Abstract: A problem is inputted into an operation unit. A computation unit searches for a ground state of an Ising model. A management unit converts the problem inputted from the operation unit to the Ising model, inputs the Ising model produced by conversion and initial operating conditions into the computation unit, and has the computation unit search for the ground state using overall operating conditions produced by changing the initial operating conditions based on a result of the computation unit searching for the ground state using the initial operating conditions.

Abstract: An information processing device includes: a memory; and a processor configured to: hold each of values of state variables included in an evaluation function representing energy; calculate the change value of the energy for each of state transitions, when a state transition occurs due to a change of any of the values of the state variables; control a temperature value representing temperature; select any of the state transitions, based on priority information set based on state transition information updated last time with respect to identification information for identifying each state transition, and transition acceptance information indicating transition acceptance determined based on the change value, and a generated thermal noise; and output a lowest energy state which is the values of the state variables when the energy to be updated based on the selected state transition becomes a lowest value.

Abstract: A non-transitory computer-readable recording medium storing a function generation program that causes processor to execute a process, the process includes acquiring problem information representing a discrete optimization problem that have a constraint condition, and generating, by subtracting a conserved value function having a certain value when a solution satisfies the constraint condition from a first cost function, or by adding the conserved value function to the first cost function, a second evaluation function including a second cost function that has a second absolute value smaller than a first absolute value of the first cost function of a first evaluation function, the first evaluation function being represented based on the problem information, and being represented by a linear sum of the first cost function and a penalty function that becomes 0 when the constraint condition is satisfied and becomes a value other than 0 when the constraint condition is not satisfied.

Abstract: An optimization device includes: search circuits, each configured to: hold values of state variables included in an evaluation function representing an energy value; calculate a change value of the energy value for each of state transitions which occurs in response to a change in one of the state variables; and determine stochastically whether to accept one of the state transitions according to a relative relationship between the change value of the energy value and thermal excitation energy, based on a set temperature value, the change value, and a random number value; and a controller configured to: acquire statistical information regarding a transition of a temperature value in each search circuit; determine a temperature value to be set in each search circuit based on the statistical information; set the temperature value for each search circuit; and exchange the temperature value or the values of the state variables between the search circuits.

Abstract: A random number generation device includes: a pseudo-random number generation circuit configured to generate a plurality of first pseudo-random numbers; and an orthogonal transformation circuit configured to generate a plurality of normal random numbers by performing orthogonal transformation on the plurality of first pseudo-random numbers, or by performing orthogonal transformation on the plurality of first pseudo-random numbers and a second pseudo-random number.

Abstract: An optimization device includes: a processor; and search circuits configured to determine energy values for combinations of two state variables of a state variables, based on weight values each indicating strength of connection between the two state variables, and values of the two state variables, determine values of the state variables, based on results of comparison between evaluation values obtained by adding a noise value corresponding to a temperature to each energy value, and a threshold value, and be set to be equal to each other in connection states between the state variables based on the weight values, the processor is configured to: determine an exchange count, based on a difference between a temperature set for a search circuit corresponding to the lowest energy value, and a minimum temperature; set a temperature for each search circuit; and exchange the set temperatures between the search circuits for the exchange count.

Abstract: An optimization device includes: a state hold circuit that holds values of state variables included in an evaluation function that represents energy; an objective function calculation circuit that calculates an energy change value in an objective function included in the evaluation function for each of state transitions when a state transition occurs in response to a change in any of the values of the state variables; a constraint term calculation circuit that calculates a constraint term evaluation value, which is an evaluation value of a constraint term included in the evaluation function, for each of the state transitions; a temperature control circuit that controls a temperature value that indicates a temperature; and a transition control circuit that determines stochastically whether to accept any of the state transitions based on the temperature value, a random number value, and a sum of the change value and the constraint term evaluation value.

Abstract: A random number generation device includes: a pseudo-random number generation circuit configured to generate a plurality of first pseudo-random numbers; and an orthogonal transformation circuit configured to generate a plurality of normal random numbers by performing orthogonal transformation on the plurality of first pseudo-random numbers, or by performing orthogonal transformation on the plurality of first pseudo-random numbers and a second pseudo-random number.

Abstract: A first evaluation function calculation unit and a second evaluation function calculation unit calculate a cost function term Ei and a penalty function term Pi in an evaluation function, respectively. A transition control unit stochastically determines whether to accept any of state transitions, based on a product of a ratio between an inverse temperature ?i and a penalty factor ?i and Pi and Ei. An exchange control unit supplies ?i and ?i to each annealing unit, ?i and ?i having been set such that each annealing unit has a different ratio between ?i and ?i, receives Ei and Pi from each annealing unit, and exchanges ?i between first and second annealing units among the plurality of annealing units and ?i between the first and second annealing units, in accordance with a probability based on ?i, ?i, Ei, and Pi of the first and second annealing units.

Abstract: An optimization device includes: a processor; and search circuits configured to determine energy values for combinations of two state variables of a state variables, based on weight values each indicating strength of connection between the two state variables, and values of the two state variables, determine values of the state variables, based on results of comparison between evaluation values obtained by adding a noise value corresponding to a temperature to each energy value, and a threshold value, and be set to be equal to each other in connection states between the state variables based on the weight values, the processor is configured to: determine an exchange count, based on a difference between a temperature set for a search circuit corresponding to the lowest energy value, and a minimum temperature; set a temperature for each search circuit; and exchange the set temperatures between the search circuits for the exchange count.

