qml.estimator.resources_base.Resources¶

class Resources(zeroed, any_state=0, algo_wires=0, gate_types=None)[source]¶

Bases: object

A container for the resources used throughout a quantum circuit.

The resources tracked include: number of wires (by state), and number of gates (by type).

Parameters:

zeroed (int) – Number of zeroed state work wires.
any_state (int) – Number of work wires in an unknown state, default is 0.
algo_wires (int) – Number of algorithmic wires, default value is 0.
gate_types (dict) – A dictionary storing operations (ResourceOperator) as keys and the number of times they are used in the circuit (int) as values.

Example

>>> from pennylane import estimator as qre
>>> H = qre.resource_rep(qre.Hadamard)
>>> X = qre.resource_rep(qre.X)
>>> RX = qre.resource_rep(qre.RX, {"precision":1e-8})
>>> RX_2 = qre.resource_rep(qre.RX, {"precision":1e-6})
>>> gt = defaultdict(int, {H: 10, X:7, RX:2, RX_2:2})
>>>
>>> res = qre.Resources(zeroed=3, gate_types=gt)
>>> print(res)
--- Resources: ---
 Total wires: 2
    algorithmic wires: 0
    allocated wires: 2
         zero state: 2
         any state: 0
 Total gates : 21
  'RX': 4,
  'X': 7,
  'Hadamard': 10
>>>
>>> print(res.gate_breakdown())
RX total: 4
    RX {'eps': 1e-08}: 2
    RX {'eps': 1e-06}: 2
X total: 7
Hadamard total: 10

Attributes

gate_counts

Produce a dictionary which stores the gate counts using the operator names as keys.

gate_counts¶

Produce a dictionary which stores the gate counts using the operator names as keys.

Returns:

A dictionary with operator names (str) as keys: and the number of occurances in the circuit (int) as values.

Return type:

dict

Methods

`add_parallel`(other)	Add two Resources objects in parallel.
`add_series`(other)	Add two Resources objects in series.
`gate_breakdown`([gate_set])	Generates a string breakdown of gate counts by type and parameters, optionally for a specific set of gates.
`multiply_parallel`(scalar)	Scale a Resources object in parallel
`multiply_series`(scalar)	Scale a Resources object in series

add_parallel(other)[source]¶

Add two Resources objects in parallel.

When combining resources for parallel execution, the following rules apply:

Zeroed wires: The maximum of the zeroed auxiliary wires is used, as they can be reused across parallel circuits.
Any state wires: The any_state wires are added together, as they cannot be reused between circuits.
Algorithmic wires: The algo_wires are added together, as each circuit is a separate unit running simultaneously.
Gates: The gates from each circuit are added together.

Parameters:: other (Resources) – other resource object to combine with
Returns:: combined resources
Return type:: Resources

Example

>>> from pennylane import estimator as qre
>>> gate_set = {"X", "Y", "Z", "CNOT", "T", "S", "Hadamard"}
>>> res1 = qre.estimate(qre.Toffoli(), gate_set)
>>> res2 = qre.estimate(qre.QFT(num_wires=4), gate_set)
>>> res_in_parallel = res1.add_parallel(res2)
>>> print(res_in_parallel)
--- Resources: ---
 Total wires: 9
    algorithmic wires: 7
    allocated wires: 2
         zero state: 2
         any state: 0
 Total gates : 838
  'T': 796,
  'CNOT': 28,
  'Z': 2,
  'S': 3,
  'Hadamard': 9

add_series(other)[source]¶

Add two Resources objects in series.

When combining resources for serial execution, the following rules apply:

Zeroed wires: The total zeroed auxiliary wires are the maximum of the zeroed wires in each circuit, as they can be reused.
Any state wires: The any_state wires are added together, as they cannot be reused.
Algorithmic wires: The total algo_wires are the maximum of the algo_wires from each circuit.
Gates: The gates from each circuit are added together.

Parameters:: other (Resources) – the other resource object to add in series with
Returns:: combined resources
Return type:: Resources

Example

>>> from pennylane import estimator as qre
>>> gate_set = {"X", "Y", "Z", "CNOT", "T", "S", "Hadamard"}
>>> res1 = qre.estimate(qre.Toffoli(), gate_set)
>>> res2 = qre.estimate(qre.QFT(num_wires=4), gate_set)
>>> res_in_series = res1.add_series(res2)
>>> print(res_in_series)
--- Resources: ---
 Total wires: 6
    algorithmic wires: 4
    allocated wires: 2
         zero state: 2
         any state: 0
 Total gates : 838
  'T': 796,
  'CNOT': 28,
  'Z': 2,
  'S': 3,
  'Hadamard': 9

gate_breakdown(gate_set=None)[source]¶

Generates a string breakdown of gate counts by type and parameters, optionally for a specific set of gates.

Parameters:: gate_set (list) – A list of gate names to break down. If None, details will be provided for all gate types.

Example

>>> from pennylane import estimator as qre
>>> res1 = qre.estimate(qre.SemiAdder(10))
>>> print(res1.gate_breakdown())
Toffoli total: 9
    Toffoli {'elbow': 'left'}: 9
CNOT total: 60
Hadamard total: 27

multiply_parallel(scalar)[source]¶

Scale a Resources object in parallel

Parameters:: scalar (int) – integer value by which to scale the resources
Returns:: scaled resources
Return type:: Resources

Example

>>> from pennylane import estimator as qre
>>> gate_set = {"X", "Y", "Z", "CNOT", "T", "S", "Hadamard"}
>>> res1 = qre.estimate(qre.Toffoli(), gate_set)
>>> res_in_parallel = res1.multiply_parallel(3)
>>> print(res_in_parallel)
--- Resources: ---
 Total wires: 11
    algorithmic wires: 9
    allocated wires: 2
         zero state: 2
         any state: 0
 Total gates : 72
  'T': 12,
  'CNOT': 30,
  'Z': 6,
  'S': 9,
  'Hadamard': 15

multiply_series(scalar)[source]¶

Scale a Resources object in series

Parameters:: scalar (int) – integer value by which to scale the resources
Returns:: scaled resources
Return type:: Resources

Example

>>> from pennylane import estimator as qre
>>> gate_set = {"X", "Y", "Z", "CNOT", "T", "S", "Hadamard"}
>>> res1 = qre.estimate(qre.Toffoli(), gate_set)
>>> res_in_series = res1.multiply_series(3)
>>> print(res_in_series)
--- Resources: ---
 Total wires: 5
    algorithmic wires: 3
    allocated wires: 2
         zero state: 2
         any state: 0
 Total gates : 72
  'T': 12,
  'CNOT': 30,
  'Z': 6,
  'S': 9,
  'Hadamard': 15

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qml.estimator.resources_base.Resources¶

Attributes

Methods

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