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Advanced Project Features
Projects have can be given values for various options to adjust settings such as the search type or gateset.
import search_compiler as sc
myproject = sc.Project("myproject")
myproject["option"] = value
In addition, the Project
class has a few management functions.
You can configure options that the compiler used by a project using myproject["config_key"] = config_value
. The supported keys are described here.
-
threshold
is afloat
that defines the termination condition of the compilation. The compiler will return when it finds a circuit with aerror_func
value less than this threshold. The default value is1e-10
. -
gateset
is asc.gatesets.Gateset
object that is used by the compiler. The default value issc.gatesets.QubitCNOTLinear()
. -
error_func
is a distance function that compares twonumpy.matrix
objects. It must returnfloat
values that greater than or equal to zero such that input matrices that are close to the same will result in outputs close to zero. The default value issc.utils.matrix_distance_squared
. -
search_type
is astring
that can be set to"breadth"
to perform a breadth-first search, or"greedy"
to perform a greedy search using onlyerror_func
. When set to any other value, including the default, A* search is performed usingheuristic
. -
heuristic
is a function that takes a value fromerror_func
and a search depth, and returns afloat
. It is used to order the priority queue used for searching. Setting this option overridessearch_type
. -
solver
is asc.solver.Solver
object. It is used to set the numerical optimizer used to solve for circuit parameters. The default value is dynamically chosen based on thegateset
anderror_func
. Details are given below. -
beams
can be sets the number of nodes popped off of the priority queue during each search layer. The default is-1
. Setting a positive value will cause the compiler to examine multiple search paths in parallel, and may result in faster runtimes. Setting a negative value will have the compiler calculate a number of beams to maximize CPU utilization. Setting a value of 1 will use the fewest threads.
There are a few more features that the Project class provides that might be needed. You may need to remove or reset compilations.
myproject.remove_compilation("gate_name") # deletes all data relating to the specified gate and removes it from the project
myproject.reset() # deletes all in-progress or completed compilation data in the project. You may need this if you decide to tweak compiler parameters.
myproject.reset("gate_name") # deletes all in-progress or completed compilation data for the specified gate. You may need this if the compiler does not always find the same solution for your gate.
myproject.clear() # deletes all data from the project, putting it in the same state as a fresh project.
You can also get output in the form of search_compiler.circuits.QuantumStep
objects. More detail on how to use these objects below.
# circuit is a QuantumStep object, and vector is a numpy array of floats, to be used by certain QuantumStep functions
circuit, vector = myproject.get_result("gate_name")
# U is the numpy ndarray that was specified as the target unitary when adding this gate
U = myproject.get_target("gate_name")
# time is the numer of seconds it took to compile the gate, or None if the gate has not finished compiling.=
time = myproject.get_time("gate_name")
You can use
myproject.status() # to check the overall status of a project
myproject.status(name) # to check the status of a specific circuit in a project
You can access a project from a separate process while it is running in another process. You can use project.status()
from the second process in order to check on the status of a project without stopping it. If you change project settings or add or remove compilations while it is running in another process, changes will not take effect until that process is stopped and restarted. It is not recommended to attempt to run a project from two processes at the same time.
If no solver is provided, a Project will choose a solver dynamically based on the provided gateset
and error_func
, based on the following rules. If error_func
is matrix_distance_squared
and the gateset
is one of the provided gatesets consisting of CNOT
and single qubit gates, LeastSquares_Jac_Solver
will be used. Otherwise, if the gateset
has implementations of the jacobian, BFGS_Jac_Solver
will be used. Otherwise, COBYLA_Solver
will be used. The default settings of these parameters will cause LeastSquares_Jac_Solver
to be chosen. Additionally, if the Native Gateset is installed and compatible with the given gateset
, it will be used.