| name | state-preparation |
| description | Quantum state-preparation algorithms for loading target amplitude vectors into UnitaryLab circuits, including sparse Superposition, Möttönen decomposition, Matrix Product State preparation, recursive Multiplexer preparation, and variational Pauli-word preparation. |
Quantum State Preparation Algorithms
Purpose
This file routes requests for loading target amplitude vectors into quantum circuits.
Use this category when the user asks to prepare a general complex state, exploit sparse support or tensor-network structure, use controlled-rotation decompositions, or optimize a trainable state-preparation circuit.
Routing Rules
- If the user explicitly names Superposition, Möttönen, MPS, Multiplexer, or Pauli-word preparation:
- Read the named leaf skill.
- If the user provides a general complex target state without a method or special structure:
- Read
./mottonen/SKILL.md as the default deterministic route.
- If the target has small computational-basis support or needs coefficient loading followed by a support permutation:
- Read
./superposition/SKILL.md.
- If the user supplies MPS tensors or a known low-bond-dimension representation:
- If the user asks for a recursive probability tree, controlled RY scheduling, or basis-selective phase loading:
- Read
./multiplexer/SKILL.md.
- If the user asks for trainable Pauli-word rotations, fidelity optimization, or variational preparation:
Available Leaf Skills
- Sparse Superposition:
./superposition/SKILL.md
- Möttönen State Preparation:
./mottonen/SKILL.md
- Matrix Product State Preparation:
./mps/SKILL.md
- Multiplexer State Preparation:
./multiplexer/SKILL.md
- Pauli-Word State Preparation:
./pauli/SKILL.md
Response Contract
- Identify the requested method or target structure and determine whether deterministic, approximate, tensor-network, or variational preparation is appropriate.
- Default a general complex target with no special structure or method preference to
./mottonen/SKILL.md.
- Read the matching leaf skill before writing code or commands.
- Keep method-specific APIs, ordering rules, validation tolerances, error metrics, and implementation details in the leaf skill.