arXiv subjects

Lucas K. Wagner

Publications and source records attributed to Lucas K. Wagner.

At least 37 records · Page 2Linked to original sources

arXiv2020

Electric field effects on the band gap and edge states of monolayer 1T'-WTe2

Monolayer 1T'-WTe2 is a quantum spin Hall insulator with a gapped bulk and gapless helical edge states persisting to temperatures around 100 K. Recent studies have revealed a topological-to-trivial phase transition as well the emergence of an unconventional, potentially topological superconducting state upon tuning the carrier concentration with gating. However, despite extensive studies, the effects of gating on the band structure and the helical edge states have not yet been established. In this work we present a combined low-temperature STM and first principles study of back-gated monolayer 1T'-WTe2 films grown on graphene. Consistent with a quantum spin Hall system, the films show well-defined bulk gaps and clear edge states that span the gap. By directly measuring the density of states with STM spectroscopy, we show that the bulk band gap magnitude shows substantial changes with applied gate voltage, which is contrary to the naïve expectation that a gate would rigidly shift the bands relative to the Fermi level. To explain our data, we carry out density functional theory and model Hamiltonian calculations which show that a gate electric field causes doping and inversion symmetry breaking which polarizes and spin-splits the bulk bands. Interestingly, the calculated spin splitting from the effective Rashba-like spin-orbit coupling can be in the tens of meV for the electric fields in the experiment, which may be useful for spintronics applications. Our work reveals the strong effect of electric fields on the bulk band structure of monolayer 1T'-WTe2, which will play a critical role in our understanding of gate-induced phenomena in this system.

cond-mat.mes-hall↗

arXiv2020

Recent developments in the PySCF program package

PYSCF is a Python-based general-purpose electronic structure platform that both supports first-principles simulations of molecules and solids, as well as accelerates the development of new methodology and complex computational workflows. The present paper explains the design and philosophy behind PYSCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PYSCF as a development environment. We then summarize the capabilities of PYSCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PYSCF across the domains of quantum chemistry, materials science, machine learning and quantum information science.

physics.chem-ph↗

arXiv2020

Combining density functional theories to correctly describe the energy, lattice structure and electronic density of functional oxide perovskites

Functional oxide perovskites are the pillar of cutting-edge technological applications. Density functional theory (DFT) simulations are the theoretical methods of choice to understand and design perovskite materials. However, tests on the reliability of DFT to describe fundamental properties of oxide perovskites are scarce and mostly ill-defined due to a lack of rigorous theoretical benchmarks for solids. Here, we present a quantum Monte Carlo benchmark study of DFT on the archetypal perovskite BaTiO$_{3}$ (BTO). It shows that no DFT approximation can simultaneously reproduce the energy, structure, and electronic density of BTO. Traditional protocols to select DFT approximations are empirical and fail to detect this shortcoming. An approach combining two different non-empirical DFT schemes, "SCAN" and "HSE06", is able to holistically describe BTO with accuracy. Combined DFT approaches should thus be considered as a promising alternative to standard methods for simulating oxide perovskites.

cond-mat.mtrl-sci↗

arXiv2020

A comparison of computed and experimental neutron diffraction intensity at large momentum for MnO and NiO

Magnetic neutron scattering measures spin-spin correlations giving information about the long-range spin order as well as the shape of the spin density in magnetic materials. Similarly, detailed first principles calculations directly compute the spin density in materials. In this work, the authors carefully compare experimentally measured magnetic neutron intensities to three levels of theory: density functional theory in two approximations, and fixed-node diffusion Monte Carlo. While each theory performs similarly for the simple antiferromagnet MnO, there are significant differences between density functional theory and diffusion Monte Carlo in NiO. For both materials, fixed-node diffusion Monte Carlo shows the lowest RMS error with respect to experiment for the form factor and the intensity. Through connection of the intensities and form factors to the real-space spin densities, it is shown that diffusion Monte Carlo spin density becomes more diffuse by spreading spin away from the bond directions. This benchmark is of importance when considering the efficacy of an ab initio calculation in capturing both the long-range magnetic correlations and the microscopic spin details of magnetic systems.

