A wish. Looking for a couple of suitable post-docs. Covid-19 in India.

1. A wish…

I wish there were a neat, scholarly, account of the early development regarding the relativity theory. …

… There are tons of material on the topic, but not a single one seems to be to my liking…. I mean, even while rapidly browsing through so many of them, they all seem to fall short—rather, so awfully short. Reason: Most, if not all of them, seem intent on deifying Einstein, and / or, the primacy of maths over physics. [Did I cover all the eigenbases? May be not. So, let me add.] … The worst of them spend themselves out on promoting the idea that coming up with good but radical ideas in physics is all about getting lucky in some day-dreaming involving some mathematical ideas. 

OTOH, The “model” for the book which I have in mind here is something like what Prof. Malcolm Longair has done for QM; see his book: “Quantum concepts in physics: an alternative approach to the understanding of quantum mechanics.” [^].

… High time someone should have undertaken a similar effort. But unfortunately, it’s entirely lacking.

… The wish isn’t without purpose. The more I study the quantum mechanical spin, the more I realize the handicap which I have of not having already studied the relativity theory.

I can always postpone the fully consistent description, following my new approach, for the QM spin. [No one / no organization has ever sponsored my research. [Though, they all are hell bent on “following up” on me.]]

However, now that I have developed (what I believe to be) a good, basic, ontology for the QM phenomena, I have begun to see a promising pathway, at least from the viewpoint of a basic ontology, from a non-relativistic description of QM to a relativistic one—I mean the special relativistic one.


2. Looking for a couple of suitable post-docs…

Another possibility I am toying with, currently, is this:

Over a considerable period of time, say over a year or so, to build a series of Python/C++ scripts/programs that illustrate the classical EM in action, but following my new ontological ideas. These ideas are for the Maxwell-Lorentz EM, but I do anticipate that these would provide the easiest pathway to integrating the Special Relativity with the non-relativistic QM.

The trouble is: I will have to get into the FDTD algorithmics too, and I don’t have the time to do it. (In case you didn’t know, when it comes to EM, the best technique is FDTD.)

Wish I had a competent post-doc—actually two—working simultaneously with me! Right now!!

One could build the above-mentioned FDTD applets, but following the way I want them to be built.

The other one could work on “FEM-ization” of my FDM code (i.e., for the He atom, done with my new approach, and yet to be published). Once he is done, he could explore doing the same with FDTD (yes of course!), and compare and contrast the two. The FEM-ization of my FDM code won’t be very highly demanding, in the sense, people have done the finite elements formulation for the helium atom, and also have implemented it in code—decades ago… But of course, they did so following the mainstream QM. It would be a fun for the post-doc to implement it using the ideas I will be proposing—shortly.

Then, both could work on the ideas for the relativistic QM. … The pace of the work would depend on what they bring to the table, and how they perform.

Fallout? If you are a smart PhD in the concerned areas, I need not provide even a hint about it…


3. Status update on my QM research:

Currently, I am typing a set of notes on the topic of the quantum mechanical angular momentum, including the spin. For the time being, I am mostly following Dan Schroeder’s notes (which I mentioned in the post before the last, here [^]). Once done, I don’t mind uploading these notes—for proofreading by you the potential post-docs. [Who else?]

While typing these notes, it has become once again very clear to me—crystal clear, in fact—as to how my “theory” for the QM spin (following my new approach) falls short. … So short, in fact. … My “theory” doesn’t just look awfully arbitrary; it is so.

All in all, don’t expect the same kind of confidence from me for the spin-related aspects as for the spin-less ones. I mean, in the upcoming document on my new approach.


4. Back to the potential post-docs:

Exciting enough?

If yes, drop me a line. Especially, if you are working with Google / similar company. I gather they officially allow you some fraction of your official time for your own hobby projects too…


5. If you are someone young and enthusiastic, say from the Pune city and all (and in general, from India):

They have relaxed the curbs. However, I have a word of advice for you.

Don’t step out unless absolutely necessary, and if so doing, take all the precautions.

It’s just a matter of a few months now…

…BTW, I am also thinking whether the government shouldn’t relax the enforced gap of three months in between the first and the second dose for the jabs. … There are circumstantial matters which indicate that a gap in between two to three months might be ideal; that three months might be too long a period. (Actually, this matter had struck me right on the day that the Central Government increased the gap from 6 weeks to 12 weeks in one, single, move. …However, at that time, I had thought it prudent to wait and watch. Now, I think I can—nay, should—share my opinon. … I also have some other points about these matters, but these are not so important. I will sure mention these as and when it becomes necessary to do so.)


