Skip to content

parse

Parser for converting stim circuits to ZX graph representations.

parse_parametric_tag

parse_parametric_tag(
    tag: str,
) -> tuple[str, dict[str, Fraction]] | None

Parse a parametric gate tag like R_Z(theta=0.3*pi).

Supports gates: R_Z, R_X, R_Y, U3.

Parameters:

Name Type Description Default
tag str

The instruction tag to parse, e.g. "R_Z(theta=0.3pi)" or "U3(theta=0.3pi, phi=0.24pi, lambda=0.49pi)".

required

Returns:

Type Description
tuple[str, dict[str, Fraction]] | None

Tuple of (gate_name, params_dict) or None if not a valid parametric tag.

Source code in src/tsim/core/parse.py
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
def parse_parametric_tag(tag: str) -> tuple[str, dict[str, Fraction]] | None:
    """Parse a parametric gate tag like R_Z(theta=0.3*pi).

    Supports gates: R_Z, R_X, R_Y, U3.

    Args:
        tag: The instruction tag to parse, e.g. "R_Z(theta=0.3*pi)" or
             "U3(theta=0.3*pi, phi=0.24*pi, lambda=0.49*pi)".

    Returns:
        Tuple of (gate_name, params_dict) or None if not a valid parametric tag.

    """
    match = re.match(r"^(\w+)\((.*)\)$", tag)
    if not match:
        return None

    gate_name = match.group(1)
    params_str = match.group(2)

    params = {}
    for param in params_str.split(","):
        param = param.strip()
        if not param:
            continue
        # Match param=value*pi (value can be negative/decimal)
        param_match = re.match(r"^(\w+)=([-+]?[\d.]+)\*pi$", param)
        if not param_match:
            return None
        param_name = param_match.group(1)
        value = Fraction(param_match.group(2))
        params[param_name] = value

    return gate_name, params

parse_stim_circuit

parse_stim_circuit(
    stim_circuit: Circuit,
) -> GraphRepresentation

Parse a stim circuit into a GraphRepresentation.

Parameters:

Name Type Description Default
stim_circuit Circuit

The stim circuit to convert.

required

Returns:

Type Description
GraphRepresentation

A GraphRepresentation containing the ZX graph and all auxiliary data.

Source code in src/tsim/core/parse.py
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
def parse_stim_circuit(
    stim_circuit: stim.Circuit,
) -> GraphRepresentation:
    """Parse a stim circuit into a GraphRepresentation.

    Args:
        stim_circuit: The stim circuit to convert.

    Returns:
        A GraphRepresentation containing the ZX graph and all auxiliary data.

    """
    b = GraphRepresentation()

    for instruction in stim_circuit.flattened():
        assert not isinstance(instruction, stim.CircuitRepeatBlock)

        name = instruction.name
        if name in ["QUBIT_COORDS", "SHIFT_COORDS"]:
            # TODO: handle these visualization annotations
            continue

        if name == "I_ERROR":
            continue

        if name == "S" and instruction.tag == "T":
            name = "T"
        elif name == "S_DAG" and instruction.tag == "T":
            name = "T_DAG"

        # Handle parametric gates via tags (e.g., I with tag "R_Z(theta=0.3*pi)")
        if name == "I" and instruction.tag:
            result = parse_parametric_tag(instruction.tag)
            if result is not None:
                gate_name, params = result
                targets = [t.value for t in instruction.targets_copy()]
                for qubit in targets:
                    if gate_name == "R_Z":
                        r_z(b, qubit, params["theta"])
                    elif gate_name == "R_X":
                        r_x(b, qubit, params["theta"])
                    elif gate_name == "R_Y":
                        r_y(b, qubit, params["theta"])
                    elif gate_name == "U3":
                        u3(b, qubit, params["theta"], params["phi"], params["lambda"])
                    else:
                        raise ValueError(f"Unknown parametric gate: {gate_name}")
                continue

        if name == "TICK":
            tick(b)
            continue
        if name == "MPP":
            current_paulis: list[tuple[Literal["X", "Y", "Z"], int]] = []
            invert = False
            targets = instruction.targets_copy()

            for i, target in enumerate(targets):
                # Products are separated by non-combiner boundaries
                if target.is_combiner:
                    continue

                if target.is_x_target:
                    pauli_type = "X"
                elif target.is_y_target:
                    pauli_type = "Y"
                elif target.is_z_target:
                    pauli_type = "Z"
                else:
                    raise ValueError(f"Invalid MPP target: {target}")

                # XOR all inversions - only parity matters (sign is global)
                invert ^= target.is_inverted_result_target

                current_paulis.append((pauli_type, target.value))

                # Product ends if next target is not a combiner (or end of list)
                next_idx = i + 1
                if next_idx >= len(targets) or not targets[next_idx].is_combiner:
                    mpp(b, current_paulis, invert)
                    current_paulis = []
                    invert = False

            continue
        if name == "E" or name == "ELSE_CORRELATED_ERROR":
            if name == "E":
                finalize_correlated_error(b)
            targets = [t.value for t in instruction.targets_copy()]
            types: list[Literal["X", "Y", "Z"]] = []
            for t in instruction.targets_copy():
                if t.is_x_target:
                    types.append("X")
                elif t.is_y_target:
                    types.append("Y")
                elif t.is_z_target:
                    types.append("Z")
                else:
                    raise ValueError(f"Invalid target: {t}")
            correlated_error(b, targets, types, instruction.gate_args_copy()[0])
            continue
        if name == "DETECTOR":
            targets = [t.value for t in instruction.targets_copy()]
            detector(b, targets)
            continue
        if name == "OBSERVABLE_INCLUDE":
            targets = [t.value for t in instruction.targets_copy()]
            args = instruction.gate_args_copy()
            observable_include(b, targets, int(args[0]))
            continue

        # instruction dispatch
        if name not in GATE_TABLE:
            raise ValueError(f"Unknown gate: {name}")

        gate_func, num_qubits = GATE_TABLE[name]
        targets = [t.value for t in instruction.targets_copy()]
        invert = [t.is_inverted_result_target for t in instruction.targets_copy()]
        is_classically_controlled = [
            t.is_measurement_record_target for t in instruction.targets_copy()
        ]
        args = instruction.gate_args_copy()

        for i_target in range(0, len(targets), num_qubits):
            chunk = targets[i_target : i_target + num_qubits]
            cc_chunk = is_classically_controlled[i_target : i_target + num_qubits]
            assert not (invert[i_target] and is_classically_controlled[i_target])
            if invert[i_target]:
                gate_func(b, *chunk, *args, invert=True)
            elif any(cc_chunk):
                gate_func(b, *chunk, *args, classically_controlled=cc_chunk)
            else:
                gate_func(b, *chunk, *args)

    finalize_correlated_error(b)
    return b