Multi-Object Tracking with Interacting Vehicles and Road Map Information

In many applications, tracking of multiple objects is crucial for a perception of the current environment. Most of the present multi-object tracking algorithms assume that objects move independently regarding other dynamic objects as well as the static environment. Since in many traffic situations objects interact with each other and in addition there are restrictions due to drivable areas, the assumption of an independent object motion is not fulfilled. This paper proposes an approach adapting a multi-object tracking system to model interaction between vehicles, and the current road geometry. Therefore, the prediction step of a Labeled Multi-Bernoulli filter is extended to facilitate modeling interaction between objects using the Intelligent Driver Model. Furthermore, to consider road map information, an approximation of a highly precise road map is used. The results show that in scenarios where the assumption of a standard motion model is violated, the tracking system adapted with the proposed method achieves higher accuracy and robustness in its track estimations

Information Flow of quantum states interacting with closed timelike curves

Recently, the quantum information processing power of closed timelike curves have been discussed. Because the most widely accepted model for quantum closed timelike curve interactions contains ambiguities, different authors have been able to reach radically different conclusions as to the power of such interactions. By tracing the information flow through such systems we are able to derive equivalent circuits with unique solutions, thus allowing an objective decision between the alternatives to be made. We conclude that closed timelike curves, if they exist and are well described by these simple models, would be a powerful resource for quantum information processing.Comment: Now includes appendix proving Deutsch's maximum entropy conjectur

Comment on "Information flow of quantum states interacting with closed timelike curves"

We show that recent results on the interaction of causality-respecting particles with particles on closed timelike curves derived in [Phys. Rev. A 82, 062330 (2010)] depend on ambiguous assumption about the form of the state which is inputted into the proposed equivalent circuit. Choosing different form of this state leads to opposite conclusion on the power of closed timelike curves

Adaptive Dynamics for Interacting Markovian Processes

Dynamics of information flow in adaptively interacting stochastic processes is studied. We give an extended form of game dynamics for Markovian processes and study its behavior to observe information flow through the system. Examples of the adaptive dynamics for two stochastic processes interacting through matching pennies game interaction are exhibited along with underlying causal structure

Clustering of Conditional Mutual Information for Quantum Gibbs States above a Threshold Temperature

We prove that the quantum Gibbs states of spin systems above a certain threshold temperature are approximate quantum Markov networks, meaning that the conditional mutual information decays rapidly with distance. We demonstrate the exponential decay for short-ranged interacting systems and power-law decay for long-ranged interacting systems. Consequently, we establish the efficiency of quantum Gibbs sampling algorithms, a strong version of the area law, the quasilocality of effective Hamiltonians on subsystems, a clustering theorem for mutual information, and a polynomial-time algorithm for classical Gibbs state simulations

AIC and BIC for cosmological interacting scenarios

In this work we study linear and non-linear cosmological interactions, which depend on dark matter and dark energy densities in the framework of General Relativity. By using the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) with data from SnIa (Union 2.1 and binned JLA), H(z), BAO and CMB we compare the interacting models among themselves and analyze whether more complex interacting models are favored by these criteria. In this context, we find some suitable interactions that alleviate the coincidence problem.Comment: 24 pages, 4 figures, minor changes, file replaced to match published version to appear in EPJ