home / skills / plurigrid / asi / quantum-music
This skill enables quantum-inspired music composition and performance using ZX-calculus notation, quantum circuits, and instruments for expressive, topological
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---
name: quantum-music
description: Quantum computer music composition and performance using quantum circuits, ZX-calculus notation, and quantum instruments
version: 1.0.0
---
# Quantum Music
**Trit**: 0 (ERGODIC - bridging classical and quantum)
**Field**: Quantum Computer Music
**Reference**: Miranda (2022) "Quantum Computer Music" Springer
---
## Overview
Quantum Music encompasses:
1. **Composition**: Using quantum algorithms/circuits
2. **Notation**: ZX-calculus augmented scores
3. **Instruments**: Quantum Guitar, Q1Synth, Actias
4. **Performance**: Live quantum state manipulation
## History
| Year | Milestone |
|------|-----------|
| 2022 | First quantum-composed music (Ludovico Quanthoven) |
| 2022 | Miranda's "Quantum Computer Music" book |
| 2023 | Q1Synth (Miranda, Thomas, Itaboraí) |
| 2024 | Quantum Guitar debuts (Edinburgh) |
| 2024 | Black Tish at Wacken with quantum |
| 2025 | "Bell" composition (ZX notation) |
## Compositional Approaches
### 1. Quantum Random (QRandom)
```python
from qiskit import QuantumCircuit, execute, Aer
def quantum_melody(n_notes, n_pitches=12):
"""Generate melody via quantum measurement."""
qc = QuantumCircuit(4, 4)
qc.h(range(4)) # Superposition
qc.measure(range(4), range(4))
backend = Aer.get_backend('qasm_simulator')
result = execute(qc, backend, shots=n_notes).result()
melody = []
for bitstring, count in result.get_counts().items():
pitch = int(bitstring, 2) % n_pitches
melody.extend([pitch] * count)
return melody
```
### 2. Quantum Walk Composition
```python
def quantum_walk_melody(graph, steps):
"""Melody from quantum walk on graph."""
from discopy.quantum import qubit, H, CNOT
# Initialize walker in superposition
walker = uniform_superposition(len(graph.nodes))
for _ in range(steps):
# Coin flip
walker = apply_coin(walker)
# Shift
walker = apply_shift(walker, graph)
# Measure to get note sequence
return measure_melody(walker)
```
### 3. Grover Search for Harmony
```python
def find_chord(target_quality='major'):
"""Use Grover to find chord voicing."""
# Oracle marks good voicings
oracle = chord_quality_oracle(target_quality)
# Grover iterations
circuit = grover_circuit(oracle, n_qubits=12)
# Measure result
return measure_chord(circuit)
```
## ZX-Calculus Notation
"Bell" by Abdyssagin & Coecke uses ZX as score:
```
Quantum Guitar Grand Piano
│ │
┌──┴──┐ ┌──┴──┐
│ X │ │ Z │
└──┬──┘ └──┬──┘
│ │
└──────────────────────┘
Bell pair
Measurement collapses entanglement
→ Correlated musical phrases
```
## Instruments
| Instrument | Creator | Mechanism |
|------------|---------|-----------|
| Q1Synth | Miranda et al. | Software qubit synth |
| Actias | Moth | Web-based, MIDI control |
| Quantum Guitar | Coecke | Physical + Actias |
| Quantum Piano | Abdyssagin | Mental model + notation |
## Genre Applications
### Industrial/Metal
- Black Tish: Full album with Quantum Guitar
- NIN-style experimentation
- Wacken performances
### Classical/Contemporary
- Cathedral Organ + Quantum Guitar
- "Quantum Universe" Symphony
- Chamber music with ZX notation
### Electronic
- EDM descendants of industrial
- Quantum random for generative
## DisCoPy for Composition
```python
from discopy import Ty, Box, Diagram
from discopy.quantum import qubit, Ket, Bra, H, CX
# Musical types
note = Ty('note')
chord = Ty('chord')
# Quantum composition as diagram
def compose_phrase():
# Prepare Bell state
bell = Ket(0, 0) >> (H @ Id(1)) >> CX
# Map to musical space
to_music = Box('sonify', qubit @ qubit, note @ note)
return bell >> to_music
```
## Live Performance Protocol
```yaml
quantum_music_performance:
setup:
- Actias on dedicated laptop
- MIDI routing configured
- Bloch sphere projection
soundcheck:
- Test foot controllers
- Verify measurement response
- Classical/quantum blend levels
performance:
- Smooth classical→quantum transitions
- Real-time qubit manipulation
- Measured moments for phrase endings
```
## GF(3) Conservation in Music
| Section | Trit | Character |
|---------|------|-----------|
| Intro (classical) | -1 | Grounded |
| Development (quantum) | 0 | Superposed |
| Resolution (measured) | +1 | Collapsed |
**Σ = 0**: Complete musical arc conserves
## References
1. Miranda, E.R. (2022). Quantum Computer Music. Springer
2. Coecke, B. (2025). A Quantum Guitar. arXiv:2509.04526
3. Abdyssagin & Coecke (2025). Bell composition
4. Miranda et al. (2023). Q1Synth. Applied Sciences
---
**Skill Name**: quantum-music
**Type**: Composition / Performance
**Trit**: 0 (ERGODIC)
## Non-Backtracking Geodesic Qualification
**Condition**: μ(n) ≠ 0 (Möbius squarefree)
This skill is qualified for non-backtracking geodesic traversal.
## SDF Interleaving
This skill connects to **Software Design for Flexibility** (Hanson & Sussman, 2021):
### Primary Chapter: 1. Flexibility through Abstraction
**Concepts**: combinators, compose, parallel-combine, spread-combine, arity
### GF(3) Balanced Triad
```
quantum-music (○) + SDF.Ch1 (+) + [balancer] (−) = 0
```
**Skill Trit**: 0 (ERGODIC - coordination)
### Connection Pattern
Combinators compose operations. This skill provides composable abstractions.
This skill implements quantum computer music composition and live performance tools that combine quantum circuits, ZX-calculus notation, and hybrid quantum-classical instruments. It provides generation techniques (quantum random, quantum walks, Grover-based harmony), notation mapping using ZX diagrams, and practical instrument interfaces like a software qubit synth and MIDI bridges. The goal is actionable primitives for composing, sonifying, and performing with quantum states.
The skill exposes routines to build and run small quantum circuits that map measurement outcomes to pitches, chords, or control parameters. It translates ZX-calculus diagrams into musical routing and correlation patterns, and offers adapters to common audio/MIDI systems and web instruments for real-time control. Performance protocols coordinate state preparation, measurement timing, and classical–quantum blending to produce reproducible yet stochastic musical material.
Do I need a quantum computer to use this skill?
No. You can run algorithms on simulators for composition and testing. Hardware access is optional for live hardware-driven performance.
How do ZX diagrams map to sound?
ZX diagrams represent entanglement and information flow; map nodes and wires to instrument channels and correlated MIDI events so that measurement correlations produce linked musical outcomes.