amplify.IsingIntQuadraticModel

class IsingIntQuadraticModel

Is the quadratic model which represents the Ising model with integer coefficients.

The class abstracts a "logical model" from multivariate polynomial, matrix, and constraints. The "logical model" is a formulation for inputting into the ising machines. This class generates a logical model by reducing the order of multivariate polynomial to quadratic and reallocating variable index.

The class converts to a logical model from the below objects.

• Multivariate polynomial

  • Includes polynomial with the order greater than three.

• Matrix

• Constraint

  • Includes multiple constraints

注釈

For more details of the conversion source, see __init__() and its examples.

Through attributes of this class, you can get a raw input model, a converted logical model, and mapping from an input model to a logical model.

注釈

The following operators are defined for the class.

• Addition: a + b (__add__(), __radd__(), __iadd__())

__init__(*args, **kwargs)

Returns the Ising quadratic model initialized by input and constraints.

Overloads:

• __init__(poly, constraints)

• __init__(matrix, constant, constraints)

パラメータ:

• poly (IsingIntPoly) --

  • polynomial of the Ising model.

• matrix (IsingIntMatrix) --

  • the Ising matrix of the Ising model

• constant (int, optional) --

  • a constant term of the Ising model

• constraints (IsingIntConstraint, IsingIntConstraints, optional) --

  • constraints of the Ising model

Example

>>> from amplify import (gen_symbols,
... IsingIntQuadraticModel)
>>> from amplify.constraint import equal_to
>>> s = gen_symbols(IsingIntQuadraticModel, 3)
>>> model = IsingIntQuadraticModel(s[0] + s[1] + s[2], equal_to(s[0], 1))
>>> model.input_poly
s_0 + s_1 + s_2

>>> from amplify import (IsingIntMatrix,
... IsingIntQuadraticModel)
>>> mat = IsingIntMatrix(3)
>>> mat[0, 1] = 1
>>> mat[0, 2] = 2
>>> mat[1, 2] = 3
>>> model = IsingIntQuadraticModel(mat, 4)
>>> model.input_matrix
([[0, 1, 2],
 [0, 0, 3],
 [0, 0, 0]], 4)

Methods

__init__(*args, **kwargs)	Returns the Ising quadratic model initialized by input and constraints.
check_constraints(*args, **kwargs)	Overloaded function.

Attributes

input_constraints	Returns the constraints of the Ising quadratic model.
input_matrix	Equivalent to logical_matrix.
input_poly	Returns the input IsingIntPoly.
logical_mapping	Returns the mapping from input varieties to logical varieties.
logical_matrix	Returns the pair of IsingIntMatrix and the constant term of the Ising quadratic model.
logical_model_matrix	Is almost same as logical_matrix, but includes the constraint terms.
logical_model_poly	Is almost same as logical_poly, but includes the constraint terms.
logical_poly	Returns IsingIntPoly, which represents the Ising quadratic model.
num_input_vars	Returns the number of variables in the input Ising quadratic model.
num_logical_vars	Returns the number of variables in the converted Ising quadratic model.
substituion_multiplier

check_constraints(*args, **kwargs)

Overloaded function.

1. check_constraints(self: amplify.IsingIntQuadraticModel, arg0: List[int]) -> List[Tuple[amplify.IsingIntConstraintTermRef, bool]]

no docstring

2. check_constraints(self: amplify.IsingIntQuadraticModel, arg0: Dict[int, int]) -> List[Tuple[amplify.IsingIntConstraintTermRef, bool]]

3. check_constraints(self: amplify.IsingIntQuadraticModel, arg0: function) -> List[Tuple[amplify.IsingIntConstraintTermRef, bool]]

property input_constraints

Returns the constraints of the Ising quadratic model.

