Hirotaka Tamura has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
Abstract: A liquid composition contains a thiophene polymer and a solvent, and the difference |?p2??p1| is 7.7 MPa0.5 or more and 13.4 MPa0.5 or less between a dipole-dipole force term ?p1 of Hansen solubility parameter of the thiophene polymer and a dipole-dipole force term ?p2 of Hansen solubility parameter of the solvent.
April 20, 2022
November 17, 2022
FUJIFILM Business Innovation Corp., NATIONAL UNIVERSITY CORPORATION CHIBA UNIVERSITY
Abstract: In an optimization apparatus, calculation circuits individually calculate a change in energy based on first local field values each associated with one of n bits (n is an integer greater than or equal to 2) amongst a plurality of bits corresponding to spins in an Ising model, values of the n bits, and one or more weight values representing strength of interaction among the n bits. The change in energy is caused by flips of the n bits. An update bit selection circuit selects the n bits for which value update is accepted, based on the magnitude relationship between thermal excitation energy and each of the calculated changes in energy. An update circuit flips the n bits, and also updates, based on the flips of the n bits, second local field values including the first local field values and each associated with the plurality of individual bits.
Abstract: An optimization device includes: k first calculation circuits, N?k second calculation circuits, a selection circuit, an identification information calculation circuit and an update circuit. The first calculation circuit calculates a first energy change of an Ising model due to a change of a value of one of k first bits having values of 1 and a change of a value of a second bit having a value of 0 selected based on a generated first random number. The second calculation circuit calculates a second energy change of the Ising model due to a change of a value of one of (N?k) third bits having the values of 0 and a change of a value of a fourth bit having a value of 1 selected based on a generated second random number.
Abstract: Storage devices each hold corresponding one of n weight coefficient groups obtained by dividing weight coefficients such that each group includes weight coefficients about at least two bits. Bit value calculation circuits each output a result (flag information) by determining whether to accept updating about each of the bits based on the weight coefficient group, a value of an updated bit, identification information, and thermal excitation energy and an updated value of an accepted bit whose uprate has been accepted. First selection circuits each select an accepted bit based on the flag information and output a state signal including the flag information, the updated value, and identification information associated with the accepted bit. A second selection circuit determines the updated bit based on the flag information in the state signal and supplies the value of the updated bit and the identification information to each of optimization apparatuses.
Abstract: An information processing device includes: a memory configured to hold values of state variables included in an evaluation function presenting energy and a weight value for each set of the state variables; and a processor coupled to the memory and configured to: calculate an energy change value when each of the values of the state variables is set as a next change candidate based on the values of the state variables and the weight value; calculate a total energy change value by adding a penalty value according to an excess amount violating an inequality constraint, to each of the energy change values calculated for the state variables, the excess amount being calculated based on a coupling coefficient and a threshold value; and change any value of the state variables in the memory based on a set temperature value, a random number value, and the total energy change values.
Abstract: An optimization apparatus includes a memory and a processor. The memory stores one or more coupling coefficients that represent interaction of a plurality of variables corresponding to a plurality of bits included in an energy function. The processor selects, based on a difference of a value of the energy function associated with inversion of a value of each of the plurality of bits, adoption or rejection of bit inversion to perform optimization. The processor specifies a coupling coefficient corresponding to an auxiliary variable from the one or more coupling coefficients, the auxiliary variable being a product of variables corresponding to respective bits from which a variable corresponding to a specific bit in the energy function is excluded, and executes calculation of a term of a third-order or higher of a difference associated with inversion of the specific bit using the auxiliary variable and the coupling coefficient.
Abstract: An information processing device includes: a memory; and a processor coupled to the memory and configured to calculate, for a plurality of bits corresponding to a plurality of spins included in an Ising model obtained by converting a problem to be calculated, in a case where the plurality of bits is divided into a plurality of groups, on the basis of a first local field value for a first bit having a value of 1 and a second local field value for a second bit having a value of 0 among a plurality of bits included in each of the plurality of groups, a first energy change of the Ising model due to a change of the value of the first bit from 1 to 0 and a change of the value of the second bit from 0 to 1.
