Publications
99 results found
Lou WT, Sutterud H, Cassella G, et al., 2024, Neural Wave Functions for Superfluids, Physical Review X, ISSN: 2160-3308
Wells T, Foulkes W, Dudarev S, et al., 2023, The Einstein-de Haas effect in an Fe₁₅ cluster, Journal of Physics: Condensed Matter, Vol: 35, Pages: 1-16, ISSN: 0953-8984
Classical models of spin-lattice coupling are at present unable to accurately reproduce results for numerous properties of ferromagnetic materials, such as heat transport coefficients or the sudden collapse of the magnetic moment in hcp-Fe under pressure. This failure has been attributed to the absence of a proper treatment of effects that are inherently quantum mechanical in nature, notably spin-orbit coupling. This paper introduces a time-dependent, non-collinear tight binding model, complete with spin-orbit coupling and vector Stoner exchange terms, that is capable of simulating the Einstein-de Haas effect in a ferromagnetic Fe15 cluster. The tight binding model is used to investigate the adiabaticity timescales that determine the response of the orbital and spin angular momenta to a rotating, externally applied Β field, and we show that the qualitative behaviours of our simulations can be extrapolated to realistic timescales by use of the adiabatic theorem. 
An analysis of the trends in the torque contributions with respect to the field strength demonstrates that SOC is necessary to observe a transfer of angular momentum from the electrons to the nuclei at experimentally realistic Β fields.
The simulations presented in this paper demonstrate the Einstein-de Haas effect from first principles using a Fe cluster.
Hermann J, Spencer J, Choo K, et al., 2023, Ab-initio quantum chemistry with neural-network wavefunctions, Nature Reviews Chemistry, Vol: 7, Pages: 692-709, ISSN: 2397-3358
Deep learning methods outperform human capabilities in pattern recognition and data processing problems and now have an increasingly important role in scientific discovery. A key application of machine learning in molecular science is to learn potential energy surfaces or force fields from ab initio solutions of the electronic Schrödinger equation using data sets obtained with density functional theory, coupled cluster or other quantum chemistry (QC) methods. In this Review, we discuss a complementary approach using machine learning to aid the direct solution of QC problems from first principles. Specifically, we focus on quantum Monte Carlo methods that use neural-network ansatzes to solve the electronic Schrödinger equation, in first and second quantization, computing ground and excited states and generalizing over multiple nuclear configurations. Although still at their infancy, these methods can already generate virtually exact solutions of the electronic Schrödinger equation for small systems and rival advanced conventional QC methods for systems with up to a few dozen electrons.
Cassella G, Sutterud H, Azadi S, et al., 2023, Discovering quantum phase transitions with fermionic neural networks, Physical Review Letters, Vol: 130, Pages: 036401-1-036401-6, ISSN: 0031-9007
Deep neural networks have been extremely successful as highly accurate wavefunction ans\"atze for variational Monte Carlo calculations of molecular groundstates. We present an extension of one such ansatz, FermiNet, to calculationsof the ground states of periodic Hamiltonians, and study the homogeneouselectron gas. FermiNet calculations of the ground-state energies of smallelectron gas systems are in excellent agreement with previous initiator fullconfiguration interaction quantum Monte Carlo and diffusion Monte Carlocalculations. We investigate the spin-polarized homogeneous electron gas anddemonstrate that the same neural network architecture is capable of accuratelyrepresenting both the delocalized Fermi liquid state and the localized Wignercrystal state. The network is given no \emph{a priori} knowledge that a phasetransition exists, but converges on the translationally invariant ground stateat high density and spontaneously breaks the symmetry to produce thecrystalline ground state at low density.
