized states.
Picture by Marion Barbeau, illustrating the virtual hopping processes in single (left) and two-orbital (right) Hubbard models. We discovered that coherent transfer between the lowest spin states and highest double occupied charge states is feasible.
Quantum many-body dynamics of the Einstein–de Haas effect
Over a century ago Einstein and de Haas and Barnett demonstrated that changing magnetization causes mechanical rotation, and vice versa. However, understanding how and how fast transfer of angular momentum can occur is still unknown and fundamental for research on a wide variety of magnetic systems today. Microscopic modeling of the Einstein and de Haas effect is highly challenging since it requires coupling of practically an infinite amount of quantum angular momenta. In a recent paper we demonstrated a new way to solve this problem by reformulating it in terms of the recently discovered angulon quasiparticle, which results in a rotationally invariant quantum many-body theory. Surprisingly, we find that that nonperturbative effects take place even if the electron-phonon coupling is weak and can give rise to angular momentum transfer on femtosecond timescales.
Illustration by Misha Lemeshko of the angulon quasiparticle in solid-state systems. A localized magnetic impurity exchanging angular momentum with lattice exci- tations can be described as the angulon quasiparticle, characterized by total (electrons+phonons) angular momentum.
Manipulating magnetism by ultrafast control of the exchange interaction
In recent years, the optical control of exchange interactions has emerged as an exciting new direction in the study of the ultrafast optical control of magnetic order. In this article, we review recent theoretical works on antiferromagnetic systems, devoted to (i) simulating the ultrafast control of exchange interactions, (ii) modeling the strongly nonequilibrium response of the magnetic order and (iii) the relation with relevant experimental works developed in parallel. In addition to the excitation of spin precession, we discuss examples of rapid cooling and the control of ultrafast coherent longitudinal spin dynamics in response to femtosecond optically induced perturbations of exchange interactions. These elucidate the potential for exploiting the control of exchange interactions to find new scenarios for both faster and more energy-efficient manipulation of magnetism.
Condensed matter physics inspired by the brain
May 2017 [NO LONGER AVAILABLE]
This project is part of a new research direction that we aim to develop based on our extensive experience for multi-scale modelling op laser-induced nonequilibrium dynamics of magnetism. On the one hand, it aims to predict how solid state magnetic materials can be dynamically manipulated to exhibit learning behavior, a property usually associated with the brain. On the other hand, it aims to exploit neural principles to describe the dynamics of quantum spin systems more efficiently on classical computers using concepts from machine learning. Basing on methodologies from condensed matter theory, both approaches will be developed in close connection with theoretical neuroscience and experimental condensed matter physicists, ultimately aimed at enabling information processing concepts that operate at orders of magnitude lower energy cost than existing technology.
New route for switching magnets using lightSeptember 2015
In a publication in Nature Communications, we have shown experimentally that a strong pulse of light can have a direct effect on the strong quantum mechanical 'exchange interaction'. The results are supported by theoretical calculations and suggest that reversing the poles of magnets must be possible without using heating or a magnetic field.
Picture by D.V. Afanasiev. Press release available from Radboud University.
Turning back time and more efficient switching of magnets with lightMarch 2015
Picture © MPSD J.M. Harms. Press releases available from Max Planck Institute for the Structure and Dynamics of Matter (English) and Radboud University (Dutch).
Manipulating magnetic forces with lightJuly 2014
The magnetic forces in materials like iron can be rapidly manipulated with light. We have demonstrated this theoretically in a publication in Physical Review Letters by combining two recent major methodological developments. Rapid and effective manipulation of magnetic states is of high fundamental and technological value. For example, it could be used for the development of faster hard disks.
Magnets are chaotic – and fast – at the very smallest scaleJanuary 2013
Using a new type of camera that makes extremely fast snapshots with an extremely high resolution, it is now possible to observe the behaviour of magnetic materials at the nanoscale. This behaviour is more chaotic than previously thought, as we reported with an international team of scientists in Nature Materials.
Press release available from Radboud University.
Magnetism on the timescale of the exchange interaction - explanations and predictionsOctober 2012
You will find my PhD thesis here.
Scientists 'record' magnetic breakthroughFebruary 2012
With an international team of scientists we have demonstrated a revolutionary new way of magnetic recording without the use of a magnetic field. Instead we could record information using only an ultra short heat pulse – a previously unimaginable scenario. As reported in Nature Communications, this discovery may not only allow information to be processed hundreds of times faster than by current hard drive technology, but it can be more energy-efficient too.
Press release available from the University of York.
Breakthrough in the understanding of magnetismJanuary 2012
A new theory on how magnetism actually works on short time scales opens up possibilities for whole new experiments to rapidly store data. The theory is published in Physical Review Letters. We are able to explain recent highly counter-intuitive experimental results on laser-induced magnetic switching and provide predictions for new and revolutionary ways of controlling magnetism.
Press release available from Radboud University (in Dutch).