Table of contents

Barry M Klein¹, Warren E Pickett² and Richard T Scalettar²

Department of Physics, University of California, Davis CA 95616, USA

¹Conference Chair and Proceedings Co-Editor

²Conference Vice Chair and Proceedings Co-Editor

E-mail: bmklein@ucdavis.edu, wepickett.ucdavis.edu, rtscalettar@ucdavis.edu

Abstract. This paper represents a preface to the Proceedings of the XXX IUPAP Conference on Computational Physics held at the University of California, Davis, 29 July – 2 August 2018. Background information and the organizational structure of the meeting, and acknowledgements of the contributions of the many people who made the conference a success are presented.

List of Background, Acknowledgements, CCP2018 Organization, International Advisory Board and Program and Local Committee are available in this pdf.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

Fueled by advances in software, microelectronics, and large optics fabrication, a new type of sky survey will soon begin. In a relentless campaign of 15 second exposures with a 3 gigapixel camera, the Large Synoptic Survey Telescope will cover the sky deeply every week for ten years. LSST will chart billions of remote galaxies, providing multiple probes of the mysterious Dark Matter and Dark Energy. Multiple probes of the effects of dark energy over an unprecedented volume of the universe will allow us to measure how dark energy behaves over time to high precision. Hundreds of petabytes of high dimensional complex data will be mined and compared with Exascale simulations. After reviewing the LSST project, I will describe some of the computational challenges and opportunities.

The Fermi-Löwdin orbital (FLO) approach to the Perdew-Zunger self-interaction correction (PZ-SIC) to density functional theory (DFT) is described and an improved approach to the problem of optimizing the Fermi-orbitals in order to minimize the DFT-SIC total energy is introduced. To illustrate the use of the FLO-SIC method, results are given for several applications involving problems where self-interaction errors are pronounced.

There has been a good deal of work on algorithms to simulate quantum many-body systems with fault-tolerant quantum computers- those with full error correction. Fault-tolerant quantum computers of scale requisite to achieve computational advantage for these problems are likely over a decade away. Moreover, devices that we can build in the near term, called Noisy Intermediate Scale Quantum computers (NISQ), have too much noise to implement the long circuits required by these algorithms. We review heuristic, short-depth quantum algorithms more suited to NISQ computers; specifically, their scaling properties when applied to electronic and nuclear structure calculations, including Hamiltonian complexity with particle number, ansatz state preparation, convergence, and noise. We will present examples of actual quantum structure calculations with NISQ computers, as well as a newly-developed error mitigation technique that significantly improves accuracy. We end with an outlook for "advantage" – when NISQ systems might excel conventional HPC approaches for comparable problems.

We describe the algorithmic details and a performance evaluation of a Langevin approach to a strongly interacting electron-phonon system, and show it has a near linear scaling with lattice size N_s. Many of the limitations of previous attempts to employ such methods to condensed matter lattice Hamiltonians are absent. In particular, the iterative linear algebra solution remains well behaved at strong coupling and low temperatures. The use of Fourier Acceleration is crucial for efficiency, and its use makes the method competitive with the widely-used local update methods, which scale as ${N}_{s}^{3}$ for on-site interactions and ${N}_{s}^{4}$ for long range electron-phonon coupling, even on rather small lattice sizes.

Motivated by recent advances in the representation of ground state wavefunctions of quantum many-body systems using restricted Boltzmann machines as variational ansatz, we utilize an open-source platform for constructing such ansatz called NetKet to explore the extent of applicability of restricted Boltzmann machines to bosonic lattice models. Within NetKet, we design and train these machines for the one-dimensional Bose-Hubbard model through a Monte Carlo sampling of the Fock space. We vary parameters such as the strength of the onsite repulsion, the chemical potential, the system size and the maximum site occupancy and use converged equations of state to identify phase boundaries between the Mott insulating and superfluid phases. We compare the average density and the energy to results from exact diagonalization and map out the ground state phase diagram, which agrees qualitatively with previous finding obtained through conventional means.

Machine learning techniques have been widely used in the study of strongly correlated systems in recent years. Here, we review some applications to classical and quantum many-body systems and present results from an unsupervised machine learning technique, the principal component analysis, employed to identify the finite-temperature phase transition of the three-dimensional Fermi-Hubbard model to the antiferromagnetically ordered state. We find that this linear method can capture the phase transition as well as other more complicated and nonlinear counterparts.

