qsearch.gates
¶
This module defines the Gate class, which represents a quantum gate, as well as implementations of many common Gates.
Through the use of KroneckerGate and ProductGate, Gates can be formed for complex circuit structures. The matrix and mat_jac functions are used for numerical optimization of parameterized gates. The assemble function is used to generate an intermediate language of tuples that can be used by Assemblers to output descriptions of quantum circuits in other formats.
Module Contents¶
Classes¶
This class shows the framework for working with quantum gates in Qsearch. 

Represents an identity gate of any number of qudits of any size. 

Represents a parameterized X rotation on one qubit. 

Represents a parameterized Y rotation on one qubit. 

Represents a parameterized Z rotation on one qubit. 

Represents a sqrt(X) rotation on one qubit, which is equivalent to XGate() with a paramter of pi/2, up to an overall phase. 

Represents an arbitrary parameterized singlequbit gate, decomposed into 3 parameterized Z gates separated by X(PI/2) gates. 

Represents a partially parameterized single qubit gate, equivalent to ZXZXZ but without the first Z gate. This is useful because that first Z gate can commute through the control of a CNOT, thereby reducing the number of parameters we need to solve for. 

Represents an arbitrary parameterized single qubit gate, parameterized in the same way as IBM's U3 gate. 

Represents a parameterized single qubit gate, parameterized in the same way as IBM's U2 gate. 

Represents an parameterized single qubit gate, parameterized in the same way as IBM's U1 gate. 

This gate represents an arbitrary parameterized singlequtrit gate. 

Represents the constant twoqutrit gate CSUM 

Represents the constant twoqutrit gate CPI. 

Represents the constant twoqutrit gate CPI with phase differences. 

Represents the constant twoqubit gate CNOT. 

Represents the constant twoqubit gate ControlledZ. 

Represents the constant twoqubit gate ISwap. 

Represents the constant twoqubit gate XX(pi/2). 

Represents the twoqubit gate CNOT, but between two qubits that are not necessarily next to each other. 

Represents an arbitrary constant gate, defined by the unitary passed to the initializer. 

Represents a constant gate, based on the Gate passed to its initializer, but upgraded to act on qudits of a larger size. 

Represents an arbitrary controlled gate, defined by the unitary passed to the initializer. 

Represents the sqrt(CNOT) gate. Two sqrt(CNOT) gates in a row will form a CNOT gate. 

Represents the Kronecker product of a list of gates. This is equivalent to performing those gate in parallel in a quantum circuit. 