Chen AP, Heuer A, Finnis M, et al., 2022, The electronic structure of α-Al2O2 grain boundaries containing reactive element segregants, Physical Review Materials, Vol: 6, Pages: 1-9, ISSN: 2475-9953
It has long been known that the addition of small quantities (“doping”) of so-called reactive elements (RE) such as Y, Zr, and Hf to high-temperature Al2O3 scale-forming alloys improves oxidation resistance. The presence of reactive elements at grain boundaries lowers the growth rate of the α-Al2O3 scales, but the cause of the reduced scale growth kinetics is not fully understood. Explanations based on steric effects and explanations based on reducing the grain boundary electronic conductivity have been proposed. We have used density functional theory to study the structural and electronic properties of two Σ7 bicrystal grain boundaries containing Y, Hf, and Zr substitutional defects on Al sites. The presence of RE substitutional defects plays a minimal direct role in reducing the density of electronic states near the valence-band maximum. However, Hf4+ or Zr4+ substitutions at the grain boundary repel the positively charged oxygen vacancy VO2+. As VO2+ contributes a defect state above the valence-band maximum but below the Fermi energy, this indirectly lowers the density of current carrying holes and thus the electronic conductivity of the grain boundary. Replacing Al3+ ions with Hf4+ or Zr4+ ions also makes the grain boundary positively charged, further reducing the hole density.
Chen AP, Foulkes W, Heuer AH, et al., 2022, Diffusion of oxygen in Mg-doped α-Al2O3: the corundum conundrum explained, Physics Review Materials, Vol: 6, Pages: 1-7, ISSN: 2475-9953
It has been a puzzle for over two decades that the enhancement of oxygen diffusion in α-Al_{2}O_{3} ,with respect to the amount of Mg doping, is several orders of magnitude less than expected. The standard model, which envisages that transport is mediated by oxygen vacancies induced to compensate the charge of Mg 2+ ions substituting Al 3+ ions, has not been able to explain this anomaly. Here, we report a detailed study of populations of point defects and defect clusters in Mg-doped α-Al_{2}O_{3}. By taking into account calculated defect formation energies from the literature, the condition of charge neutrality, and the environmental parameters (chemical potentials) under which the anomalous trend in oxygen diffusivities were previously observed, we are able to arrive at an explanation. A non-linear relationship between Mg concentration in the system and key native point defects, which serve as mediators of self-diffusion in α-Al_{2}O_{3_ , is predicted: the concentrations of such defects increase much more slowly in the supersaturation regime than in the pre-saturation regime, matching the anomalous result previously observed in α-Al_{2}O_{3} . We identify the reason for this as buffering by positively charged Mg interstitials and Mg–oxygen vacancy clusters, which compensate the negative charges of Mg substitutional defects (Mg^{1−}Al ). This study answers part of the long-standing question about self-diffusion in alumina, referred to by Heuer and Lagerlöf in 1999 as the Corundum Conundrum.
Heuer AH, Finnis MW, Foulkes WMC, et al., 2022, Comment on “Self-diffusion in high-purity α-Al2O3: Comparison of Ti-doped, Mg-doped and undoped single crystals”, P. Fielitz, S. Ganschow, K. Klemens, and G. Borchardt, J. Eur. Ceram. Soc., 41, (2021), 663-668.", Journal of the European Ceramic Society, Vol: 42, Pages: 1829-1831, ISSN: 0955-2219
We comment on recent observations of O and Al self-diffusion in single-crystal sapphire with variable doping concentrations of Mg and Ti by Fielitz et al [1]. The paper reports a null effect of aliovalent doping on oxygen diffusivity. We posit that the extensive heat treatment involved in their experimental protocol may have caused dopant evaporation near the surface, and therefore the null result in oxygen diffusivity, whereas an effect on Al diffusivity is still discernible due to a greater diffusion depth of Al. We propose that buffering mechanisms are ultimately responsible for modest increases of self-diffusion with respect to dopant concentrations; in the Mg-doped case, DFT calculations suggest that negatively charged Mg interstitial defects are the principal charge compensating defects for positively charged Mg substitutional ions.
Fagerholm E, Foulkes W, Gallero-Salas Y, et al., 2022, Estimating anisotropy directly via neural timeseries, Journal of Computational Neuroscience, Vol: 50, ISSN: 0929-5313
An isotropic dynamical system is one that looks the same in every direction, i.e., if we imagine - standing somewhere within an isotropic system, we would not be able to differentiate between different lines of sight. Conversely, anisotropy is a measure of the extent to which a system deviates from perfect isotropy, with larger values indicating greater discrepancies between the structure of the system along its axes. Here, we derive the form of a generalised scalable (mechanically similar) discretized field theoretic Lagrangian that allows for levels of anisotropy to be directly estimated via timeseries of arbitrary dimensionality. We generate synthetic data for both isotropic and anisotropic systems and, by using Bayesian model inversion and reduction, show that we can discriminate between the two datasets – thereby demonstrating proof of principle. We then apply this methodology to murine calcium imaging data collected in rest and task states, showing that anisotropy can be estimated directly from different brain states and cortical regions in an empirical in vivo biological setting. We hope that this theoretical foundation, together with the methodology and publicly available MATLAB code, will provide an accessible way for researchers to obtain new insight into the structural organization of neural systems in terms of how scalable neural regions grow – both ontogenetically during the development of an individual organism, as well as phylogenetically across species.
