Ahuja, A., Desrochers, T. M., & Sheinberg, D. L. (2021). A role for visual areas in physics simulations. Cognitive neuropsychology, 38(7-8), 425–439.
https://doi.org/10.1080/02643294.2022.2034609
This article explores the process of making predictions about physical scenes and suggests that simulation, or the ability to introspectively manipulate mental models of the world, plays a crucial role in this process. The study aimed to investigate the neural mechanisms of simulation by examining whether simulating physical events activates visual areas associated with imagery-like representations. Using functional magnetic resonance imaging, the researchers found that when participants were asked to predict the trajectory of a falling ball, motion-sensitive brain regions were activated, resembling patterns observed during actual perception of motion. This suggests that mental simulations recreate sensory representations of how a physical scene is likely to unfold.
Altvater, A. (2023, May 2). What is SDLC? understand the software development life cycle. Stackify.
https://stackify.com/what-is-sdlc/
This article provides an overview of the Software Development Life Cycle (SDLC) and its six phases: requirement analysis, planning, software design, development, testing, and deployment. It highlights the importance of SDLC in producing high-quality software efficiently and at a low cost. The article emphasizes the significance of testing throughout the SDLC process and encourages organizations to focus more on testing to avoid rework and save time and money. It also outlines best practices for each stage, including identifying current problems, planning, design, development, code testing, and software deployment. The stages are described as essential for a smooth, efficient, and productive software development process.
Hecker, C. (n.d.). Rigid body dynamics.
https://www.chrishecker.com/Rigid_Body_Dynamics
Article by Chris Hecker on angular physics in games. The article covers the important equations for doing linear rigid body dynamics, such as position, velocity, acceleration, force, center of mass, and momentum for a rigid body. It then introduces rotational motion as another aspect that needs to be considered. Many of these are counterparts to linear motion, but some important equations are for angular momentum, torque, and moment of inertia. These equations are enough to start creating a working simulation.
Nasrollahi, S. (2021, June 25). Real-time physics simulations and machine learning. Medium.
https://seyedhn.medium.com/real-time-physics-simulations-and-machine-learning-90e6e1ef1b3d
An article that describes the various ways that real-life is simulated, with there being a trade-off between accuracy and speed. For instance, rigid-body dynamics are useful for non-deforming objects, it’s not suitable for hair and clothes that don’t fit the criteria. For those, you would use soft-body dynamics models such as Spring-Mass, PBD, FEM and MPM to differing degrees of accuracy and speed. While there was little room for improvement in physics simulations, the article describes the use of machine learning, which has been found to potentially increase speeds by 2 billion times. It accomplishes this by using trained neural network model to predict the the behavior, and emulate an actual physics solver.
Turkle, S. (2017, August 29). The value of simulation. Physics World.
https://physicsworld.com/a/the-value-of-simulation
Computer simulations have revolutionized many areas of science and engineering. The use of simulations can also be associated with an increasing distance from physical reality. Simulations can offer advantages in many fields. Users should be concerned about their reliance on “black box” software that they do not fully understand. Science progresses by building on previous work, rather than by scientists re-inventing the wheel; in many cases, simply understanding the principles behind the wheel is sufficient.
YouTube. (2020). The History of Super Mario 64’s BLJ. YouTube. Retrieved June 13, 2023, from
https://www.youtube.com/watch?v=gKf_bFNXuu8&t=1s
Video going through the history of the backwards long jump exploit found in Super Mario 64. There is an explanation on how the exploit is done, and the principles which allow it to work. Essentially, the act of long jumping backwards allows for theoretically infinite velocity which causes the displacement of each frame to directly bypass hit-boxes without being detected.