The study of large scale structure (LSS) of the Universe has entered a precision era due to all-sky surveys and numerical simulations. The new data has provided a way to bring new methods to bear to analyze the cosmology as probed by large scale structure. We use wavelet packets to investigate fractal point-processes on galactic scales. In particular, we develop a method to calculate the angular fractal dimension of galaxy distributions as a function of cosmological comoving distance. Taking advantage of the self-similarity and localization properties of discrete wavelets, we compute the angular fractal dimension of galaxies in narrow redshift bins. The narrow bins assure that dynamical evolution in the range being studied has not occurred to a significant extent. We use both real and simulated data from the Baryon Oscillation Spectroscopic Survey (BOSS) and the Mock Galaxy Catalogs produced by the Sloan Digital Sky Survey (SDSS). Using the wavelet packet power spectrum, we find areas in the galaxy distribution which have power law like behavior indicating fractal processes are present. The exponent of the power law is the Hurst exponent H, which is directly related to the fractal dimension of spatial point processes. We find the fractal dimension ranges from D = 1.1 to D = 1.4 for BOSS Galaxies while it ranges from D = 1.4 to D = 1.8 for Mock Galaxy Catalogs. The results are mildly dependent on the number of galaxies present in each redshift bin and less so on the resolution at which the data is binned. We conclude that this method can be used to characterize large scale structure and its evolution as a function of redshift. There are hints that the galaxy distribution may be fractal at higher redshifts than previously reported, however more data is necessary before a firmer conclusion is reached.

This paper concerns the use of compression methods applied to large scientific data. Specifically the paper addresses the effect of lossy compression on approximation error. Computer simulations, experiments and imaging technologies generate terabyte-scale datasets making necessary new approaches for compression coupled with data analysis. Lossless compression techniques compress data with no loss of information, but they generally do not produce a large-enough reduction when compared to lossy compression methods. Lossy multi-resolution compression techniques make it possible to compress large datasets significantly with small numerical error, preserving coherent features and statistical properties needed for analysis. Lossy data compression reduces I/O data transfer cost and makes it possible to store more data at higher temporal resolution. We present results obtained with lossy multi-resolution compression, with a focus on astrophysics datasets. Our results confirm that lossy data compression is capable of preserving data characteristics very well, even at extremely high degrees of compression.

The Curie temperature (T_C) of RT binary compounds consisting of 3d transition-metal (T ) and 4f rare-earth elements (R) is analyzed systematically by a developed machine learning technique called kernel regression-based model evaluation. Twenty-one descriptive variables were designed assuming completely obtained information of the T_C. Multiple kernel regression analyses with different kernel types: cosine, linear, Gaussian, polynomial, and Laplacian kernels were implemented and examined. All possible descriptive variable combinations were generated to construct the corresponding prediction models. As a result, by appropriate combinations between descriptive variable sets and kernel formulations, we demonstrate that a number of kernel regression models can accurately reproduce the T_C of the RT compounds. The relevance of descriptive variables for predicting T_C are systematically investigated. The results indicate that the rare-earth concentration is the most relevant variable in the T_C phenomenon. We demonstrate that the regression-based model selection technique can be applied to learn the relationship between the descriptive variables and the actuation mechanism of the corresponding physical phenomenon, i.e., T_C in the present case.

We present here the first principle calculations of the electrical properties of in-plate heterojunctions of armchair graphene nanoribbon/h-BN(AGNR/h-BN)s. The calculations are carried out using SIESTA package, which is comprised of numerical codes of the density functional theory(DFT) and the non-equilibrium Green's function(NEGF). Especially, adopting the conductive (3n-1)-family of AGNR((3n-1)-AGNR) makes the lead parts on both side of the model metallic. Two transverse arrays of h-BN, which is a wide-gap semiconductor, are embedded in the middle of (3n-1)-AGNR and act as a double barrier system.

