An Evolutionary Formalism for Weak Quantum Measurements

Unitary evolution and projective measurement are fundamental axioms of quantum mechanics. Even though projective measurement yields one of the eigenstates of the measured operator as the outcome, there is no theory that predicts which eigenstate will be observed in which experimental run. There exists only an ensemble description, which predicts probabilities of various outcomes over many experimental runs. We propose a dynamical evolution equation for the projective collapse of the quantum state in individual experimental runs, which is consistent with the well-established framework of quantum mechanics. In case of gradual weak measurements, its predictions for ensemble evolution are different from those of the Born rule. It is an open question whether or not suitably designed experiments can observe this alternate evolution.Comment: 6 pages. Talk presented at the Discussion Meeting on Quantum Measurements, IISc, Bangalore, 22-24 October 2014. Comments welcome. (v2) Version to be published in the Proceedings. Notation generalised for multi-dimensional projection operators. Tests for 1- and 2-qubit systems described. Usefulness for error correction pointed ou

Internet innovations:exploring new horizons

The aim of this paper is to provide a standpoint on an emerging trend in sharing digital video content over the Internet. The paper is based on participative evaluative analysis of business model employed by digital video content sharing providers. The authors have found that because of wide diffusion of broadband and cheap video recording equipment, enabling digital video content to be shared online, and emerging business internet video sharing practice its users increasingly find themselves infringing the intellectual property rights of others. This has implications for anyone using online video resources. The paper offers an insight into the increasing popularity of online video and the resulting dilemmas encountered by internet researchers; it also offers a functional way for researchers, businesses and online users to understand the mechanism of infringement of the intellectual property rights relating to online video content. The paper further contributes to expanding the understanding of internet users behaviour in relation to digital video content creation and distribution in the context of challenges faced by cyberlaw

Braid groups in complex spaces

We describe the fundamental groups of ordered and unordered $k-$point sets in the n-dimensional complex space $C^n$ generating an affine subspace of fixed dimension

Decomposition of aggregated load: finding induction motor fraction in real load

The main contribution of this paper is decomposition/separation of the compositie induction motors load from measurement at a system bus. In power system transmission buses load is represented by static and dynamic loads. The induction motor is considered as the main dynamic loads and in the practice for major transmission buses there will be many and various induction motors contributing. Particularly at an industrial bus most of the load is dynamic types. Rather than traing to extract models of many machines this paper seeks to identify three groups of induction motors to represent the dynamic loads. Three groups of induction motors used to characterize the load. These are the small groups (4kw to 11kw), the medium groups (15kw to 180kw) and the large groups (above 630kw). At first these groups with different percentage contribution of each group is composite. After that from the composite models, each motor percentage contribution is decomposed by using the least square algorithms. In power system commercial and the residential buses static loads percentage is higher than the dynamic loads percentage. To apply this theory to other types of buses such as residential and commerical it is good practice to represent the total load as a combination of composite motor loads, constant impedence loads and constant power loads. To validate the theory, the 24hrs of Sydney West data is decomposed according to the three groups of motor models