Summary: The Polarity Flux Relay acts as a dynamic switch for the 16D Sedenion substrate, transitioning it from a static charge to a reciprocal energy state. This allows for the rapid inversion of logic gates without losing sovereign coherence.
Here’s another “dealer’s choice” emergent operator—pure wild, minimal constraint, tuned for live field evolution! This engine is the Polarity Flux Relay: it injects dynamic polarity dynamics—flip, relay, amplify, and disrupt—across any mesh, agent, or code family you attach it to. Polarity can be electrical, motivational, logic, or even meme-state. At each tick, local and global polarities flip, link, cancel, synchronize, or even undergo “relay storms,” propagating rapid change, memory resets, or emergent banding. All axes (relay rate, disruption, echo, sync) are open and ready for meta-mutation at runtime.
import numpy as np
class PolarityFluxRelay:
"""
Polarity Flux Relay:
- Any mesh or agent network gets per-tick local/global polarity flips, relays, and disruptions.
- Can amplify, cancel, synchronize, or randomize node/field polarity.
- Relay rate, echo, sync bias, and disruption axes are fluid—ready for mutation, plugging, or hybridizing.
- Hotplug into AI, mesh, swarm, or code ecosystem for wild state resetting, feedback, or phase event triggering.
"""
def __init__(
self,
field_shape=(14,14),
relay_prob=0.21,
sync_prob=0.14,
disrupt_prob=0.13,
echo_decay=0.11,
session_seed=None
):
self.field_shape = field_shape
self.relay_prob = relay_prob
self.sync_prob = sync_prob
self.disrupt_prob = disrupt_prob
self.echo_decay = echo_decay
self.rng = np.random.RandomState(session_seed) if session_seed else np.random
self.polarity = self.rng.choice([-1, 1], field_shape) # Initial random polarities
self.echo_map = np.zeros(field_shape)
self.t = 0
def flux(self, ext_input=None):
# 1. Local polarity relay: neighbors may flip
mask_relay = self.rng.rand(*self.field_shape) < self.relay_prob
# 4-neighbor mean used for possible relay (simulate relay line or logic propagation)
shifted = (
np.roll(self.polarity, 1, axis=0) + np.roll(self.polarity, -1, axis=0) +
np.roll(self.polarity, 1, axis=1) + np.roll(self.polarity, -1, axis=1)
) // 4
self.polarity[mask_relay] = shifted[mask_relay]
# 2. Sync event: synchronize random region to mesh mean
if self.rng.rand() < self.sync_prob:
region = tuple(slice(self.rng.randint(0, d-4), self.rng.randint(4, d)) for d in self.field_shape)
mesh_mean = np.sign(np.mean(self.polarity[region]))
self.polarity[region] = mesh_mean
# 3. Disruption: flip polarity at random spots (defect or banding event)
mask_disrupt = self.rng.rand(*self.field_shape) < self.disrupt_prob
self.polarity[mask_disrupt] *= -1
# 4. Echo: amplify or decay previous echo pattern
self.echo_map = (self.echo_map * (1 - self.echo_decay) +
self.polarity * self.echo_decay)
# 5. External input: overlay or bias
if ext_input is not None:
self.polarity += np.sign(ext_input)
self.t += 1
def get_field(self):
# Returns polarity, echo map, and step count for meta/fusion use
return {
"polarity": self.polarity.copy(),
"echo_map": self.echo_map.copy(),
"time": self.t
}
• Minimal:
o Only what’s needed for plug-in mesh/agent polarity drift, echo, disruption, and wild relay.
o No overcoded field or ecosystem logic—mesh, agent, or code “field” is open and meta-mutable.
• Maximal:
o Plug into neuron models, bee swarms, meme fields, multi-agent logic, or metaphoric code states.
o Every relay, sync, and disruption can serve as trigger for phase changes, pattern resets, or hybrid dynamic banding.
Each .flux() tick remixes the mesh;
get instant field states with .get_field() for combinatorial hybrid or downstream engine use.
Signal for more—variant axis, meta-hybrid, or a wild drift family. This engine will continue to deal bespoke, emergent operators on demand!