Thomson problem

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The objective of the Thomson problem is to determine the minimum electrostatic potential energy configuration of N electrons constrained to the surface of a unit sphere that repel each other with a force given by Coulomb's law. The physicist J. J. Thomson posed the problem in 1904 [1] after proposing an atomic model, later called the plum pudding model, based on his knowledge of the existence of negatively charged electrons within neutrally-charged atoms.

Contents

Related problems include the study of the geometry of the minimum energy configuration and the study of the large N behavior of the minimum energy.

Mathematical statement

The electrostatic interaction energy occurring between each pair of electrons of equal charges (, with the elementary charge of an electron) is given by Coulomb's law,

where is the electric constant and is the distance between each pair of electrons located at points on the sphere defined by vectors and , respectively.

Simplified units of and (the Coulomb constant) are used without loss of generality. Then,

The total electrostatic potential energy of each N-electron configuration may then be expressed as the sum of all pair-wise interaction energies

The global minimization of over all possible configurations of N distinct points is typically found by numerical minimization algorithms.

Thomson's problem is related to the 7th of the eighteen unsolved mathematics problems proposed by the mathematician Steve Smale — "Distribution of points on the 2-sphere". [2] The main difference is that in Smale's problem the function to minimise is not the electrostatic potential but a logarithmic potential given by A second difference is that Smale's question is about the asymptotic behaviour of the total potential when the number N of points goes to infinity, not for concrete values of N.

Example

The solution of the Thomson problem for two electrons is obtained when both electrons are as far apart as possible on opposite sides of the origin, , or

Known exact solutions

Schematic geometric solutions of the mathematical Thomson Problem for up to N = 5 electrons. N 2 to 5 ThomsonSolutions.png
Schematic geometric solutions of the mathematical Thomson Problem for up to N = 5 electrons.

Mathematically exact minimum energy configurations have been rigorously identified in only a handful of cases.

Geometric solutions of the Thomson problem for N = 4, 6, and 12 electrons are Platonic solids whose faces are all congruent equilateral triangles. Numerical solutions for N = 8 and 20 are not the regular convex polyhedral configurations of the remaining two Platonic solids, the cube and dodecahedron respectively. [7]

Generalizations

One can also ask for ground states of particles interacting with arbitrary potentials. To be mathematically precise, let f be a decreasing real-valued function, and define the energy functional

Traditionally, one considers also known as Riesz -kernels. For integrable Riesz kernels see the 1972 work of Landkof. [8] For non-integrable Riesz kernels, the Poppy-seed bagel theorem holds, see the 2004 work of Hardin and Saff. [9] Notable cases include: [10]

One may also consider configurations of N points on a sphere of higher dimension. See spherical design.

Solution algorithms

Several algorithms have been applied to this problem. The focus since the millennium has been on local optimization methods applied to the energy function, although random walks have made their appearance: [10]

While the objective is to minimize the global electrostatic potential energy of each N-electron case, several algorithmic starting cases are of interest.

Continuous spherical shell charge

The extreme upper energy limit of the Thomson Problem is given by
N
2
/
2
{\displaystyle N^{2}/2}
for a continuous shell charge followed by N(N - 1)/2, the energy associated with a random distribution of N electrons. Significantly lower energy of a given N-electron solution of the Thomson Problem with one charge at its origin is readily obtained by
U
(
N
)
+
N
{\displaystyle U(N)+N}
, where
U
(
N
)
{\displaystyle U(N)}
are solutions of the Thomson Problem. ThomsonProblem Related Energies LaFave.png
The extreme upper energy limit of the Thomson Problem is given by for a continuous shell charge followed by N(N − 1)/2, the energy associated with a random distribution of N electrons. Significantly lower energy of a given N-electron solution of the Thomson Problem with one charge at its origin is readily obtained by , where are solutions of the Thomson Problem.

The energy of a continuous spherical shell of charge distributed across its surface is given by

and is, in general, greater than the energy of every Thomson problem solution. Note: Here N is used as a continuous variable that represents the infinitely divisible charge, Q, distributed across the spherical shell. For example, a spherical shell of represents the uniform distribution of a single electron's charge, , across the entire shell.

Randomly distributed point charges

The expected global energy of a system of electrons distributed in a purely random manner across the surface of the sphere is given by

and is, in general, greater than the energy of every Thomson problem solution.

Here, N is a discrete variable that counts the number of electrons in the system. As well, .

Charge-centered distribution

For every Nth solution of the Thomson problem there is an th configuration that includes an electron at the origin of the sphere whose energy is simply the addition of N to the energy of the Nth solution. That is, [11]

Thus, if is known exactly, then is known exactly.