Abstract: [Problem] There is provided a goods inspection device making it possible to make a diagnosis easily for inspection function failure caused by dynamic behavior of goods attributed to a conveyance subsystem of an inspection line. [Solution] The goods inspection device 1 that inspects goods being carried on an inspection line includes a diagnosis unit 25c that diagnoses a conveyance subsystem of the inspection line, based on data of acceleration and angular velocity obtained with respect to respective axial directions from a test object 2 when the test object 2 having a motion sensor 12 to detect acceleration and angular velocity with respect to respective directions of three-dimensional axes is carried.
Abstract: An information processing apparatus includes one or more memories; and one or more processors coupled to the one or more memories and the one or more processors configured to decompose a first matrix of a coupling coefficient which represents interaction between a plurality of variables into a plurality of matrices by using a rank number, obtain, from the plurality of matrices, a second element that corresponds to a first element of the coupling coefficient, and restore the first element based on the second element.
Abstract: An optical fiber has a structure uniform in a longitudinal direction. This optical fiber includes a core and a cladding that surrounds the core in a cross-section perpendicular to the longitudinal direction. A refractive index of the cladding is lower than a refractive index of the core. The cladding has, in the cross-section, an inner cladding layer including an inner circumferential surface of the cladding, and an outer cladding layer including an outer circumferential surface of the cladding. The inner cladding layer contains fluorine. The inner and outer cladding layers have refractive indexes different from each other. The outer cladding layer includes a local maximum portion where a residual stress, which is a tensile stress, becomes local maximum. A radial distance between the local maximum portion and an inner circumferential surface of the outer cladding layer is 10 ?m or less.
Abstract: An information processing apparatus includes: a memory; and a processor coupled to the memory and configured to: hold values of a plurality of state variables included in an evaluation function representing energy, and outputs, every certain number of trials, the values of the plurality of state variables; compute, when a state transition occurs in response to changing of one of the values of the plurality of state variables, an energy change value for each state transition based on a weight value selected based on an update index value; and determine a first offset value based on a plurality of the energy change values such that at least one of the state transitions is allowed, outputs a plurality of first evaluation values obtained by adding the first offset value to the plurality of energy change values, and outputs, every certain number of trials, the first offset value.
Abstract: An individual ising device connected to common buses includes neuron circuits, a memory, and a router. The memory holds connection destination information per neuron circuit. An individual item of connection destination information includes first address information identifying one of a plurality of connection destination neuron circuits of a neuron circuit and second address information identifying a first ising device including at least one of the connection destination neuron circuits, the first and second address information being correlated.
Abstract: An optimization device includes a plurality of calculation circuits; a selection circuit; an identification information calculation circuit, and an updating circuit. Each of the plurality of calculation circuits calculates, for a plurality of bits corresponding to a plurality of spins included in an Ising model obtained by converting a problem to be calculated, a first energy change of the Ising model due to a value of a first bit having the value of 1 being changed from 1 to 0 and a value of a second bit having the value of 0 being changed from 0 to 1. The selection circuit outputs first bit identification information identifying one second bit having a value permitted to be updated from 0 to 1, based on a magnitude relationship between thermal excitation energy and the first energy change output by each of the plurality of calculation circuits.
Abstract: An optimization method implemented by a computer configured to search for a solution using a replica exchange method, the optimization method includes: generating a reference bit to be referred to by each of a plurality of replicas, based on first states of respective replicas of the plurality of replicas at a time that is predetermined; causing each of the plurality of replicas to refer to the generated reference bit; and specifying second states at a time later than the time.
