A statistical model for the calculation of the ionisation-cluster size distribution in nanodosimetry is proposed. It is based on a canonical ensemble and derives from the well-known nuclear droplet model. The model especially can be applied to the scenario 'low energy primaries (smaller than 100 eV) moving in nanovolumes (in the order of a few nanometers)'; a scenario to which trajectory models should not be used. The focus of this work is on presenting the model and demonstrating its feasibility.
We review an explicit approach to obtaining numerical solutions of the Schrödinger equation that is conceptionally straightforward and capable of significant accuracy and efficiency. The method and its efficacy are illustrated with several examples. Because of its explicit nature, the algorithm can be readily extended to systems with a higher number of spatial dimensions. We show that the method also generalizes the staggered-time approach of Visscher and allows for the accurate calculation of the real and imaginary parts of the wave function separately.
The Atomic Cluster Expansion (ACE) [R. Drautz, Phys. Rev. B, 99:014104 (2019)] provides a systematically improvable, universal descriptor for the environment of an atom that is invariant to permutation, translation and rotation. ACE is being used extensively in newly emerging interatomic potentials based on machine learning. This commentary discusses the ACE framework and its potential impact.
Fundamental bounds on quadratic electromagnetic metrics are formulated and solved via convex optimization. Both dual formulation and method-of-moments formulation of the electric field integral equation are used as key ingredients. The trade-off between metrics is formulated as a multi-objective optimization resulting in Pareto-optimal sets. Substructure fundamental bounds are also introduced and formulated as additional affine constraints. The general methodology is demonstrated on a few examples of minimal complexity and all examples are supported with freely available MATLAB codes contained in the developed package on fundamental bounds.
We present a new open source software for the integration of the radial Dirac equation developed specifically with muonic atoms in mind. The software, called mudirac, is written in C++ and can be used to predict frequencies and probabilities of the transitions between levels of the muonic atom. In this way, it provides an invaluable tool in helping with the interpretation of muonic X-ray spectra for elemental analysis. We introduce the details of the algorithms used by the software, show the interpretation of a few example spectra, and discuss the more complex issues involved with predicting the intensities of the spectral lines. The software is available publicly at https://github.com/muon-spectroscopy-computational-project/mudirac.
Tensor-ring decomposition of tensors plays a key role in various applications of tensor network representation in physics as well as in other fields. In most heuristic algorithms for the tensor-ring decomposition, one encounters the problem of local-minima trapping. Particularly, the minima related to the topological structure in the correlation are hard to escape. Therefore, identification of the correlation structure, somewhat analogous to finding matching ends of entangled strings, is the task of central importance. We show how this problem naturally arises in physical applications, and present a strategy for winning this string-pull game.
A recent paper compares density functional theory results for atomization energies and dipole moments using a multi-wavelet based method with traditional Gaussian basis set results, and concludes that Gaussian basis sets are problematic for achieving high accuracy. We show that by a proper choice of Gaussian basis sets they are capable of achieving essentially the same accuracy as the multi-wavelet approach, and identify a couple of possible problems in the multi-wavelet calculations.
Comsol finite element technique was applied to study heating and cooling of a microspot on the cathode surface. The reasons why there seems to be no common model for vacuum arcs, in spite of the importance of this field and the level of effort expended over more than one hundred years, were explored.
We narrow the gap between simulations of nuclear magnetic resonance dynamics on digital domains (such as CT-images) and measurements in D-dimensional porous media. We point out with two basic domains, the ball and the cube in D dimensions, that due to a digital uncertainty in representing the real pore surfaces of dimension D-1, there is a systematic error in simulated dynamics. We then reduce this error by introducing local Robin boundary conditions.
We discuss physical implications of the explicit method in numerical analysis. Numerical methods have there own condition for causality, known as the Courant-Friedrichs-Lewy condition. It is proposed that numerical causality merges with physical causality as the grid interval size approaches zero. We discuss the implications of this proposition on the numerical analysis of the wave equation. We also show that, insisting on physical causality, the numerical analysis of Schrodinger's equation implies that the minimum space interval should satisfy $Δx \ge a_0 λ_c$, where $λ_c$ is the reduced Compton wavelength and $a_0$ is a constant of the order unity.
A new numerical method is presented to find full complex roots of a complex dispersion equation. For the application of the solution, the complex dispersion equation of a cylindrical metallic nanowire is investigated. By using this method, locus of Brewster angle, complex dispersion curves of Surface Plasmon Polaritons (SPPs) and complex bulk modes can be obtained in once calculation. Approximate analytical solution to the complex dispersion equation has also been derived to verify our method.
Efficient and accurate numerical propagation of the time dependent Schroedinger equation is a problem with applications across a wide range of physics. This paper develops an efficient, trivially parallelizeable method for relaxing a trial wavefunction toward a variationally optimum propagated wavefunction which minimizes the propagation error relative to a platonic wavefunction which obeys the time dependent Schroedinger equation exactly. This method is shown to be well suited for incorporation with multigrid methods, yielding rapid convergence to a minimum action solution even for Hamiltonians which are not positive definite.
This paper presents a new technique to calculate the evolution of a quantum wavefunction in a chosen spatial basis by minimizing the accumulated action. Introduction of a finite temporal basis reduces the problem to a set of linear equations, while an appropriate choice of temporal basis set offers improved convergence relative to methods based on matrix exponentiation for a class of physically relevant problems.
In this note, we address formally the issue of symmetry for probabilities of different dynamical pathways in the forward and reverse directions of a conformational transition. Our discussion is based on a decomposition of equilibrium into opposing steady states, and makes clear the conditions necessary for symmetry to apply. From a practical point of view, we also discuss when approximate symmetry is to be expected.
In previous works it was shown that protein 3D-conformations could be encoded into discrete sequences called dominance partition sequences (DPS), that generated a linear partition of molecular conformational space into regions of molecular conformations that have the same DPS. In this work we describe procedures for building in a cubic lattice the set of 3D-conformations that are compatible with a given DPS. Furthermore, this set can be structured as a graph upon which a combinatorial algorithm can be applied for computing the mean energy of the conformations in a cell.
We survey results in lattice quantum chromodynamics from groups in the USQCD Collaboration. The main focus is on physics, but many aspects of the discussion are aimed at an audience of computational physicists.
We consider several issues related to the multidimensional integration using a network of heterogeneous computers. Based on these considerations, we develop a new general purpose scheme which can significantly reduce the time needed for evaluation of integrals with CPU intensive integrands. This scheme is a parallel version of the well-known adaptive Monte Carlo method (the VEGAS algorithm), and is incorporated into a new integration package which uses the standard set of message-passing routines in the PVM software system.