In the meanwhile, you all take care, and bye for now…


A song I like:

(Hindi) ज़िंदगी आ रहा हूँ मैं… (“zindagi aa rahaa hoon main…”)
Lyrics: Javed Akhtar
Music: Hridaynath Mangeshkar
Singer: Kishore Kumar

[

Credits happily listed in a random order. A good quality audio is here [^]. … Although I haven’t seen this movie, recently I watched the video for this song, and found that I enjoyed it too. A good quality video is here [^].

… I always loved this song, esp. the tune and the arrangement / orchestration. … And of course, Javed Akhtar’s awesome lyrics. … Well, yes, Kishore does sound, at places in this song, just a slight bit… and how shall I put it?… He doesn’t sound as if he were in his best frame of singing, here. His voice sounds a bit too “broad”, and perhaps heavy, and even a bit “tired” perhaps? as if he were straining a bit?…  Even then, of course, being Kishore, he does manage to pull a great job. [It’s just that, knowing Kishore, one wants to note this aside… I know, hair-splitting, it is. … Can’t help. … Sometimes.]

… [BTW, if you are young and dynamic and result-oriented etc.: The guy in this video is Sonam Kapoor’s dad. He used to be young. Once upon time. Me too. [Though I never ever had the hair-style he displays here. A lot of my class-mates did, mostly following The “Bachchan”. Not me. […Yeah, I know.]]

… All the same, all that you’ve to do now is to wait for just a few more months, that’s all… 2021 isn’t a meme on Twitter the way 2020 was. Nevertheless, in India, we have to wait. So, just listen to songs like this for just a wee bit more. … I can tell you, from experience: The scenery, esp. the Sahyaadri’s, does stay great also well until January / February next year. (And if you really love Sahyaadri’s, well, they are there, forever…)

…So there.]

…And if you are new to this song, see if you too like it…

Take care and bye for now…

]

 

The monsoon is here! Also, a fun aspect of QM.

1. Status update:

The monsoon is officially here, in the Pune city, and somehow, my spring-break [^] too gets over—finally!

(…There were no rains on the day that the Met. department officially announced the arrival of monsoon in the Pune city. The skies were, in fact, fairly clear on that day! … However, this year, everything is different. It was raining on almost every day in the month of May!)

Anyway, to come back to the reason for the permanent break in the spring-break which I had taken…

Looks like I have found a minimum working clarity regarding the phenomenon of the quantum mechanical spin. … I guess the level of clarity which I have now got is, perhaps, as good as what might be possible within the confines of a strictly non-relativistic analysis.

So… I can now with some placid satisfaction proceed to watching the remaining lectures of the MIT courses.

I will begin writing the document on my new approach a little later. I now expect to be able to put it out by 15th July 2021, perhaps earlier. [Err… Any suggestions for the (Hindi) “muhurat”s for either / both?]

…But yes, the quantum spin turned out to be a tricky topic to get right. Very tricky.

…But then, that way, all of QM is tricky. … Here, let me highlight just one aspect that’s especially fun to think through…


2. One fun aspect of QM:

The Schrodinger equation for a one-particle system is given as:

i\hbar \dfrac{\partial}{\partial t} \Psi(x,t) = \hat{H} \Psi(x,t),

where the notation is standard; in particular, i is the imaginary unit, and \hat{H} is the system Hamiltonian operator.

The observation I have in mind is the following:

Express the complex-valued function \Psi(x,t) explicitly as the sum of its real and imaginary parts:

\Psi(x,t) = \Psi_R(x,t) + i \Psi_I(x,t),

where \Psi_R \in \mathcal{R}, and do note, also \Psi_I \in \mathcal{R}, that is, both are real-valued functions. (In contrast, the original \Psi(x,t) \in \mathcal{C}; it’s a complex-valued function.)

Substitute the preceding expression into the Schrodinger equation, collect the real- and imaginary- terms, and obtain a system of two coupled equations:

\hbar \dfrac{\partial}{\partial t} \Psi_R(x,t) = \hat{H} \Psi_I(x,t)
and
- \hbar \dfrac{\partial}{\partial t} \Psi_I(x,t) = \hat{H} \Psi_R(x,t).