The quantum double barrier tunneling is found in the transmission functions(TF) and I-V characteristics of 8, 11, 14-AGNR/h-BN. The TF shows significantly spiky peaks in the neighborhood of the Fermi energy, and consequently, it results in step-sise I-V characteristics. Simple one-dimensional Dirac equation model for the double barrier system is also proposed to analyze numerical results. Our model reproduces most of the peaks of the transmission functions nearby the Fermi energy, as a result of quantum tunneling.

We present example applications of an approach to high-throughput first-principles calculations of the electronic properties of materials implemented within the Exabyte.io platform[1, 2]. We deploy computational techniques based on the Density Functional Theory with both Generalized Gradient Approximation (GGA) and Hybrid Screened Exchange (HSE) in order to extract the electronic band gaps and band structures for a set of 775 binary compounds. We find that for HSE, the average relative error fits within 22%, whereas for GGA it is 49%. We find the average calculation time on an up-to-date server centrally available from a public cloud provider to fit within 1.2 and 36 hours for GGA and HSE, respectively. The results and the associated data, including the materials and simulation workflows, are standardized and made available online in an accessible, repeatable and extensible setting.

Orbital field matrix (OFM) descriptors were developed with an emphasis on atomic orbitals for representing material structures in datasets of multi-element compounds. The descriptors were based on atomic valence shell electrons and their coordination. In addition to original OFM and OFM1 which is OFM with a column representing information on the center atom, in this work, we present another version, named OFM0, which is OFM1 without information on atomic distances, for predicting the properties of unoptimized structures. We focus on formation energy and phase stability of crystalline systems, while the atomization energy is examined for molecules. With the emphasis on the ability to identify materials with similar properties, here, the applicabilities of OFM, OFM1, and OFM0 are systematically examined with decision tree (DT) regression, random forest (RF) regression, and kernel ridge regression (KRR). We show that the family of OFM descriptors are highly capable to build predictive models for the properties of solids and molecules. The accuracy of a DT and a forest of trees (RF) is comparable to that of the KRR models. The KRR with a Laplacian kernel estimated by OFM1 yields the most accurate predictions, with the formation energy, phase stability, and atomization energy having mean absolute errors (MAEs) of 0.072 eV/atom, 0.059 eV/atom, and 6.74 kcal/mol, respectively. The OFM0 without atomic distances also yields acceptable predictions with respective MAEs of 0.090 eV/atom, 0.069 eV/atom, and 7.77 kcal/mol. The results imply that our descriptors are highly useful to find similar materials.

Optimized geometries, vibrational frequencies, as well as infrared intensities and Raman activities were calculated for water (H₂O) utilizing popular quantum mechanical approaches. Here, density functional theory (DFT) calculations were performed using the B3LYP (Becke, three-parameter, Lee-Yang-Parr) functional, as well as ab initio calculations using second-order Møller-Plesset (MP2) perturbation theory and coupled-cluster with single, double and perturbative triple excitations [CCSD(T)] levels of theory were used. We assess and benchmark the performance of 69 different atomic orbital basis sets including various popular families of medium-sized basis sets typically of two to four zeta quality and differing levels of augmentation by polar and diffuse functions. The basis sets range from the commonly adopted Pople-style (6-31G & 6-311G), Dunning's correlation consistent (cc-pV(n+d)Z & aug-cc-pV(n+d)Z, as well as Truhlar's calendar variations, Jensen's polarization consistent (pc-n & aug-pc-n), Ahlrichs (def2-...), Sapporo's and Karlsruches as well as atomic natural orbitals (ANOs) such as NASA Ames (ANOn), Neese-style, and Roos-style. We also compare several basis sets specifically designed to calculate vibrational and electronic properties, including the Sadlej-pVTZ (and LPol-X families), as well as SNS families of Barone. The results are compared to experimental values where available, or calculations performed with 5 or 6 zeta-level (e.g., cc-pV6Z). The performance of each family of basis sets is discussed in terms of their accuracy (and pitfalls), as well as computational resource scaling and efficiency. The Def2 basis family performs very well overall, yielding more accurate results with lower runtimes than traditional basis sets. 'May' basis sets also provide accurate predictions of vibrational frequencies at significantly lower costs. Raman activities can be accurately calculated using MP2 under harmonic approximation with several 'spectroscopic' families performing well.

