A new implementation of density functional theory (DFT), namely orbital-corrected orbital-free (OO) DFT, has been developed. With at most two non-self-consistent iterations, OO-DFT accomplishes the accuracy comparable to fully self-consistent Kohn-Sham DFT as demonstrated by its application on the cubic-diamond Si and the face-centered-cubic Ag systems. Our work provides a new impetus to furthe...

For many years, the semiconductor industry has been predicting the emergence of DFT tester market, enabled by increasing number of devices being designed with DFT methodologies such as scan and BIST. The search for low cost DFT tester solutions has resulted in the first ITRS roadmap for a DFT tester in 1999 and a major revision of this roadmap in 2001. While it is generally understood that a DF...

The DFT and Test challenges faced, and the solutions applied, to the ARMl026EJ microprocessor core are described in this paper. New DFT techniques have been created to address the challenges of distributing a DFT core solution that will ultimately end up in many different environments. This core was instantiated into a test chip. The new DFT features were utilized successfully in the SOC.

Large scale Density Functional Theory (DFT) based electronic structure calculations are highly time consuming and scale poorly with system size. While semi-empirical approximations to DFT result in a reduction in computational time versus ab initio DFT, creating such approximations involves significant manual intervention and is highly inefficient for high-throughput electronic structure screen...

The DFT and Test challenges faced, and the solutions applied, to the ARM1026EJ microprocessor core are described in this paper. New DFT techniques have been created to address the challenges of distributing a DFT core solution that will ultimately end up in many different environments. This core was instantiated into a test chip. The new DFT features were utilized successfully in the SoC.

We present an extension of reverse engineered Kohn-Sham potentials from a density matrix renormalization group calculation towards the construction functional theory via deep learning. Instead applying machine learning to energy itself, we apply these techniques potentials. To this end develop scheme train neural network represent mapping local densities Finally, use up-scale simulation larger ...

In this article, we investigate the linear precoder based on the maximization of the minimum Euclidean distance between two received data vectors. This new precoding matrix is expressed as the product of a power allocation matrix and an input-shaping matrix. The input-shaping matrix is selected as a normalized discrete Fourier transform-matrix, and the optimal power allocation depends on the ch...

Orbital-free density-functional theory (OF-DFT) with modern kinetic-energy density functionals (KEDFs) is a linear scaling technique that accurately describes nearly-free-electron-like (main group) metals. In an attempt towards extending OF-DFT to transition metals, here we consider whether OF-DFT can be used effectively to study Ag, a metal with a localized d shell. OF-DFT has two approximatio...

This paper presents a novel two-dimensional split-vector-radix fast-Fourier-transform (2D svr-FFT) algorithm. The modularizing feature of the 2D svr-FFT structure enables us to explore its characteristics by identifying the local structural property. Each local module is designated as a DFT (non-DFT) block if its output corresponds to DFT (non-DFT) values. The block attribute (DFT or non-DFT) d...

There are three different way to calculate DFT. First method is using formula of DFT or simultaneous equation. Second is Correlation technique and third one is using Fast Fourier Transform (FFT). First method is useful for understanding of basic idea of DFT, but it is not fit for practical and application purpose. In second method is based on detecting known waveform in another signal. It is us...