---
title: GMS (v1.0)
description: API reference for qiskit.circuit.library.GMS in qiskit v1.0
source: https://eu-de.quantum.cloud.ibm.com/docs/en/api/qiskit/1.0/qiskit.circuit.library.GMS
---

# GMS

*class* `qiskit.circuit.library.GMS(num_qubits, theta)`

[GitHub](https://github.com/Qiskit/qiskit/tree/stable/1.0/qiskit/circuit/library/generalized_gates/gms.py#L27-L93)

Bases: [`QuantumCircuit`](/docs/api/qiskit/1.0/qiskit.circuit.QuantumCircuit "qiskit.circuit.quantumcircuit.QuantumCircuit")

Global Mølmer–Sørensen gate.

**Circuit symbol:**

```python
     ┌───────────┐
q_0: ┤0          ├
     │           │
q_1: ┤1   GMS    ├
     │           │
q_2: ┤2          ├
     └───────────┘
```

**Expanded Circuit:**

![../\_images/qiskit-circuit-library-GMS-1.png](https://eu-de.quantum.cloud.ibm.com/docs/images/api/qiskit/1.0/qiskit-circuit-library-GMS-1.avif)

The Mølmer–Sørensen gate is native to ion-trap systems. The global MS can be applied to multiple ions to entangle multiple qubits simultaneously \[1].

In the two-qubit case, this is equivalent to an XX(theta) interaction, and is thus reduced to the RXXGate. The global MS gate is a sum of XX interactions on all pairs \[2].

$$
GMS(\chi_{12}, \chi_{13}, ..., \chi_{n-1 n}) =
exp(-i \sum_{i=1}^{n} \sum_{j=i+1}^{n} X{\otimes}X \frac{\chi_{ij}}{2})
$$

**References:**

\[1] Sørensen, A. and Mølmer, K., Multi-particle entanglement of hot trapped ions. Physical Review Letters. 82 (9): 1835–1838. [arXiv:9810040](https://arxiv.org/abs/quant-ph/9810040)

\[2] Maslov, D. and Nam, Y., Use of global interactions in efficient quantum circuit constructions. New Journal of Physics, 20(3), p.033018. [arXiv:1707.06356](https://arxiv.org/abs/1707.06356)

Create a new Global Mølmer–Sørensen (GMS) gate.

**Parameters**

- **num\_qubits** ([*int*](https://docs.python.org/3/library/functions.html#int)) – width of gate.
- **theta** ([*List*](https://docs.python.org/3/library/typing.html#typing.List)*\[*[*List*](https://docs.python.org/3/library/typing.html#typing.List)*\[*[*float*](https://docs.python.org/3/library/functions.html#float)*]] |* [*ndarray*](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray)) – a num\_qubits x num\_qubits symmetric matrix of interaction angles for each qubit pair. The upper triangle is considered.

## Attributes

### ancillas

Returns a list of ancilla bits in the order that the registers were added.

### calibrations

Return calibration dictionary.

The custom pulse definition of a given gate is of the form `{'gate_name': {(qubits, params): schedule}}`

### clbits

Returns a list of classical bits in the order that the registers were added.

### data

Return the circuit data (instructions and context).

**Returns**

a list-like object containing the [`CircuitInstruction`](/docs/api/qiskit/1.0/qiskit.circuit.CircuitInstruction "qiskit.circuit.CircuitInstruction")s for each instruction.

**Return type**

QuantumCircuitData

### global\_phase

Return the global phase of the current circuit scope in radians.

### instances

Default value: `177`

### layout

Return any associated layout information about the circuit

This attribute contains an optional [`TranspileLayout`](/docs/api/qiskit/1.0/qiskit.transpiler.TranspileLayout "qiskit.transpiler.TranspileLayout") object. This is typically set on the output from [`transpile()`](/docs/api/qiskit/1.0/compiler#qiskit.compiler.transpile "qiskit.compiler.transpile") or [`PassManager.run()`](/docs/api/qiskit/1.0/qiskit.transpiler.PassManager#run "qiskit.transpiler.PassManager.run") to retain information about the permutations caused on the input circuit by transpilation.

