Density functional theory

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Density functional theory (DFT) is a quantum mechanical modelling method used in physics and chemistry to investigate the electronic structure of many-body systems, in particular atoms, molecules, and the condensed phases. (Wikipedia.org)






Conferences related to Density functional theory

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2021 IEEE Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE 21st International Conference on Vacuum Electronics (IVEC)

Technical presentations will range from the fundamental physics of electron emission and modulated electron beams to the design and operation of devices at UHF to THz frequencies, theory and computational tool development, active and passive components, systems, and supporting technologies.System developers will find that IVEC provides a unique snapshot of the current state-of-the-art in vacuum electron devices. These devices continue to provide unmatched power and performance for advanced electromagnetic systems, particularly in the challenging frequency regimes of millimeter-wave and THz electronics.Plenary talks will provide insights into the history, the broad spectrum of fundamental physics, the scientific issues, and the technological applications driving the current directions in vacuum electronics research.


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Robotics and Automation (ICRA)

The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.


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Periodicals related to Density functional theory

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Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Communications Letters, IEEE

Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)


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Most published Xplore authors for Density functional theory

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Xplore Articles related to Density functional theory

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Frequency adaptation efficiency of spread spectrum communications under narrowband interference

Radio Science, 2003

We investigate a new possibility of frequency adaptation for spread spectrum communication systems. A special index is introduced to characterize the adaptation gain referring to the nonadaptive case. An existence of frequency band limit is developed for the allocated frequency band for possible frequency maneuver. The investigation method can be adapted both to direct sequence and frequency hopping spread spectrum ...


A Markoff envelope process

IRE Transactions on Information Theory, 1958

It is shown that the envelope of a narrow-band Gaussian noise constitutes a first-order Markoff process if the power spectrum of the noise is the same as would be obtained from a singly tuned RLC filter with white noise at the input.


Numerical Model Based Approach for Estimating Probability of Detection in NDE Applications

Digest of the Fifth Biennial IEEE Conference on Electromagnetic Field Computation, 1992

None


Like and cross-polarized scatter cross sections for two-dimensional, multiscale rough surfaces based on a unified full wave variational technique

Radio Science, 2011

A variational method is used to select the specific, smooth decomposition of the total surface height spectral density function into surface height spectral density functions for the larger- and smaller-scale surfaces. Using this decomposition, the total like and cross-polarized scatter cross sections are expressed as weighted sums of physical optics scatter cross sections associated with the larger-scale surfaces and the ...


Classification Bias of the k-Nearest Neighbor Algorithm

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984

The k-nearest neighbor classifier has been used extensively in pattern analysis applications. This classifier can, however, have substantial bias when there is little class separation and the sample sizes are unequal. This classification bias is examined for the two-class situation and formulas presented that allows selection of values of k that yields minimum bias.


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Educational Resources on Density functional theory

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IEEE.tv Videos

Molecular Cellular Networks: A Non von Neumann Architecture for Molecular Electronics - Craig Lent: 2016 International Conference on Rebooting Computing
Erasing Logic-Memory Boundaries in Superconductor Electronics - Vasili Semenov: 2016 International Conference on Rebooting Computing
AlGaN/GaN Plasmonic Terahertz Detectors
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 3 of 7 - MEG and ULF-MRI
Superconductive Energy-Efficient Computing - ASC-2014 Plenary-series - 6 of 13 - Wednesday 2014/8/13
Bayesian Perception & Decision from Theory to Real World Applications
Q&A with Jack Gallant: IEEE Brain Podcast, Episode 11
International Future Energy Challenge (IFEC) 2017
Materials Challenges for Next-Generation, High-Density Magnetic Recording - Kazuhiro Hono: IEEE Magnetics Distinguished Lecture 2016
CASS Lecture with Dr. Claude Gauthier, "Automotive Ethernet and Functional Safety"
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Magdalena Salazar Palma
Fast Scale Prototyping for Folded Millirobots
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - David M. Pozar
International Future Energy Challenge 2018
IMS 2012 Special Sessions: A Retrospective of Field Theory in Microwave Engineering - Constantine A. Balanis
Inspiring Brilliance: The impact of control theory and cybernetics of Maxwell's paper: On governors
Multi-Function VCO Chip for Materials Sensing and More - Jens Reinstaedt - RFIC Showcase 2018
Infineon Technologies: Power Efficiency from Generation to Consumption
Larson Collection interview with John V. Atanasoff
IMS 2015: Four scientists who saved Maxwells Theory

IEEE-USA E-Books

  • Frequency adaptation efficiency of spread spectrum communications under narrowband interference

    We investigate a new possibility of frequency adaptation for spread spectrum communication systems. A special index is introduced to characterize the adaptation gain referring to the nonadaptive case. An existence of frequency band limit is developed for the allocated frequency band for possible frequency maneuver. The investigation method can be adapted both to direct sequence and frequency hopping spread spectrum techniques. In the paper only the narrowband interference case is treated.

  • A Markoff envelope process

    It is shown that the envelope of a narrow-band Gaussian noise constitutes a first-order Markoff process if the power spectrum of the noise is the same as would be obtained from a singly tuned RLC filter with white noise at the input.

  • Numerical Model Based Approach for Estimating Probability of Detection in NDE Applications

    None

  • Like and cross-polarized scatter cross sections for two-dimensional, multiscale rough surfaces based on a unified full wave variational technique

    A variational method is used to select the specific, smooth decomposition of the total surface height spectral density function into surface height spectral density functions for the larger- and smaller-scale surfaces. Using this decomposition, the total like and cross-polarized scatter cross sections are expressed as weighted sums of physical optics scatter cross sections associated with the larger-scale surfaces and the tilt-modulated scatter cross sections for the smaller-scale surfaces. This variational technique has been shown to be stationary over a wide range of the variational parameter. Since only the slopes of the larger-scale surfaces tilt modulate the cross sections of the smaller-scale surfaces, it is necessary to select surface height spectral density functions for the larger-scale surfaces that do not require the introduction of artificial spatial cutoff wave numbers for the spectral density functions. The methods used to smoothly decompose the surface height spectral density functions result in no artificial rapid fluctuations in the corresponding surface height autocorrelation functions for the smaller- and larger-scale surfaces. This method can be applied to the remote sensing of rough sea or land surfaces.

  • Classification Bias of the k-Nearest Neighbor Algorithm

    The k-nearest neighbor classifier has been used extensively in pattern analysis applications. This classifier can, however, have substantial bias when there is little class separation and the sample sizes are unequal. This classification bias is examined for the two-class situation and formulas presented that allows selection of values of k that yields minimum bias.

  • Structural reliability evaluation by importance sampling and Kalman filter

    A simulation method is proposed in which data are effectively sampled from an importance sampling density function and the probabilities of limit state functions are adaptively updated by using Kalman filter. The important constants for the procedure proposed are examined using a highly nonlinear problem.<<ETX>>

  • 2 GHz single-floor indoor propagation results

    Indoor propagation embraces various situations differing by the geometry of the buildings and their constituent materials. If the effects on propagation of these various parameters can be efficiently studied by a simulation approach, for instance by ray-tracing methods, it is necessary to assess the results of such studies by as much experimental data as possible collected in various types of environment.

  • Simplified Pseudopotential Problems for the Classroom

    Ab initio methods have been used for many decades to accurately predict properties of solids such as the physical, electronic, optical, magnetic, and elastic. A generation ago, many research groups developed their own in-house codes to perform ab initio calculations. In doing so, research students were intimately involved in many aspects of the coding, such as developing the theoretical framework, and algorithmic and programming details. Over time, however, collaborations between various research groups within academia and in industry have resulted in the creation of more than 50 large, open source, and commercial electronic structure packages. These software packages are widely used today for condensed matter research by students who, unfortunately, often have little understanding of the fundamental aspects of these codes. To address this shortcoming, a program at the University of Pretoria aims to devise a range of simplified, easily programmable computational problems appropriate for the classroom, which can be used to teach advanced undergraduate students about particular theoretical and computational aspects of the electronic structure method. This article focuses on the pseudopotential, which is a centrally important concept in many modern ab initio methods. Whereas the full implementation of the pseudopotential construct in a real electronic structure code requires complex numerical methods--for example, accelerated convergence to self-consistency including the interactions between all the electrons in the system--the essential principles of the pseudopotential can, nevertheless, be presented in a simpler class of problems, which students can readily code.

  • Correlation and coherence in many-electron system

    The inclusion of the correlation effect in many electron system was shown in the self-consistent density functional theory to yield the virial theorem, an important relation between the kinetic and the potential energies. This provides a correspondence principle and an accuracy that could rule out mechanisms not begetting results within the error limit. The coherence effect of exchange antisymmetry for fermions can readily couple with the correlation effect to result in rich physics. We show from a variational quantum Monte Carlo code that in the excited states of helium atom, the triplet state of like spins tends to have less repulsive dispersion than the singlet state of opposite spins.

  • MCMC and EM-based methods for inference in heavy-tailed processes with /spl alpha/-stable innovations

    In this paper we present both stochastic and deterministic iterative methods for inference about random processes with symmetric stable innovations. The proposed methods use a scale mixtures of normals (SMiN) representation of the symmetric stable law to express the processes in conditionally Gaussian form. This allows standard procedures for dealing with the Gaussian case to be re- used directly as part of the scheme. In contrast with other recently published work on the topic, we propose a novel hybrid rejection sampling method for simulating the scale parameters from their full conditional distributions, making use of asymptotic approximations for the tail of a positive stable distribution when rejection rates are too high. This hybrid approach potentially leads to improved performance compared with straightforward rejection sampling or Metropolis-Hastings (M-H) approaches. The methods can be applied to any model with symmetric stable terms, but we illustrate their application to linear models and present simulations for AR time series with stable innovations.



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