On the Statistics of Reaction-Diffusion Simulations for Molecular Communication
May 19, 2015 Β· Declared Dead Β· π Annual International Conference on Nanoscale Computing and Communication
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Adam Noel, Karen C. Cheung, Robert Schober
arXiv ID
1505.05080
Category
physics.chem-ph
Cross-listed
cs.IT
Citations
2
Venue
Annual International Conference on Nanoscale Computing and Communication
Last Checked
3 months ago
Abstract
A molecule traveling in a realistic propagation environment can experience stochastic interactions with other molecules and the environment boundary. The statistical behavior of some isolated phenomena, such as dilute unbounded molecular diffusion, are well understood. However, the coupling of multiple interactions can impede closed-form analysis, such that simulations are required to determine the statistics. This paper compares the statistics of molecular reaction-diffusion simulation models from the perspective of molecular communication systems. Microscopic methods track the location and state of every molecule, whereas mesoscopic methods partition the environment into virtual containers that hold molecules. The properties of each model are described and compared with a hybrid of both models. Simulation results also assess the accuracy of Poisson and Gaussian approximations of the underlying Binomial statistics.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.chem-ph
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Machine learning for molecular simulation
R.I.P.
π
404 Not Found
TorchMD: A deep learning framework for molecular simulations
R.I.P.
π»
Ghosted
Coarse-Graining Auto-Encoders for Molecular Dynamics
R.I.P.
π»
Ghosted
Sampling molecular conformations and dynamics in a multi-user virtual reality framework
R.I.P.
π»
Ghosted
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted