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Exploring the boundary between atoms and the continuum by computers: a personal history

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Abstract

In this admittedly personal account of the history of atomistic simulations of fluids (at the atomic or molecular level), I will focus on the competing efforts to reach the boundary between atoms and the continuum. The prevailing wisdom was that thermal fluctuations at the atomistic scale—both time (a few mean collision times) and space (a few atomic spacings)—would make the connection virtually impossible. This is just a part of the story about how molecular dynamics was able to connect to Navier–Stokes–Fourier hydrodynamics. Resistance in the theoretical physics community to computer simulations of equilibrium fluids at the atomistic scale was only exceeded by the even stiffer objections to non-equilibrium molecular-dynamics simulations: after the fifty years from Boltzmann to molecular dynamics, it took another quarter century to overcome the doubts.

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Fig. 1

Reproduced with kind permission of The European Physical Journal (EPJ) (Holian 2010)

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Notes

  1. A thorough review can be found in Mareschal and Holian (1992). The modern history of computational physics is presented in Battimelli et al. (2020).

  2. There are computers that are machines, but these human computers were women, in fact, much like the ones who later were the basis of the post-Sputnik NASA space program. Soon, we will speak of a very important woman, a programmer of computers, Maryann Mansigh.

  3. Stated in oversimplified terns, the moves in Metropolis Monte Carlo are made particle-by-particle, such that, if the new configuration’s potential energy change, \(\Delta E\), is the same or less, the move is allowed; if, however, the move increases potential energy, the move is allowed only if a random number between 0 and 1 is selected that is less than the Boltzmann probability factor, exp(\(-\Delta \textit{E}/{\textit{kT}}\)).

  4. See Gubernatis (2003). An earlier issue of Los Alamos Science, Special Issue, Stanislaw Ulam 1909-1984 (NUMBER 15, 1987, LA-UR-87-3600) includes a fascinating interview between Stanislaus Ulam, co-inventor (with Edward Teller) of the fusion bomb, and Gian-Carlo Rota, a brilliant Italian-American mathematician, with whom I shared an office in my early post-postdoc days at LASL (1974) and spent many stimulating hours talking about all manner of topics in science, math, and philosophy—including Robert Pirsig’s new book, Zen and the Art of Motorcycle Maintenance.

  5. The Leapfrog algorithm is so venerable in physics that Richard Feynman used it (without attribution) in his classic textbook to illustrate for Caltech freshmen the numerical solution of the harmonic oscillator (Eq. 9.16) and then went on to solve the problem of planetary motion around the Sun (Feynman et al. 1963). Higher-order difference schemes are legion, but have never been as robust and widely used as Leapfrog and its variants.

  6. In their classic book, a compendium of essential MC and MD statistical mechanics papers (Ciccotti et al. 1987), the editors included the Vineyard team’s paper and quoted the following autobiographical remarks of G.H. Vineyard: “Somewhere the idea came up that a computer might be applied to follow in more detail what actually goes on in radiation damage cascades. We got into quite an argument, some maintaining that it wasn’t possible to do this on a computer, others that it wasn’t necessary. John Fisher insisted that the job could be done well enough by hand, and was then goaded into promising to demonstrate. He went off to his room to work. Next morning he asked for a little more time, promising to send me the results as soon as he got home. After about two weeks, not having heard from him, I called and he admitted that he had given up. This stimulated me to think further about how to get a high-speed computer into the game...”

  7. The transport coefficients for a fluid characterize the diffusivity of mass, momentum, and energy: the diffusion coefficient describes the ease of moving individual masses around; viscosity describes the resistance to changes in fluid velocity (shear or bulk compression); and thermal conductivity describes heat flow (from hot regions to cold).

  8. Green–Kubo fluctuation-dissipation theory (Kubo 1957) is so named to include, for sake of priority, Mel Green, whose presentation (Green 1954) was so obscure and nomenclature so obtuse as to be overlooked by almost everyone in the fluids community. There is precedence in the history of physics: who (simultaneously) invented the calculus? Newton or Leibniz? We all certainly prefer, by far, to use the latter’s notation and nomenclature.

  9. I sometimes jokingly hold up both hands, with all ten fingers, and tell rolling-eyed, groaning students, “See! I do explosive shockwave computer simulations, and can still sit at a keyboard and type the old-fashioned way.”

