Physics 2T: Dynamic Video

What is 2T?

2T is the second layer of transformations, expanding scalar values from 1T into dynamic, real-time 3D representations. Imagine a video representation of scalar data being visualized in 3D space, tracking changes over time using pulse pings that measure and map this transformation.

At this level, scalar points become part of a larger 3D video that maps evolving systems, showing the flow and interaction of objects, energy, and data as they move through space and time.

How Pulse Pings and Selective Tracking Work

In the MiCi system, pulse pings work collaboratively, selectively analyzing data in real time. Rather than capturing every possible detail, these pings act much like a choir in unison—each ping focused on its task but aware of the system’s overall structure. This allows the system to be both precise and adaptive, adjusting based on key observations while minimizing unnecessary data overload.

When plugged into the CAD NET, the system uses this selective pinging to analyze a light replica of the data cubes would traditionally track. The survey data collected by CAD NET allows the system to focus on relevant details, creating a streamlined view of the environment without losing sight of important dynamics.

This process enables the system to not only monitor real-time transformations but also to selectively enhance areas of interest, ensuring the 3D map remains both accurate and efficient in terms of processing power.

The Role of Time in 2T

Time is integral to 2T, anchoring each scalar transformation. The pulse pings are sent at defined intervals, allowing the system to track how each point shifts and evolves. This creates a smooth, continuous video of objects or values moving and interacting in 3D space.

These transformations happen across relative time, capturing the full trajectory of how scalars, vectors, and cubes evolve in real-time video format.

Applications of Pulse-Ping Dynamic Videos

Using pulse pings and cubes to measure dynamic videos has broad applications in the MiCi framework, such as:

• Object Motion: Accurately map the motion of physical objects as they traverse the 3D environment.
• Energy Flow: Track energy as it moves and transforms through the space in real-time.
• Field Interactions: Visualize how electromagnetic, gravitational, or other fields interact dynamically over time.
• Data Visualization: Observe how data or information flows and interacts within a system, as cubes track transformations over time.

Further Reading

• Preparing To Blur Density

Next Steps

Continue exploring the MiCi system by delving into the WOW Perspective concept, where we examine how changing the observer's perspective can reveal new layers of understanding within these dynamic transformations.