Decoding the conductance of disordered nanostructures: a quantum inverse problem

Obtaining conductance spectra for a concentration of disordered impurities distributed over a nanoscale device with sensing capabilities is a well-defined problem. However, to do this inversely, i.e., extracting information about the scatters from the conductance spectrum alone, is not an easy task. In the presence of impurities, even advanced techniques of inversion can become particularly challenging. This article extends the applicability of a methodology we proposed capable of extracting composition information about a nanoscale sensing device using the conductance spectrum. The inversion tool decodes the conductance spectrum to yield the concentration and nature of the disorders responsible for conductance fluctuations in the spectra. We present the method for simple one-dimensional systems like an electron gas with randomly distributed delta functions and a linear chain of atoms. We prove the generality and robustness of the method using materials with complex electronic structures like hexagonal boron nitride, graphene nanoribbons, and carbon nanotubes. We also go on to probe distribution of disorders on the sublattice structure of the materials using the proposed inversion tool.

Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices

Despite the fact that GeTe is known to be a very interesting material for applications in thermoelectrics and for phase-change memories, the knowledge on its low-temperature transport properties is only limited. We report on phase-coherent phenomena in the magnetotransport of GeTe nanowires. From universal conductance fluctuations measured on GeTe nanowires with Au contacts, a phase-coherence length of about 280 nm at 0.5 K is determined. The distinct phase-coherence is confirmed by the observation of Aharonov–Bohm type oscillations for parallel magnetic fields. We interpret the occurrence of these magnetic flux-periodic oscillations by the formation of a tubular hole accumulation layer. For Nb/GeTe-nanowire/Nb Josephson junctions we obtained a critical current of 0.2 μA at 0.4 K. By applying a perpendicular magnetic field the critical current decreases monotonously with increasing field, whereas in a parallel field the critical current oscillates with a period of the magnetic flux quantum confirming the presence of a tubular hole channel.

Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. Through carefully chosen parameter fits, solvable in the least-squares sense, we obtain accurate reduced compartmental models at any level of complexity. We show that (back-propagating) action potentials, Ca2+ spikes, and N-methyl-D-aspartate spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input resistance between the ablated branches and the next proximal dendrite. Furthermore, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide software that automatizes the simplification, eliminating a common hurdle toward including dendritic computations in network models.

Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. We present a flexible and fast method to obtain simplified neuron models at any level of complexity. Through carefully chosen parameter fits, solvable in the least squares sense, we obtain optimal reduced compartmental models. We show that (back-propagating) action potentials, calcium-spikes and NMDA-spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping the affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input impedance between the ablated branches and the next proximal dendrite. Further, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide a software toolbox that automatizes the simplification, eliminating a common hurdle towards including dendritic computations in network models.