Azadi S, Drummond ND, Foulkes WMC, 2021, Quasiparticle effective mass of the three-dimensional fermi liquid by quantum Monte Carlo, Physical Review Letters, Vol: 127, Pages: 1-6, ISSN: 0031-9007
According to Landau's Fermi liquid theory, the main properties of thequasiparticle excitations of an electron gas are embodied in the effective mass$m^*$, which determines the energy of a single quasiparticle, and the Landauinteraction function, which indicates how the energy of a quasiparticle ismodified by the presence of other quasiparticles. This simple paradigmunderlies most of our current understanding of the physical and chemicalbehavior of metallic systems. The quasiparticle effective mass of thethree-dimensional homogeneous electron gas has been the subject of theoreticalcontroversy and there is a lack of experimental data. In this work, we deploydiffusion Monte Carlo (DMC) methods to calculate $m^*$ as a function of densityfor paramagnetic and ferromagnetic three-dimensional homogeneous electrongases. The DMC results indicate that $m^*$ decreases when the density isreduced, especially in the ferromagnetic case. The DMC quasiparticle energybands exclude the possibility of a reduction in the occupied bandwidth relativeto that of the free-electron model at density parameter $r_s=4$, whichcorresponds to Na metal.
Fagerholm ED, Foulkes W, Friston KJ, et al., 2021, Rendering neuronal state equations compatiblewith the principle of stationary action, Journal of Mathematical Neuroscience, Vol: 11, Pages: 1-15, ISSN: 2190-8567
The principle of stationary action is a cornerstone of modern physics, providing a powerful framework for investigating dynamical systems found in classical mechanics through to quantum field theory. However, computational neuroscience, despite its heavy reliance on concepts in physics, is anomalous in this regard as its main equations of motion are not compatible with a Lagrangian formulation and hence with the principle of stationary action. Taking the Dynamic Causal Modelling (DCM) neuronal state equation as an instructive archetype of the first-order linear differential equations commonly found in computational neuroscience, we show that it is possible to make certain modifications to this equation to render it compatible with the principle of stationary action. Specifically, we show that a Lagrangian formulation of the DCM neuronal state equation is facilitated using a complex dependent variable, an oscillatory solution, anc a Hermitian intrinsic connectivity matrix. We first demonstrate proof of principle by using Bayesian model inversion to show that both the original and modified models can be correctly identified via in silico data generated directly from their respective equations of motion. We then provide motivation for adopting the modified models in neuroscience by using three different types of publicly available in vivo neuroimaging datasets, together with open source MATLAB code, to show that the modified (oscillatory) model provides a more parsimonious explanation for some of these empirical timeseries. It is our hope that this work will, in combination with existing techniques, allow people to explore the symmetries and associated conservation laws within neural systems – and to exploit the computational expediency facilitated by direct variational techniques.
Fagerholm ED, Foulkes W, Gallero-Salas Y, et al., 2021, Neural systems under change of scale, Frontiers in Computational Neuroscience, Vol: 15, ISSN: 1662-5188
We derive a theoretical construct that allows for the characterisation of both scalable and scale free systems within the Dynamic Causal Modelling framework. We define a dynamical system to be ‘scalable’ if the same equation of motion continues to apply as the system changes in size. As an example of such a system, we simulate planetary orbits varying in size and show that our proposed methodology can be used to recover Kepler’s third law from the timeseries. In contrast, a ‘scale free’ system is one in which there is no characteristic length scale, meaning that images of such a system are statistically unchanged at different levels of magnification. As an example of such a system, we use calcium imaging collected in murine cortex and show that the dynamical critical exponent, as defined in renormalization group theory, can be estimated in an empirical biological setting. We find that a task-relevant region of the cortex is associated with higher dynamical critical exponents in task vs. spontaneous states and vice versa for a task-irrelevant region.
