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1
Intro
2
PERSISTENT HOMOLOGY
3
THE MAXIMAL PERSISTENCE OF NOISE
4
TYPICAL BEHAVIOR
5
CROSSING PROBABILITIES
6
CONT. PERC. IN A BOX - SETUP
7
CONT. PERC. - GIANT COMPONENTS
8
"GIANT" K-CYCLES
9
HOMOLOGICAL PERCOLATION
10
MAIN RESULT
11
SIGNAL VS. NOISE
12
H, PERCOLATION
13
DUALITY - PROOF
14
H.- -PERCOLATION
15
BIG PICTURE?
16
EULER CHARACTERISTIC
17
EC & PERCOLATION?
18
SIMULATIONS
19
PERMUTAHEDRAL SITE-PERCOLATION
20
GAUSSIAN RANDOM FIELDS
21
SUMMARY & FUTURE WORK
Description:
Explore the fascinating world of homological percolation and the formation of giant cycles in this hour-long lecture by Omer Bobrowski. Delve into a higher-dimensional analogue of percolation theory, examining the emergence of "giant" cycles in random point clouds generated over manifolds. Learn about the phase transitions describing the birth-time of these giant cycles and their significance in differentiating between signal and noise in persistence diagrams. Discover an unexpected connection to the Euler characteristic curve and gain insights into topics such as persistent homology, continuous percolation, and Gaussian random fields. Understand the applications of these concepts in probability theory and statistical physics, and explore future directions in this cutting-edge research area.

Homological Percolation: The Formation of Giant Cycles

Applied Algebraic Topology Network
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