compute

name	compute
description	High-performance numerical and quantum compute skill for scientific workloads; use when working on numeric algorithms, simulation, or acceleration.

Skill: Compute

Domain: build | Depth: axiom

Capabilities

• High-performance numerical computation (numpy, scipy, numba)
• JIT compilation for CPU/GPU acceleration (numba)
• Scientific computing: optimization, integration, interpolation (scipy)
• Quantum circuit simulation (qiskit, pennylane, cirq)
• GPU tensor compute via Apple MPS (torch)
• Parallel and vectorized operations

Apple Silicon (local)

Path	Role
agents/core/stream.py	MLX + Ollama streaming
agents/core/memory/vector.py	ONNX Runtime → CoreML EP (Neural Engine) for embeddings
scripts/mlx-neural-bridge.sh	Trinity MLX HTTP helper (mirror nexus-core/mlx-neural-bridge.py)

Libraries

Library	Purpose
numpy	Vectorized array compute
scipy	Scientific algorithms
numba	JIT compilation — CPU/GPU
torch	GPU compute via MPS
qiskit	Quantum circuit simulation
pennylane	Quantum ML and variational circuits
cirq	Google quantum framework

Module

agents/skills/compute.py

Key Functions

• jit_compute(fn, *args) — JIT-compile and run a function
• optimize(fn, x0) — numerical optimization
• fft(signal) — fast Fourier transform
• quantum_circuit(gates) — build and simulate a quantum circuit
• gpu_tensor(data) — move tensor to MPS (Apple GPU)