Pfau D, Spencer JS, Matthews AGDG, et al., 2020, Ab-initio solution of the many-electron Schrödinger equation with deepneural networks, Physical Review Research, Vol: 2, ISSN: 2643-1564
Given access to accurate solutions of the many-electron Schr\"odingerequation, nearly all chemistry could be derived from first principles. Exactwavefunctions of interesting chemical systems are out of reach because they areNP-hard to compute in general, but approximations can be found usingpolynomially-scaling algorithms. The key challenge for many of these algorithmsis the choice of wavefunction approximation, or Ansatz, which must trade offbetween efficiency and accuracy. Neural networks have shown impressive power asaccurate practical function approximators and promise as a compact wavefunctionAnsatz for spin systems, but problems in electronic structure requirewavefunctions that obey Fermi-Dirac statistics. Here we introduce a novel deeplearning architecture, the Fermionic Neural Network, as a powerful wavefunctionAnsatz for many-electron systems. The Fermionic Neural Network is able toachieve accuracy beyond other variational quantum Monte Carlo Ans\"atze on avariety of atoms and small molecules. Using no data other than atomic positionsand charges, we predict the dissociation curves of the nitrogen molecule andhydrogen chain, two challenging strongly-correlated systems, to significantlyhigher accuracy than the coupled cluster method, widely considered the mostaccurate scalable method for quantum chemistry at equilibrium geometry. Thisdemonstrates that deep neural networks can improve the accuracy of variationalquantum Monte Carlo to the point where it outperforms other ab-initio quantumchemistry methods, opening the possibility of accurate direct optimisation ofwavefunctions for previously intractable molecules and solids.
Foulkes WMC, 2020, Variational Wave Functions for Molecules and Solids, Topology, Entanglement, and Strong Correlations, Editors: Pavarini, Koch, Publisher: Forschungszentrum Juelich GmbH, Institute for Advanced Simulations, Pages: 2.1-2.1, ISBN: 978-3-95806-466-9
Fagerholm ED, Foulkes W, Gallero-Salas Y, et al., 2020, Conservation laws by virtue of scale symmetries in neural systems, PLoS Computational Biology, Vol: 16, ISSN: 1553-734X
In contrast to the symmetries of translation in space, rotation in space, and translation in time, the known laws of physics are not universally invariant under transformation of scale. However, a special case exists in which the action is scale invariant if it satisfies the following two constraints: 1) it must depend upon a scale-free Lagrangian, and 2) the Lagrangian must change under scale in the same way as the inverse time, . Our contribution lies in the derivation of a generalised Lagrangian, in the form of a power series expansion, that satisfies these constraints. This generalised Lagrangian furnishes a normal form for dynamic causal models–state space models based upon differential equations–that can be used to distinguish scale symmetry from scale freeness in empirical data. We establish face validity with an analysis of simulated data, in which we show how scale symmetry can be identified and how the associated conserved quantities can be estimated in neuronal time series.
Azadi S, Foulkes WMC, 2019, Efficient method for grand-canonical twist averaging in quantum Monte Carlo calculations, Physical Review B: Condensed Matter and Materials Physics, Vol: 100, ISSN: 1098-0121
We introduce a simple but efficient method for grand-canonical twistaveraging in quantum Monte Carlo calculations. By evaluating the thermodynamic grand potential instead of the ground state total energy, we greatly reduce the sampling errors caused by twist-dependent fluctuations in the particle number. We apply this method to the electron gas and to metallic lithium, aluminum, and solid atomic hydrogen. We show that, even when using a small number of twists, grand-canonical twist averaging of the grand potential produces better estimates of ground state energies than the widely used canonical twist-averaging approach.
Fagerholm ED, Foulkes WMC, Gallero-Salas Y, et al., 2019, Estimating quantities conserved by virtue of scale invariance in timeseries
In contrast to the symmetries of translation in space, rotation in space, andtranslation in time, the known laws of physics are not universally invariantunder transformation of scale. However, the action can be invariant underchange of scale in the special case of a scale free dynamical system that canbe described in terms of a Lagrangian, that itself scales inversely with time.Crucially, this means symmetries under change of scale can exist in dynamicalsystems under certain constraints. Our contribution lies in the derivation of ageneralised scale invariant Lagrangian - in the form of a power seriesexpansion - that satisfies these constraints. This generalised Lagrangianfurnishes a normal form for dynamic causal models (i.e., state space modelsbased upon differential equations) that can be used to distinguish scaleinvariance (scale symmetry) from scale freeness in empirical data. We establishface validity with an analysis of simulated data and then show how scaleinvariance can be identified - and how the associated conserved quantities canbe estimated - in neuronal timeseries.