  10. When I arrived at the Laboratory in October 1972, the LASL Director was Harold Agnew, who had flown in the bombing mission over Hiroshima and filmed the mushroom cloud as it rose; as Director, he was famous for walking the corridors of the old Eisenhower-functional Administration Building and poking his head in to find out what we “workers” were up to, regardless of our “status”—that is to say, he even wanted to hear from lowly postdocs. My first Theoretical Division Leader at LASL was the Canadian physicist from Manhattan Project days, Carson Mark, followed by Peter Carruthers, a brilliant Cornell particle theorist who hired me back into T-Division after my post-postdoc hiatus in the Engineering Department (doing theoretical analysis of the diffusion of fission products through graphite for reactor-safety modeling and then beginning to do radiation-damage MD), and later, George Bell, who was instrumental in setting up, with Walter Goad, the Human Genome Project, using Los Alamos computer power. One of the most prominent members of the Manhattan Project I had the honor to work with at LASL (post-postdoc) was John Manley, who had been J. Robert Oppenheimer’s chief assistant. John was incredibly gracious to me, a young theoretical staff member, helping me to navigate some very tricky Laboratory politics with experimentalists at Louis Rosen’s MESON accelerator facility.

  11. Topsy was a minor comic character in Harriet Beecher Stowe’s Uncle Tom’s Cabin, a black girl, battered by the institution of slavery, who grew up without any direction or plan, hence, “to grow like Topsy.”

  12. My Maxwell Demon NEMD results finally appeared in full detail in Erpenbeck and Wood (1977), where it was credited as “Holian et al. (in preparation)”; but of course, that paper never materialized. I had long since moved on.

  13. I received no kind words about my Maxwell Demon experiment from Berni (my thesis advisor) or from Bill Wood (my postdoc advisor). I found myself somewhere in between these two Kirkwood postdocs in temperament, namely, not as brilliantly intuitive as Uncle Berni, nor as mathematically rigorous as Bill Wood. I was truly grateful for Bill Hoover’s NEMD inspiration, Bill Ashurst’s kind help at a critical juncture in my study, and Joel Lebowitz’s kind praise at the Yeshiva meeting. Some twenty years after Yeshiva, Joel told me that he had recently heard Eddie Cohen tell him that he—Eddie—was the one who had invented my Maxwell Demon self-diffusion experiment. I was flabbergasted! I could only conclude that Eddie had re-invented history in his mind. Why else would a famous statistical mechanician like Eddie want to claim a lowly LASL postdoc’s one good idea?

  14. Rather than being a local function like particle velocity, the stress tensor for viscosity and heat flux for thermal conductivity are averages over the entire computational cell; therefore, their correlation functions already behave like the 1/N thermodynamic limit, so that extrapolating to the hydrodynamic limit in 3D is therefore much easier than for self-diffusion.

  15. Ashurst’s velocity rescaling (Ashurst 1974) is probably the most straightforward and practical “thermostat” ever invented, and believe me, there are more of those than a plethora. Anyway, Evans and Holian showed that thermostats appear not to matter very much in the calculation of transport properties in the non-equilibrium steady state (Evans and Holian 1985).

  16. Rigorous sinusoidal clamping of the temperature profile for thermal conduction was proposed much earlier, but was thought to display system-size convergence difficulties for less than 1000 particles (Ciccotti et al. 1978).

  17. An endnote: Berni Alder was a profound influence on my career. He was a strict editor, insisting that every paper should tell a story that is succinct and clear, emulating Albert Einstein’s style of prose. What this meant was—as with giving seminar lectures—a great deal of hard work had to go into preparing effective scientific communications. I confess that I had some “difficulty,” in particular, with a curmudgeon on the committee for my thesis defense. He was an older experimentalist with a missing digit (counter-exemplifying the wisdom of computer, over wet-lab, experiments), and had been, a few years earlier, a coauthor on a paper with Berni about solid surfaces. After a couple of tortuous hours of prelim exam that seemed to me like North Korean-style interrogation, I was told by the chair that I had to re-do the experience a couple months later. In the meantime, three times a week when Berni was at Berkeley, he spent two or three hours in the afternoon with me in his office in Joel Hildebrand’s chemistry laboratory, me practicing my thesis defense, and him grilling me on all kinds of physics topics that might possibly come up. It was then that Berni admonished me to know my subject well enough to be able to derive things “while riding on horseback through the desert.” Thanks to Berni’s tutelage, the second exam was successful—and in less than a half hour. Berni was always a model mentor, supportive of young students like me; in my case, helping me to get up after stumbling and dust myself off, as he smiled and said, “You’re OK? Good. Back to work!”.