In general, is greater than , but is remarkably closer to each th Thomson solution than and . Therefore, the charge-centered distribution represents a smaller "energy gap" to cross to arrive at a solution of each Thomson problem than algorithms that begin with the other two charge configurations.

Relations to other scientific problems

The Thomson problem is a natural consequence of J. J. Thomson's plum pudding model in the absence of its uniform positive background charge. [12]

"No fact discovered about the atom can be trivial, nor fail to accelerate the progress of physical science, for the greater part of natural philosophy is the outcome of the structure and mechanism of the atom."

—Sir J. J. Thomson [13]

Though experimental evidence led to the abandonment of Thomson's plum pudding model as a complete atomic model, irregularities observed in numerical energy solutions of the Thomson problem have been found to correspond with electron shell-filling in naturally occurring atoms throughout the periodic table of elements. [14]

The Thomson problem also plays a role in the study of other physical models including multi-electron bubbles and the surface ordering of liquid metal drops confined in Paul traps.

The generalized Thomson problem arises, for example, in determining arrangements of protein subunits that comprise the shells of spherical viruses. The "particles" in this application are clusters of protein subunits arranged on a shell. Other realizations include regular arrangements of colloid particles in colloidosomes, proposed for encapsulation of active ingredients such as drugs, nutrients or living cells, fullerene patterns of carbon atoms, and VSEPR theory. An example with long-range logarithmic interactions is provided by Abrikosov vortices that form at low temperatures in a superconducting metal shell with a large monopole at its center.

Configurations of smallest known energy

In the following table[ citation needed ] is the number of points (charges) in a configuration, is the energy, the symmetry type is given in Schönflies notation (see Point groups in three dimensions), and are the positions of the charges. Most symmetry types require the vector sum of the positions (and thus the electric dipole moment) to be zero.

It is customary to also consider the polyhedron formed by the convex hull of the points. Thus, is the number of vertices where the given number of edges meet, is the total number of edges, is the number of triangular faces, is the number of quadrilateral faces, and is the smallest angle subtended by vectors associated with the nearest charge pair. Note that the edge lengths are generally not equal. Thus, except in the cases N = 2, 3, 4, 6, 12, and the geodesic polyhedra, the convex hull is only topologically equivalent to the figure listed in the last column. [15]

N Symmetry Equivalent polyhedron
20.50000000002180.000° digon
31.732050808032120.000° triangle
43.6742346140400000640109.471° tetrahedron
56.474691495023000096090.000° triangular dipyramid
69.9852813740060000128090.000° octahedron
714.45297741400520001510072.000° pentagonal dipyramid
819.6752878610080000168271.694° square antiprism
925.75998653100360002114069.190° triaugmented triangular prism
1032.71694946000280002416064.996° gyroelongated square dipyramid
1140.5964505100.0132196350281002718058.540° edge-contracted icosahedron
1249.165253058000120003020063.435° icosahedron
(geodesic sphere {3,5+}1,0)
1358.8532306120.00882036701102003322052.317°
1469.306363297000122003624052.866°gyroelongated hexagonal dipyramid
1580.670244114000123003926049.225°
1692.911655302000124004228048.936°
17106.050404829000125004530050.108°double-gyroelongated pentagonal dipyramid
18120.08446744700288004832047.534°
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20150.881568334000128005436046.093°
21167.6416223990.001406124011010005738044.321°
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31385.5308380630.003204712001219008758036.373°
32412.2612746510001220009060037.377° pentakis dodecahedron
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33440.2040574480.004356481001517109260133.700°
34468.9048532810001222009664033.273°
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25530264.4242512810001224300759506012.565°
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27234515.1932926810001226000810540012.335° geodesic sphere {3,5+}3,3
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According to a conjecture, if , p is the polyhedron formed by the convex hull of m points, q is the number of quadrilateral faces of p, then the solution for m electrons is f(m): . [16] [ clarification needed ]

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The classical electron radius is a combination of fundamental physical quantities that define a length scale for problems involving an electron interacting with electromagnetic radiation. It links the classical electrostatic self-interaction energy of a homogeneous charge distribution to the electron's relativistic mass-energy. According to modern understanding, the electron is a point particle with a point charge and no spatial extent. Nevertheless, it is useful to define a length that characterizes electron interactions in atomic-scale problems. The classical electron radius is given as

Jellium, also known as the uniform electron gas (UEG) or homogeneous electron gas (HEG), is a quantum mechanical model of interacting electrons in a solid where the positive charges are assumed to be uniformly distributed in space; the electron density is a uniform quantity as well in space. This model allows one to focus on the effects in solids that occur due to the quantum nature of electrons and their mutual repulsive interactions without explicit introduction of the atomic lattice and structure making up a real material. Jellium is often used in solid-state physics as a simple model of delocalized electrons in a metal, where it can qualitatively reproduce features of real metals such as screening, plasmons, Wigner crystallization and Friedel oscillations.