Represents a matrix product of Gates. This is equivalent to performing those gates sequentially in a quantum circuit. 
Attributes¶
 qsearch.gates.native_from_object¶
 class qsearch.gates.Gate¶
This class shows the framework for working with quantum gates in Qsearch.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 abstract matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 abstract assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __eq__(other)¶
Return self==value.
 __hash__()¶
Return hash(self).
 copy()¶
 _parts()¶
 __copy__()¶
 __deepcopy__(memo)¶
 __repr__()¶
Return repr(self).
 validate_structure()¶
 class qsearch.gates.IdentityGate(qudits=1, d=2)¶
Bases:
Gate
Represents an identity gate of any number of qudits of any size.
 Parameters:
qudits – The number of qudits represented by this identity.
d – The size of qudits represented by this identity (2 for qubits, 3 for qutrits, etc.)
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.XGate¶
Bases:
Gate
Represents a parameterized X rotation on one qubit.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.YGate¶
Bases:
Gate
Represents a parameterized Y rotation on one qubit.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.ZGate¶
Bases:
Gate
Represents a parameterized Z rotation on one qubit.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.SXGate¶
Bases:
Gate
Represents a sqrt(X) rotation on one qubit, which is equivalent to XGate() with a paramter of pi/2, up to an overall phase.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.ZXZXZGate¶
Bases:
Gate
Represents an arbitrary parameterized singlequbit gate, decomposed into 3 parameterized Z gates separated by X(PI/2) gates.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.XZXZGate¶
Bases:
Gate
Represents a partially parameterized single qubit gate, equivalent to ZXZXZ but without the first Z gate. This is useful because that first Z gate can commute through the control of a CNOT, thereby reducing the number of parameters we need to solve for.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.U3Gate¶
Bases:
Gate
Represents an arbitrary parameterized single qubit gate, parameterized in the same way as IBM’s U3 gate.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __eq__(other)¶
Return self==value.
 __repr__()¶
Return repr(self).
 class qsearch.gates.U2Gate¶
Bases:
Gate
Represents a parameterized single qubit gate, parameterized in the same way as IBM’s U2 gate.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __eq__(other)¶
Return self==value.
 __repr__()¶
Return repr(self).
 class qsearch.gates.U1Gate¶
Bases:
Gate
Represents an parameterized single qubit gate, parameterized in the same way as IBM’s U1 gate.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __eq__(other)¶
Return self==value.
 __repr__()¶
Return repr(self).
 class qsearch.gates.SingleQutritGate¶
Bases:
Gate
This gate represents an arbitrary parameterized singlequtrit gate.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CSUMGate¶
Bases:
Gate
Represents the constant twoqutrit gate CSUM
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _csum¶
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CPIGate¶
Bases:
Gate
Represents the constant twoqutrit gate CPI.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _cpi¶
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CPIPhaseGate¶
Bases:
Gate
Represents the constant twoqutrit gate CPI with phase differences.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CNOTGate¶
Bases:
Gate
Represents the constant twoqubit gate CNOT.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _cnot¶
 __eq__(other)¶
Return self==value.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CZGate¶
Bases:
Gate
Represents the constant twoqubit gate ControlledZ.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _gate¶
 __eq__(other)¶
Return self==value.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.ISwapGate¶
Bases:
Gate
Represents the constant twoqubit gate ISwap.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _gate¶
 __eq__(other)¶
Return self==value.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.XXGate¶
Bases:
Gate
Represents the constant twoqubit gate XX(pi/2).
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _gate¶
 __eq__(other)¶
Return self==value.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.NonadjacentCNOTGate(qudits, control, target)¶
Bases:
Gate
Represents the twoqubit gate CNOT, but between two qubits that are not necessarily next to each other.
 Parameters:
qudits – The total number of qubits that a unitary of the size returned by this gate would represent. For this gate, usually this is the total number of qubits in the larger circuit.
control – The index of the control qubit, relative to the 0th qubit that would be affected by the unitary returned by this gate.
target – The index of the target qubit, relative to the 0th qubit that would be affected by the unitary returned by this gate.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 validate_structure()¶
 class qsearch.gates.UGate(U, d=2, gatename='CUSTOM', gateparams=(), gateindices=None)¶
Bases:
Gate
Represents an arbitrary constant gate, defined by the unitary passed to the initializer.
 Parameters:
U – The unitary for the operation that this gate represents, as a numpy ndarray with datatype=”complex128”.
d – The size of qudits for the operation that this gate represents. The default is 2, for qubits.
gatename – A name for this gate, which will get passed to the Assembler at assembly time.
