rqm-circuits

Canonical external circuit IR for the RQM Technologies quantum software stack.

What is rqm-circuits?

rqm-circuits is the single source-of-truth wire format for API and Studio traffic in the RQM Technologies quantum software stack. It defines the canonical circuit object model that sits between the quaternion math layer and the internal optimization engine.

Architecture

rqm-core       – quaternion/math foundation
rqm-circuits   – canonical external circuit IR   ← you are here
rqm-compiler   – internal optimization / canonicalization engine
rqm-qiskit     – Qiskit translation/execution bridge
rqm-braket     – Amazon Braket translation/execution bridge
rqm-api        – hosted API (accepts rqm-circuits JSON payloads)
Studio         – visual circuit editor (emits rqm-circuits JSON payloads)

Key roles:

• rqm-circuits = canonical external circuit IR. API payloads and Studio traffic use rqm-circuits as the wire format. The JSON representation is versioned and stable.
• rqm-compiler = internal engine. Compiler descriptors are internal; they are not the public API payload.
• rqm-circuits is lightweight and backend-neutral: no dependency on Qiskit, Braket, or rqm-compiler.

What it is NOT

• Not a backend adapter
• Not a transpiler to Qiskit / Braket / PennyLane
• Not a simulator
• Not a quaternion math library (rqm-core handles that)
• Not the compiler's internal IR (rqm-compiler has its own descriptor types)

Quaternion connection

Every single-qubit SU(2) gate can be represented exactly as a unit quaternion

q = cos(θ/2) + u·sin(θ/2)

where u is the unit pure-imaginary quaternion (rotation axis) and θ is the physical Bloch-sphere rotation angle. rqm-circuits annotates each standard gate with its quaternion form (gate.quaternion_form) as an informational field. The mathematical evaluation of those forms lives in rqm-core.

Rx(angle) → q = cos(angle/2) + i·sin(angle/2)
Ry(angle) → q = cos(angle/2) + j·sin(angle/2)
Rz(angle) → q = cos(angle/2) + k·sin(angle/2)
H         → q = (i+k)/√2   (π-rotation about (x̂+ẑ)/√2)
X         → q = i           (π-rotation about x̂)
Y         → q = j           (π-rotation about ŷ)
Z         → q = k           (π-rotation about ẑ)

phaseshift(angle) has matrix diag(1, exp(i·angle)); its quaternion metadata uses the determinant-one Rz(angle) representative, which is equivalent up to global phase.

The universal single-qubit gate u1q is parameterised directly by the unit quaternion components (w, x, y, z):

u1q(w, x, y, z) → q = w + xi + yj + zk  (|q| = 1)

Standard two-qubit interaction rotations use the same half-angle convention:

c = Circuit(num_qubits=2)
c.rxx(0.25, 0, 1)
c.ryy(0.50, 0, 1)
c.rzz(0.75, 0, 1)

Their matrices are exp[-i·angle·P/2] for P = X⊗X, Y⊗Y, or Z⊗Z. These families are entangling-capable, but a nonzero angle—especially for rzz—does not imply that every input state becomes entangled.

Better Coordinates for Better Measurement

This project uses quaternions because they preserve more of what physical systems are doing: phase, rotation, orientation, polarization, and coherence. Standard complex-number methods are powerful, but they can flatten these relationships too early. Quaternionic coordinates keep them together as one structured object, giving software a richer view of the measured system.

For RQM Technologies, better coordinates mean better measurement: more informative diagnostics, cleaner transformations, and more precise control across quantum, wave, sensing, imaging, and communications workflows.

Install

pip install rqm-circuits

Or for development:

git clone https://github.com/RQM-Technologies-dev/rqm-circuits.git
cd rqm-circuits
pip install -e ".[dev]"

Quick start

Bell circuit

from rqm_circuits import Circuit, make_instruction

# Create a 2-qubit Bell circuit
c = Circuit(num_qubits=2, name="bell")
c.add(make_instruction("h", targets=[0]))
# cx: supply the control qubit via controls=, the target via targets=
c.add(make_instruction("cx", targets=[1], controls=[0]))

print(c.summary())
# Circuit 'bell': 2 qubit(s), 0 clbit(s), 2 instruction(s)
#   [  0] h  q[0]
#   [  1] cx ctrl:q[0]  q[1]

GHZ circuit

from rqm_circuits import Circuit, make_instruction

n = 3
c = Circuit(num_qubits=n, name="ghz")
c.add(make_instruction("h", [0]))
for i in range(1, n):
    c.add(make_instruction("cx", targets=[i], controls=[0]))

Rotation gate with a parameter

import math
from rqm_circuits import Circuit, make_instruction, Parameter

c = Circuit(num_qubits=1, name="rotation")
# Canonical parameter name for all rotation gates is "angle"
c.add(make_instruction("rx", targets=[0], params=[Parameter("angle", value=math.pi / 2)]))

