29 citations · 84 across the 21 of their papers we have counts for
23 papers
Score-based stochastic reduced-order models of barotropic quasi-geostrophic turbulence
Ludovico Theo Giorgini
In many turbulent flows, the quantities of interest are coarse-grained variables, either because resolving the fine scales is computationally prohibitive or because only coarse obs…
Conditional Score-Based Modeling of Effective Langevin Dynamics
Ludovico T. Giorgini
Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains chal…
Stochastic coupling of climate variables and ice volume over the Late Pleistocene glacial cycles
Pijush Patra, Ludovico T. Giorgini, J. S. Wettlaufer
Understanding the interactions between ice sheets and global climate forcings over geological timescales is essential for projecting their future. Previous studies have highlighted…
Integrating Score-Based Generative Modeling and Neural ODEs for Accurate Representation of Multiscale Chaotic Dynamics
Giulio Del Felice, Ludovico Theo Giorgini
Multiscale dynamical systems characterized by interacting fast and slow processes are ubiquitous across scientific domains, from climate dynamics to fluid mechanics. Accurate model…
Statistical Parameter Calibration via the Generalized Fluctuation Dissipation Theorem and Generative Modeling
Ludovico T. Giorgini, Tobias Bischoff, Andre N. Souza
We introduce a response-theoretic framework that recasts parameter calibration of ergodic stochastic differential equations as a fluctuation-dissipation problem. Our central result…
Reduced-Order Modeling of Cyclo-Stationary Time Series Using Score-Based Generative Methods
Ludovico Theo Giorgini, Tobias Bischoff, Andre Noguiera Souza
Many natural systems exhibit cyclo-stationary behavior characterized by periodic forcing such as annual and diurnal cycles. We present a data-driven method leveraging recent advanc…
Score-Based Modeling of Effective Langevin Dynamics
Ludovico Theo Giorgini
We introduce a constructive framework to learn effective Langevin equations from stationary time series. Unlike conventional approaches that require iterative calibration to match…
Predicting Forced Responses of Probability Distributions via the Fluctuation-Dissipation Theorem and Generative Modeling
Ludovico T. Giorgini, Fabrizio Falasca, Andre N. Souza
We present a novel and flexible data-driven framework for estimating the response of higher-order moments of nonlinear stochastic systems to small external perturbations. The class…
KGMM: A K-means Clustering Approach to Gaussian Mixture Modeling for Score Function Estimation
Ludovico T. Giorgini, Tobias Bischoff, Andre N. Souza
We propose a hybrid method for accurately estimating the score function, i.e., the gradient of the log steady-state density, using a Gaussian Mixture Model (GMM) in conjunction wit…
Learning dissipation and instability fields from chaotic dynamics
Ludovico T Giorgini, Andre N Souza, Domenico Lippolis +2
To make predictions or design control, information on local sensitivity of initial conditions and state-space contraction is both central, and often instrumental. However, it is no…
Analytical Survival Analysis of the Non-autonomous Ornstein-Uhlenbeck Process
L. T. Giorgini, W. Moon, J. S. Wettlaufer
The survival probability for a periodic non-autonomous Ornstein-Uhlenbeck process is calculated analytically using two different methods. The first uses an asymptotic approach. We…
Instantons in Theories: Transseries, Virial Theorems and Numerical Aspects
Ludovico T. Giorgini, Ulrich D. Jentschura, Enrico M. Malatesta +2
We discuss numerical aspects of instantons in two- and three-dimensional theories with an internal symmetry group, the so-called -vector model. Combining asymptotic…
Response Theory via Generative Score Modeling
Ludovico Theo Giorgini, Katherine Deck, Tobias Bischoff +1
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the Generalized Fluctuation-D…
Reduced Markovian Models of Dynamical Systems
Ludovico Theo Giorgini, Andre N. Souza, Peter J. Schmid
Leveraging recent work on data-driven methods for constructing a finite state space Markov process from dynamical systems, we address two problems for obtaining further reduced sta…
Stochastic Paleoclimatology: Modeling the EPICA Ice Core Climate Records
N. D. B. Keyes, L. T. Giorgini, J. S. Wettlaufer
We analyze and model the stochastic behavior of paleoclimate time series and assess the implications for the coupling of climate variables during the Pleistocene glacial cycles. We…
The Thermodynamic Cost of Erasing Information in Finite-time
L. T. Giorgini, R. Eichhorn, M. Das +2
The Landauer principle sets a fundamental thermodynamic constraint on the minimum amount of heat that must be dissipated to erase one logical bit of information through a quasi-sta…
Correlation Functions of the Anharmonic Oscillator: Numerical Verification of Two-Loop Corrections to the Large-Order Behavior
Ludovico T. Giorgini, Ulrich D. Jentschura, Enrico M. Malatesta +3
Recently, the large-order behavior of correlation functions of the -anharmonic oscillator has been analyzed by us in [L. T. Giorgini et el., Phys. Rev. D 101, 125001 (2020)].…
Analytical solution of stochastic resonance in the nonadiabatic regime
W. Moon, L. T. Giorgini, J. S. Wettlaufer
We generalize stochastic resonance to the nonadiabatic limit by treating the double-well potential using two quadratic potentials. We use a singular perturbation method to determin…
A Non-Gaussian Stochastic Model for the El Niño Southern Oscillation
L. T. Giorgini, W. Moon, N. Chen +1
A non-autonomous stochastic dynamical model approach is developed to describe the seasonal to interannual variability of the El Niño-Southern Oscillation (ENSO). We determine the m…
Two-Loop Corrections to the Large-Order Behavior of Correlation Functions in the One-Dimensional N-Vector Model
L. T. Giorgini, U. D. Jentschura, E. M. Malatesta +3
For a long time, the predictive limits of perturbative quantum field theory have been limited by our inability to carry out loop calculations to arbitrarily high order, which becom…
Analytical Survival Analysis of the Ornstein-Uhlenbeck Process
L. T. Giorgini, W. Moon, J. S. Wettlaufer
We use asymptotic methods from the theory of differential equations to obtain an analytical expression for the survival probability of an Ornstein-Uhlenbeck process with a potentia…
Predicting Critical Transitions in Multiscale Dynamical Systems Using Reservoir Computing
Soon Hoe Lim, Ludovico Theo Giorgini, Woosok Moon +1
We study the problem of predicting rare critical transition events for a class of slow-fast nonlinear dynamical systems. The state of the system of interest is described by a slow…
Precursors to Rare Events in Stochastic Resonance
L. T. Giorgini, S. H. Lim, W. Moon +1
In stochastic resonance, a periodically forced Brownian particle in a double-well potential jumps between minima at rare increments, the prediction of which poses a major theoretic…