Time: Wednesday, October 10th, 14:00
Speaker: Laura HEYDERMAN, ETH Zurich
Artificial spin systems [1] have received much attention in recent years, following the creation of arrays of dipolar-coupled nanomagnets with frustrated geometries analogous to that of the rare earth titanate pyrochlores [2], which are referred to as spin ices due to a geometric frustration that leads to a spin arrangement analogous to the proton ordering in water ice [3]. Such arrays of nanomagnets are appropriately named artificial spin ice [4] where single-domain elongated magnets, which have Ising-like moments pointing along one of two directions, are commonly placed on the sites of a square or kagome lattice. At every vertex where the magnets meet, there is a characteristic low energy configuration where the so-called ice rule is obeyed. Going beyond these basic designs, it is possible to devise artificial spin systems with various intricate motifs that display behaviour that is characteristic of a particular geometry.
In this tutorial, I will introduce this topic with the aim to provide the link between artificial spin ice and computation by covering a number of possibilities for control. For example, the creation and separation of emergent magnetic monopoles and their associated Dirac strings on application of a magnetic field can be controlled by modifying the shape of particular nanomagnets in the array [5]. Such modifications to individual nanomagnets can also be used to control the chirality of artificial kagome spin ice building blocks consisting of a small number of hexagonal rings of magnets [6]. Indeed, chirality control is a recurring theme, with a further example being the control of the dynamic chirality, which can be achieved in the so-called chiral ice [7], where the stray field energy associated with the magnetic configurations at the edges of the array defines the sense of rotation of the average magnetisation on thermal relaxation. In addition, the chirality of domain walls will determine how they pass through a connected artificial kagome spin ice [8].
I will address other possibilities to control and access magnetic information in artificial spin ice including further geometries, temperature, local magnetic and electric fields, fast dynamics, as well as methods for computation [9].
[2] R.F. Wang et al. Nature 439, 303 (2006)
[3] M.J. Harris et al. Phys. Rev. Letts. 79, 2554 (1997)
[4] C. Nisoli, R. Moessner and P. Schiffer, Rev. Mod. Phys. 85, 1473 (2013)
[5] E. Mengotti et al. Nat. Phys. 7, 68 (2011); R.V. Hügli et al. Phil. Trans. Roy. Soc. A 370, 5767 (2012)
[6] R.V. Chopdekar et al. New Journal of Physics 15, 125033 (2013)
[7] S. Gliga et al. Nat. Mater. 16, 1106 (2017)
[8] K. Zeissler et al. Sci. Rep. 3, 1252 (2013); A. Pushp et al. Nat. Phys. 9, 505 (2013)
[9] H. Arava et al. Nanotechnology 29, 265205 (2018); P. Gypens et al. Phys. Rev. Appl. 9, 034004 (2018)