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Haobin Wang

Bio: Haobin Wang is an academic researcher from University of Colorado Denver. The author has contributed to research in topics: Hartree & Quantum dynamics. The author has an hindex of 53, co-authored 137 publications receiving 8263 citations. Previous affiliations of Haobin Wang include Lawrence Berkeley National Laboratory & University of California, Santa Cruz.


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TL;DR: In this paper, a multilayer formulation of the multiconfiguration time-dependent Hartree (MCTDH) theory is presented, where the single-particle (SP) functions in the original MCTDH method are further expressed employing a timedependent multi-figurational expansion, and the Dirac-Frenkel variational principle is applied to optimally determine the equations of motion.
Abstract: A multilayer (ML) formulation of the multiconfiguration time-dependent Hartree (MCTDH) theory is presented. In this new approach, the single-particle (SP) functions in the original MCTDH method are further expressed employing a time-dependent multiconfigurational expansion. The Dirac–Frenkel variational principle is then applied to optimally determine the equations of motion. Following this strategy, the SP groups are built in several layers, where each top layer SP can contain many more Cartesian degrees of freedom than in the previous formulation of the MCTDH method. As a result, the ML-MCTDH method has the capability of treating substantially more physical degrees of freedom than the original MCTDH method, and thus significantly enhances the ability of carrying out quantum dynamical simulations for complex molecular systems. The efficiency of the new formulation is demonstrated by converged quantum dynamical simulations for systems with a few hundred to a thousand degrees of freedom.

768 citations

Journal ArticleDOI
TL;DR: In this paper, two different semiclassical approaches are presented for extending flux correlation function methodology for computing thermal reaction rate constants, which has been extremely successful for the direct calculation of small molecule (∼3-4) reactions, to complex molecular systems, i.e., those with many degrees of freedom.
Abstract: Two different semiclassical approaches are presented for extending flux correlation function methodology for computing thermal reaction rate constants, which has been extremely successful for the “direct” calculation of rate constants in small molecule (∼3–4 atoms) reactions, to complex molecular systems, i.e., those with many degrees of freedom. First is the popular mixed quantum-classical approach that has been widely used by many persons, and second is an approximate version of the semiclassical initial value representation that has recently undergone a rebirth of interest as a way for including quantum effects in molecular dynamics simulations. Both of these are applied to the widely studied system-bath model, a one-dimensional double well potential linearly coupled to an infinite bath of harmonic oscillators. The former approximation is found to be rather poor while the latter is quite good.

397 citations

Journal ArticleDOI
TL;DR: In this paper, a linearized approximation to the semiclassical initial value representation (SC-IVR) was used to calculate reactive flux correlation functions for a model of a chemical reaction on a single potential energy surface.
Abstract: A linearized approximation to the semiclassical initial value representation (SC-IVR), referred to herein as the LSC-IVR, was used by us in a recent paper [J. Chem. Phys. 108, 9726 (1998)] to calculate reactive flux correlation functions for a model of a chemical reaction on a single potential energy surface. This paper shows how the LSC-IVR—which is much easier to apply than the full SC-IVR because it linearizes the phase difference between interfering classical trajectories—can be applied to electronically nonadiabatic processes, i.e., those involving transitions between different potential-energy surfaces. Applications to several model problems are presented to show its usefulness: These are the nonadiabatic scattering problems used by Tully to test surface-hopping models, and also the spin–boson model of coupled electronic states in a condensed phase environment. Though not as accurate as the full SC-IVR, the LSC-IVR does a reasonably good job for all these applications, even describing correctly Stuc...

364 citations

Journal ArticleDOI
TL;DR: In this paper, Wang et al. applied the self-consistent hybrid approach to the spin-boson problem with Debye spectral density as a model for electron-transfer reactions in a solvent exhibiting Debye dielectric relaxation.
Abstract: The self-consistent hybrid approach [H. Wang, M. Thoss, and W. H. Miller, J. Chem. Phys. 115, 2979 (2001), preceding paper] is applied to the spin-boson problem with Debye spectral density as a model for electron-transfer reactions in a solvent exhibiting Debye dielectric relaxation. The population dynamics of the donor and acceptor states in this system is studied for a broad range of parameters, including the adiabatic (slow bath), nonadiabatic (fast bath), as well as the intermediate regime. Based on illustrative examples we discuss the transition from damped coherent dynamics to purely incoherent decay. Using the numerically exact results of the self-consistent hybrid approach as a benchmark, several approximate theories that have been widely used to describe the dynamics in the spin-boson model are tested: the noninteracting blip approximation, the Bloch–Redfield theory, the Smoluchowski-equation treatment of the reaction coordinate (Zusman equations), and the classical path approach (Ehrenfest model). The parameter range where the different methods are applicable are discussed in some detail.

