Controlled Operations

Introduction

Controlled operations are one of the main ways quantum programs apply operations depending on the state of quantum variables. In classical programming, an if statement chooses which instructions run based on a classical Boolean value. In quantum programming, the analogous idea is more subtle: the condition may itself be quantum, meaning it may be in superposition. In Qmod, controlled quantum behavior is expressed using the control statement. The statement applies a unitary operation conditionally, depending on a quantum state, and may optionally apply a different operation if the condition does not hold. The condition can be given either as a single qubit or qubit array, or as a quantum Boolean expression over quantum variables. When the control variable is in superposition, the controlled operation entangles the objects used in the controlled block with the condition. In this guide, we cover:

Controlled operations: applying quantum operations only on states that satisfy a quantum condition.
Else blocks: applying one operation when the condition is true and another when it is false.
Operations controlled by expressions: using Boolean expressions over quantum variables as control conditions.

A controlled operation applies a quantum operation subject to a condition satisfied by the quantum state. The simplest case is control by a single qubit. If the control qubit is in state

\vert 1 \rangle

, the operation is applied to the target. If the control qubit is in state

\vert 0 \rangle

, the operation is not applied. In Qmod, this is written with control:

from classiq import *


@qfunc
def main(ctrl: Output[QBit], target: Output[QBit]):
    allocate(ctrl)
    allocate(target)

    H(ctrl)
    control(ctrl, lambda: Y(target))

In the Python SDK, the controlled statement block is passed as a Python callable, commonly written using lambda.

This quantum program:

Allocates a control qubit ctrl and a target qubit target.
Applies the Hadamard gate, $H$ , to ctrl, creating the superposition $\vert \text{ctrl} \rangle = \frac{1}{\sqrt{2}}\left( \vert 0 \rangle + \vert 1 \rangle\right)$ .
Applies the Pauli-Y gate to target conditioned on ctrl == 1.
The resulting state is $\frac{1}{\sqrt{2}}\left( \vert 00 \rangle + i\vert 11 \rangle\right),$ where the first qubit is ctrl and the second is target.

This means that the target is flipped only in the part of the state where the control qubit is 1. Since the control qubit is in superposition, the result is an entangled state rather than a classical branch selection. This is the same control mechanism underlying gates such as CY, but Qmod generalizes it to arbitrary statement blocks and quantum expressions.

The control statement applies quantum operations coherently. It should not be interpreted as measuring the condition and then choosing a branch.

Multi-qubit control

The control variable can also be a quantum array. In that case, the controlled block is applied only when all qubits in the control array are in state

\vert 1 \rangle

from classiq import *
from classiq.qmod.symbolic import pi


@qfunc
def main(ctrl: Output[QArray[QBit]], target: Output[QArray[QBit]]):
    allocate(3, ctrl)
    allocate(4, target)

    hadamard_transform(ctrl)

    control(ctrl, lambda: qft(target))

This quantum program:

Allocates a 3-qubit control array.
Puts the control array into a uniform superposition over all 3-bit strings.
Applies a Quantum Fourier Transform to target only on the basis state ctrl == 111.

Because the control array is in superposition, the QFT is applied only to the component corresponding to ctrl == 111.

Else blocks

A control statement may include an else_block. The main block is applied for states where the condition is true, and the else block is applied for states where the condition is false. When the condition is a qubit array, the condition holds only when all qubits in the control array are in state

\vert 1 \rangle

; otherwise, the else block applies.

from classiq import *


@qfunc
def main(ctrl: Output[QBit], target: Output[QBit]):
    allocate(ctrl)
    allocate(target)

    H(ctrl)

    control(
        ctrl,
        lambda: X(target),
        lambda: H(target),
    )

This quantum program:

Allocates ctrl and target.
Puts ctrl in superposition.
Applies the Pauli-X gate to target on the branch where ctrl == 1.
Applies Hadamard gate (H) to target on the branch where ctrl == 0.

This is analogous to the following classical structure:

if ctrl:
    X(target)
else:
    H(target)

However, the quantum version is not a classical branching. If ctrl is in superposition, both branches are applied coherently to the corresponding parts of the quantum state.

Example: choosing between two rotations

The next example uses an else block to apply one rotation when a control qubit is 1 and a different rotation when it is 0.

from classiq import *
from classiq.qmod.symbolic import pi


@qfunc
def main(ctrl: Output[QBit], target: Output[QBit]):
    allocate(ctrl)
    allocate(target)

    H(ctrl)

    control(
        ctrl,
        lambda: RX(pi / 2, target),
        lambda: RX(pi / 3, target),
    )

Whose outputs are closer to:

ctrl	target	counts	probability	bitstring
1	0	749	0.245117	01
0	0	749	0.365723	00
0	1	502	0.128906	10
1	1	533	0.260254	11

This program creates a state in which the target qubit is rotated differently depending on the value of ctrl. Since ctrl is in superposition, the two rotations are applied to different components of the full quantum state.

A control statement, like other control-flow statements such as if_, repeat, foreach, and power, must preserve the initialization status of variables declared outside its blocks. A variable declared outside the controlled block may be allocated inside the block only if it is also released within that same block. Similarly, variables declared inside a controlled block must be uninitialized by the end of that block.

