# AND

*class *`qiskit.circuit.library.AND(num_variable_qubits, flags=None, mcx_mode='noancilla')`

Bases: `QuantumCircuit`

A circuit implementing the logical AND operation on a number of qubits.

For the AND operation the state $|1\rangle$ is interpreted as `True`

. The result qubit is flipped, if the state of all variable qubits is `True`

. In this format, the AND operation equals a multi-controlled X gate, which is controlled on all variable qubits. Using a list of flags however, qubits can be skipped or negated. Practically, the flags allow to skip controls or to apply pre- and post-X gates to the negated qubits.

The AND gate without special flags equals the multi-controlled-X gate:

Using flags we can negate qubits or skip them. For instance, if we have 5 qubits and want to return `True`

if the first qubit is `False`

and the last two are `True`

we use the flags `[-1, 0, 0, 1, 1]`

.

Create a new logical AND circuit.

**Parameters**

**num_variable_qubits**(*int*) – The qubits of which the OR is computed. The result will be written into an additional result qubit.**flags**(*list**[**int**] | None*) – A list of +1/0/-1 marking negations or omissions of qubits.**mcx_mode**(*str*) – The mode to be used to implement the multi-controlled X gate.

## 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`

s for each instruction.

**Return type**

QuantumCircuitData

### extension_lib

Default value: `'include "qelib1.inc";'`

### global_phase

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

### header

Default value: `'OPENQASM 2.0;'`

### instances

Default value: `193`

### layout

Return any associated layout information about the circuit

This attribute contains an optional `TranspileLayout`

object. This is typically set on the output from `transpile()`

or `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()`

function, an initial layout which permutes the qubits based on the selected physical qubits on the `Target`

, and a final layout which is an output permutation caused by `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** – When circuit is not scheduled.

### parameters

The parameters defined in the circuit.

This attribute returns the `Parameter`

objects in the circuit sorted alphabetically. Note that parameters instantiated with a `ParameterVector`

are still sorted numerically.

**Examples**

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

```
>>> 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.

```
>>> 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`

can be used.

` `

```
>>> 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`

objects in the circuit.

### prefix

Default value: `'circuit'`

### qubits

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