activity
20202026
most citedClosing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming

21 citations · 52 across the 27 of their papers we have counts for

collaborators

28 papers

astro-ph.IM2026

Continuous Learning of Gravity Field Irregularities Around Small Bodies via Neural Hamiltonian ODEs

Giacomo Acciarini, Dario Izzo

We propose to learn the unknown dynamics in the proximity of a small body directly from tracking data, representing them as a feed-forward neural network embedded in the system Ham…

cs.CV2026

Methane Detection On Board Satellites from Unorthorectified Imagery

Luca Marini, Maggie Chen, Hala Lamdouar +3

As a potent greenhouse gas, methane is a major driver of climate change. Its effective mitigation relies on timely detection. Conventional detection methods rely on orthorectificat…

astro-ph.EP2026

The Maximum Initial Mass

Dario Izzo, Giacomo Acciarini

We introduce the maximum-initial-mass problem as a standalone optimal-control formulation for low-thrust trajectory design and analyze its structure within Pontryagin's framework.…

cs.LG2026

Pretrained Approximators for Low-Thrust Trajectory Cost and Reachability

Zhong Zhang, Giacomo Acciarini, Dario Izzo +2

Low-thrust trajectory design relies heavily on repeated evaluations of fuel consumption and transfer feasibility, which require expensive optimal control solutions. In this work, w…

eess.SY2026

Reachability for Low-Thrust Trajectories via Maximum Initial Mass

Giacomo Acciarini, Dario Izzo, Zhong Zhang

Reachability analysis plays a central role in low-thrust spacecraft trajectory optimization by identifying which target states can be achieved under constraints on time, thrust, an…

astro-ph.IM2026

A practical guide to implementing zero-order-hold interplanetary trajectory legs

Dario Izzo, Harry Holt, Giacomo Acciarini +2

We study the practical implementation of zero-order-hold (ZOH) transcriptions for spacecraft trajectory optimisation, identifying a set of design principles that render them robust…

math.OC2026

The Keplerian Traveling Salesperson Problem

Max Bannach, Giacomo Acciarini, Dario Izzo

We address a fundamental challenge in space mission design and space logistics: planning interplanetary trajectories for missions that must rendezvous with multiple bodies. Such mi…

cs.LG2025

IonCast: A Deep Learning Framework for Forecasting Ionospheric Dynamics

Halil S. Kelebek, Linnea M. Wolniewicz, Michael D. Vergalla +8

The ionosphere is a critical component of near-Earth space, shaping GNSS accuracy, high-frequency communications, and aviation operations. For these reasons, accurate forecasting a…

cs.LG2025

Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers

Giacomo Acciarini, Simone Mestici, Halil Kelebek +7

The ionosphere critically influences Global Navigation Satellite Systems (GNSS), satellite communications, and Low Earth Orbit (LEO) operations, yet accurate prediction of its vari…

cs.CV2025

Towards Methane Detection Onboard Satellites

Maggie Chen, Hala Lamdouar, Luca Marini +3

Methane is a potent greenhouse gas and a major driver of climate change, making its timely detection critical for effective mitigation. Machine learning (ML) deployed onboard satel…

eess.SY2025

Probability of collision in nonlinear dynamics by moment propagation

Théo Verhelst, Giacomo Acciarini, Dario Izzo +1

Estimating the probability of collision between spacecraft is crucial for risk management and collision-avoidance strategies. Current methods often rely on Gaussian assumptions and…

astro-ph.EP2025

EclipseNETs: Learning Irregular Small Celestial Body Silhouettes

Giacomo Acciarini, Dario Izzo, Francesco Biscani

Accurately predicting eclipse events around irregular small bodies is crucial for spacecraft navigation, orbit determination, and spacecraft systems management. This paper introduc…

math.OC2025

High-order expansion of Neural Ordinary Differential Equations flows

Dario Izzo, Sebastien Origer, Giacomo Acciarini +1

Artificial neural networks, widely recognised for their role in machine learning, are now transforming the study of ordinary differential equations (ODEs), bridging data-driven mod…

astro-ph.EP2024★ 9 cited

Asteroid Mining: ACT&Friends' Results for the GTOC 12 Problem

Dario Izzo, Marcus Märtens, Laurent Beauregard +8

In 2023, the 12th edition of Global Trajectory Competition was organised around the problem referred to as "Sustainable Asteroid Mining". This paper reports the developments that l…

eess.SY2024

Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifold

Sebastien Origer, Dario Izzo, Giacomo Acciarini +4

We perform uncertainty propagation on an event manifold for Guidance & Control Networks (G&CNETs), aiming to enhance the certification tools for neural networks in this field. This…

cs.LG2024

EclipseNETs: a differentiable description of irregular eclipse conditions

Giacomo Acciarini, Francesco Biscani, Dario Izzo

In the field of spaceflight mechanics and astrodynamics, determining eclipse regions is a frequent and critical challenge. This determination impacts various factors, including the…

physics.space-ph2024★ 9 cited

Nonlinear Propagation of Non-Gaussian Uncertainties

Giacomo Acciarini, Nicola Baresi, David Lloyd +1

This paper presents a novel approach for propagating uncertainties in dynamical systems building on high-order Taylor expansions of the flow and moment-generating functions (MGFs).…

astro-ph.EP2024

NeuralODEs for VLEO simulations: Introducing thermoNET for Thermosphere Modeling

Dario Izzo, Giacomo Acciarini, Francesco Biscani

We introduce a novel neural architecture termed thermoNET, designed to represent thermospheric density in satellite orbital propagation using a reduced amount of differentiable com…

astro-ph.EP2024

Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach

Giacomo Acciarini, Laurent Beauregard, Dario Izzo

Low-thrust trajectories play a crucial role in optimizing scientific output and cost efficiency in asteroid belt missions. Unlike high-thrust transfers, low-thrust trajectories req…

physics.space-ph2024

Global Optimization for Trajectory Design via Invariant Manifolds in the Earth-Moon Circular Restricted Three-Body Problem

Flavio Tagliaferri, Emmanuel Blazquez, Giacomo Acciarini +1

This study addresses optimal impulsive trajectory design within the Circular Restricted Three-Body Problem (CR3BP), presenting a global optimization-based approach to identify mini…

physics.space-ph2024★ 1 cited

Stochastic Continuation of Trajectories in the Circular Restricted Three-Body Problem via Differential Algebra

Giacomo Acciarini, Nicola Baresi, David J. B. Lloyd +1

Numerical continuation techniques are powerful tools that have been extensively used to identify particular solutions of nonlinear dynamical systems and enable trajectory design in…

physics.space-ph2024

Breaking traditions: introducing a surrogate Primer Vector in non Keplerian dynamics

Laurent Beauregard, Dario Izzo, Giacomo Acciarini

In this study, we investigate trajectories involving multiple impulses within the framework of a generic spacecraft dynamics. Revisiting the age-old query of "How many impulses?",…

cs.LG2024★ 21 cited

Closing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming

Giacomo Acciarini, Atılım Güneş Baydin, Dario Izzo

The Simplified General Perturbations 4 (SGP4) orbital propagation method is widely used for predicting the positions and velocities of Earth-orbiting objects rapidly and reliably.…

physics.space-ph2023

High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery

Shreshth A. Malik, James Walsh, Giacomo Acciarini +2

Accurate estimation of thermospheric density is critical for precise modeling of satellite drag forces in low Earth orbit (LEO). Improving this estimation is crucial to tasks such…