Covariant influences for finite discrete dynamical systems
- URL: http://arxiv.org/abs/2111.13695v5
- Date: Wed, 8 Feb 2023 05:43:21 GMT
- Title: Covariant influences for finite discrete dynamical systems
- Authors: Carlo Maria Scandolo, Gilad Gour, Barry C. Sanders
- Abstract summary: We develop a rigorous theory of external influences on finite discrete dynamical systems.
Our approach employs the framework of resource theories, borrowed quantum information theory, to the study of finite discrete dynamical systems.
The laws we articulate unify the behavior of different types of finite discrete dynamical systems, and their mathematical flavor makes them rigorous and checkable.
- Score: 6.2997667081978825
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We develop a rigorous theory of external influences on finite discrete
dynamical systems, going beyond the perturbation paradigm, in that the external
influence need not be a small contribution. Indeed, the covariance condition
can be stated as follows: if we evolve the dynamical system for $n$ time steps
and then we disturb it, it is the same as first disturbing the system with the
same influence and then letting the system evolve for $n$ time steps. Applying
the powerful machinery of resource theories, we develop a theory of covariant
influences both when there is a purely deterministic evolution and when
randomness is involved. Subsequently, we provide necessary and sufficient
conditions for the transition between states under deterministic covariant
influences and necessary conditions in the presence of stochastic covariant
influences, predicting which transitions between states are forbidden. Our
approach, for the first time, employs the framework of resource theories,
borrowed from quantum information theory, to the study of finite discrete
dynamical systems. The laws we articulate unify the behavior of different types
of finite discrete dynamical systems, and their mathematical flavor makes them
rigorous and checkable.
Related papers
- Unified Causality Analysis Based on the Degrees of Freedom [1.2289361708127877]
This paper presents a unified method capable of identifying fundamental causal relationships between pairs of systems.
By analyzing the degrees of freedom in the system, our approach provides a more comprehensive understanding of both causal influence and hidden confounders.
This unified framework is validated through theoretical models and simulations, demonstrating its robustness and potential for broader application.
arXiv Detail & Related papers (2024-10-25T10:57:35Z) - Sequential Representation Learning via Static-Dynamic Conditional Disentanglement [58.19137637859017]
This paper explores self-supervised disentangled representation learning within sequential data, focusing on separating time-independent and time-varying factors in videos.
We propose a new model that breaks the usual independence assumption between those factors by explicitly accounting for the causal relationship between the static/dynamic variables.
Experiments show that the proposed approach outperforms previous complex state-of-the-art techniques in scenarios where the dynamics of a scene are influenced by its content.
arXiv Detail & Related papers (2024-08-10T17:04:39Z) - Counterfactual-based Root Cause Analysis for Dynamical Systems [0.33748750222488655]
We propose a causal method for root cause identification using a Residual Neural Network.
We show that more root causes are identified when an intervention is performed on the structural equation and the external influence.
We illustrate the effectiveness of the proposed method on a benchmark dynamic system as well as on a real world river dataset.
arXiv Detail & Related papers (2024-06-12T11:38:13Z) - Interpretable Imitation Learning with Dynamic Causal Relations [65.18456572421702]
We propose to expose captured knowledge in the form of a directed acyclic causal graph.
We also design this causal discovery process to be state-dependent, enabling it to model the dynamics in latent causal graphs.
The proposed framework is composed of three parts: a dynamic causal discovery module, a causality encoding module, and a prediction module, and is trained in an end-to-end manner.
arXiv Detail & Related papers (2023-09-30T20:59:42Z) - Quantifying environment non-classicality in dissipative open quantum
dynamics [0.0]
We propose a measure that quantifies how far the environment action on a system departs from the influence of classical noise fluctuations.
It relies on the lack of commutativity between the initial reservoir state and the system-environment total Hamiltonian.
arXiv Detail & Related papers (2023-05-25T15:11:06Z) - Quantum non-Markovian environment-to-system backflows of information:
non-operational vs. operational approaches [0.0]
We analyze and compare how this concept is interpreted and implemented in different approaches to quantum non-Markovianity.
We study a non-operational approach, defined by the istinguishability between two system states.
We study a non-Markovian depolarizing map induced by the interaction of the system of interest with an environment characterized by incoherent and coherent self-dynamics.
arXiv Detail & Related papers (2022-05-06T16:12:17Z) - Capturing Actionable Dynamics with Structured Latent Ordinary
Differential Equations [68.62843292346813]
We propose a structured latent ODE model that captures system input variations within its latent representation.
Building on a static variable specification, our model learns factors of variation for each input to the system, thus separating the effects of the system inputs in the latent space.
arXiv Detail & Related papers (2022-02-25T20:00:56Z) - Decimation technique for open quantum systems: a case study with
driven-dissipative bosonic chains [62.997667081978825]
Unavoidable coupling of quantum systems to external degrees of freedom leads to dissipative (non-unitary) dynamics.
We introduce a method to deal with these systems based on the calculation of (dissipative) lattice Green's function.
We illustrate the power of this method with several examples of driven-dissipative bosonic chains of increasing complexity.
arXiv Detail & Related papers (2022-02-15T19:00:09Z) - Unification of Random Dynamical Decoupling and the Quantum Zeno Effect [68.8204255655161]
We show that the system dynamics under random dynamical decoupling converges to a unitary with a decoupling error that characteristically depends on the convergence speed of the Zeno limit.
This reveals a unification of the random dynamical decoupling and the quantum Zeno effect.
arXiv Detail & Related papers (2021-12-08T11:41:38Z) - Causal influence in operational probabilistic theories [0.0]
We study the relation of causal influence between input systems of a reversible evolution and its output systems.
One is the notion based on signalling, the other is the notion used to define the neighbourhood of a cell in a quantum cellular automaton.
arXiv Detail & Related papers (2020-12-30T16:10:57Z) - Causal Discovery in Physical Systems from Videos [123.79211190669821]
Causal discovery is at the core of human cognition.
We consider the task of causal discovery from videos in an end-to-end fashion without supervision on the ground-truth graph structure.
arXiv Detail & Related papers (2020-07-01T17:29:57Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.