We report an algorithm for simulating oxygen K-edge RIXS for weakly correlated systems, using maximally localized Wannier functions as the basis set. The N-electron wavefunctions are formulated using single Slater determinants, and many-body effects are treated explicitly at the dipole matrix element level. The simulated results for oxygen K-edge RIXS from solid state Li₂CO₃ matches well with the experimental data. Aside from being efficient and reasonably accurate, this algorithm also shows potential to extend to more complex RIXS problems.

In order to understand the dynamics of the self-organized macrosteps, the vicinal surface with faceted macrosteps is studied by the Monte Carlo method based on a microscopic lattice model, the restricted solid-on-solid model with point-contact-type step-step attraction (p-RSOS model). We focus on the dynamical effects caused by the change of the surface roughness or the change of the kink density which are masked by the effect of the surface and volume diffusion of the crystal atoms in the ambient phase. Contrast to the step-bunching in the diffusion-limited cases, the height of the faceted macrostep decreases as the driving force for the crystal growth increases.

In 1913, x-ray crystallography was first used to determine the crystal structure of diamond. Since that time hundreds of thousands, if not millions, of crystal structures have been determined. Published structures require critical review and indexing to make them easily available to other researchers. One of the first systems for doing this was Strukturbericht (Structure Reports), published in Germany from 1931-1943 and covering research from 1913-1939, and now best known for the Strukturbericht symbols which label common crystal structures. A comprehensive history of Strukturbericht has not been written. This brief report sketches the early history of Strukturbericht, as well as its post-World War II successor publications, handbooks, and online resources.

Scientific discoveries across all fields, from physics to biology, are increasingly driven by computer simulations. At the same time, the computational demand of many problems necessitates large-scale calculations on high-performance supercomputers. Developing and maintaining the underlying codes, however, has become a challenging task due to a combination of factors. Leadership computer systems require massive parallelism, while their architectures are diversifying. New sophisticated algorithms are continuously developed and have to be implemented efficiently for such complex systems. Finally, the multidisciplinary nature of modern science involves large, changing teams to work on a given codebase. Using the example of the DCA++ project, a highly scalable and efficient research code to solve quantum many-body problems, we explore how computational science can overcome these challenges by adopting modern software engineering approaches. We present our principles for scientific software development and describe concrete practices to meet them, adapted from agile software development frameworks.

To compare folding behavior among lattice proteins which have similar corresponding structures in nature, Crambin homologues are tested in the semi-flexible H0P lattice model using replica-exchange Wang-Landau sampling. Our simulation shows that, at low temperature, these lattice homologues have two common signals in their specific heat curves, implying similarity in the thermodynamic behaviors; while the structural behaviors are more diverse, showing the different stability of their ground state structures at very low temperature. The ground state structures of different homologues can also vary dramatically.

In order to study the effects of lattice constraints on coarse-grained protein models, we apply Wang-Landau sampling to the continuum analogue of the hydrophobic-polar (HP) lattice protein model. The continuum version is inspired by the AB polymer model but incorporates potentials chosen specifically to mimic those of the lattice case. Because of their relative simplicity, both the lattice and continuum models offer significant computational advantage over all-atom simulations, but the impact of the additional lattice constraint on generic folding behavior is unknown. In this preliminary study, we compare and contrast thermodynamics during the folding process of the continuum model to the original HP lattice protein model for sequences mapped from Crambin, a 46 amino acid plant protein. We find that the folding process for both of these coarse-grained models is quite similar, with major structural transitions occurring at almost exactly the same temperatures.

All-atom molecular dynamics (MD) simulations of pure 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer and POPC bilayer containing cholesterol (POPC/CHOL) with CHARMM36 force field were carried out to investigate the effects of CHOL on structure and lipid translocation across the membranes. We calculated the potential mean force (PMF) profiles for translocation of POPC and CHOL along the pure POPC and the POPC/CHOL bilayer normal by umbrella sampling method. The obtained PMF profile of the POPC translocation was in good agreement with that of the previous MD study, showing that the estimated PMF profiles with the CHARMM36 force field should be reasonable. We found that the PMF peak appears slightly beyond the bilayer center. The CHOL effects on the PMF profile of POPC translocation were clearly observed; the free energy barrier for the flip-flop of lipid increased and, the energy for the desorption of lipid decreased. These changes in the PMF profile should be responsible for the tight packing of the POPC/CHOL bilayer. The PMF profiles for the CHOL translocation showed that the free energy barriers at the bilayer center were sufficiently smaller than those of POPC translocation, indicating that the CHOL can easily flip over compared to the POPC in the membrane. In the case of PMF of CHOL translocation in the POPC/CHOL system, while the PMF energy in the hydrophobic core region was higher than that of the pure POPC bilayer, the free energy difference at bilayer center was small.

