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arxivcs.NE2026-07-01

BFF: Simple explanations for complex phenomena

Charlotte Knierim, Luca Versari, Robert Obryk, Blaise Agüera y Arcas, Rif A. Saurous

The ''Computational Life'' paper (Agüera y Arcas et al., 2024) argues that paired interactions in a computational soup are an effective way to find self-replicators. In this work, aided by recent developments in self-replicator detection, we explore the alternate hypothesis that self-replicators can be found at least as easily using simple mutation random walks in program space. We also explore the claim that capping the maximum ''depth'' and ''width'' of the ancestry tree stops self-replicators from emerging, showing instead that it merely stops self-replicators from taking over the soup.

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arxivcs.NE2026-07-10

Co-evolution of self-replication and function in a digital primordial soup

Francesco Cicala, Eyvind Niklasson, Ettore Randazzo, Sami Boukortt, Alessio Basti, Mayalen Etcheverry, et al.

While traditional evolutionary algorithms hard-code reproduction, self-replication can emerge spontaneously within digital ``primordial soups''. This paper investigates the co-evolution of this emergent self-replication alongside problem-solving capabilities. We initialize a popu…

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arxivcs.ETcond-mat.mes-hallcs.ARcs.LGcs.NE2026-07-30

Nanoparticle Networks for Neuromorphic Computing

Jonas Mensing, Wilfred G. van der Wiel, Andreas Heuer

Physical computing leverages complex dynamical systems for energy-efficient data processing. In this work, we present a neuromorphic architecture based on metallic nanoparticles interconnected by molecular junctions on a $\text{SiO}_2$/Si substrate. We demonstrate that surroundin…

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arxivcs.NE2026-07-22

SpikingMOT: A Spike-Driven Multi-Object Tracker

Yiding Sun, Xiangyang Yang, Dongxu Zhang, Qirui Wang, Zijie Xu, Wenxuan Liu, et al.

Multi-object tracking (MOT) plays a fundamental role in visual perception, where accurate trajectory prediction is essential for reliable target association under complex motion patterns. Recent trackers have improved motion modeling with densely activated artificial neural netwo…

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arxivcs.LGcs.NE2026-06-29

Partition-Guided Distance Saliency: Bridging Decision and Objective Spaces in Many-Objective Optimization

Cláudio Lúcio do Val Lopes, Flávio Vinícius Cruzeiro Martins, Elizabeth Fialho Wanner

Explainability in Many-Objective Optimization (MaO) is currently hindered by the escalating complexity of the Pareto front, which renders the relationship between high-dimensional decision variables and objective outcomes increasingly opaque. As the number of objectives exceeds t…

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arxivcs.NE2026-07-17

Transient State Reorganization and Cell Differentiation in the Developmental Dynamics of Growing Neural Cellular Automata

Hiroki Sato, Atsushi Masumori, Takashi Ikegami

Growing Neural Cellular Automata (GNCA) develop complex morphologies from a single seed cell through shared local rules, yet the internal dynamics of this process remain poorly understood. To investigate how GNCA grows, the full developmental trajectory of trained GNCA models was…

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arxivcs.NEnlin.CDphysics.bio-ph2026-07-02

Electronic Bursting Neuron: design, equations and hardware implementation

Lev V. Takaishvili, Vladimir I. Ponomarenko, Maksim V. Kornilov, Ilya V. Sysoev

Electronic neurons are a keystone for construction of the spiking neural networks which have numerous applications in neuroprosthetics, artificial memory, intensive calculations etc. A number of concepts of electronic neurons has been already proposedm with some of them implement…

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