Leap’s Hybrid Solvers¶
Not all accounts have access to this type of solver.
Leap’s quantum-classical hybrid solvers are intended to solve arbitrary application problems formulated as binary quadratic models (BQM).
These solvers, which implement state-of-the-art classical algorithms together with intelligent allocation of the quantum processing unit (QPU) to parts of the problem where it benefits most, are designed to accommodate even very large problems. Leap’s solvers can relieve you of the burden of any current and future development and optimization of hybrid algorithms that best solve your problem.
These solvers have the following characteristics:
Generally Available Solvers¶
Currently, all Leap™ accounts have access to these hybrid solvers:
This section describes the properties of Leap‘s solvers, in alphabetical order.
Type of solver. Hybrid solvers support the following categories:
hybrid—quantum-classical hybrid; typically one or more classical algorithms run on the problem while outsourcing to a quantum processing unit (QPU) parts of the problem where it benefits most.
Maximum number of problem variables accepted by the solver.
Minimum required run time, in seconds, the solver must be allowed to work on the
given problem. Specifies the minimum time required for the number of problem variables,
as a piecewise-linear curve defined by a set of floating-point pairs.
The first element in each pair is the number of problem variables; the second is the
minimum required time. The minimum time for any particular number of variables
is a linear interpolation calculated on two pairs that represent the relevant range
for the given number of variables. For example, if
minimum_time_limit for a hybrid
[[1, 0.1], [100, 10.0], [1000, 20.0]], then the minimum time
for a 50-variable problem would be 5 seconds, the linear interpolation of the
first two pairs that represent problems with between 1 to 100 variables.
Maximum allowed run time, in hours, that can be specified for the solver.
Ratio of time charged to Leap account quotas between QPU and hybrid solver usage. For example, for a value of 20, using 20 seconds of hybrid solver time is has an equivalent cost to using 1 second of QPU time.
Indicates what problem types are supported for the solver. Hybrid solvers support the following energy-minimization problem types:
bqm—binary quadratic model (BQM) problems; use \(0/1\)-valued variables and \(-1/1\)-valued variables.