There are two types of permutations caused by the [`transpile()`](/docs/api/qiskit/1.0/compiler#qiskit.compiler.transpile "qiskit.compiler.transpile") function, an initial layout which permutes the qubits based on the selected physical qubits on the [`Target`](/docs/api/qiskit/1.0/qiskit.transpiler.Target "qiskit.transpiler.Target"), and a final layout which is an output permutation caused by [`SwapGate`](/docs/api/qiskit/1.0/qiskit.circuit.library.SwapGate "qiskit.circuit.library.SwapGate")s inserted during routing.

### metadata

The user provided metadata associated with the circuit.

The metadata for the circuit is a user provided `dict` of metadata for the circuit. It will not be used to influence the execution or operation of the circuit, but it is expected to be passed between all transforms of the circuit (ie transpilation) and that providers will associate any circuit metadata with the results it returns from execution of that circuit.

### num\_ancillas

Return the number of ancilla qubits.

### num\_clbits

Return number of classical bits.

### num\_parameters

The number of parameter objects in the circuit.

### num\_qubits

Return number of qubits.

### op\_start\_times

Return a list of operation start times.

This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.

**Returns**

List of integers representing instruction start times. The index corresponds to the index of instruction in `QuantumCircuit.data`.

**Raises**

[**AttributeError**](https://docs.python.org/3/library/exceptions.html#AttributeError) – When circuit is not scheduled.

### parameters

The parameters defined in the circuit.

This attribute returns the [`Parameter`](/docs/api/qiskit/1.0/qiskit.circuit.Parameter "qiskit.circuit.Parameter") objects in the circuit sorted alphabetically. Note that parameters instantiated with a [`ParameterVector`](/docs/api/qiskit/1.0/qiskit.circuit.ParameterVector "qiskit.circuit.ParameterVector") are still sorted numerically.

**Examples**

The snippet below shows that insertion order of parameters does not matter.

```python
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> a, b, elephant = Parameter("a"), Parameter("b"), Parameter("elephant")
>>> circuit = QuantumCircuit(1)
>>> circuit.rx(b, 0)
>>> circuit.rz(elephant, 0)
>>> circuit.ry(a, 0)
>>> circuit.parameters  # sorted alphabetically!
ParameterView([Parameter(a), Parameter(b), Parameter(elephant)])
```

Bear in mind that alphabetical sorting might be unintuitive when it comes to numbers. The literal “10” comes before “2” in strict alphabetical sorting.

```python
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> angles = [Parameter("angle_1"), Parameter("angle_2"), Parameter("angle_10")]
>>> circuit = QuantumCircuit(1)
>>> circuit.u(*angles, 0)
>>> circuit.draw()
   ┌─────────────────────────────┐
q: ┤ U(angle_1,angle_2,angle_10) ├
   └─────────────────────────────┘
>>> circuit.parameters
ParameterView([Parameter(angle_1), Parameter(angle_10), Parameter(angle_2)])
```

To respect numerical sorting, a [`ParameterVector`](/docs/api/qiskit/1.0/qiskit.circuit.ParameterVector "qiskit.circuit.ParameterVector") can be used.

```python
>>> from qiskit.circuit import QuantumCircuit, Parameter, ParameterVector
>>> x = ParameterVector("x", 12)
>>> circuit = QuantumCircuit(1)
>>> for x_i in x:
...     circuit.rx(x_i, 0)
>>> circuit.parameters
ParameterView([
    ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
    ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
    ..., ParameterVectorElement(x[11])
])
```

**Returns**

The sorted [`Parameter`](/docs/api/qiskit/1.0/qiskit.circuit.Parameter "qiskit.circuit.Parameter") objects in the circuit.

### prefix

Default value: `'circuit'`

### qubits

Returns a list of quantum bits in the order that the registers were added.