cond-mat.mtrl-sci↗

arXiv2020

A light weight regularization for wave function parameter gradients in quantum Monte Carlo

The parameter derivative of the expectation value of the energy, $\partial E/\partial p$, is a key ingredient in variational quantum Monte Carlo (VMC) wave function optimization methods. In some cases, a naïve Monte Carlo estimate of this derivative suffers from an infinite variance which inhibits the efficiency of optimization methods that rely on a stable estimate of the derivative. In this work, we derive a simple regularization of the naïve estimator which is trivial to implement in existing VMC codes, has finite variance, and a negligible bias which can be extrapolated to zero bias with no extra cost. We use this estimator to construct an unbiased, finite variance estimation of $\partial E/\partial p$ for a multi-Slater-Jastrow trial wave function on the LiH molecule. This regularized estimator is a simple and efficient estimator of $\partial E/\partial p$ for VMC optimization techniques.

physics.comp-ph↗

arXiv2019

Direct comparison of many-body methods for realistic electronic Hamiltonians

A large collaboration carefully benchmarks 20 first principles many-body electronic structure methods on a test set of 7 transition metal atoms, and their ions and monoxides. Good agreement is attained between the 3 systematically converged methods, resulting in experiment-free reference values. These reference values are used to assess the accuracy of modern emerging and scalable approaches to the many-electron problem. The most accurate methods obtain energies indistinguishable from experimental results, with the agreement mainly limited by the experimental uncertainties. Comparison between methods enables a unique perspective on calculations of many-body systems of electrons.

cond-mat.mtrl-sci↗

arXiv2019

Many-Body Electric Multipole Operators in Extended Systems

The quantum mechanical position operators, and their products, are not well-defined in systems obeying periodic boundary conditions. Here we extend the work of Resta who developed a formalism to calculate the electronic polarization as an expectation value of a many-body operator, to include higher multipole moments, e.g., quadrupole and octupole. We define $n$-th order multipole operators whose expectation values can be used to calculate the $n$-th multipole moment when all of the lower moments are vanishing (modulo a quantum). We show that changes in our operators are tied to flows of $n-1$-st multipole currents, and encode the adiabatic evolution of the system in the presence of an $n-1$-st gradient of the electric field. Finally, we test our operators on a set of tightbinding models to show that they correctly determine the phase diagrams of topological quadrupole and octupole models, capture an adiabatic quadrupole pump, and distinguish a bulk quadrupole moment from other mechanisms that generate corner charges.

cond-mat.str-el↗

arXiv2018

Prediction for the singlet-triplet excitation energy for the spinel MgTi$_2$O$_4$ using first-principles diffusion Monte Carlo

The spinel, MgTi$_2$O$_4$, undergoes a transition into a dimerized state at low temperatures that is expected to be a spin singlet. However, no signature of a singlet-triplet transition has been discovered, in part due to the difficulty of predicting the energy of the transition from theory. We find that the dimers of MgTi$_2$O$_4$ can be described by a Heisenberg model with very small interactions between different dimers. Using high-accuracy first-principles quantum Monte Carlo combined with a novel model-fitting approach, we predict the singlet-triplet gap of these dimers to be 350(50) meV, a higher energy than previous experimental observations have considered. The prediction is published in advance of experimental confirmation.

cond-mat.str-el↗

arXiv2018

Effective spin-orbit models using correlated first-principles wave functions

Diffusion Monte Carlo is one of the most accurate scalable many-body methods for solid state systems. However, to date, spin-orbit interactions have not been incorporated into these calcualtions at a first-principles level; only having been applied to small systems. In this technique, we use explicitly correlated first-principles quantum Monte Carlo calculations to derive an effective spin-orbit model Hamiltonian. The simplified model Hamiltonian is then solved to obtain the energetics of the system. To demonstrate this method, benchmark studies are performed in main-group atoms and monolayer tungsten disulfide, where high accuracy is obtained.

