TY  - JOUR
AB  - Nanoscaled magnetic particle ensembles are promising building blocks for realizing magnon based binary logic. Element-specific real-space monitoring of magnetic resonance modes with sampling rates in the GHz regime is imperative for the experimental verification of future complex magnonic devices. Here we present the observation of different phasic magnetic resonance modes using the element-specific technique of time-resolved scanning transmission x-ray microscopy within a chain of dipolarly coupled Fe3O4 nanoparticles (40-50 nm particle size) inside a single cell of a magnetotactic bacterium Magnetospirillum magnetotacticum. The particles are probed with 25 nm resolution at the Fe L3 x-ray absorption edge in response to a microwave excitation of 4.07 GHz. A plethora of resonance modes is observed within multiple particle segments oscillating in- and out-of-phase, well resembled by micromagnetic simulations.
AU  - Feggeler, T.*
AU  - Lill, J.*
AU  - Günzing, D.*
AU  - Meckenstock, R.U.*
AU  - Spoddig, D.*
AU  - Efremova, M.V.
AU  - Wintz, S.*
AU  - Weigand, M.*
AU  - Zingsem, B.W.*
AU  - Farle, M.*
AU  - Wende, H.*
AU  - Ollefs, K.J.*
AU  - Ohldag, H.*
C1  - 68583
C2  - 53566
CY  - Temple Circus, Temple Way, Bristol Bs1 6be, England
TI  - Spatially-resolved dynamic sampling of different phasic magnetic resonances of nanoparticle ensembles in a magnetotactic bacterium Magnetospirillum magnetotacticum.
JO  - New J. Phys.
VL  - 25
IS  - 4
PB  - Iop Publishing Ltd
PY  - 2023
ER  - 

TY  - JOUR
AB  - Random multistate networks, generalizations of the Boolean Kauffman networks, are generic models for complex systems of interacting agents. Depending on their mean connectivity, these networks exhibit ordered as well as chaotic behavior with a critical boundary separating both regimes. Typically, the nodes of these networks are assigned single discrete states. Here, we describe nodes by fuzzy numbers, i.e. vectors of degree-of-membership (DOM) functions specifying the degree to which the nodes are in each of their discrete states. This allows our models to deal with imprecision and uncertainties. Compatible update rules are constructed by expressing the update rules of the multistate network in terms of Boolean operators and generalizing them to fuzzy logic (FL) operators. The standard choice for these generalizations is the Godel FL, where AND and OR are replaced by the minimum and maximum of two DOMs, respectively. In mean-field approximations we are able to analytically describe the percolation and asymptotic distribution of DOMs in random Godel FL networks. This allows us to characterize the different dynamic regimes of random multistate networks in terms of FL. In a low-dimensional example, we provide explicit computations and validate our mean-field results by showing that they agree well with network simulations.
AU  - Wittmann, D.M.
AU  - Theis, F.J.
C1  - 6261
C2  - 29084
TI  - Dynamic regimes of random fuzzy logic networks.
JO  - New J. Phys.
VL  - 13
PB  - IOP Publishing LTD
PY  - 2011
ER  -