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Stochastic Simulations Monday, 9/9/2002 Monte Carlo simulations are generally concerned with large series of computer experiments using uncorrelated random numbers. Explore order out of •Random sampling •Fractoemission •Diffusion •Polymer •Growth model

Stochastic Simulations

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Stochastic Simulations. Monday, 9/9/2002. Random sampling Fractoemission Diffusion Polymer Growth model. Monte Carlo simulations are generally concerned with large series of computer experiments using uncorrelated random numbers. Explore order out of randomness. - PowerPoint PPT Presentation

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Page 1: Stochastic Simulations

Stochastic Simulations

Monday, 9/9/2002

Monte Carlo simulations are generally concerned with large series of computer experiments using uncorrelated random numbers.

Explore order out of randomness

•Random sampling•Fractoemission•Diffusion•Polymer•Growth model

Page 2: Stochastic Simulations

Hit-or-Miss Random Sampling

π ⋅12

22 =nhitnall

π =4nhitnall

Page 3: Stochastic Simulations

Buffon’s Needle

Page 4: Stochastic Simulations

Fracto-emission

Page 5: Stochastic Simulations

Fracto-emission Measuring System

Page 6: Stochastic Simulations

Zigzag Crack Profile Model

Fracto-emission particles bounce at the irregular surfaces.

Page 7: Stochastic Simulations

Longtime Decay of theFracto-emission Intensity

Page 8: Stochastic Simulations

Random Walk

Haphazrad paths on a lattice

A drop of ink through water.

Page 9: Stochastic Simulations

One Dimensional Random Walk

http://polymer.bu.edu/java/java/1drw/1drwapplet.html

Wandering ant

Try and extract an equation from the plot relating the mean squared distance to the step number.

Page 10: Stochastic Simulations

Question

How do the answers change is the probability is p (!= 1/2) to move right and 1-p to move left (a forward- or reverse-biased motion)?

Page 11: Stochastic Simulations

Diffusion

Screen shots of the trajectory of 500 random walkers, started together at the center.

Page 12: Stochastic Simulations

Extension of Random WalkThis model is a two-dimensional extension of a random walk. Displayed is the territory covered by 500 random walkers. As the number of walkers increases the resulting interface becomes more smooth.

Page 13: Stochastic Simulations

Different kinds of random walks on a square lattice

Random Walk (RW): the walker may cross the walk in an infinite number of times with no cost.

Self-Avoiding Walk (SAW): the walker dies when attempting to intersect a portion of the already completed walk.

Growing Self-Avoiding Walk (GSAW): the process proceeds at first as for SAWs, but a walker senses a ‘trap’ and chooses instead between the remaining

‘safe’ directions so that it can cancontinue to grow.

Page 14: Stochastic Simulations

Polymer Model

Bond lengths of polymers tend to be rather fixed as do bond angles. Thus, as a more computationally friendly model we may construct a polymer which is made up of bonds which connect nearest neighbor sites (monomers) on a lattice.

Schematic model for polyethylene

Page 15: Stochastic Simulations

Polymers as Long

Molecular Chains

Page 16: Stochastic Simulations

Self-Avoiding Random Walk

Mean square distance of gyration of a linear polymer molecule consists of N monomer unites has the leading asymptotic behavior

Rg2 =AN2ν

Page 17: Stochastic Simulations

Diffusion Limited Aggregation (DLA)

A seed is placed at the center of the box. A point is chosen at random in the box, excluding a zone around the cluster. A particle then random walks from this point until it either sticks to the cluster or is lost from the box.

Page 18: Stochastic Simulations

DLA Growth Model

http://apricot.polyu.edu.hk/~lam/dla/dla.html

Page 19: Stochastic Simulations

Thermodynamic Force DrivenSelf Assembly

How to grow desired fine nanoscale structures by pre-patterning some coarse structures.

Page 20: Stochastic Simulations

Monte Carlo vs.Kinetic Monte Carlo

pMC =exp−E1 −E2

kBT

⎝ ⎜ ⎞

⎠ ⎟

pkMC =exp−E1 −E2

kBT

⎝ ⎜ ⎞

⎠ ⎟ exp−

EA

kBT

⎝ ⎜ ⎞

⎠ ⎟