  18. The double vortex—for \(d = 3\), a torus resembling a smoke ring from a cigar—grows from the original local volume per molecule to a diffusively growing volume of shearing fluid, whose extent in each of the d dimensions is the square-root of the product of kinematic viscosity times t, that is, the mean free path times square-root of t (in units of the mean collision time). Thus, the ratio of original to final vortex volume is proportional to \(t^{-d/2}\).

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Acknowledgements

This personal history arose during the 2020 pandemic isolation from a string of emails back and forth with Giovanni Ciccotti. Ever since the 1985 Varenna Conference he organized with Bill Hoover, he has been an intellectual guide, much in the style of a modern Galileo. He showed me the sights of his city, Rome, and how to cook his version of pasta fresca. I also want to thank Michel Mareschal and Ramon Ravelo for their collaboration on atomistics and hydrodynamics, providing inspiration going back many decades. They never failed to keep me from incoherence, despite our mutual enjoyment of champagne et huîtres.

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Correspondence to Brad Lee Holian.

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Dedicated to the memory of Berni Julian Alder (1925-2020)

Appendix: Correcting self-diffusion by the long-time tail

Appendix: Correcting self-diffusion by the long-time tail

To obtain the self-diffusion coefficient D in d dimensions, you need to integrate the velocity autocorrelation function (vacf) from zero to infinity in time. Out to a couple of mean collision times, the decay of the vacf is rapid (approximately exponential for hard disks in 2D or hard spheres in 3D), and its time-integral gives what is referred to as the Enskog-theory value, \(D_{E}\) Beyond that early time of a few collisions, the hydrodynamic long-time tailFootnote 18 of the vacf goes like \(t^{-d/2}\), until the leading sound wave from the double vortex (moving at c, the adiabatic bulk sound speed) reaches the edge of the periodic computational box of volume \(V = L^{d} \sim N\), at the sound-traversal time \(t_{L} = L/c\). Thereafter, the double vortex quickly decays exponentially, due to interaction with its periodic images, and the hydrodynamic correction to D in a finite system thus depends on \(t_{\mathrm {L}} \sim N^{1/d}\).

For hard spheres in 3D, the time-integral of \(t^{-3/2}\) approaches \(-t_{L}^{-1/2} \sim -(N^{1/3})^{-1/2} = -N^{-1/6}\). Thus, \(D =D_{\infty } - {\textit{const.}}\) \(N^{-1/6}\), which displays a finite hydrodynamic limit in 3D, as \(N \rightarrow \infty \).

On the other hand, for hard disks in 2D, the time-integral of \(t^{-1}\) approaches \(\hbox {ln}(t_{L})\sim \hbox {ln}(N^{1/2}) \sim \hbox {ln}(N)\). Thus, \(D = D_{E} + {\textit{const.}}\) ln(N), which shows that there is no bound (i.e., no hydrodynamic limit) in 2D, as \(N\rightarrow \infty \).

In 2D, Holian’s Maxwell Demon NEMD results for \(N = 168\), 1512, and 5822 hard disks (Erpenbeck and Wood 1977), can be fitted over the entire range of system sizes by nonlinear least squares,

$$\begin{aligned} D/D_{E} = 0.757 + 0.126 ~\hbox {ln}(N) , \end{aligned}$$

while in 3D, the Demon’s results for \(N = 108\), 500, and 4000 hard spheres (Erpenbeck and Wood 1977) can be fitted by nonlinear least-squares,

$$\begin{aligned} D/D_{E} = 1.44 - 0.580 \, N^{-1/6} . \end{aligned}$$

Alder et al.’s Green–Kubo equilibrium MD results for \(N = 108\) and 500 hard spheres (Alder et al. 1970a), can be fitted by \(D/D_{E} = 1.43 - 0.585\,N^{-1/6}\), which agrees very well indeed with NEMD.

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Holian, B.L. Exploring the boundary between atoms and the continuum by computers: a personal history. EPJ H 46, 2 (2021). https://doi.org/10.1140/epjh/s13129-021-00010-z

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