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In quantum electrodynamics with fermions f = e,\mu..., knowledge of the vacuum polarization spectral function determined from the tree level e^+e^- -> f^+f^- cross sections, together with a single low energy measurement of the fine…
The effective electron-electron interaction in the electron gas depends on both the density and spin local field factors. Variational Diagrammatic Quantum Monte Carlo calculations of the spin local field factor are reported and used to…
Density functional theory is the standard theory for computing the electronic structure of materials, which is based on a functional that maps the electron density to the energy. However, a rigorous form of the functional is not known and…
The determination of the effective Coulomb interactions to be used in low-energy Hamiltonians for materials with strong electronic correlations remains one of the bottlenecks for parameter-free electronic structure calculations. We propose…
Jet production and jet substructure modification in heavy-ion collisions have played an essential role in revealing the in-medium evolution of parton showers and the determination of the properties of strongly-interacting matter under…
Applying general symmetry properties of electromagnetic interaction, information from electron proton elastic scattering data can be related to charge asymmetry in the annihilation channels $e^++e^-\leftrightarrow \bar p + p$ and to the…
Recent measurements of charge-dependent azimuthal correlations in high-energy heavy-ion collisions have indicated charge-separation signals perpendicular to the reaction plane, and have been related to the chiral magnetic effect (CME).…
We show the importance of separated efficiency corrections between positively and negatively charged particles for cumulant calculations by Monte Carlo toy models and analytical calculations. Our results indicate that S{\sigma} in published…
Machine learning (ML) can facilitate efficient thermoelectric (TE) material discovery essential to address the environmental crisis. However, ML models often suffer from poor experimental generalizability despite high metrics. This study…
The elastic electron-proton scattering data are analysed in order to determine proton charge and magnetic rms radii, r_E and r_M. Along with the usual statistical error, we try to estimate a systematic error in the radii, caused by the…
We present numerical results on electron tunneling in a single-electron box at low temperature. The effective action of this device is equivalent to the Hamiltonian of a classical XY spin chain with long ranged interactions. Using an…
Traditionally, yield strength prediction relies on detailed and resource-intensive microstructural characterization combined with empirical equations. However, quantifying microstructural feature length scales for novel processes like…
We introduce a local machine-learning method for predicting the electron densities of periodic systems. The framework is based on a numerical, atom-centred auxiliary basis, which enables an accurate expansion of the all-electron density in…
The development of machine learning sheds new light on the traditionally complicated problem of thermodynamics in multicomponent alloys. Successful application of such a method, however, strongly depends on the quality of the data and…
In order to calculate the effective mass of quasiparticles for a strongly correlated metallic system in which the number of carriers, n, is less than that of atoms (or lattices), l, the metallic system is averaged by one effective charge…
Large values of Born effective charges are generally considered as reliable indicators of the genuine tendency of an insulator towards ferroelectric instability. However, these quantities can be very much influenced by strong electron…
In this paper, we develop a hybrid prediction framework for accurate electric vehicle (EV) charging time estimation, a capability that is critical for trip planning, user satisfaction, and efficient operation of charging infrastructure. We…
We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated alloys. From this, other physical properties can be inferred,…
We present a new estimate of the hadronic contribution to the shift in the fine structure constant at LEP and TESLA energies and calculate the effective fine structure constant. Substantial progress in a precise determination of this…
Constructing a self-consistent first-principles framework that accurately predicts the properties of electron transfer reactions through finite-temperature molecular dynamics simulations is a dream of theoretical electrochemists and…