The preceding system of two equations, when taken together, is fully equivalent to the single complex-valued Schrodinger’s equation noted in the beginning. The emphasis is on the phrase: “fully equivalent”. Yes. The equivalence is mathematically valid—fully!

Now, notice that this latter system of equations has no imaginary unit i appearing in it. In other words, we are dealing with pure real numbers here.

Magic?

… Ummm, not really. Did you notice the negative sign stuck on the left hand-side of the second equation? That negative sign, together with the fact that the in the first equation, you have the real-part \Psi_R on the left hand-side but the imaginary part \Psi_I on the right hand-side, and vice versa for the second equation, pulls the necessary trick.

This way of looking at the Schrodinger equation is sometimes helpful in the computational modeling work, in particular, while simulating the time evolution, i.e., the transients. (However, it’s not so directly useful when it comes to modeling the stationary states.) For a good explanation of this viewpoint, see, e.g., James Nagel’s SciPy Cookbook write-up and Python code here [^]. The link to his accompanying PDF document (containing the explanation) is given right in the write-up. He also has an easy-to-follow peer-reviewed paper on the topic; see here [^]. I had run into this work many years ago. BTW, there is another paper dealing with the same idea, here [^]. I have known it for a long time too. …Some time recently, I recalled them both.

Now, what is so tricky about it, you ask? Well, here is a homework for you:

Homework: Compare and contrast the aforementioned, purely real-valued, formulation of quantum mechanics with the viewpoint expressed in a recent Quanta Mag article, here [^]. Also include this StackExchange thread [^] in your analysis.

Happy thinking!


OK, take care, and bye for now…


A song I like:

[TBD]

Finding a cozy n comfy enough a spot…

Update on 2021.02.02:

I have made a couple of inline updates in the sections 5. and 7. below.


I have already begun cleaning up and reorganizing the code, and writing the boring document. The work so far has come along pretty well. I have by now achieved a satisfactory level of consistency in the numerical results for the hydrogen atom in a 3D box.

As indicated in my last post here, I had found that it’s more useful to focus on the cell-side of the mesh rather than on the physical size of the box or the number of nodes per side of the cube.

Now, given below are some of the details of certain further, systematic, trials which I conducted, in order to arrive at optimum ranges for numerical parameters.

Since the analytical solution is available only for the hydrogenic atoms (i.e. systems with a positively charged nucleus and just one electron, e.g. the hydrogen atom and the He+ ion), these systematic studies were conducted only for them.

If you came here expecting that I might have something to say about the reproducibility for the helium atom, then well, you will have to wait for some 2–3 weeks. The nature of the issues themselves is like that. You can’t hurry things like these too much, as the studies below sure bring out.

So, anyway, here are the highlights of the systematic studies I conducted and some of the representative results.

All the results reported in this post are in the atomic units.


1. Finitization policy to replace the singularity of the Coulomb field:

In my last post here, I had mentioned that in FDM, we have to use a finite value in place of the -\infty at the nucleus. As a necessary consequence, we have to adopt some policy for this finitization.

While conducting my studies, now I found that it is better to frame this policy not in terms of a chosen fraction of the cell-side, but in terms of a certain relevant datum and a multiplying factor. The better procedure is this:

Whatever be the degree of mesh refinement, having constructed the mesh, calculate the always-finite PE value at the FDM node right next to the singularity. Then, multiply this PE value by a certain factor, and use it in place of the theoretically -\infty value at the singular node. Let’s give a name to this multiplying factor; let’s call it the Coulomb Field’s Singularity Finitization Factor (“CFSF” for short).

Notice that using this terminology, a CFSF value of 2.0 turns out to be exactly the same as using the half cell-side rule. However, framing the finitization policy in terms of the CFSF factor has the advantage that it makes it easier to compare the differences in the relative sharpness of the potential well at different mesh-refinement levels.

OK.

I then found that while using FDM, the eigenvalue solver is very sensitive to even small variations to the value of CFSF.

If you use a CFSF value of 1.8, then it turns out that the PE well does not go down enough in the neighbourhood of the singularity, and therefore, the reported ground-state eigenvalues can easily go to about -0.45, -0.2, or even worse. Refining the mesh doesn’t help—within the domain and mesh sizes which are both practicable on my laptop and relevant for the H and He atom modelling. Note, the analytical solution is: -0.5, exactly.

Conclusion: Using even a slightly lower CFSF spoils the results.

OTOH, if you use a CFSF of 2.2 to 2.5, then the ground-state energy can go lower than the exact value of -0.5. Now, this is a sure-shot indication that your numerical modelling has gone wrong.