cond-mat.mtrl-sci↗

arXiv2018

Non-orthogonal determinants in multi-Slater-Jastrow trial wave functions for fixed-node diffusion Monte Carlo

The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms benefits greatly from compact variational trial wave functions that accurately reproduce ground state properties of a system. We investigate the possibility of using multi-Slater-Jastrow trial wave functions with non-orthogonal determinants by optimizing identical single particle orbitals independently in separate determinants. As a test case, we compute variational and fixed-node diffusion Monte Carlo (FN-DMC) energies of a C$_2$ molecule. For a given multi-determinant expansion, we find that this non-orthogonal orbital optimization results in a consistent improvement in the variational energy and the FN-DMC energy on the order of a few tenths of an eV. Our calculations indicate that trial wave functions with non-orthogonal determinants can improve computed energies in a QMC calculation when compared to their orthogonal counterparts.

cond-mat.mtrl-sci↗

arXiv2018

Uncovering anisotropic magnetic phases via fast dimensionality analysis

A quantitative geometric predictor for the dimensionality of magnetic interactions is presented. This predictor is based on networks of superexchange interactions and can be quickly calculated for crystalline compounds of arbitrary chemistry, occupancy, or symmetry. The resulting data is useful for classifying structural families of magnetic compounds. Starting with 42,520 compounds, we have classified and quantified compounds with $3d$ transition metal cations. The predictor reveals trends in magnetic interactions that are often not apparent from the space group of the compounds, such as triclinic or monoclinic compounds that are strongly 2D. We present specific cases where the predictor identifies compounds that should exhibit competition between 1D and 2D interactions, and how the predictor can be used to identify sparsely-populated regions of chemical space with as-yet-unexplored topologies of specific $3d$ magnetic cations. The predictor can be accessed for the full list of compounds using a searchable web form, and further information on the connectivity, symmetry, and valence of cation-anion and cation-cation coordination can be freely exported.

cond-mat.mtrl-sci↗

arXiv2017

From real materials to model Hamiltonians with density matrix downfolding

Due to advances in computer hardware and new algorithms, it is now possible to perform highly accurate many-body simulations of realistic materials with all their intrinsic complications. The success of these simulations leaves us with a conundrum: how do we extract useful physical models and insight from these simulations? In this article, we present a formal theory of downfolding--extracting an effective Hamiltonian from first-principles calculations. The theory maps the downfolding problem into fitting information derived from wave functions sampled from a low-energy subspace of the full Hilbert space. Since this fitting process most commonly uses reduced density matrices, we term it density matrix downfolding (DMD).

cond-mat.str-el↗

arXiv2017

Quantum Monte Carlo study of the metal to insulator transition on a honeycomb lattice with 1/r interactions

Describing correlated electron systems near phase transitions has been a major challenge in computational condensed-matter physics. In this paper, we apply highly accurate fixed node quantum Monte Carlo techniques, which directly work with many body wave functions and simulate electron correlations, to investigate the metal to insulator transition of a correlated hydrogen lattice. By calculating spin and charge properties, and analyzing the low energy Hilbert space, we identify the transition point and identify order parameters that can be used to detect the transition. Our results provide a benchmark for density functional theories seeking to treat correlated electron systems.

cond-mat.str-el↗

arXiv2017

Computation of the unifying thread in high temperature superconductors from first principles quantum Monte Carlo

It has long been a challenge to describe the origin of unconventional superconductivity. The two known examples with high Tc, based on iron and copper, have very different electronic structures, while other materials with similar electronic structure may not show superconductivity at all. In this paper, the authors show that by using high accuracy diffusion Monte Carlo calculations, the unconventional superconductors of both high Tc types form a cluster at intermediate spin-charge coupling. The spin-charge coupling may serve as a normal state marker for unconventional superconductivity, and provides evidence that unconventional superconductivity is due to interaction of charge with local spins in materials.

cond-mat.supr-con↗

arXiv2017

The importance of sigma bonding electrons for the accurate description of electron correlation in graphene