Abstract: According to an aspect of an embodiment, operations may include obtaining a first matrix associated with an optimization problem associated with a system and obtaining a second matrix associated with the optimization problem. The operations may include obtaining a local field matrix that indicates interactions between the variables of the system as influenced by their respective weights. The operations may include updating the local field matrix. Updating the local field matrix may include performing arithmetic operations with respect to a first portion of the first matrix and a second portion of the second matrix that correspond to a third portion of the local field matrix that corresponds to the one or more variables. The operations may include updating an energy value of the system based on the updated local field matrix and determining a solution to the optimization problem based on the energy value.
April 15, 2020
October 21, 2021
FUJITSU LIMITED, THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO
Mohammad BAGHERBEIK, Ali SHEIKHOLESLAMI, Hirotaka TAMURA, Kouichi KANDA
Abstract: A sampling method includes: executing a state update process; executing a repetition count calculation process; executing an exchange control process; and executing an output process, the state update process being configured to hold values of a plurality of state variable groups each including a plurality of state variables, the plurality of state variables being included in an evaluation function indicating energy of an Ising model, and generate a state transition by changing any of the plurality of state variables in each attempt on the basis of a temperature value, in which different values are respectively associated with the plurality of state variable groups, and an amount of change in the energy due to a change in any of the plurality of state variables, the output process being configured to output values of the plurality of state variables and an expected value at a predetermined interval.
Abstract: A method includes: accessing first storage configured to store a first weight coefficient group which is at least some of a plurality of weight coefficients indicating a magnitude of interaction between a plurality of state variables in an evaluation function representing energy of an Ising model; accessing a plurality of second storages each of the plurality of second storage being configured to store a second weight coefficient group related to a state variable having a value of 1 in any of a plurality of state variable groups respectively including the plurality of state variables among the plurality of weight coefficients; outputting, for each of the plurality of state variable groups, a search result obtained by performing searching processing configured to perform processing of searching for an optimum solution by repeatedly performing a first update process with a first constraint or a second update process with a second constraint.
Abstract: An optimization method executed by a computer upon attempting to solve a ground state of an Ising model by simulating a state change of the Ising model when a magnetic field applied to the Ising model is reduced, the Ising model representing a problem to be solved, the method including: executing a first process, the first process being a real time propagation in which an intensity of the magnetic field is reduced with progress of time in simulation; and in response to the progress of time in the real time propagation of the first process, executing a second process, the second process including reducing energy of the Ising model based on an imaginary time propagation method.
Abstract: According to an aspect of an embodiment, operations may include obtaining a first fixed temperature and a second fixed temperature of a replica exchange Markov Chain Monte Carlo (MCMC) process used to solve an optimization problem associated with a system, and obtaining a plurality of replicas of the system. The operations may also include obtaining a target swap acceptance probability with respect to swapping, during the replica exchange MCMC process, between replicas that correspond to adjacently ordered temperatures of a set of temperatures between the first fixed temperature and the second fixed temperature. The operations may include determining a respective average swap acceptance probability with respect to one or more respective adjacent pairs of temperatures. Further, the operations may include adjusting one or more of the variable temperatures based on a relationship between the target swap acceptance probability and each of one or more of the respective swap acceptance probabilities.
January 5, 2021
September 9, 2021
FUJITSU LIMITED, THE GOVERNING COUNCIL OF THE UNIVERSITY OF TORONTO
Keivan DABIRI, Ali SHEIKHOLESLAMI, Mehrdad MALEKMOHAMMADI, Hirotaka TAMURA
Abstract: Boltzmann machine includes a plurality of circuit units each having an adder that adds weighted input signals and a comparison unit that compares an output signal of the adder with a threshold signal to output a binary output signal; and digital arithmetic units each generating the weighted input signals by weighting the binary output signal of the circuit units with a weight. The comparison unit has a first comparator that compares a thermal noise with a reference voltage to output a binary digital random signal, a DA converter that converts the digital random signal to an analog random signal and varies a magnitude of the analog random signal, and a second comparator that compares the output signal of the adder with the analog random signal to generate the binary output signal with a predetermined probability function.