Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials

Neural message passing on molecular graphs is one of the most promising methods for predicting formation energy and other properties of molecules and materials. In this work we extend the neural message passing model with an edge update network which allows the information exchanged between atoms to depend on the hidden state of the receiving atom. We benchmark the proposed model on three publicly available datasets (QM9, The Materials Project and OQMD) and show that the proposed model yields superior prediction of formation energies and other properties on all three datasets in comparison with the best published results. Furthermore we investigate different methods for constructing the graph used to represent crystalline structures and we find that using a graph based on K-nearest neighbors achieves better prediction accuracy than using maximum distance cutoff or the Voronoi tessellation graph

Materials property prediction using symmetry-labeled graphs as atomic-position independent descriptors

Computational materials screening studies require fast calculation of the properties of thousands of materials. The calculations are often performed with Density Functional Theory (DFT), but the necessary computer time sets limitations for the investigated material space. Therefore, the development of machine learning models for prediction of DFT calculated properties are currently of interest. A particular challenge for \emph{new} materials is that the atomic positions are generally not known. We present a machine learning model for the prediction of DFT-calculated formation energies based on Voronoi quotient graphs and local symmetry classification without the need for detailed information about atomic positions. The model is implemented as a message passing neural network and tested on the Open Quantum Materials Database (OQMD) and the Materials Project database. The test mean absolute error is 20 meV on the OQMD database and 40 meV on Materials Project Database. The possibilities for prediction in a realistic computational screening setting is investigated on a dataset of 5976 ABSe$_3$ selenides with very limited overlap with the OQMD training set. Pretraining on OQMD and subsequent training on 100 selenides result in a mean absolute error below 0.1 eV for the formation energy of the selenides.Comment: 14 pages including references and 13 figure

Early Memories of Individuals on the Autism Spectrum Assessed Using Online Self-Reports

"When I was one and a half years old, I was on a ferry lying on red seats" - while several autobiographical accounts by people with autism reveal vivid memories of early childhood, the vast amount of experimental investigations found deficits in personal autobiographic memory in autism. To assess this contradiction empirically, we implemented an online questionnaire on early childhood events to compare people on the autism spectrum (AS) and non-autistic people with respect to their earliest autobiographical episodic memories and the earliest semantic know event as told by another person. Results indicate that people on the AS do not differ from non-autistic people in the age of their earliest know events but remember events from an earlier age in childhood and with more sensory details, contradicting the assumption of an overall deficit in personal episodic memory in autism. Furthermore, our results emphasize the supporting influence of language for memory formation and give evidence for an important role of sensory features in memories of people on the AS.publishe

Empirical macromodels under test: a comparative simulation study of the employment effects of a revenue neutral cut in social security contributions

In the paper we simulate a revenue-neutral cut in the social security contribution rate using five different types of macro- / microeconomic models, namely two models based on time-series data where the labour market is modelled basically demand oriented, two models of the class of computable equilibrium models which are supply oriented and finally a firm specific model for international tax burden comparisons. Our primary interest is in the employment effects the models predict due to the cut in the contribution rate. It turns out that qualitatively all models considered predict an increase in employment three years after the cut. But the employment effects differ considerably in magnitude, which follows immediately from the different behavioral assumptions underlying the different models. -- In dem Beitrag wird der Beschäftigungseffekt infolge einer aufkommensneutralen Senkung der Sozialversicherungsbeiträge simuliert. Zu diesem Zweck werden fünf unterschiedliche ökonomische Modelle verwendet, namentlich zwei Modelle, die auf Zeitreihendaten aufbauen und in denen der Arbeitsmarkt überwiegend von der Nachfrageseite dominiert wird, zwei Modelle aus der Klasse der computable equilibrium models, die typischerweise angebotsorientiert sind, und ein mikroökonomisches, firmenspezifisches Steuerbelastungsvergleichsmodell. Alle Simulationsergebnisse der Modelle weisen auf einen, wenngleich teilweise kleinen, positiven Beschäftigungseffekt hin, der sich allerdings beträchtlich in seiner Größenordnung unterscheidet. Dies ist eine unmittelbare Folge aus den unterschiedlichen Verhaltensannahmen, die den einzelnen Modellen unterliegen.

Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces

Inexpensive machine learning potentials are increasingly being used to speed up structural optimization and molecular dynamics simulations of materials by iteratively predicting and applying interatomic forces. In these settings, it is crucial to detect when predictions are unreliable to avoid wrong or misleading results. Here, we present a complete framework for training and recalibrating graph neural network ensemble models to produce accurate predictions of energy and forces with calibrated uncertainty estimates. The proposed method considers both epistemic and aleatoric uncertainty and the total uncertainties are recalibrated post hoc using a nonlinear scaling function to achieve good calibration on previously unseen data, without loss of predictive accuracy. The method is demonstrated and evaluated on two challenging, publicly available datasets, ANI-1x (Smith et al.) and Transition1x (Schreiner et al.), both containing diverse conformations far from equilibrium. A detailed analysis of the predictive performance and uncertainty calibration is provided. In all experiments, the proposed method achieved low prediction error and good uncertainty calibration, with predicted uncertainty correlating with expected error, on energy and forces. To the best of our knowledge, the method presented in this paper is the first to consider a complete framework for obtaining calibrated epistemic and aleatoric uncertainty predictions on both energy and forces in ML potentials

Beam position monitor offset determination at LEP

For the performance of an electron positron storage ring it is important that the beam orbit passes well centred through the quadrupole magnets. Beam position monitors (BPM) aligned relative to the magnets can still have a residual mechanical or electronical offset with respect to the magnetic axis. A beam-based method is used at LEP to measure these offsets. During the machine operation for physics the gradient of selected quadrupoles is modulated with low frequencies (few Hz) and very small amplitudes (of the order of 10-4). The effect on the beam is observed with a high sensitivity pick-up. The observed effect passes through a minimum when the beam is centred in the quadrupole. Offsets for about 70 different BPM's were determined. Systematically different offsets were found for different type of BPM electronics and different types of quadrupoles. Simulations based on the past results show that the level of spin polarisation can be increased by further offset measurements

Formation rates of iron-acceptor pairs in crystalline silicon

The characteristic association time constant describing the formation of iron-acceptor pairs in crystalline silicon has been measured for samples of various p-type dopant concentrations and species (B, Ga, and In) near room temperature. The results show that the dopant species has no impact on the pairing kinetics, suggesting that the pairing process is entirely limited by iron diffusion. This conclusion was corroborated by measurement of the activation energy of pair formation, which coincides with the migration enthalpy of interstitial iron in silicon. The results also indicate that the pair-formation process occurs approximately twice as fast as predicted by a commonly used expression.This work has been supported by the Australian Research Council and the State of Lower Saxony

Lithium in strong magnetic fields

The electronic structure of the lithium atom in a strong magnetic field 0 <= gamma <= 10 is investigated. Our computational approach is a full configuration interaction method based on a set of anisotropic Gaussian orbitals that is nonlinearly optimized for each field strength. Accurate results for the total energies and one-electron ionization energies for the ground and several excited states for each of the symmetries ^20^+, ^2(-1)^+, ^4(-1)^+, ^4(-1)^-, ^2(-2)^+, ^4(-2)^+, $^4(-3)^{+}$ are presented. The behaviour of these energies as a function of the field strength is discussed and classified. Transition wave lengths for linear and circular polarized transitions are presented as well.Comment: 12 pages, 13 figures, accepted for publication in Phys. Rev.

Preliminary Spectral Analysis of the Type II Supernova 1999em

We have calculated fast direct spectral model fits to two early-time spectra of the Type-II plateau SN 1999em, using the SYNOW synthetic spectrum code. The first is an extremely early blue optical spectrum and the second a combined HST and optical spectrum obtained one week later. Spectroscopically this supernova appears to be a normal Type II and these fits are in excellent agreement with the observed spectra. Our direct analysis suggests the presence of enhanced nitrogen. We have further studied these spectra with the full NLTE general model atmosphere code PHOENIX. While we do not find confirmation for enhanced nitrogen (nor do we rule it out), we do require enhanced helium. An even more intriguing possible line identification is complicated Balmer and He I lines, which we show falls naturally out of the detailed calculations with a shallow density gradient. We also show that very early spectra such as those presented here combined with sophisticated spectral modeling allows an independent estimate of the total reddening to the supernova, since when the spectrum is very blue, dereddening leads to changes in the blue flux that cannot be reproduced by altering the ``temperature'' of the emitted radiation. These results are extremely encouraging since they imply that detailed modeling of early spectra can shed light on both the abundances and total extinction of SNe II, the latter improving their utility and reliability as distance indicators.Comment: to appear in ApJ, 2000, 54

Tests of relativity using a microwave resonator

The frequencies of a cryogenic sapphire oscillator and a hydrogen maser are compared to set new constraints on a possible violation of Lorentz invariance. We determine the variation of the oscillator frequency as a function of its orientation (Michelson-Morley test) and of its velocity (Kennedy-Thorndike test) with respect to a preferred frame candidate. We constrain the corresponding parameters of the Mansouri and Sexl test theory to $\delta - \beta + 1/2 = (1.5\pm 4.2) \times 10^{-9}$ and $\beta - \alpha - 1 = (-3.1\pm 6.9) \times 10^{-7}$ which is equivalent to the best previous result for the former and represents a 30 fold improvement for the latter.Comment: 8 pages, 2 figures, submitted to Physical Review Letters (October 3, 2002