gateparams – A tuple of parameters that will get passed to the Assembler at assembly time.
gateindices – A tuple of indices for the qubits that this gate acts on, which will get passed to the Assembler at assembly time. This overrides the default behavior, which is to return a tuple of all the indices starting with the one passed in assemble(v, i), and ending at i+self.qudits
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.UpgradedConstantGate(other, df=3)¶
Bases:
Gate
Represents a constant gate, based on the Gate passed to its initializer, but upgraded to act on qudits of a larger size.
 Parameters:
other – A Gate of a lower qudit size.
df – The final, upgraded qudit size. The default is 3, for upgrading gates from qubits to qutrits.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CUGate(U, gatename='Name', gateparams=(), flipped=False)¶
Bases:
Gate
Represents an arbitrary controlled gate, defined by the unitary passed to the initializer.
 Parameters:
U – The unitary to form the controlledunitary gate, in the form of a numpy ndarray with dtype=”complex128”
gatename – A name for this controlled gate which will get passed to the Assembler at assembly time.
gateparams – A tuple of parameters that will get passed to the Assembler at assembly time.
flipped – A boolean flag, which if set to true, will flip the direction of the gate. The default direction is for the control qubit to be the lower indexed qubit.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.CNOTRootGate¶
Bases:
Gate
Represents the sqrt(CNOT) gate. Two sqrt(CNOT) gates in a row will form a CNOT gate.
Gates must set the following variables in __init__
self.num_inputs : The number of parameters needed to generate a unitary. This can be 0. self.qudits : The number of qudits acted on by a unitary of the size generated by the gate. For example, this would be 1 for U3, 2 for CNOT.
 _cnr¶
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 __repr__()¶
Return repr(self).
 class qsearch.gates.KroneckerGate(*subgates)¶
Bases:
Gate
Represents the Kronecker product of a list of gates. This is equivalent to performing those gate in parallel in a quantum circuit.
 Parameters:
*subgates – An sequence of Gates. KroneckerGate will return the kronecker product of the unitaries returned by those Gates.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 appending(gate)¶
Returns a new KroneckerGate with the new gate added to the list.
 Parameters:
gate – A Gate to be added to the end of the list of gates in the new KroneckerGate.
 _parts()¶
 __deepcopy__(memo)¶
 __repr__()¶
Return repr(self).
 validate_structure()¶
 class qsearch.gates.ProductGate(*subgates)¶
Bases:
Gate
Represents a matrix product of Gates. This is equivalent to performing those gates sequentially in a quantum circuit.
 Parameters:
subgates – A list of Gates to be multiplied together. ProductGate returns the matrix product of the unitaries returned by those Gates.
 matrix(v)¶
Generates a matrix using the given vector of input parameters. For a constant gate, v will be empty.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A unitary matrix with dtype=”complex128”, equal in size to d**self.qudits, where d is the intended qudit size (d is 2 for qubits, 3 for qutrits, etc.)
 Return type:
np.ndarray
 mat_jac(v)¶
Generates a matrix and the jacobian(s) using the given vector of input parameters.
It is not required to implement mat_jac for constant gates, nor is it required when using gradientfree Solvers.
The jacobian matrices will be complex valued, and should be the elementwise partial derivative with respect to each of the parameters. There should be self.num_inputs matrices in the array, with the ith entry being the partial derivative with respect to v[i]. See U3Gate for an example implementation.
 Parameters:
v – A numpy array of real floating point numbers, ranging from 0 to 2*PI. Its size is equal to self.num_inputs
 Returns:
A tuple of the same unitary that would be returned by matrix(v), and an array of Jacobian matrices.
 Return type:
tuple
 assemble(v, i=0)¶
Generates an array of tuples as an intermediate format before being processed by an Assembler for conversion to other circuit formats.
 Parameters:
v – The same numpy array of real floating point numbers that might be passed to matrix(v).
i – The index of the lowestindexed qubit that the unitary generated by the gate acts on.
 Returns:
A list of tuples following the format described above.
 Return type:
list
The format of the tuples returned looks like:
(“gate”, gatename, (*gateparameters), (*gateindices))
Where gatename corresponds to a gate that an Assembler will recognize, gateparameters corresponds to the parameters for the specified gate (usually but not always calculated from v), and gateindices corresponds to the qubit indices that the gate acts on (usually but not always calculated from i).
You can also have tuples of the form (“block”, *tuples) Where tuples is an array of tuples in this same format.
For some helpful examples, look at U3Gate, XZXZGate, CNOTGate, and NonadjacentCNOTGate.
 appending(*gates)¶
Returns a new ProductGate with the new gates appended to the end.
 Parameters:
gates – A list of Gates to be appended.
 inserting(*gates, depth=1)¶
Returns a new ProductGate with new gates inserted at some index depth.
 Parameters:
gates – A list of Gates to be inserted.
depth – An index in the subgates of the ProductGate after which the new gates will be inserted. The default value of 1 will insert these gates at the begining of the ProductGate.
 __deepcopy__(memo)¶
 __repr__()¶
Return repr(self).
 validate_structure()¶