Phase-shift gate

from rqm_circuits import Circuit, make_instruction, Parameter

c = Circuit(num_qubits=1)
c.add(make_instruction("phaseshift", targets=[0], params=[Parameter("angle", value=0.5)]))

Universal single-qubit gate (u1q)

import math
from rqm_circuits import Circuit, make_instruction, Parameter

# Hadamard expressed as a unit quaternion
norm = 1.0 / math.sqrt(2)
c = Circuit(num_qubits=1)
c.add(make_instruction(
    "u1q", targets=[0],
    params=[
        Parameter("w", value=0.0),
        Parameter("x", value=norm),
        Parameter("y", value=0.0),
        Parameter("z", value=norm),
    ],
))

Symbolic (unbound) parameter

c = Circuit(num_qubits=1)
c.add(make_instruction("rz", targets=[0], params=[Parameter("angle")]))

from rqm_circuits import is_parametric
print(is_parametric(c))  # True

Measurement

c = Circuit(num_qubits=1, num_clbits=1)
c.add(make_instruction("x", targets=[0]))
c.add(make_instruction("measure", targets=[0], clbits=[0]))

JSON serialization

rqm-circuits is designed as an API-ready IR layer. Every circuit serializes to a clean, deterministic JSON payload (schema version "0.2").

from rqm_circuits import Circuit, make_instruction

c = Circuit(num_qubits=2, name="bell")
c.add(make_instruction("h", [0]))
c.add(make_instruction("cx", targets=[1], controls=[0]))

# Serialize
json_str = c.to_json()
print(json_str)

# Deserialize
c2 = Circuit.from_json(json_str)
assert c == c2

Example JSON output:

{
  "instructions": [
    {
      "gate": {
        "arity": 1,
        "categories": ["clifford", "single_qubit"],
        "description": "Hadamard gate.  π-rotation about the (x+z)/√2 axis.",
        "name": "h",
        "num_params": 0,
        "quaternion_form": "q = (i+k)/√2  (axis = (x̂+ẑ)/√2, angle = π)"
      },
      "targets": [{"index": 0, "type": "qubit"}]
    },
    {
      "controls": [{"index": 0, "type": "qubit"}],
      "gate": {
        "arity": 1,
        "categories": ["clifford", "two_qubit"],
        "description": "Controlled-X (CNOT) gate.  One control qubit, one target qubit.",
        "name": "cx",
        "num_controls": 1,
        "num_params": 0
      },
      "targets": [{"index": 1, "type": "qubit"}]
    }
  ],
  "name": "bell",
  "num_qubits": 2,
  "schema_version": "0.2"
}

Schema versioning

Schema "0.1" payloads are accepted on ingestion and transparently normalized. Adding the Pauli-pair rotations is backward-compatible, so no existing payload shape or accepted schema version changes.

IR analysis helpers

from rqm_circuits import (
    circuit_depth,
    gate_counts,
    has_measurements,
    is_parametric,
    qubit_usage,
    filter_by_category,
    GateCategory,
)

print(circuit_depth(c))          # 2
print(gate_counts(c))            # {'cx': 1, 'h': 1}
print(has_measurements(c))       # False
print(is_parametric(c))          # False
print(qubit_usage(c))            # {0: [0, 1], 1: [1]}

Standard gate set

Controlled gates (cx, cy, cz): supply the control qubit via controls=[{"index": ctrl}] and the target qubit via targets=[{"index": tgt}]. The legacy encoding (both qubits in targets, arity=2) is still accepted on ingestion for schema "0.1" backward compatibility.

Rotation gates (rx, ry, rz, phaseshift, rxx, ryy, rzz): the canonical parameter name is "angle". Legacy names "theta" and "phi" are silently normalized to "angle" on ingestion.

Package layout

src/rqm_circuits/
    __init__.py        Public API surface
    circuit.py         Circuit class
    gates.py           Gate definitions + standard registry
    instructions.py    Instruction model + make_instruction()
    registers.py       QubitRef / ClassicalBitRef
    params.py          Parameter (concrete + symbolic)
    validators.py      Validation rules
    serialization.py   JSON helpers + schema versioning
    ir.py              IR analysis utilities
    errors.py          Custom exceptions
    types.py           Type aliases and enumerations
    schema.py          JSON Schema + TypedDict definitions
tests/
    test_circuit.py
    test_gates.py
    test_serialization.py
    test_validation.py
    test_schema.py
    test_new_features.py

Error handling

All errors are structured and human-readable:

Breaking changes (schema 0.1 → 0.2)

Schema "0.1" payloads remain accepted on ingestion; they are transparently normalized to the "0.2" internal representation.

Development

pip install -e ".[dev]"
pytest

License

Apache License 2.0 — see LICENSE.