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Understanding the Structure of Physical Laws

This introduction discusses the world's effective description, systems and their approximations, modeling examples, symmetries and their role in physical laws, as well as the best fit fields algorithm. It also explores the reduction of trajectory from field formalism.

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Understanding the Structure of Physical Laws

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  1. Introduction

  2. Herbert Goldstein (1922-2005) Charles P. Poole John L. Safko The textbook “Classical Mechanics” (3rd Edition) By H. Goldstein, C. P. Poole, J. L. Safko Addison Wesley, ISBN: 0201657023 Misprints: http://astro.physics.sc.edu/goldstein/

  3. World picture • The world is imbedded in independent variables (dimensions) xn • Effective description of the world includes fields (functions of variables): • Only certain dependencies of the fields on the variables are observable – ηm(xn)– we call them physical laws

  4. Systems • Usually we consider only finite sets of objects: systems • Complete description of a system is almost always impossible: need of approximations (models, reductions, truncations, etc.) • Some systems can be approximated as closed, with no interaction with the rest of the world • Some systems can not be adequately modeled as closed and have to be described as open, interacting with the environment

  5. Example of modeling • To describe a mass on a spring as a harmonic oscillator we neglect: • Mass of the spring • Nonlinearity of the spring • Air drag force • Non-inertial nature of reference frame • Relativistic effects • Quantum nature of motion • Etc. • Account of the neglected effects significantly complicates the solution

  6. World picture • How to find the rules that separate the observable dependencies from all the available ones? • Approach that seems to work so far: use symmetries (structure) of the system • Symmetry - property of a system to remain invariant (unchanged) relative to a certain operation on the system

  7. Symmetries and physical laws (observable dependencies) • Something we remember from the kindergarten: • For an object on the surface with a translational symmetry, the momentum is conserved in the direction of the symmetry: p = const p ≠ const

  8. Physical Laws Physical Laws Structure Structure • Symmetries and physical laws (observable dependencies) • Observed dependencies (physical laws) should somehow comply with the structure (symmetries) of the systems considered How? Best Fit

  9. Fields Physical Laws Best Fit Fields Structure Structure • Recipe • 1. Bring together structure and fields • 2. Relate this togetherness to the entire system • 3. Make them fit best when the fields have observable dependencies:

  10. Algorithm • 1. Construct a function of the fields and variables, containing structure of the system • 2. Integrate this function over the entire system: • 3. Assign a special value for I in the case of observable field dependencies:

  11. Some questions • Why such an algorithm? • Suggest anything better that works • How difficult is it to construct an appropriate relationship between system structure and fields? • It depends. You’ll see (here and in other physics courses) • Is there a known universal relationship between symmetries and fields? • Not yet • How do we define the “best fit” value for I ? • You’ll see

  12. Evolution of a point object • How about time evolution of a point object in a 3D space (trajectory)? • At each moment of time there are three (Cartesian) coordinates of the point object • Trajectory can be obtained as a reduction from the field formalism

  13. Trajectory: reduction from the field formalism • Let us introduce 3 fields R1(x’,y’,z’,t), R2(x’,y’,z’,t), and R3(x’,y’,z’,t) • We can picture those three quantities as three components of a vector (vector field)

  14. And they move! • Trajectory: reduction from the field formalism • Different points (x’,y’,z’) are associated with different values of three time-dependent quantities

  15. Trajectory: reduction from the field formalism • Here comes a reduction: the vector field iz zero everywhere except at the origin (or other fixed point) No (x’,y’,z’) dependence!

  16. How about our algorithm? • 1. • 2.

  17. How about our algorithm? • 3. • Let’s change notation • Not bad so far!!! 

  18. Questions?

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