260 citations


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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: This chapter discusses the development of DFT as a tool for Calculating Atomic andMolecular Properties and its applications, as well as some of the fundamental and Computational aspects.
Abstract: I. Introduction: Conceptual vs Fundamental andComputational Aspects of DFT1793II. Fundamental and Computational Aspects of DFT 1795A. The Basics of DFT: The Hohenberg−KohnTheorems1795B. DFT as a Tool for Calculating Atomic andMolecular Properties: The Kohn−ShamEquations1796C. Electronic Chemical Potential andElectronegativity: Bridging Computational andConceptual DFT1797III. DFT-Based Concepts and Principles 1798A. General Scheme: Nalewajski’s ChargeSensitivity Analysis1798B. Concepts and Their Calculation 18001. Electronegativity and the ElectronicChemical Potential18002. Global Hardness and Softness 18023. The Electronic Fukui Function, LocalSoftness, and Softness Kernel18074. Local Hardness and Hardness Kernel 18135. The Molecular Shape FunctionsSimilarity 18146. The Nuclear Fukui Function and ItsDerivatives18167. Spin-Polarized Generalizations 18198. Solvent Effects 18209. Time Evolution of Reactivity Indices 1821C. Principles 18221. Sanderson’s Electronegativity EqualizationPrinciple18222. Pearson’s Hard and Soft Acids andBases Principle18253. The Maximum Hardness Principle 1829IV. Applications 1833A. Atoms and Functional Groups 1833B. Molecular Properties 18381. Dipole Moment, Hardness, Softness, andRelated Properties18382. Conformation 18403. Aromaticity 1840C. Reactivity 18421. Introduction 18422. Comparison of Intramolecular ReactivitySequences18443. Comparison of Intermolecular ReactivitySequences18494. Excited States 1857D. Clusters and Catalysis 1858V. Conclusions 1860VI. Glossary of Most Important Symbols andAcronyms1860VII. Acknowledgments 1861VIII. Note Added in Proof 1862IX. References 1865

3,890 citations

Journal ArticleDOI
TL;DR: The main theoretical and experimental aspects of quantum simulation have been discussed in this article, and some of the challenges and promises of this fast-growing field have also been highlighted in this review.
Abstract: Simulating quantum mechanics is known to be a difficult computational problem, especially when dealing with large systems However, this difficulty may be overcome by using some controllable quantum system to study another less controllable or accessible quantum system, ie, quantum simulation Quantum simulation promises to have applications in the study of many problems in, eg, condensed-matter physics, high-energy physics, atomic physics, quantum chemistry and cosmology Quantum simulation could be implemented using quantum computers, but also with simpler, analog devices that would require less control, and therefore, would be easier to construct A number of quantum systems such as neutral atoms, ions, polar molecules, electrons in semiconductors, superconducting circuits, nuclear spins and photons have been proposed as quantum simulators This review outlines the main theoretical and experimental aspects of quantum simulation and emphasizes some of the challenges and promises of this fast-growing field

1,941 citations

Journal ArticleDOI
TL;DR: The most recent developments, since version 9 was released in April 2006, of the Amber and AmberTools MD software packages are outlined, referred to here as simply the Amber package.
Abstract: Molecular dynamics (MD) allows the study of biological and chemical systems at the atomistic level on timescales from femtoseconds to milliseconds. It complements experiment while also offering a way to follow processes difficult to discern with experimental techniques. Numerous software packages exist for conducting MD simulations of which one of the widest used is termed Amber. Here, we outline the most recent developments, since version 9 was released in April 2006, of the Amber and AmberTools MD software packages, referred to here as simply the Amber package. The latest release represents six years of continued development, since version 9, by multiple research groups and the culmination of over 33 years of work beginning with the first version in 1979. The latest release of the Amber package, version 12 released in April 2012, includes a substantial number of important developments in both the scientific and computer science arenas. We present here a condensed vision of what Amber currently supports and where things are likely to head over the coming years. Figure 1 shows the performance in ns/day of the Amber package version 12 on a single-core AMD FX-8120 8-Core 3.6GHz CPU, the Cray XT5 system, and a single GPU GTX680. © 2012 John Wiley & Sons, Ltd.

1,734 citations