arXiv subjects

M. A. C. Potenza

Publications and source records attributed to M. A. C. Potenza.

4 recordsLinked to original sources

arXiv2025

The receptron is a nonlinear threshold logic gate with intrinsic multi-dimensional selective capabilities for analog inputs

Threshold logic gates (TLGs) have been proposed as artificial counterparts of biological neurons with classification capabilities based on a linear predictor function combining a set of weights with the feature vector. The linearity of TLGs limits their classification capabilities requiring the use of networks for the accomplishment of complex tasks. A generalization of the TLG model called receptron, characterized by input-dependent weight functions allows for a significant enhancement of classification performances even with the use of a single unit. Here we formally demonstrate that a receptron, characterized by nonlinear input-dependent weight functions, exhibit intrinsic selective activation properties for analog inputs, when the input vector is within cubic domains in a 3D space. The proposed model can be extended to the n-dimensional case for multidimensional applications. Our results suggest that receptron-based networks can represent a new class of devices capable to manage a large number of analog inputs, for edge applications requiring high selectivity and classification capabilities without the burden of complex training.

cs.ET↗

arXiv2024

DEDALO: Device for Enhanced Dust Analyses with Light Obscuration sensors

Instruments based on light obscuration sensors are widely used for measuring the size distribution of insoluble sub-visible particles in liquid suspensions, being fast and suitable for in situ and real-time measurements. Such instruments are typically calibrated by means of reference polystyrene spherical particles with a specific refractive index, which unavoidably leads to systematic errors when determining the size of particles of different materials. In this paper, we propose a reliable and consistent method to overcome this limitation by setting the refractive index value according to the sample, thus achieving an improved particle size distribution (PSD) measurement. An ad hoc, ready-to-use, open source code with a graphical interface able to drive an in-line instrument and obtain a real-time correction to the PSD has been developed. The method has been extensively validated with several oil emulsions characterized by different refractive index values and the results have been compared with an independent optical method. As an example of application, we have adopted this approach for the analysis of dust suspended in meltwater of an ice core from a glacier in the Aosta Valley (Italy). We believe that our approach will strongly improve the accuracy in characterizing liquid suspensions and reduce discrepancies between data obtained with different methods. The code has been made publicly available at:https://instrumentaloptics.fisica.unimi.it/dedalo/ and on the GitHub page of the corresponding author (https://github.com/LucaTeruzzi/DEDALO).

physics.ins-det↗

arXiv2022

Solving classification tasks by a receptron based on nonlinear optical speckle fields

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a different paradigm compared to ANNs and it is based on random networks of nonlinear nanoscale junctions resulting from the assembling of nanoparticles or nanowires as substrates for neuromorphic computing. These networks show the presence of emergent complexity and collective phenomena in analogy with biological neural networks characterized by self-organization, redundancy, non-linearity. Starting from this background, we propose and formalize a generalization of the perceptron model to describe a classification device based on a network of interacting units where the input weights are nonlinearly dependent. We show that this model, called "receptron", provides substantial advantages compared to the perceptron as, for example, the solution of non-linearly separable Boolean functions with a single device. The receptron model is used as a starting point for the implementation of an all-optical device that exploits the non-linearity of optical speckle fields produced by a solid scatterer. By encoding these speckle fields we generated a large variety of target Boolean functions without the need for time-consuming machine learning algorithms. We demonstrate that by properly setting the model parameters, different classes of functions with different multiplicity can be solved efficiently. The optical implementation of the receptron scheme opens the way for the fabrication of a completely new class of optical devices for neuromorphic data processing based on a very simple hardware.

cond-mat.dis-nn↗

arXiv2003

Three dimensional imaging of short pulses

We exploit a slightly noncollinear second-harmonic cross-correlation scheme to map the 3D space-time intensity distribution of an unknown complex-shaped ultrashort optical pulse. We show the capability of the technique to reconstruct both the amplitude and the phase of the field through the coherence of the nonlinear interaction down to a resolution of 10 $μ$m in space and 200 fs in time. This implies that the concept of second-harmonic holography can be employed down to the sub-ps time scale, and used to discuss the features of the technique in terms of the reconstructed fields.

physics.optics↗