We performed a quantum chemical study on evaluating chemical reactivity for drug molecules in Cytochrome P450 (CYP) metabolic reaction. In this study, we focused on two insights for analysing the chemical reactivity: one is the Fukui reaction indices for a molecule, and the other is the minimum energy paths of hydrogen transition reaction between drug molecule and FeO-Porphyrin ring part on the CYP metabolic reaction. The Fukui indices are obtained numerically by using the familiar population analysis method in quantum chemical calculations. We performed the assessments of some population analyses to clarify the numerical behaviour clearly and then evaluated the potential of the reactivity of drug molecule. On the other hand, in the analysis of the minimum energy path for the CYP metabolic reaction, we performed the nudged elastic band (NEB) calculations for the hydrogen transition reaction in the first step of the CYP metabolic reaction. We report the findings for the reactivity from the Fukui indices method and also show the NEB results for the reaction paths.

Thermal ratchets achieve net particle transport through recti cation of thermal uctuations, which arise from one or more heat baths in the system. We propose a new formulation of heat dissipation from the ratchet to the thermal baths, using a rocking Büttiker-Landauer ratchet model. We found that heat transport between the ratchet and the heat baths is related to the effective temperature through the generalization of the uctuation-dissipation theorem for systems far from equilibrium. We showed that the net heat transport between the ratchet and the heat baths is different from Fourier's law and is the sum of two terms which are proportional to the nth power of the difference between the effective temperature of ratchet and the temperature of the baths. The power n depends only on the temperature of the bath, while the thermal conductivity also depends on the ratchet potential. These ndings suggest that anomalous heat dissipation can be a non-equilibrium measure for systems far from equilibrium.

The Madelung fluid transformation is applied to find the link between the modified Korteweg-de Vries and the quadratic-cubic nonlinear Schrödinger equation. The two-dimensional solitary wave solution of the quadratic-cubic nonlinear Schrödinger equation will be determined by the Petviashvili method. This solution will be used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.

The Adomian decomposition method (ADM), is the one of the semi-analytical method, will be applied to study the time evolution of the soliton solution to the modified Korteweg-de Vries equation. We also provide the conservation laws to verify the dark solution obtained from this method. The ADM gives a good result for the approximation solution of the weakly nonlinear wave equation.

In this multispecies plasma model, consisting of negative mobile dusts, non-thermal ions and Boltzmann electrons, dust-ion acoustic solitary waves are studied through reductive perturbative technique by deriving corresponding Korteweg-de Vries (KdV) equation. The number of dust charge contained in a dust particle (Z_d) and the streaming speeds of mobile dusts (u_d0) and ions (u_i0) are observed to play very important role to form dust-ion acoustic compressive and rarefactive KdV solitons. Remarkably, some initial streaming of dust (u_d0) are found to be instrumental for both compressive and rarefactive KdV solitons in a short range of Z_d separating both kinds by some asymptotic lines. Also, the presence of low dust charges and lower ion streaming, compressive and rarefactive KdV solitons of either concave or convex characters are shown to reflect. For the higher streaming of mobile dusts, the amplitudes of the rarefactive KdV solitons characteristically changes from higher to lower showing convex character for this plasma model. A rigorous theoretical investigation has been made to show how the number of dust charge contained in a dust particle (Z_d) drastically change the amplitudes of the compressive and rarefactive KdV solitons.

