scholarly journals The size of the primes obstructing the existence of rational points

2020 ◽  
pp. 1-53
Author(s):  
E. Sofos
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Prime Numbers ◽  
Rational Points ◽  
Arithmetic Geometry ◽  
Random Behaviour ◽  
Typical Variety

Abstract The sequence of prime numbers p for which a variety over ℚ has no p-adic point plays a fundamental role in arithmetic geometry. This sequence is deterministic, however, we prove that if we choose a typical variety from a family then the sequence has random behaviour. We furthermore prove that this behaviour is modelled by a random walk in Brownian motion. This has several consequences, one of them being the description of the finer properties of the distribution of the primes in this sequence via the Feynman–Kac formula.

Self-avoiding random walk: A Brownian motion model with local time drift

1987 ◽  
Vol 74 (2) ◽  
pp. 271-287 ◽  
Author(s):  
J. R. Norris ◽  
L. C. G. Rogers ◽  
David Williams
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Local Time ◽  
Motion Model ◽  
Time Drift ◽  
Brownian Motion Model

scholarly journals Thick points for planar Brownian motion and the Erdős-Taylor conjecture on random walk

2001 ◽  
Vol 186 (2) ◽  
pp. 239-270 ◽  
Author(s):  
Amir Dembo ◽  
Yuval Peres ◽  
Jay Rosen ◽  
Ofer Zeitouni
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Planar Brownian Motion ◽  
Thick Points

Extremes in Branching Random Walk and Branching Brownian Motion

2013 ◽  
Vol 10 (2) ◽  
pp. 1205-1251
Author(s):  
Louigi Addario-Berry ◽  
Nathanaël Berestycki ◽  
Nina Gantert
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Branching Random Walk ◽  
Branching Brownian Motion

scholarly journals A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Bao Pang ◽  
Yong Song ◽  
Chengjin Zhang ◽  
Hongling Wang ◽  
Runtao Yang
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Swarm Robotics ◽  
Search Strategy ◽  
Lévy Flight ◽  
Step Size ◽  
Levy Flight ◽  
Random Walk Method ◽  
Robotic Exploration ◽  
Exploration Mission

An environment can be searched far more efficiently if the appropriate search strategy is used. Because of the limited individual abilities of swarm robots, namely, local sensing and low processing power, random searching is the main search strategy used in swarm robotics. The random walk methods that are used most commonly are Brownian motion and Lévy flight, both of which mimic the self-organized behavior of social insects. However, both methods are somewhat limited when applied to swarm robotics, where having the robots search repeatedly can result in highly inefficient searching. Therefore, by analyzing the characteristics of swarm robotic exploration, this paper proposes an improved random walk method in which each robot adjusts its step size adaptively to reduce the number of repeated searches by estimating the density of robots in the environment. Simulation experiments and experiments with actual robots are conducted to study the effectiveness of the proposed method and evaluate its performance in an exploration mission. The experimental results presented in this paper show that an area is covered more efficiently using the proposed method than it is using either Brownian motion or Lévy flight.

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