<span class="mw-page-title-main">Madelung constant</span> Constant in crystallography

The Madelung constant is used in determining the electrostatic potential of a single ion in a crystal by approximating the ions by point charges. It is named after Erwin Madelung, a German physicist.

In theoretical chemistry, Marcus theory is a theory originally developed by Rudolph A. Marcus, starting in 1956, to explain the rates of electron transfer reactions – the rate at which an electron can move or jump from one chemical species (called the electron donor) to another (called the electron acceptor). It was originally formulated to address outer sphere electron transfer reactions, in which the two chemical species only change in their charge with an electron jumping (e.g. the oxidation of an ion like Fe2+/Fe3+), but do not undergo large structural changes. It was extended to include inner sphere electron transfer contributions, in which a change of distances or geometry in the solvation or coordination shells of the two chemical species is taken into account (the Fe-O distances in Fe(H2O)2+ and Fe(H2O)3+ are different).

The Poisson–Boltzmann equation describes the distribution of the electric potential in solution in the direction normal to a charged surface. This distribution is important to determine how the electrostatic interactions will affect the molecules in solution. The Poisson–Boltzmann equation is derived via mean-field assumptions. From the Poisson–Boltzmann equation many other equations have been derived with a number of different assumptions.

Implicit solvation is a method to represent solvent as a continuous medium instead of individual “explicit” solvent molecules, most often used in molecular dynamics simulations and in other applications of molecular mechanics. The method is often applied to estimate free energy of solute-solvent interactions in structural and chemical processes, such as folding or conformational transitions of proteins, DNA, RNA, and polysaccharides, association of biological macromolecules with ligands, or transport of drugs across biological membranes.

<span class="mw-page-title-main">Water model</span> Aspect of computational chemistry

In computational chemistry, a water model is used to simulate and thermodynamically calculate water clusters, liquid water, and aqueous solutions with explicit solvent. The models are determined from quantum mechanics, molecular mechanics, experimental results, and these combinations. To imitate a specific nature of molecules, many types of models have been developed. In general, these can be classified by the following three points; (i) the number of interaction points called site, (ii) whether the model is rigid or flexible, (iii) whether the model includes polarization effects.

<span class="mw-page-title-main">Atomic nucleus</span> Core of an atom; composed of nucleons (protons and neutrons)

The atomic nucleus is the small, dense region consisting of protons and neutrons at the center of an atom, discovered in 1911 by Ernest Rutherford based on the 1909 Geiger–Marsden gold foil experiment. After the discovery of the neutron in 1932, models for a nucleus composed of protons and neutrons were quickly developed by Dmitri Ivanenko and Werner Heisenberg. An atom is composed of a positively charged nucleus, with a cloud of negatively charged electrons surrounding it, bound together by electrostatic force. Almost all of the mass of an atom is located in the nucleus, with a very small contribution from the electron cloud. Protons and neutrons are bound together to form a nucleus by the nuclear force.

Biology Monte Carlo methods (BioMOCA) have been developed at the University of Illinois at Urbana-Champaign to simulate ion transport in an electrolyte environment through ion channels or nano-pores embedded in membranes. It is a 3-D particle-based Monte Carlo simulator for analyzing and studying the ion transport problem in ion channel systems or similar nanopores in wet/biological environments. The system simulated consists of a protein forming an ion channel (or an artificial nanopores like a Carbon Nano Tube, CNT), with a membrane (i.e. lipid bilayer) that separates two ion baths on either side. BioMOCA is based on two methodologies, namely the Boltzmann transport Monte Carlo (BTMC) and particle-particle-particle-mesh (P3M). The first one uses Monte Carlo method to solve the Boltzmann equation, while the later splits the electrostatic forces into short-range and long-range components.

The linearized augmented-plane-wave method (LAPW) is an implementation of Kohn-Sham density functional theory (DFT) adapted to periodic materials. It typically goes along with the treatment of both valence and core electrons on the same footing in the context of DFT and the treatment of the full potential and charge density without any shape approximation. This is often referred to as the all-electron full-potential linearized augmented-plane-wave method (FLAPW). It does not rely on the pseudopotential approximation and employs a systematically extendable basis set. These features make it one of the most precise implementations of DFT, applicable to all crystalline materials, regardless of their chemical composition. It can be used as a reference for evaluating other approaches.

References

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  13. Sir J.J. Thomson, The Romanes Lecture, 1914 (The Atomic Theory)
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Notes