Fagerholm ED, Foulkes WMC, Gallero-Salas Y, et al., 2019, Network constraints in scale free dynamical systems
Scale free dynamics are observed in a variety of physical and biologicalsystems. These include neural activity in which evidence for scale freeness hasbeen reported using a range of imaging modalities. Here, we derive the ways inwhich connections within a network must transform - relative to system size -in order to maintain scale freeness and test these theoretical transformationsvia simulations. First, we explore the known invariance of planetary motion fororbits varying in size. Using parametric empirical Bayesian modelling and ageneric dynamical systems model, we show that we recover Kepler's third lawfrom orbital timeseries, using our proposed transformations; thereby providingconstruct validation. We then demonstrate that the dynamical critical exponentis inversely proportional to the time rescaling exponent, in the context ofcoarse graining operations. Using murine calcium imaging data, we then showthat the dynamical critical exponent can be estimated in an empiricalbiological setting. Specifically, we compare dynamical critical exponents -associated with spontaneous and task states in two regions of imaged cortex -that are classified as task-relevant and task-irrelevant. We find, consistentlyacross animals, that the task-irrelevant region exhibits higher dynamicalcritical exponents during spontaneous activity than during task performance.Conversely, the task-relevant region is associated with higher dynamicalcritical exponents in task vs. spontaneous states. These data support the ideathat higher dynamical critical exponents, within relevant cortical structures,underwrite neuronal processing due to the implicit increase in cross-scaleinformation transmission.
Wells T, Horsfield A, Foulkes WMC, et al., 2019, The microscopic Einstein-de Haas effect, Journal of Chemical Physics, Vol: 150, ISSN: 0021-9606
The Einstein-de Haas (EdH) effect, where the spin angular momentum of electrons is transferred to the mechanical angular momentum of atoms, was established experimentally in 1915. While a semiclassical explanation of the effect exists, modern electronic structure methods have not yet been applied to model the phenomenon. In this paper, we investigate its microscopic origins by means of a noncollinear tight-binding model of an O2 dimer, which includes the effects of spin-orbit coupling, coupling to an external magnetic field, and vector Stoner exchange. By varying an external magnetic field in the presence of spin-orbit coupling, a torque can be generated on the dimer, validating the presence of the EdH effect. The avoided energy level crossings and the rate of change of magnetic field determine the evolution of the spin. We also find that the torque exerted on the nuclei by the electrons in a time-varying B field is not only due to the EdH effect. The other contributions arise from field-induced changes in the electronic orbital angular momentum and from the direct action of the Faraday electric field associated with the time-varying magnetic field.
Spencer JS, Blunt NS, Choi S, et al., 2019, The HANDE-QMC project: open-source stochastic quantum chemistry from the ground state up, Journal of Chemical Theory and Computation, Vol: 15, Pages: 1728-1742, ISSN: 1549-9618
Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative stochastic approaches to solve electronic structure problems have emerged over the past decade. The full configuration interaction quantum Monte Carlo (FCIQMC) method allows one to systematically approach the exact solution of such problems, for cases where very high accuracy is desired. The introduction of FCIQMC has subsequently led to the development of coupled cluster Monte Carlo (CCMC) and density matrix quantum Monte Carlo (DMQMC), allowing stochastic sampling of the coupled cluster wave function and the exact thermal density matrix, respectively. In this Article, we describe the HANDE-QMC code, an open-source implementation of FCIQMC, CCMC and DMQMC, including initiator and semistochastic adaptations. We describe our code and demonstrate its use on three example systems; a molecule (nitric oxide), a model solid (the uniform electron gas), and a real solid (diamond). An illustrative tutorial is also included.
