Economic Model
I. Block Rewards
We adopt a Logarithmic Decay Algorithm based on issuance ratio (LSED model).
The core logic is based on the formula log2(1 / (1 - ratio))
, and the emission decay presents a 1/2ⁿ
pattern.
1. Mathematical Expression of the Decay Algorithm
R
is the current total issuance (total_issuance)S
is the total supply (total_supply) = 21,000,000 HETUE₀
is the default block reward: 1 HETU/blockr = R / S
is the current issuance ratio (0 ≤ r < 1)E(r)
is the current actual reward
Then:
If
r ≥ 1
,E(r) = 0
2. Trigger Points of Each Decay Cycle
0
0% ~ 50%
1
1
50% ~ 75%
0.5
2
75% ~ 87.5%
0.25
3
87.5% ~ 93.75%
0.125
4
93.75% ~ 96.875%
0.0625
5
96.875% ~ 98.4375%
0.03125
6
98.4375% ~ 99.21875%
0.015625
...
...
...
3. Cycle Schedule Calculated Based on 12-Second Blocks
Total supply: 21,000,000 HETU
Initial reward per block: 1 HETU
Block generation speed: 12 seconds/block ≈ 5 blocks/minute
We estimate the duration based on the amount of HETU that can be released in each stage:
0
1
0% ~ 50%
10,500,000
~4
0 ~ 10.5M
1
0.5
50% ~ 75%
5,250,000
~4
10.5M ~ 15.75M
2
0.25
75% ~ 87.5%
2,625,000
~4
15.75M ~ 18.375M
3
0.125
87.5% ~ 93.75%
1,312,500
~4
...
...
...
...
...
~4
...
4. Reward Decay Curve (Issuance Ratio vs. Block Reward)
(Exponential decay graph with issuance ratio on the horizontal axis and block reward on the vertical axis)

Horizontal axis: proportion of total issuance (0% to 100%)
Vertical axis: block reward (unit: HETU)
The reward decreases exponentially, and a halving is triggered whenever the issuance ratio reaches
1 - 1/2ⁿ
5. Release Model Curve

II. Block Reward Allocation
1. Introduction to Block Rewards
Stakework rewards (subnet rewards)
Main network rewards
Community (community pool): 2%
Validator (commission): 5%
Validator (validator rewards, allocated according to weight and delegation): 93%

2. Introduction to Subnet Rewards
(1) Algorithm Introduction
Logarithmic Subnet Incentive (LSI) "logarithmic" subnet reward mechanism
Calculation formula:
subnet_reward_ratio = min( max_ratio, base + k * log(1 + subnet_count) )
Where:
base: Initial subnet reward ratio (e.g., 0.10)
k: Growth rate coefficient (e.g., 0.16)
max_ratio: Maximum subnet reward ratio (e.g., 0.9)
(2) Calculation Process
0
0
1
0.1109035489
2
0.1757779662
3
0.2218070978
4
0.257510066
5
0.2866815151
6
0.3113456238
7
0.3327106467
8
0.3515559324
9
0.3684136149
10
0.3836632436
(3) Subnet Reward Growth Curve Chart:

As the number of subnets increases, the reward ratio gradually increases.
The growth rate is controlled by the parameter k.
The reward ratio is limited by the maximum value of max_ratio = 0.9, and it will not increase after reaching the upper limit.
Explanation:
Initial stage (number of subnets < 50)
The ratio starts from
base=0.10
and grows slowly withlog(1+subnet_count)
.For example:
1 subnet:
0.10 + 0.1*log(2) ≈ 0.17
10 subnets:
0.10 + 0.1*log(11) ≈ 0.34
Rapid growth stage (50 ≤ number of subnets < 300)
The logarithmic function enters a significant growth interval, and the ratio rises rapidly.
For example:
100 subnets:
0.10 + 0.1*log(101) ≈ 0.56
200 subnets:
0.10 + 0.1*log(201) ≈ 0.66
Saturation stage (number of subnets ≥ 300)
When the ratio is close to
max_ratio=0.9
, the formula triggers themin()
function to limit growth.Calculation of the turning point:
0.10 + 0.1*log(1+x) = 0.9
→log(1+x)=8
→x≈e⁸≈2981
Actually, due to the limitation of calculation accuracy, it is close to the upper limit when x≈300 in the figure.
After that, the ratio remains unchanged at
0.9
(horizontal line).
3. Incentive Sharing Curve Chart

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