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17 lines
1.4 KiB
YAML
17 lines
1.4 KiB
YAML
# Full scaled-k parameter sweep. Mean accuracy / q_eff / convergence are k-invariant,
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# so k is scaled down for tractability; re-run headline + variance figures at full scale
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# with fullscale.yaml.
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# Sweep axes (cartesian product x replicates); every value is a list.
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n_nodes: [1000, 2000, 4000] # number of nodes / stake holders
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stake_dist: [uniform, pareto] # stake distribution (uniform = equal, pareto = heavy-tailed)
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latency: [0, 1, 2, 4, 6, 8, 10, 15, 20, 30] # L: network latency in slots; block visible at t+L
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max_uncles: [0, 1, 2, 3, 4, 8, 10] # U: max uncle references per block (0 = baseline)
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uncle_strategy: [oldest, random] # uncle selection: oldest-first fill vs random coin-flip
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replicates: 12 # independent RNG replicates per grid cell
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base: # per-run settings shared by every cell (not swept)
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k: 256 # security parameter (scaled; T = 6*floor(256/f) = 46080 slots)
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epochs: 75 # epochs simulated per trajectory
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f: 0.03333333333333333 # slot activation coefficient (default 1/30); configurable
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genesis_d_factor: 0.5 # genesis D_est = factor x true total stake
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pareto_shape: 1.16 # Pareto (Lomax) tail index for the pareto stake distribution
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