Spatial transformation

SPATIAL TRANSFORMATION Spatial transformation / Abassiharofteh, Milad (Rights reserved) ( -

Spatial Localization and Relativistic Transformation of Quantum Spins

The purity of a reduced state for spins that is pure in the rest frame will most likely appear to degrade because spin and momentum become mixed when viewed by a moving observer. We show that such a boost-induced decrease in spin purity observed in a moving reference frame is intrinsically related to the spatial localization properties of the wave package observed in the rest frame. Furthermore, we prove that, for any localized pure state with separable spin and momentum in the rest frame, its reduced density matrix for spins inevitably appears to be mixed whenever viewed from a moving reference frame.Comment: 5 pages, 1 figur

Gestural control of sonic swarms: Composing with grouped sound objects

This paper outlines an alternative controller designed to diffuse and manipulate a swarm of sounds in 3- dimensional space and discusses the compositional issues that emerge from its use. The system uses an algorithm from a nature-derived model describing the spatial behavior of a swarm. The movement of the swarm is mapped in the 3- dimensional space and a series of sound transformation functions for the sonic agents are implemented. The notion of causal relationships is explored regarding the spatial movement of the swarm and sound transformation of the agents by employing the physical controller as a performance, compositional and diffusion tool

Segue: Overviewing Evolution Patterns of Egocentric Networks by Interactive Construction of Spatial Layouts

Getting the overall picture of how a large number of ego-networks evolve is a common yet challenging task. Existing techniques often require analysts to inspect the evolution patterns of ego-networks one after another. In this study, we explore an approach that allows analysts to interactively create spatial layouts in which each dot is a dynamic ego-network. These spatial layouts provide overviews of the evolution patterns of ego-networks, thereby revealing different global patterns such as trends, clusters and outliers in evolution patterns. To let analysts interactively construct interpretable spatial layouts, we propose a data transformation pipeline, with which analysts can adjust the spatial layouts and convert dynamic egonetworks into event sequences to aid interpretations of the spatial positions. Based on this transformation pipeline, we developed Segue, a visual analysis system that supports thorough exploration of the evolution patterns of ego-networks. Through two usage scenarios, we demonstrate how analysts can gain insights into the overall evolution patterns of a large collection of ego-networks by interactively creating different spatial layouts.Comment: Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2018