Controls alpha value curve shape.
Current Value
0xe803The Big Picture
Alpha values in Liquid Alpha use a sigmoid function to map inputs to outputs. Steepness controls how quickly the sigmoid transitions from low to high values. High steepness = sharp transition (binary-like); low steepness = gradual transition (smooth gradient). This shapes how alpha responds to network conditions.
Why This Matters
Steepness affects how alpha changes with stake or performance. High steepness creates sharp cutoffs; low steepness creates gradual transitions. Your position matters less with low steepness.
Example
With high steepness, crossing a threshold might jump your alpha from 0.2 to 0.8 quickly. With low steepness, the same threshold crossing moves alpha gradually from 0.4 to 0.6. Sharp vs smooth incentive curves.
Common Questions
- What is alpha in this context?
- Alpha is a parameter in Liquid Alpha mechanics affecting emission distribution. It adjusts based on stake, performance, and other factors via this sigmoid function.
- Can subnet owners adjust steepness?
- Typically via hyperparameters. Different subnets may prefer sharper or smoother incentive curves based on their goals.
From Chain Metadata
AlphaSigmoidSteepness constant.
Use Cases
- Alpha calculations
Code Examples
import { ApiPromise, WsProvider } from "@polkadot/api";
import { stringCamelCase } from "@polkadot/util";
const provider = new WsProvider("wss://entrypoint-finney.opentensor.ai:443");
const api = await ApiPromise.create({ provider });
// Query InitialAlphaSigmoidSteepness constant
const value = api.consts[stringCamelCase("SubtensorModule")][stringCamelCase("InitialAlphaSigmoidSteepness")];
console.log("InitialAlphaSigmoidSteepness:", value.toHuman());Type Information
- Type
- i16
- Byte Size
- 2 bytes
- Encoding
- fixed
- Raw Hex
- 0xe803
Version History
Runtime Info
- Pallet
- SubtensorModule
- First Version
- v273
- Latest Version
- v273
- Current Runtime
- v393