Spin Dynamics Associated with Local Magnons in FeF2:Mn

Abstract

It has long been recognized [1] that substitutional impurities in solids can be invaluable as local probes on an atomic scale. This is certainly the case in insulating magnets — ferro-, antiferro- and paramagnetic — where there are readily available resonant experimental techniques highly specific to individual chemical species or even to the local environment of a given atom. On the theoretical side initial interest was focused on isolated impurities and the powerful techniques available to handle localized perturbations in systems with crystalline translational symmetry, but there has also been increasing study of macroscopically disordered systems, with finite concentrations of impurities. Perhaps the remarkable thing is that after two decades or more of study there are still interesting things to be learned, even about the simplest prototype insulating magnets. There are of course, the active and exciting investigations associated with the random field problem, an example of macroscopic disorder, which has been discussed earlier in this workshop. But what we will present here is a detailed picture of a remarkable variety of phenomena in a rather more conventional — or, at least familiar — system, FeF2:Mn, which has recently been the subject of intensive experimental and theoretical investigation. This picture has evolved over a period of years to give what we believe to be a single consistent and reliable description of a very interesting system. Though perhaps not absolutely complete, it is certainly nearly so, at least in the independent impurity (low concentration) limit. Though there may remain some surprises in such systems, we would expect that exciting future physics in this general area is likely to be found in the exploration of alloys and other macroscopically disordered magnets.KeywordsLocal ModeImpurity ModeSingle ImpurityHost ModeLocal Mode FrequencyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.