Abstract: An information processing device includes: a memory; and a processor configured to: hold each of values of state variables included in an evaluation function representing energy; calculate the change value of the energy for each of state transitions, when a state transition occurs due to a change of any of the values of the state variables; control a temperature value representing temperature; select any of the state transitions, based on priority information set based on state transition information updated last time with respect to identification information for identifying each state transition, and transition acceptance information indicating transition acceptance determined based on the change value, and a generated thermal noise; and output a lowest energy state which is the values of the state variables when the energy to be updated based on the selected state transition becomes a lowest value.

Abstract: An optimization device includes: a state hold circuit that holds values of state variables included in an evaluation function that represents energy; an objective function calculation circuit that calculates an energy change value in an objective function included in the evaluation function for each of state transitions when a state transition occurs in response to a change in any of the values of the state variables; a constraint term calculation circuit that calculates a constraint term evaluation value, which is an evaluation value of a constraint term included in the evaluation function, for each of the state transitions; a temperature control circuit that controls a temperature value that indicates a temperature; and a transition control circuit that determines stochastically whether to accept any of the state transitions based on the temperature value, a random number value, and a sum of the change value and the constraint term evaluation value.

Abstract: An optimization device includes: search circuits, each configured to: hold values of state variables included in an evaluation function representing an energy value; calculate a change value of the energy value for each of state transitions which occurs in response to a change in one of the state variables; and determine stochastically whether to accept one of the state transitions according to a relative relationship between the change value of the energy value and thermal excitation energy, based on a set temperature value, the change value, and a random number value; and a controller configured to: acquire statistical information regarding a transition of a temperature value in each search circuit; determine a temperature value to be set in each search circuit based on the statistical information; set the temperature value for each search circuit; and exchange the temperature value or the values of the state variables between the search circuits.

Abstract: An optimization device includes: a state hold circuit that holds values of a plurality of state variables included in an evaluation function representing energy; a calculation circuit that calculates a change value of the energy for each transition occurred in response to a change in any of the values of the plurality of state variables; and a transition control circuit including: a plurality of first selection circuits each of which randomly selects an intermediate candidate from a predetermined number of state transitions based on a propriety of acceptance of each of the state transitions, the propriety being obtained by comparing thermal excitation energy with an energy change for a corresponding state transition, the thermal excitation energy being calculated using each of independent random numbers a number of which is same as the predetermined number; and a second selection circuit that randomly selects one state transition from intermediate candidates selected.

Abstract: When a transition control unit stochastically determines whether to accept one of a plurality of state transitions, using a temperature, an energy change, and a random number, depending on a relative relationship between the energy change and thermal excitation energy, the transition control unit adds an offset to the energy change, controls the offset so as to be larger at a local minimum, at which the energy is locally minimized, than at a solution at which the energy is not minimized, and resets the offset to zero when the energy change value is larger than a threshold.

Abstract: When stochastically deciding, based on a change in energy and a random number relating to thermal excitation, whether to accept any of a plurality of state transitions according to the relative relationship between the change in energy and thermal excitation energy, a transition control unit adds an offset to the change in energy, performs control so that the offset at a local minimum where energy is locally minimized is larger than an offset when the energy is not minimized, holds transition information (a transition number) indicating a previous state transition, and prohibits, based on a decoding result for the held transition information, a first state transition out of the present state transition candidates.

Abstract: A problem is inputted into an operation unit. A computation unit searches for a ground state of an Ising model. A management unit converts the problem inputted from the operation unit to the Ising model, inputs the Ising model produced by conversion and initial operating conditions into the computation unit, and has the computation unit search for the ground state using overall operating conditions produced by changing the initial operating conditions based on a result of the computation unit searching for the ground state using the initial operating conditions.

Abstract: A first evaluation function calculation unit and a second evaluation function calculation unit calculate a cost function term Ei and a penalty function term Pi in an evaluation function, respectively. A transition control unit stochastically determines whether to accept any of state transitions, based on a product of a ratio between an inverse temperature ?i and a penalty factor ?i and Pi and Ei. An exchange control unit supplies ?i and ?i to each annealing unit, ?i and ?i having been set such that each annealing unit has a different ratio between ?i and ?i, receives Ei and Pi from each annealing unit, and exchanges ?i between first and second annealing units among the plurality of annealing units and ?i between the first and second annealing units, in accordance with a probability based on ?i, ?i, Ei, and Pi of the first and second annealing units.

Abstract: An optimization apparatus includes: a state retention unit configured to retain a set of values of state variables for an evaluation function representing energy; a first evaluation function calculation unit configured to calculate an energy value of a first evaluation function including a first penalty coefficient; a transition control unit configured to determine whether or not a state transition for changing one of the values of the state variables is to be accepted stochastically, based on at least a variation of the energy value of the first evaluation function; a second evaluation function calculation unit configured to calculate an energy value of a second evaluation function including a second penalty coefficient larger than the first penalty coefficient; and an energy comparing unit configured to determine a minimum energy value of the energy value of the first evaluation function or the second evaluation function.

Abstract: When a transition control section stochastically determines on the basis of a temperature, an energy change, and a random number whether to allow one of a plurality of state transitions according to a relative relationship between the energy change and a thermal excitation energy, the transition control section adds an offset to the energy change and exercises control so as to set the offset at a local minimum, at which an energy is locally minimized, to be larger than an offset at the time of the energy not being minimized.