Example

>>> from amplify import (gen_symbols,
... IsingIntPoly,
... IsingIntQuadraticModel)
>>> from amplify.constraint import equal_to
>>> s = gen_symbols(IsingIntPoly, 1)
>>> model = IsingIntQuadraticModel(equal_to(s[0], 1))
>>> eq = model.input_constraints.pop()
>>> eq.is_satisfied([-1])
False
>>> eq.is_satisfied([1])
True

property input_matrix

Equivalent to logical_matrix.

property input_poly

Returns the input IsingIntPoly.

Example

>>> from amplify import (IsingIntPoly,
... IsingIntQuadraticModel)
>>> poly = IsingIntPoly({(0, 1, 2) : 1})
>>> model = IsingIntQuadraticModel(poly)
>>> model.input_poly
s_0 s_1 s_2

property logical_mapping

Returns the mapping from input varieties to logical varieties.

Example

>>> from amplify import (IsingIntMatrix,
... IsingIntQuadraticModel)
>>> mat = IsingIntMatrix(3)
>>> model = IsingIntQuadraticModel(mat)
>>> model.logical_mapping
{2: 2, 0: 0, 1: 1}

property logical_matrix

Returns the pair of IsingIntMatrix and the constant term of the Ising quadratic model.

Example

>>> from amplify import (IsingIntMatrix,
... IsingIntQuadraticModel)
>>> mat = IsingIntMatrix(3)
>>> mat[0, 1] = 1
>>> mat[0, 2] = 2
>>> mat[1, 2] = 3
>>> poly = mat.to_Poly()
>>> poly += 4
>>> model = IsingIntQuadraticModel(poly)
>>> model.logical_matrix
([[0, 1, 2],
 [0, 0, 3],
 [0, 0, 0]], 4)

property logical_model_matrix

Is almost same as logical_matrix, but includes the constraint terms.

Example

>>> from amplify import (IsingIntMatrix,
... IsingIntQuadraticModel)
>>> from amplify.constraint import equal_to
>>> mat = IsingIntMatrix(3)
>>> mat[0, 1] = 1
>>> mat[0, 2] = 2
>>> mat[1, 2] = 3
>>> poly = mat.to_Poly()
>>> poly += 4
>>> model = IsingIntQuadraticModel(poly, equal_to(s[0], 1))
>>> model.logical_model_matrix
([[-2, 1, 2],
 [0, 0, 3],
 [0, 0, 0]], 6)

property logical_model_poly

Is almost same as logical_poly, but includes the constraint terms.

Example

>>> from amplify import (gen_symbols,
... IsingIntQuadraticModel)
>>> from amplify.constraint import equal_to
>>> s = gen_symbols(IsingIntQuadraticModel, 3)
>>> model = IsingIntQuadraticModel(s[0] + s[1] + s[2], equal_to(s[0], 1))
>>> model.logical_model_poly
s_0 + s_1 - s_2 + 2

property logical_poly

Returns IsingIntPoly, which represents the Ising quadratic model.

Note

The logical_poly variables don't always correspond to the input_poly variables, even if input_poly is quadratic.

Example

>>> from amplify import (IsingIntPoly,
... IsingIntQuadraticModel)
>>> poly = IsingIntPoly({(0, 1, 2) : 1})
>>> model = IsingIntQuadraticModel(poly)
>>> model.logical_poly
s_0 s_1 + s_0 s_2 - 2 s_0 s_3 + s_1 s_2 - 2 s_1 s_3 - 2 s_2 s_3 + s_0 + s_1 + s_2 - 2 s_3 + 3

property num_input_vars

Returns the number of variables in the input Ising quadratic model.

Example

>>> from amplify import (IsingIntPoly,
... IsingIntQuadraticModel)
>>> poly = IsingIntPoly({(0, 1, 2) : 1})
>>> model = IsingIntQuadraticModel(poly)
>>> model.num_input_vars
3

property num_logical_vars

Returns the number of variables in the converted Ising quadratic model.

Example

>>> from amplify import (IsingIntPoly,
... IsingIntQuadraticModel)
>>> poly = IsingIntPoly({(0, 1, 2) : 1})
>>> model = IsingIntQuadraticModel(poly)
>>> model.num_logical_vars
4