Operations controlled by expressions

In Qmod, a control condition may also be a quantum logical expression over quantum variables. Expressions over quantum variables evaluate coherently over superpositions, producing correlated quantum values rather than a single classical value. Qmod supports arithmetic operators such as +, -, *, **, relational operators such as ==, !=, <, <=, >, >=, and logical operators such as logical_and/&, logical_or/|, and logical_not/ ~ for Boolean expressions.

Example: Uniformly controlled rotations

The following example applies a sequence of multi-controlled rotations

from classiq import *
from classiq.qmod.symbolic import pi

num_qubits = 2
max_iterations = 2**num_qubits
min_angle = pi/max_iterations

@qfunc
def main(x: Output[QNum], target: Output[QBit]):
    allocate(num_qubits, x)
    allocate(target)

    hadamard_transform(x)

    repeat(max_iterations, 
           lambda i: control( x == i, 
                             lambda: RX(min_angle * i, target)))

This quantum program:

Allocates x as a 2-qubit quantum number.
Places x in a superposition over the values $\{0, 1, 2, 3\}$ .
Applies a RX rotation with angle dependent on the numeric value of x.

This can be interpreted as:

x value	Operation on target
0	No rotation
1	$RX(\pi / 4)$
2	$RX(\pi / 2)$
3	$RX(3\pi / 4)$

The target qubit becomes entangled with x, because only different rotations occur depending on the values of x.

Example: Arithmetic condition

Control expressions can involve arithmetic over multiple quantum variables. This is useful in search, optimization, and oracle construction, where a state should be marked or modified only if it satisfies a predicate.

from classiq import *
from classiq.qmod.symbolic import pi


@qfunc
def main(x: Output[QNum[2]], y: Output[QNum[2]], target: Output[QBit]):
    allocate(x)
    allocate(y)
    allocate(target)

    hadamard_transform(x)
    hadamard_transform(y)

    control(x + y >= 5, lambda: X(target))

This program:

Allocates two 2-qubit quantum numbers, x and y.
Places both in uniform superposition.
Flips target only for basis states satisfying x + y >= 5

The satisfying assignments are:

x	y
2	3
3	2
3	3

After the controlled operation, the target qubit is entangled with the predicate x + y >= 5. If target is later measured as 1, the variables x and y collapse to the subspace of satisfying assignments. This style is useful for expressing predicates directly in terms of problem variables, without manually decomposing the condition into lower-level gates.

Example: Controlled phase

A common use of controlled operations is to apply a phase only to selected states. This is central in algorithms such as Grover search, phase oracles, QAOA, and Hamiltonian-inspired constructions. The phase statement applies a fixed or state-dependent phase shift to the quantum state. For example, phase(x2, pi / 4) applies a phase proportional to the value of x2. When x is initialized over the values 0, 1, 2, and 3, the phase statement rotates each basis state according to the expression value. A controlled phase applies such a phase only under a control condition.

from classiq import *
from classiq.qmod.symbolic import pi


@qfunc
def main(q: Output[QArray[QBit, 2]]):
    allocate(q)
    hadamard_transform(q)

    control(q[0], lambda: phase(pi / 4))

This quantum program:

Allocates two qubits.
Places them in a uniform superposition.
Applies a fixed phase of $\pi/4$ only when q[0] == 1.

The affected states are those whose first qubit is 1:

q state	Relative phase
[0,0]	unchanged
[0,1]	unchanged
[1,0]	rotated by $\pi/4$
[1,1]	rotated by $\pi/4$

It is possible to apply phase under both single-qubit and multi-qubit controls; the resulting phases accumulate on states satisfying the respective control conditions.

Example: Phase oracle from an expression

A controlled phase can be used to mark states satisfying a Boolean expression. The following example treats v as a selection register over the list S. Each basis state of v represents a subset of the elements of S: if v[i] == 1, then S[i] is selected. The controlled phase marks states that select exactly three elements whose sum is at most 16.

from classiq import *
from classiq.qmod.symbolic import pi

S = [1, 3, 5, 8, 11]


@qfunc
def main(v: Output[QArray]):
    allocate(5, v)

    hadamard_transform(v)
    selected_count = sum(v[i] for i in range(v.len))
    selected_sum = sum(S[i] * v[i] for i in range(v.len))

    condition = (selected_count == 3) & (selected_sum <= 16)

    control(condition, lambda: phase(pi))

This program:

Prepares v in uniform superposition.
Applies a relative phase of $\pi$ to states representing three selected elements of S whose sum is at most 16.
Leaves all other states unchanged.

Since a phase of

\pi

corresponds to multiplying the selected amplitudes by -1, this implements a phase oracle for the satisfying assignments. This pattern is common in Grover-style algorithms: rather than writing a result into a separate flag qubit, the oracle marks satisfying states by changing their phase.

The `control` statement and runtime `if_`

Qmod provides two distinct mechanisms for conditional execution: the control statement for quantum conditions, and the if_ statement for classical conditions.

Construct	Condition type	Evaluated	Effect
`control`	Quantum	Runtime	Applies a unitary coherently, conditioned on a quantum state
`if_`	Classical	Compile time or runtime	Conditionally executes a branch based on a symbolic or runtime classical value

Use control when the condition depends on quantum variables such as qubits, quantum arrays, or expressions over quantum numbers. Use if_ when the condition is a classical Qmod expression — whether symbolic or a runtime value such as a mid-circuit measurement result. Use a Python if when the condition is a concrete Python value known at model construction time, including Python-type parameters in generative functions.

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Introduction