Electron correlation in graphene is unique because of the interplay of the Dirac cone dispersion of $π$ electrons with long range Coulomb interaction. The random phase approximation predicts no metallic screening at long distance and low energy because of the zero density of states at Fermi level, so one might expect that graphene should be a poorly screened system. However, empirically graphene is a weakly interacting semimetal, which leads to the question of how electron correlations take place in graphene at different length scales. We address this question by computing the equal time and dynamic structure factor $S(\vec q)$ and $S(\vec q, ω)$ of freestanding graphene using {\it ab-initio} fixed-node diffusion Monte Carlo and the random phase approximation. We find that the $σ$ electrons contribute strongly to $S(\vec q,ω)$ for relevant experimental values of $ω$ even at distances up to around 80 Å. These findings illustrate how the emergent physics from underlying Coulomb interactions results in the observed weakly correlated semimetal.

cond-mat.mtrl-sci↗

arXiv2016

Accurate barrier heights using diffusion Monte Carlo

Fixed node diffusion Monte Carlo (DMC) has been performed on a test set of forward and reverse barrier heights for 19 non-hydrogen-transfer reactions, and the nodal error has been assessed. The DMC results are robust to changes in the nodal surface, as assessed by using different mean-field techniques to generate single determinant wave functions. Using these single determinant nodal surfaces, DMC results in errors of 1.5(5) kcal/mol on barrier heights. Using the large data set of DMC energies, we attempted to find good descriptors of the fixed node error. It does not correlate with a number of descriptors including change in density, but does correlate with the gap between the highest occupied and lowest unoccupied orbital energies in the mean-field calculation.

physics.chem-ph↗

arXiv2016

Computational and experimental investigation of unreported transition metal selenides and sulphides

Expanding the library of known inorganic materials with functional electronic or magnetic behavior is a longstanding goal in condensed matter physics and materials science. Recently, the transition metal chalchogenides including selenium and sulfur have been of interest because of their correlated-electron properties, as seen in the iron based superconductors and the transition metal dichalcogenides. However, the chalcogenide chemical space is less explored than that of oxides, and there is an open question of whether there may be new materials heretofore undiscovered. We perform a systematic combined theoretical and experimental search over ternary phase diagrams that are empty in the Inorganic Crystal Structure Database containing cations, transition metals, and one of selenium or sulfur. In these 27 ternary systems, we use a probabilistic model to reduce the likelihood of false negative predictions, which results in a list of 24 candidate materials. We then conduct a variety of synthesis experiments to check the candidate materials for stability. While the prediction method did obtain previously unknown compositions that are predicted stable within density functional theory, none of the candidate materials formed in our experiments. We come to the conclusion that these phase diagrams are "empty" in the case of bulk synthesis, but it remains a possibility that alternate synthesis routes may produce some of these phases.

cond-mat.mtrl-sci↗

arXiv2016

Competing collinear magnetic structures in superconducting FeSe by first principles quantum Monte Carlo calculations

Resolving the interplay between magnetic interactions and structural properties in strongly correlated materials through a quantitatively accurate approach has been a major challenge in condensed matter physics. Here we apply highly accurate first principles quantum Monte Carlo (QMC) techniques to obtain structural and magnetic properties of the iron selenide (FeSe) superconductor under pressure. Where comparable, the computed properties are very close to the experimental values. Of potential ordered magnetic configurations, collinear spin configurations are the most energetically favorable over the explored pressure range. They become nearly degenerate in energy with bicollinear spin orderings at around 7 GPa, when the experimental critical temperature $T_c$ is the highest. On the other hand, ferromagnetic, checkerboard, and staggered dimer configurations become relatively higher in energy as the pressure increases. The behavior under pressure is explained by an accurate analysis of the charge compressibility and the orbital occupation as described by the QMC many-body wave function, which reveals how spin, charge and orbital degrees of freedom are strongly coupled in this compound. This remarkable pressure evolution suggests that stripe-like magnetic fluctuations may be responsible for the enhanced $T_c$ in FeSe and that higher T$_c$ is associated with nearness to a crossover between collinear and bicollinear ordering.

cond-mat.supr-con↗