Search results for " rando"
showing 10 items of 498 documents
Algebraic aspects and coherence conditions for conjoined and disjoined conditionals
2019
We deepen the study of conjoined and disjoined conditional events in the setting of coherence. These objects, differently from other approaches, are defined in the framework of conditional random quantities. We show that some well known properties, valid in the case of unconditional events, still hold in our approach to logical operations among conditional events. In particular we prove a decomposition formula and a related additive property. Then, we introduce the set of conditional constituents generated by $n$ conditional events and we show that they satisfy the basic properties valid in the case of unconditional events. We obtain a generalized inclusion-exclusion formula and we prove a …
Non-Markovianity of Gaussian Channels
2015
We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated to arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.
Dynamics of a quantum particle interacting with a thermal bath and subject to an oscillating asymmetric bistable potential
2012
Exploiting the approach of the Feynman-Vernon influence functional [1] within the framework of the discrete variable representation (DVR) [2], we consider a quantum particle described by the Caldeira-Leggett model [3]. The particle, “moving” in an asymmetric bistable potential and subject to a periodical driving, interacts with a thermal bath of harmonic oscillators. In this conditions we study the dynamics of the particle by analyzing the time evolution of the populations in the DVR. Specifically we focalize on the position eigenstate located in the shallower well, i.e. metastable state, finding a non-monotonic behaviour of the corresponding population as a function of the frequency. Moreo…
Dynamics of a Driven Dissipative Quantum System
2013
We investigate the dynamics of a driven multilevel system, consisting of a particle in an asymmetric bistable potential, strongly interacting with a thermal bath according to the Caldeira-Leggett model. The populations in the discrete (position) variable representation (DVR), are obtained as solution of a Markovian approximated master equation, which is derived from a discretized path integral approach based on the Feynman-Vernon influence functional. By varying the environmental parameters (temperature and coupling strength) as well as the driving frequency and amplitude, we study the transient dynamics and stationary configuration of the system. In particular, we analyze the population of…
Transient Dynamics of a Driven Quantum Bistable System
2013
We study the transient dynamics and the asymptotic behaviour of a multilevel system in the strong dissipation regime. The system is modeled as a periodically driven quantum particle in an asymmetric double well potential, interacting with the bosonic heat bath of the Caldeira-Leggett model. The analytical approach used is non- perturbative in the particle-bath coupling and is based on a space-discretized path integral expression for the particle’s reduced density matrix. By a suitable approximation on the Feynman-Vernon influence functional a Markov-approximated master equation is obtained for the populations in the Discrete Variable Representation (DVR).
Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution
2010
Published version of an article in the journal: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works In this paper, we present a learning-automata-like (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL random early detection (LALRED), is founded on the principles of the operations of existing RED con…
A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning
2017
The aim of this study is to combine Biological Target Volume (BTV) segmentation and Gross Target Volume (GTV) segmentation in stereotactic neurosurgery.Our goal is to enhance Clinical Target Volume (CTV) definition, including metabolic and morphologic information, for treatment planning and patient follow-up.We propose a fully automatic approach for multimodal PET and MR image segmentation. This method is based on the Random Walker (RW) and Fuzzy C-Means clustering (FCM) algorithms. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is presented, considering volume…
CORRELATIONS AMONG FORWARD RETURNS IN THE NORDIC ELECTRICITY MARKET
2009
I analyze empirical correlations of electricity forward returns from the perspective of a random field model that specifies the correlations in terms of the temporal separation between forward maturities. It turns out that temporal separation cannot fully account for the empirical forward return correlations. Specifically, the relation between correlations and temporal separation does not seem to be invariant across segments of the electricity forward market or trading periods.
Information Functionals and the Notion of (Un)Certainty: Random Matrix Theory - Inspired Case
2007
Information functionals allow one to quantify the degree of randomness of a given probability distribution, either absolutely (through min/max entropy principles) or relative to a prescribed reference one. Our primary aim is to analyze the “minimum information” assumption, which is a classic concept (R. Balian, 1968) in the random matrix theory. We put special emphasis on generic level (eigenvalue) spacing distributions and the degree of their randomness, or alternatively — information/organization deficit.
Spatial graphs and Convolutive Models
2020
In the last two decades, many complex systems have benefited from the use of graph theory, and these approaches have shown robust applicability in the field of finance, computer circuits and in biological systems. Large scale models of brain systems make also a great use of random graph models. Graph theory can be instrumental in modeling the connectivity and spatial distribution of neurons, through a characterization of the relative topological properties. However, all approaches in studying brain function have been so far limited to use experimental constraints obtained at a macroscopic level (e.g. fMRI, EEG, MEG, DTI, DSI). In this contribution, we present a microscopic use (i.e. at the …