Copertina

The Potential Impact of Neuromorphic Computing on Radio Telescope Observatories

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pritchard, Nicholas J., Dodson, Richard, Wicenec, Andreas
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Instrumentation and Methods for Astrophysics Neural and Evolutionary Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Polarisation-Inclusive Spiking Neural Networks for Real-Time RFI Detection in Modern Radio Telescopes
di: Pritchard, Nicholas J., et al.
Pubblicazione: (2025)

Spiking Neural Networks for Radio Frequency Interference Detection in Radio Astronomy
di: Pritchard, Nicholas J., et al.
Pubblicazione: (2024)

Supervised Radio Frequency Interference Detection with SNNs
di: Pritchard, Nicholas J., et al.
Pubblicazione: (2024)

Advancing RFI-Detection in Radio Astronomy with Liquid State Machines
di: Pritchard, Nicholas J, et al.
Pubblicazione: (2025)

Neuromorphic Astronomy: An End-to-End SNN Pipeline for RFI Detection Hardware
di: Pritchard, Nicholas J., et al.
Pubblicazione: (2025)

RFI Detection with Spiking Neural Networks
di: Pritchard, Nicholas J., et al.
Pubblicazione: (2023)

Enhancing Celestial Imaging: High Dynamic Range with Neuromorphic Cameras
di: Yadav, Satyapreet Singh, et al.
Pubblicazione: (2025)

Neuromorphic Cameras in Astronomy: Unveiling the Future of Celestial Imaging Beyond Conventional Limits
di: Yadav, Satyapreet Singh, et al.
Pubblicazione: (2025)

The Inefficiency of Genetic Programming for Symbolic Regression
di: Kronberger, Gabriel, et al.
Pubblicazione: (2024)

A Genetic Algorithm Framework for Optimizing Three-Impulse Orbital Transfers with Poliastro Simulation
di: Do, Phuc Hao, et al.
Pubblicazione: (2025)

Symbolic Emulators for Cosmology: Accelerating Cosmological Analyses Without Sacrificing Precision
di: Bartlett, Deaglan J., et al.
Pubblicazione: (2025)

Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up
di: Gómez-Vargas, Isidro, et al.
Pubblicazione: (2024)

syren-halofit: A fast, interpretable, high-precision formula for the $Λ$CDM nonlinear matter power spectrum
di: Bartlett, Deaglan J., et al.
Pubblicazione: (2024)

syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy
di: Sui, Ce, et al.
Pubblicazione: (2024)

A precise symbolic emulator of the linear matter power spectrum
di: Bartlett, Deaglan J., et al.
Pubblicazione: (2023)

Approximating Rayleigh Scattering in Exoplanetary Atmospheres using Physics-informed Neural Networks (PINNs)
di: Dahlbüdding, David, et al.
Pubblicazione: (2024)

syren-baryon: Analytic emulators for the impact of baryons on the matter power spectrum
di: Kammerer, Lukas, et al.
Pubblicazione: (2025)

APRIL: Auxiliary Physically-Redundant Information in Loss -- A physics-informed framework for parameter estimation with a gravitational-wave case study
di: Scialpi, Matteo, et al.
Pubblicazione: (2025)

Introduction to Symbolic Regression in the Physical Sciences
di: Bartlett, Deaglan J., et al.
Pubblicazione: (2025)

Quantization Effects of Artificial Neural Networks for Embedded Edge-Computing Applications
di: Aksoy, Alperen, et al.
Pubblicazione: (2025)

Neuromorphic Split Computing with Wake-Up Radios: Architecture and Design via Digital Twinning
di: Chen, Jiechen, et al.
Pubblicazione: (2024)

Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic Computing
di: Boccato, Tommaso, et al.
Pubblicazione: (2024)

The Potential of Combined Learning Strategies to Enhance Energy Efficiency of Spiking Neuromorphic Systems
di: Sichani, Ali Shiri, et al.
Pubblicazione: (2024)

Neuromorphic Computing - An Overview
di: Jung, Benedikt, et al.
Pubblicazione: (2025)

Deep Investigation of Neutral Gas Origins (DINGO): Options for the Processing and Storage of Radio Astronomy Data for robust Deep Spectral Line Imaging in the SKA-Era using uv-Grids
di: Williamson, Alexander, et al.
Pubblicazione: (2024)

Demonstrating the Advantages of Analog Wafer-Scale Neuromorphic Hardware
di: Schmidt, Hartmut, et al.
Pubblicazione: (2024)

Speed-based Filtration and DBSCAN of Event-based Camera Data with Neuromorphic Computing
di: Rizzo, Charles P., et al.
Pubblicazione: (2024)

Neuromorphic Sequential Arena: A Benchmark for Neuromorphic Temporal Processing
di: Chen, Xinyi, et al.
Pubblicazione: (2025)

Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing
di: Pedersen, Jens E., et al.
Pubblicazione: (2023)

Generative structural elucidation from mass spectra as an iterative optimization problem
di: Manjrekar, Mrunali, et al.
Pubblicazione: (2026)

Recovering Sparse Neural Connectivity from Partial Measurements: A Covariance-Based Approach with Granger-Causality Refinement
di: Simeon, Quilee
Pubblicazione: (2026)

Optimization of breeding program design through stochastic simulation with evolutionary algorithms
di: Hassanpour, Azadeh, et al.
Pubblicazione: (2024)

The Schwarzschild-Couder Telescope for the Cherenkov Telescope Array Observatory
di: Riitano, Luca, et al.
Pubblicazione: (2025)

Using context to adapt to sensor drift
di: Warner, J., et al.
Pubblicazione: (2020)

From Silicon to Spikes: System-Wide Efficiency Gains via Exact Event-Driven Training in Neuromorphic Computing
di: Ferdowsi, Arman, et al.
Pubblicazione: (2025)

A Neuromorphic Electronic Nose Design
di: Rastogi, Shavika, et al.
Pubblicazione: (2024)

A Neuromorphic Implementation of the DBSCAN Algorithm
di: Rizzo, Charles P., et al.
Pubblicazione: (2024)

ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers
di: Chen, Zihao, et al.
Pubblicazione: (2024)

Optimising the Processing and Storage of Visibilities using lossy compression
di: Dodson, Richard, et al.
Pubblicazione: (2024)

Neuromorphic Robust Estimation of Nonlinear Dynamical Systems Applied to Satellite Rendezvous
di: Ahmadvand, Reza, et al.
Pubblicazione: (2024)