In general, with FDM, you would expect that with mesh refinement, the convergence in the energy values would be not just monotonic but also one-sided, and also that the convergence would occur from “above” (because the energy values here are negative). In other words, if my understanding of the theory of numerical analysis is correct, then a properly done (meaningful) numerical simulation cannot produce energies below the analytical solution of -0.5.

So, clearly, using a CFSF value even slightly greater than 2.0 is bad for the health of the numerical simulations.

In the earlier trials reported in the last post, I had simply guessed that the value of 2.0 might be good enough for my initial trials. Now it turns out that my computational modeller’s intuition was pretty much on target—or at least, that I was plain lucky! The CFSF value of 2.0 indeed happens to be quite the best value to choose, given the rest of the parameters like the cell-side, the domain size, and the rest of the details of this problem (viz., the strength of the Coulomb singularity, the nature of the Schrodinger equation, the use of uniform and structured meshes, the FDM discretization, etc.).


2. Simple-minded mesh refinement doesn’t produce consistent results:

Suppose you keep the domain size fixed at, say, 20.0, and vary the mesh refinement levels.

Now, your naive expectation might be that as you refine the mesh by increasing the number of nodes per side of the cube, you should get more and more accurate results. That’s our usual experience with problems like diffusion in continua, and even for problems like convection in fluids.

However, the category of the QM problems is different! Here, we have an eigenvalue problem that must be solved with a singular potential field. The naive expectations built on simple problems like the Poisson-Laplace equation or the diffusion equation, go for a toss. Harmonic analysis might still apply in some form (frankly I don’t even know if it does!), but the singularity sure plays tricks!

This is an ugly fact, and frankly, I had not foreseen it. But it’s there. I had to keep myself reminding of the different nature of the eigenvalue problem together with the singular fields.

As you refine the mesh too much, then the absolute value of the PE at a node right next to the point of singularity increases without bound! This fact mandates that the finite value we (more or less) arbitrarily chose to use in place of the actually infinite value for the singular point, has itself to increase further too.

But, for some reasons not known to me (but which by now do feel vaguely reasonable!) the eigenvalue solver begins to experience difficulties with such increases in the absolute value of the PE value at the singularity. Roughly, the trouble begins to happen as the minimum potential energy (at the singular node) goes below -20 or so. In fact, I even found that a highly refined mesh might actually report a positive value for the ground-state energy—no bonding but, on the contrary, a repulsion of the electron!


3. Wavefunction fields are important in my new approach, but they don’t always converge to the analytical solution very well!:

With a reasonable level of mesh refinement, the ground-state energy does monotonically approach the exact figure of -0.5 However, I’ve found that a convergence in energy is not necessarily accompanied also by a good convergence trend in the absolute values of the wavefunction!

In the H-atom, for the ground-state analytical solution, the absolute value of the wavefunction has its maximum right at the nucleus; the wavefunction field forms a cusp at the nucleus, in fact. The analytical value for \psi(x)-max goes like: 0.564189584\dots. (That’s because in the atomic units, the Bohr radius a_0 is chosen to be exactly equal to 1, and so, at r = 0, the ground-state wavefunction for the H-atom becomes \psi(x_{\text{at nucleus}}) = 1/\sqrt{\pi}.)

Now the trouble I found was this:

With mesh refinement, even as the energy is nicely converging to something like -0.4938884 (against -0.5), the \psi-max might still be lingering around a lower figure like 0.516189. The \psi-max values converge more slowly, and their convergence shows opposite trend!

For relatively coarse meshes (i.e. high \Delta x of the FDM mesh), the \psi-max value is actually way much higher than the analytical solution; it even becomes as bad as 3.276834 or 1.393707. As you refine the mesh, they do begin to fall down and approach the analytical solution.

However, with further mesh refinement, the \psi-max values continue to fall down! They cross the analytical solution level of 0.564189584 too, and still continue to fall further! And, this behaviour occurs even as energy result is still approaching the exact solution in a nice-and-expected monotonic manner.

So, the trouble is: Using the right mesh size is actually a trade-off! You have to sacrifice some convergence on the energy number, so as to have a good (reliable) value for the \psi-max measure.

The trouble doesn’t stop there; see the next section.


4. Energies for the excited-states don’t always come out very well:

With appropriately high levels of mesh-refinement, the ground-state energy might be showing good convergence trends. Even the \psi-max values might be good enough (like 0.52 or so). But the energy and/or \psi-max for the first excited state still easily give trouble.