The carbuncle phenomenon is a numerical instability that affects the numerical capturing of shock waves when low-dissipative upwind scheme is used. This paper investigates shock instabilities of the HLLE-type methods for the Euler equations under the strong shock interaction, where the HLLE-type methods include the HLLE, HLLC, HLLEM, HLLCM and HLLEC Riemann solvers with specific wavespeed estimates. Based on a matrix stability analysis for two dimensional steady shocks, a new factor to influence carbuncle phenomenon is pointed out and the choice of the signal velocity plays an important role. A numerical flux function with wave velocity estimates which can crisply resolve shocks seems to be vulnerable to the shock anomalies even if the numerical fluxes to be regarded to be free from the carbuncle phenomenon. A suggestion to the choice of the wave speed is proposed when calculating strong shock wave problems.

We study a model of a spatial evolutionary game, based on the Prisoner's dilemma for two regular arrangements of players, on a square lattice and on a triangular lattice. We analyze steady state distributions of players which evolve from irregular, random initial configurations. We find significant differences between the square and triangular lattice, and we characterize the geometric structures which emerge on the triangular lattice.

The six-state clock model (SSCM) on rewired square lattice is studied using Monte Carlo simulation with Wang-Landau algorithm. This is a discrete counterpart of the well-known XY model, the native host of a unique topological phase transition called Kosterlitz-Tholess (KT) transition. The model has two KT transitions, i.e., at temperature T₁ and T₂, where T₁ < T₂. The first transition separates the lower temperature magnetic order and the quasi-long range order (QLRO) also known as KT phase; while the second transition separates the QLRO and the higher temperature paramagnetic phase. It has been established that the presence of KT phase is affected by the presence of randomness in the form of site and bond dilution. This intermediate phase is totally ruled out if bonds or sites of the lattice are no longer percolated. Here different type of randomness is probed, namely the rewired lattices, obtained by randomly adding one extra bond to each lattice site, and connect the site to one of its next-nearest neighbors. As a results, the average number of neighbors C increases. The increase of C affects the existence of KT phase. For each value of C, the KT temperatures, T₁ and T₂, were estimated from the plot of specific heats. Variation of KT temperatures for different values of C is observed, which is plotted with respect to each corresponding C to obtain the system phase diagram.

We study the distribution of the area and perimeter of the convex hull of the "true" self-avoiding random walk in a plane. Using a Markov chain Monte Carlo sampling method, we obtain the distributions also in their far tails, down to probabilities like 10⁻⁸⁰⁰. This enables us to test previous conjectures regarding the scaling of the distribution and the large-deviation rate function Φ. In previous studies, e.g., for standard random walks, the whole distribution was governed by the Flory exponent ν. We confirm this in the present study by considering expected logarithmic corrections. On the other hand, the behavior of the rate function deviates from the expected form. For this exception we give a qualitative reasoning.

We study the tunneling dynamics of N = 10 one-dimensional interacting bosons confined in a temporally driven double well potential that imitates a quantum seesaw and how we can manipulate these dynamics by changing the drive of the seesaw potential. We emulate the seesaw with a driven double well potential and consider two driving protocols: an harmonic constant-frequency drive and a chirped drive with linearly increasing frequency. We consider the time-dependent many-body Schrödinger equation of a repulsively interacting quasi-one-dimensional few-boson system. We solve it by using the multiconfigurational time-dependent Hartree method for bosons (MCTDHB) as implemented in the MCTDH-X software. For an harmonic drive and at small values of the driving amplitude, the dynamics of the particles become very slow rendering a stationary-like state. In a phase-space picture the population imbalance between the wells follows a trajectory which is restricted to a comparatively small region of space. For an harmonic drive at intermediate amplitudes, the dynamics become periodic in nature, implying that the bosons populate each of wells periodically. At comparatively large amplitudes of the harmonic drive, the dynamics show features of chaos in phase-space representation. For the chirped drive with a driving frequency increasing linearly in time, the imbalance of the atoms in the seesaw, however, has a temporal evolution that is faster for certain frequency ranges. The tunneling dynamics in such cases, for small amplitudes, show the appearance of quasi-periodicity with simultaneously present slow and fast oscillations. Increasing the amplitude of the chirped drive, we observe that the dynamics, although being periodic, become severely damped in their amplitude. Our study establishes that by tuning the temporal evolution of the quantum seesaw, a precise control of tunneling dynamics of the correlated bosons can be achieved. Since harmonic driving and chirp frequency modulation of the seesaw are experimentally achievable, our simulations can be experimentally realized in laboratories dealing with cold atomic gases.