Abstract: Analysis of an electromagnetic wave traveling in an optical device, can be performed quickly and correctly. A structure forming process simulator forms an analysis structure of a physical object to be analyzed. A hybrid optical simulator calculates time-independent data and time-dependent data of an electromagnetic field by dividing the analysis structure into parts, determining whether a metallic or magnetic material is included in each of the divided parts, and selectively applying a Beam Propagation Method (BPM) or a Finite Difference Time Domain (FDTD) method to the divided parts. A storage device stores the time-independent data and the time-dependent data output from the hybrid optical simulator as hybrid electric field data. Related methods are also described.

Abstract: Analysis of an electromagnetic wave traveling in an optical device, can be performed quickly and correctly. A structure forming process simulator forms an analysis structure of a physical object to be analyzed. A hybrid optical simulator calculates time-independent data and time-dependent data of an electromagnetic field by dividing the analysis structure into parts, determining whether a metallic or magnetic material is included in each of the divided parts, and selectively applying a Beam Propagation Method (BPM) or a Finite Difference Time Domain (FDTD) method to the divided parts. A storage device stores the time-independent data and the time-dependent data output from the hybrid optical simulator as hybrid electric field data. Related methods are also described.

Abstract: A chromosome using each of a plurality of parameters of a physical model of a semiconductor element as a gene is defined and the parameters are optimized using a genetic algorithm based on the characteristics measurement data of the semiconductor element fabricated by way of trial. In the selection processing of the genetic algorithm, a sum of a first evaluation value based on linear scale data and a second evaluation value based on logarithmic scale data is employed as the evaluation value of the chromosome.

Abstract: A chromosome using each of a plurality of parameters of a physical model of a semiconductor element as a gene is defined and the parameters are optimized using a genetic algorithm based on the characteristics measurement data of the semiconductor element fabricated by way of trial. In the selection processing of the genetic algorithm, a sum of a first evaluation value based on linear scale data and a second evaluation value based on logarithmic scale data is employed as the evaluation value of the chromosome.

Abstract: In a solution search apparatus, a parameter search range input part acquires a search range of a parameter, and stores it in a parameter search range storing part. Then, with respect to the search range of the parameter stored in the parameter search range storing part, a parameter setting part sets initial values of the parameter so that logarithmic values of parameter values may become a uniform distribution and a normal distribution for at least a part of the search range of the parameter, and stores them in the parameter storing part. A search part reads the parameter stored in the parameter storing part and searches for a solution by a predetermined algorithm.

Abstract: An optimization method for extracting a model parameter in a semiconductor circuit. A fitness function circuit 15 installed in a genetic algorithm machine 900 is provided with an evaluated value calculation section 21, which receives an offspring model parameter from an offspring model parameter file 44, obtains k model evaluated values based on the offspring model parameter received, and stores the k model evaluated values in an evaluated value file 32 in a storage section 17. The fitness function circuit 15 is also provided with an area calculation section 22, which reads the k model evaluated values stored in the evaluated value file 32 by the evaluated value calculation section 21, calculates the size of an area formed by the k model evaluated values read, and stores the size of the area in an area value file 33 in the storage section 17.

Abstract: A semiconductor memory device, in particular a dynamic random access memory cell which realizes a high speed thereof and presenting a superior controllability. The dynamic random access memory (DRAM) cell includes: a first transistor; a second transistor, electrically connected in series to the first transistor, for storing an electric charge, the second transistor including a portion for erasing the charge stored at the second transistor, wherein the first transistor and the second transistor are electrically connected between a power line and a bit line; and a diode electrically connected between the first transistor and the second transistor.

Abstract: A method of generating a discretization grid for a finite-difference simulation capable of simulating an object with a complex cross-sectional configuration accurately is disclosed. The method includes the step of generating grid through each vertex of the polygonal figure representing the cross-sectional configuration, and the step of generating additional grid through each intersection of the grid and the segments of the polygonal figure not parallel to the grid.