2,968 research outputs found
Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware
The BrainScaleS-2 (BSS-2) system implements physical models of neurons as
well as synapses and aims for an energy-efficient and fast emulation of
biological neurons. When replicating neuroscientific experiment results, a
major challenge is finding suitable model parameters. This study investigates
the suitability of the sequential neural posterior estimation (SNPE) algorithm
for parameterizing a multi-compartmental neuron model emulated on the BSS-2
analog neuromorphic hardware system. In contrast to other optimization methods
such as genetic algorithms or stochastic searches, the SNPE algorithms belongs
to the class of approximate Bayesian computing (ABC) methods and estimates the
posterior distribution of the model parameters; access to the posterior allows
classifying the confidence in parameter estimations and unveiling correlation
between model parameters. In previous applications, the SNPE algorithm showed a
higher computational efficiency than traditional ABC methods. For our
multi-compartmental model, we show that the approximated posterior is in
agreement with experimental observations and that the identified correlation
between parameters is in agreement with theoretical expectations. Furthermore,
we show that the algorithm can deal with high-dimensional observations and
parameter spaces. These results suggest that the SNPE algorithm is a promising
approach for automating the parameterization of complex models, especially when
dealing with characteristic properties of analog neuromorphic substrates, such
as trial-to-trial variations or limited parameter ranges
Efficient viscosity contrast calculation for blood flow simulations using the lattice Boltzmann method
Holographic imaging of an array of submicron light scatterers at low photon numbers
We experimentally test a recently proposed holographic method for imaging
coherent light scatterers which are distributed over a 2-dimensional grid. In
our setup the scatterers consist of a back-illuminated, opaque mask with
submicron-sized holes. We study how the imaging fidelity depends on various
parameters of the set-up. We observe that a few hundred scattered photons per
hole already suffice to obtain a fidelity of 96% to correctly determine whether
a hole is located at a given grid point. The holographic method demonstrated
here has a high potential for applications with ultracold atoms in optical
lattices.Comment: 8 pages, 9 figure
Reducing Impedance at a Li-Metal Anode/Garnet-Type Electrolyte Interface Implementing Chemically Resolvable In Layers
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