Every mission to Mars had started with wild expectations, and ended with few facts and disastrous failures. However, with each failure, the agency has learnt immensely about process, approach, and management. The current mission with Phoenix has been headed by Peter Smith is a collaborative effort by government, academics and industry.

The mission envisages to explore the history of water on the red planet and habitable conditions in its arctic region. View a video giving details of the mission to Mars.

With the initial success of Web 2.0, the essence of this set of useful technology tools have penetrated the hard-shell of scientific collaboration and publishing process. The ubiquitous things like tags, social networks, and blogs have created a new dimension to the approach of scientific publishing. Popularly called Science 2.0, the new approach facilitates publishing raw results of research and a broader platform for collaborative research.

On one hand, a section of the scientific community hails this phenomenon as a natural progression whereas others treat this as a major source of controversies about retention of patent and intellectual copyrights. There have been quite a few websites that have started using this approach whereas major print journals have started adding Web 2.0 tools to their websites. Anyway, Science 2.0 has already been here.

This new approach revolves round the principle of open access, and is perceived as more productive. Going by arguments of numerous open discussions and continual refinements by the scientific community through the last several centuries, this approach, crowdsourcing, reaffirms our unchanged direction of accumulating scientific knowledge.

The obvious pitfall in this approach is the possibility of premature exposure of research ideas and findings, thereby, resulting in breach in intellectual property rights if rival researchers exploit the situation. This may also result in hard-feeling among the genuine researchers and may jeopardise the basic safety and genuine assessment of patents.

The dynamics of a system (of any kind such as physical, chemical, or biological) is fully described by a differential equation, or a set of differential equations (of course, with an appropriate set of initial conditions) involving dynamical variables which together determine the state of the system uniquely at any instant of time.

For a classical (physical) system, the dynamics is studied using Newton’s law (a set of 6N second order coupled ordinary differential equations) with a set of initial conditions, called state variables (r(O), v(O)), to predict a future state of the system to any desired accuracy. Of course, a certain amount of uncertainty lies in the prediction because of some fluctuations in force-terms (inherent in all physical systems), which is usually ascribed to as a statistical phenomenon. But if the system is a nonlinear one, the long term behaviour thereof is often unpredictable.

As usual, the behaviour of a physical system is blueprinted on its phase space. A phase space is constructed with the components of x, and these at each point in this space uniquely determine a state of the system. A phase trajectory indicates the evolution of a system into a point attractor, a limit cycle (ref: figure), or a chaotic regime, asymptotically. A slight variation in the initial conditions can take two nearby trajectories in the phase space away from each other (known as exponential divergence of phase trajectories) contrary to the well-found belief in classical dynamics (that two nearby trajectories will maintain a constant separation throughout the time evolution of the system). This phenomenon of unpredictability of long-term behaviour ofa nonlinear system, which is very sensitive to its initial conditions, is called chaos.

Although chaos is seen in most nonlinear systems (linear systems never exhibit chaos), it is possible for a complex nonlinear system to behave in a well-predictable manner.