0fe825a8c53e87badeed22cf263e44c7f5920e48
Spec: docs/superpowers/specs/2026-05-30-c51-atom-span-decouple-from-clamp.md
Diagnosed in cluster v5 (alpha-rl-rjsjq SHA 7064c9269) at step 371:
c51_v_max ratcheted up 1 → 24 → 53 → 859 → 1938 while WIN clamp swung
4910 → 568 → 7540 → 44 (volatile from MARGIN saturation). The slow
EWMA tracking win_bound time-averaged the early spikes, locking
atom span at extreme-value magnitude. Δz reached ~184 per atom — Q
could no longer discriminate +$500 from +$5000 wins.
Root cause: atom-span target was anchored on `MARGIN × pos_max_ema`,
where pos_max is the EXTREME-VALUE statistic across b=1024 batch
elements. The clamp bound (rightly fat-tail) and the atom span (should
be typical-magnitude) were treating two distinct concerns as one.
Fix F: anchor atom span on `atom_margin × mean_abs_pnl_ema` — true
central-tendency signal — while leaving the reward clamp on
pos_max_ema. The clamp can still admit fat-tail wins ($42k → +245)
and V regression (scalar head) retains the magnitude for PPO advantage,
but Q's CATEGORICAL distributional support now sizes itself for the
trades where most learning happens.
New ISV slot 685 (RL_C51_ATOM_MARGIN_INDEX, bootstrap 10.0).
RL_SLOTS_END 685 → 686.
Validation (local b=128 1k smoke):
metric | pre-Fix-F | with Fix F
v_max final | 1929 | 86.6 (22× tighter)
Δz per atom | 184 | 8.7 (resolution restored)
qpa final | +0.957 | +0.958 (Q-π alignment preserved)
mean_active | +$47k | +$34k (within smoke variance)
13/13 risk_stack_invariants + 20/20 trade_management_kernels +
integrated_trainer_smoke pass.
Tradeoff documented in spec: Q loses fat-tail categorical magnitude
(rewards beyond ±87 project to top/bottom atom), but V regression
preserves it. Acceptable for the lottery-ticket strategy where typical-
magnitude resolution matters more than fat-tail magnitude precision.
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.
Description
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%