def fulladder_gate(in0: Variable,
in1: Variable,
in2: Variable,
sum_: Variable,
carry: Variable,
*,
strength: float = 1.0) -> BinaryQuadraticModel:
"""Return a binary quadratic model with ground states corresponding to a
full adder gate.
Args:
in0: The variable label for one of the inputs.
in1: The variable label for one of the inputs.
in2: The variable label for one of the inputs
sum_: The variable label for the sum output.
carry: The variable label for the carry output.
strength: The energy of the lowest-energy infeasible state.
Returns:
A binary quadratic model with ground states corresponding to a full
adder gate. The model has five variables and ten interactions.
"""
bqm = BinaryQuadraticModel(Vartype.BINARY)
# add the variables (in order)
bqm.add_variable(in0, bias=1)
bqm.add_variable(in1, bias=1)
bqm.add_variable(in2, bias=1)
bqm.add_variable(sum_, bias=1)
bqm.add_variable(carry, bias=4)
# add the quadratic biases
bqm.add_quadratic(in0, in1, 2)
bqm.add_quadratic(in0, in2, 2)
bqm.add_quadratic(in0, sum_, -2)
bqm.add_quadratic(in0, carry, -4)
bqm.add_quadratic(in1, in2, 2)
bqm.add_quadratic(in1, sum_, -2)
bqm.add_quadratic(in1, carry, -4)
bqm.add_quadratic(in2, sum_, -2)
bqm.add_quadratic(in2, carry, -4)
bqm.add_quadratic(sum_, carry, 4)
# the bqm currently has a strength of 1, so just need to scale
if strength <= 0:
raise ValueError("strength must be positive")
bqm.scale(strength)
return bqm
def and_gate(in0: Variable,
in1: Variable,
out: Variable,
*,
strength: float = 1.0) -> BinaryQuadraticModel:
"""Return a binary quadratic model with ground states corresponding to an
AND gate.
Args:
in0: The variable label for one of the inputs.
in1: The variable label for one of the inputs.
out: The variable label for the output.
strength: The energy of the lowest-energy infeasible state.
Returns:
A binary quadratic model with ground states corresponding to an AND
gate. The model has three variables and three interactions.
"""
bqm = BinaryQuadraticModel(Vartype.BINARY)
# add the variables (in order)
bqm.add_variable(in0)
bqm.add_variable(in1)
bqm.add_variable(out, bias=3)
# add the quadratic biases
bqm.add_quadratic(in0, in1, 1)
bqm.add_quadratic(in0, out, -2)
bqm.add_quadratic(in1, out, -2)
# the bqm currently has a strength of 1, so just need to scale
if strength <= 0:
raise ValueError("strength must be positive")
bqm.scale(strength)
return bqm