Coury MEA, Dudarev SL, Foulkes WMC, et al., 2018, Erratum: Hubbard-like Hamiltonians for interacting electrons in s, p, and d orbitals (vol 93, 075101, 2016), Physical Review B, Vol: 98, ISSN: 2469-9950
Davies PAG, Foulkes WMC, 2018, A two-phase Hessian approach improves the DFT relaxation of slabs, Journal of Physics: Condensed Matter, Vol: 30, Pages: 315901-315901, ISSN: 0953-8984
A two-phase Hessian approach to DFT slab relaxation of slabs has been implemented and tested. It addresses weaknesses in the modified Broyden and Pfrommer BFGS algorithms specific to relaxing slabs. Complete Hessian and then inverse Hessian matrices with no strain/stress components are first constructed at high force signal-to-noise ratios with no accompanying relaxation. In a second phase the static inverse Hessian is used to relax the slab down to a low force tolerance.
Groth S, Dornheim T, Sjostrom T, et al., 2017, Ab initio exchange-correlation free energy of the uniform electron gas at warm dense matter conditions, Physical Review Letters, Vol: 119, ISSN: 0031-9007
In a recent Letter [T.~Dornheim \textit{et al.}, Phys. Rev. Lett.\textbf{117}, 156403 (2016)], we presented the first \textit{ab initio} quantumMonte-Carlo (QMC) results of the warm dense electron gas in the thermodynamiclimit. However, a complete parametrization of the exchange-correlation freeenergy with respect to density, temperature, and spin polarization remained outof reach due to the absence of (i) accurate QMC results below$\theta=k_\text{B}T/E_\text{F}=0.5$ and (ii) of QMC results for spinpolarizations different from the paramagnetic case. Here we overcome bothremaining limitations. By closing the gap to the ground state and by performingextensive QMC simulations for different spin polarizations, we are able toobtain the first complete \textit{ab initio} exchange-correlation free energyfunctional; the accuracy achieved is an unprecedented $\sim 0.3\%$. This alsoallows us to quantify the accuracy and systematic errors of various previousapproximate functionals.
Dornheim T, Groth S, Malone FD, et al., 2017, Ab initio quantum Monte Carlo simulation of the warm dense electron gas, Physics of Plasmas, Vol: 24, Pages: 056303-1-056303-10, ISSN: 1089-7674
Warm dense matter is one of the most active frontiers in plasma physics due to its relevance for denseastrophysical objects as well as for novel laboratory experiments in which matter is being strongly compressede.g. by high-power lasers. Its description is theoretically very challenging as it contains correlated quantumelectrons at nite temperature|a system that cannot be accurately modeled by standard analytical or groundstate approaches. Recently several breakthroughs have been achieved in the eld of fermionic quantum MonteCarlo simulations. First, it was shown that exact simulations of a nite model system (30 : : : 100 electrons)is possible that avoid any simplifying approximations such as xed nodes [Schoof et al., Phys. Rev. Lett.115, 130402 (2015)]. Second, a novel way to accurately extrapolate these results to the thermodynamic limitwas reported by Dornheim et al. [Phys. Rev. Lett. 117, 156403 (2016)]. As a result, now thermodynamicresults for the warm dense electron gas are available that have an unprecedented accuracy on the order of0:1%. Here we present an overview on these results and discuss limitations and future directions.
Azadi S, Drummond ND, Foulkes WMC, 2017, Nature of the metallization transition in solid hydrogen, Physical Review. B, Condensed Matter, Vol: 95, ISSN: 0163-1829
We present an accurate study of the static-nucleus electronic energy band gap of solid molecular hydrogen at high pressure. The excitonic and quasiparticle gaps of the C2/c, Pc, Pbcn, and P63/mstructures at pressures of 250, 300, and 350 GPa are calculated using the fixed-node diffusion quantum Monte Carlo (DMC) method. The difference between the mean-field and many-body band gaps at the same density is found to be almost independent of system size and can therefore be applied as a scissor correction to the mean-field gap of an infinite system to obtain an estimate of the many-body gap in the thermodynamic limit. By comparing our static-nucleus DMC energy gaps with available experimental results, we demonstrate the important role played by nuclear quantum effects in the electronic structure of solid hydrogen.
