SymbolicCircuit#

class scqubits.core.symbolic_circuit.SymbolicCircuit(nodes_list_without_ground, branches_list, branch_var_dict, basis_completion='heuristic', ground_node=None, initiate_sym_calc=True, input_string='')[source]#

Describes a circuit consisting of nodes and branches.

Examples

For a transmon qubit, the input file reads:: ` # file_name: transmon_num.inp nodes: 2 branches: C 1,2 1 JJ 1,2 1 10 `
The Circuit object can be initiated using:: Circuit.from_input_file(“transmon_num.inp”)

Parameters:

nodes_list (List[Nodes]) – List of nodes in the circuit
branches_list (List[Branch]) – List of branches connecting the above set of nodes.
basis_completion (str) – choices are: “heuristic” (default) or “canonical”; selects type of basis for completing the transformation matrix.
ground_node (Optional[Node]) – If the circuit is grounded, the ground node is treated separately and should be provided to this parameter.
initiate_sym_calc (bool) – set to True by default. Initiates the object attributes by calling the function initiate_symboliccircuit method when set to True.

Return type:

SerializableType

Methods

`SymbolicCircuit.__init__`(...[, ...])
`SymbolicCircuit.are_branchsets_disconnected`(...)	Determines whether two sets of branches are disconnected.
`SymbolicCircuit.check_transformation_matrix`(...)	Method to identify the different modes in the transformation matrix provided by the user.
`SymbolicCircuit.configure`([...])	Method to initialize the CustomQCircuit instance and initialize all the attributes needed before it can be passed on to AnalyzeQCircuit.
`SymbolicCircuit.create_from_file`(filename)	Read initdata and spectral data from file, and use those to create a new SpectrumData object.
`SymbolicCircuit.default_params`()	rtype: `Dict`[`str`, `Any`]
`SymbolicCircuit.deserialize`(io_data)	Take the given IOData and return an instance of the described class, initialized with the data stored in io_data.
`SymbolicCircuit.filewrite`(filename)	Convenience method bound to the class.
`SymbolicCircuit.from_yaml`(input_string[, ...])	Constructs the instance of Circuit from an input string.
`SymbolicCircuit.generate_symbolic_hamiltonian`([...])	Returns the Hamiltonian of the circuit in terms of the new variables \(\theta_i\).
`SymbolicCircuit.generate_symbolic_lagrangian`()	Returns four symbolic expressions: lagrangian_θ, potential_θ, lagrangian_φ, potential_φ, where θ represents the set of new variables and φ represents the set of node variables
`SymbolicCircuit.is_any_branch_parameter_symbolic`()
`SymbolicCircuit.purely_harmonic_transformation`()	rtype: `Tuple`[`ndarray`, `ndarray`]
`SymbolicCircuit.round_symbolic_expr`(expr, ...)	rtype: `Expr`
`SymbolicCircuit.serialize`()	Convert the content of the current class instance into IOData format.
`SymbolicCircuit.update_param_init_val`(...)	Updates the param init val for param_name
`SymbolicCircuit.variable_transformation_matrix`()	Evaluates the boundary conditions and constructs the variable transformation matrix, which is returned along with the dictionary var_categories which classifies the types of variables present in the circuit.

static are_branchsets_disconnected(branch_list1, branch_list2)[source]#

Determines whether two sets of branches are disconnected.

Parameters:

branch_list1 (List[Branch]) – first list of branches
branch_list2 (List[Branch]) – second list of branches

Returns:

Returns True if the branches have a connection, else False

Return type:

bool

check_transformation_matrix(transformation_matrix, enable_warnings=True)[source]#

Method to identify the different modes in the transformation matrix provided by the user.

Parameters:

transformation_matrix (ndarray) – numpy ndarray which is a square matrix having the dimensions of the number of nodes present in the circuit.
warnings – If False, will not raise the warnings regarding any unidentified modes. It is set to True by default.
enable_warnings (bool) –

Returns:

A dictionary of lists which has the variable indices classified with var indices corresponding to the rows of the transformation matrix

configure(transformation_matrix=None, closure_branches=None)[source]#

Method to initialize the CustomQCircuit instance and initialize all the attributes needed before it can be passed on to AnalyzeQCircuit.

Parameters:

transformation_matrix (Optional[ndarray]) – array used to set a transformation matrix other than the one generated by the method variable_transformation_matrix.
closure_branches (Optional[List[Branch]]) – List of branches for which the external flux variables will be defined.

classmethod create_from_file(filename)#

Read initdata and spectral data from file, and use those to create a new SpectrumData object.

Returns:: new SpectrumData object, initialized with data read from file
Return type:: SpectrumData
Parameters:: filename (str) –

classmethod deserialize(io_data)#

Take the given IOData and return an instance of the described class, initialized with the data stored in io_data.

Return type:: TypeVar(SerializableType, bound= Serializable)
Parameters:: io_data (IOData) –

filewrite(filename)#

Convenience method bound to the class. Simply accesses the write function.

Return type:: None
Parameters:: filename (str) –

classmethod from_yaml(input_string, from_file=True, basis_completion='heuristic', initiate_sym_calc=True)[source]#

Constructs the instance of Circuit from an input string. Here is an example of an input string that is used to initiate an object of the class SymbolicCircuit:

` #zero-pi.yaml nodes : 4 # zero-pi branches: - [JJ, 1,2, EJ = 10, 20] - [JJ, 3,4, 10, 20] - [L, 2,3, 0.008] - [L, 4,1, 0.008] - [C, 1,3, 0.02] - [C, 2,4, 0.02] `

Parameters:

input_string (str) – String describing the number of nodes and branches connecting then along with their parameters
from_file (bool) – Set to True by default, when a file name should be provided to input_string, else the circuit graph description in YAML should be provided as a string.
basis_completion (str) – choices: “heuristic” or “canonical”; used to choose a type of basis for completing the transformation matrix. Set to “heuristic” by default.
initiate_sym_calc (bool) – set to True by default. Initiates the object attributes by calling the function initiate_symboliccircuit method when set to True. Set to False for debugging.

Returns:

Instance of the class SymbolicCircuit

generate_symbolic_hamiltonian(substitute_params=False)[source]#

Returns the Hamiltonian of the circuit in terms of the new variables \(\theta_i\).

Parameters:: substitute_params – When set to True, the symbols defined for branch parameters will be substituted with the numerical values in the respective Circuit attributes.
Return type:: Expr

generate_symbolic_lagrangian()[source]#

Returns four symbolic expressions: lagrangian_θ, potential_θ, lagrangian_φ, potential_φ, where θ represents the set of new variables and φ represents the set of node variables

Return type:: Tuple[Expr, Expr, Expr, Expr]

serialize()#

Convert the content of the current class instance into IOData format.

Return type:: IOData

update_param_init_val(param_name, value)[source]#: Updates the param init val for param_name

variable_transformation_matrix()[source]#

Evaluates the boundary conditions and constructs the variable transformation matrix, which is returned along with the dictionary var_categories which classifies the types of variables present in the circuit.

Return type:: Tuple[ndarray, Dict[str, List[int]]]
Returns:: tuple of transformation matrix for the node variables and var_categories dict which classifies the variable types for each variable index