Dornheim T, Groth S, Sjostrom T, et al., 2016, Ab initio quantum Monte Carlo simulation of the warm dense electron gas in the thermodynamic limit, Physical Review Letters, Vol: 117, ISSN: 1079-7114
We perform ab initio quantum Monte Carlo (QMC) simulations of the warm dense uniform electrongas in the thermodynamic limit. By combining QMC data with linear response theory we are able toremove finite-size errors from the potential energy over the entire warm dense regime, overcoming thedeficiencies of the existing finite-size corrections by Brown et al. [PRL 110, 146405 (2013)]. Extensivenew QMC results for up to N = 1000 electrons enable us to compute the potential energy V and theexchange-correlation free energy Fxc of the macroscopic electron gas with an unprecedented accuracyof |∆V |/|V |, |∆Fxc|/|F|xc ∼ 10−3. A comparison of our new data to the recent parametrization ofFxc by Karasiev et al. [PRL 112, 076403 (2014)] reveals significant deviations to the latter.
Foulkes WMC, 2016, Tight-Binding Models and Coulomb Interactions for s, p, and d Electrons, Quantum Materials: Experiments and Theory, Editors: Pavarini, Koch, van den Brink, Sawatzky, Jülich, Germany, Publisher: Forschungszentrum Jülich GmbH, Pages: 3.1-3.42, ISBN: 978-3-95806-159-0
Malone FD, Blunt NS, Brown EW, et al., 2016, Accurate exchange-correlation energies for the warm dense electron gas, Physical Review Letters, Vol: 117, ISSN: 1079-7114
The density matrix quantum Monte Carlo (DMQMC) method is used to sample exact-on-average N-body density matrices for uniform electron gas systems of up to 10124 matrix elements via a stochastic solution of the Bloch equation. The results of these calculations resolve a current debate over the accuracy of the data used to parametrize finite-temperature density functionals. Exchange-correlation energies calculated using the real-space restricted path-integral formalism and the k-space configuration path-integral formalism disagree by up to ∼10% at certain reduced temperatures T/TF≤0.5 and densities rs≤1. Our calculations confirm the accuracy of the configuration path-integral Monte Carlo results available at high density and bridge the gap to lower densities, providing trustworthy data in the regime typical of planetary interiors and solids subject to laser irradiation. We demonstrate that the DMQMC method can calculate free energies directly and present exact free energies for T/TF≥1 and rs≤2.
Horsfield AP, Lim A, Foulkes WMC, et al., 2016, Adiabatic perturbation theory of electronic stopping in insulators, Physical Review B, Vol: 93, Pages: 1-1, ISSN: 2469-9950
A model able to explain the complicated structure of electronic stopping at low velocities in insulating materials is presented. It is shown to be in good agreement with results obtained from time-dependent density-functional theory for the stopping of a channeling Si atom in a Si crystal. If we define the repeat frequency f=v/λ, where λ is the periodic repeat length of the crystal along the direction the channeling atom is traveling, and v is the velocity of the channeling atom, we find that electrons experience a perturbing force that varies in time at integer multiples l of f. This enables electronic excitations at low atom velocity, but their contributions diminish rapidly with increasing values of l. The expressions for stopping power are derived using adiabatic perturbation theory for many-electron systems, and they are then specialized to the case of independent electrons. A simple model for the nonadiabatic matrix elements is described, along with the procedure for determining its parameters.
Heuer AH, Azar MZ, Guhl H, et al., 2016, The band structure of polycrystalline Al2O3 and its influence on transport phenomena, Journal of the American Ceramic Society, Vol: 99, Pages: 733-747, ISSN: 1551-2916
Coury MEA, Dudarev SL, Foulkes WMC, et al., 2016, Hubbard-like Hamiltonians for interacting electrons in s, p, and d orbitals, Physical Review B, Vol: 93, ISSN: 1550-235X
Hubbard-like Hamiltonians are widely used to describe on-site Coulomb interactions in magnetic and strongly-correlated solids, but there is much confusion in the literature about the form these Hamiltonians should take for shells of p and d orbitals. This paper derives the most general s,p, and d orbital Hubbard-like Hamiltonians consistent with the relevant symmetries, and presents them in ways convenient for practical calculations. We use the full configuration interaction method to study p and d orbital dimers and compare results obtained using the correct Hamiltonian and the collinear and vector Stoner Hamiltonians. The Stoner Hamiltonians can fail to describe properly the nature of the ground state, the time evolution of excited states, and the electronic heat capacity.
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