The energy for the first excited state for the hydrogen atom is, by analytical solution, -0.125, exactly.

The numerical values, when the simulation is working right, could be like -0.11, or even better, say -0.123, or thereabout. But that happens only when the mesh is of the intermediate refinement (the cell-side is neither too small nor too large).

However, with a more refined mesh (smaller cell-sides), the PE well can remain more or less rightly shaped for the ground-state energy, but it can still become too deep for the first-excited state energy! The first excited state energy can suddenly get degraded to a value like -0.04471003.

Indeed, there seems to be some kind of a numerical compensation going on in between the \psi-max values and the energy values, especially for the first-excited state energies. The ground-state energies remain much better, in relative terms. (If the mesh refinement is very high, even the ground-state energy goes off the track to something like -0.2692952 or even positive values. That’s what I meant by “appropriately” high levels of mesh refinement.)

I didn’t compare the numerical results with the analytical solutions for energies or \psi-max values for second-excited states or higher. Computation of the bonding energy makes reference only to the ground state, and so, I stopped my exploration of this side of the FDM + eigenvalue solver behaviour at this stage.


5. Atomic sizes reported by the numerical modeling show very good trends:

Another important consideration in my new approach has to do with the atomic radius of the atoms being modelled (hydrogen and helium).

After optimizing the mesh refinement (i.e., effectively, the cell-side), I conducted a series of numerical trials using different domain sizes (from 7.5 through 40.0 ), and implemented a rough-and-ready code to estimate the following measure:

The side of the nucleus-centered sub-cube in which roughly 95 \% (or 99 \%) of the probability cloud is contained.

This size can be taken as a good measure for the atomic size.

In the above working definition, I say roughly 95 \%, because I didn’t care to interpolate the wavefunction fields in between their nodal values. What this means is that the side of the sub-cube effectively changes only in the integer steps, and therefore, the percentage of the sub-cube contained may not be exactly 95 \%; it could be 97.5 \% for one domain size, and 95.3 \% for another domain size, just to pick up some numbers.

But even while using this rough and ready measure (and implementation), I found that the results were quite meaningfully consistent.

But why conduct these trials?

Well, realize that (1) the simulation box has a finite size, and (2) the Dirichlet conditions are being imposed at all the boundary nodes. Given these two constraints, the solution is going to show boundary-/edge-effects, i.e., the solution is going to depend on the domain size.

Now, in my approach, the spread of the probability cloud enters the calculations in a crucial manner. Numerically “extracting” the size of the simulated atom was, therefore, an important part of optimizing the simulations.

The expected behaviour of the above mentioned “size effect” was that as the domain size increases, the calculated atomic size, too, should increase. The question was: Were these differences in the numerically determined sizes important enough? did they vary too much? if yes, how much? The following is what I found:

First, I fixed the domain size (cube side) at 10.0, and varied the mesh refinement (from roughly 41 nodes per side to 121 and 131). I found that the calculated atomic sizes for the hydrogen atom varied but in a relatively small range—which was a big and happy surprise to me. The calculated size went from 5.60 while using a coarse mesh (requiring eigenvalue computation time of about 10 seconds) to a value like 5.25 for an intermediate refinement of the mesh (exe. time 2 min. 32 seconds i.e. 152 seconds), to 5.23 for as fine a mesh as my machine can handle (131 \times 131 \times 131, which required an exe. time of about 20 minutes i.e. 1200 seconds, for each eigenvalue computation call). Remember, all these results were for a domain size of 10.0.

Next, I changed the domain cube side to 15.0, and repeated the trials, for various levels of mesh refinements. Then, ditto, for the domain side of 20.0 and 40.0.

Collecting the results together:

  • 10.0
    • coarse: 5.60
    • intermediate: 5.25
    • fine: 5.23
  • 15.0
    • coarse: 6.0
    • intermediate: 5.62
  • 20.0
    • coarse: 6.40
    • intermediate: 5.50
    • fine: 5.67
  • 40.0
    • coarse: 4.0
    • intermediate: 5.5
    • fine: 6.0
    • very fine: 6.15

You might be expecting very clear-cut trends and it’s not the case here. However, remember, due to the trickiness of the eigenvalue solver in the presence of a “singular” PE well, not to mention the roughness of the size-estimation procedure (only integer-sized sub-cubes considered, and no interpolations of \psi to internodal values), a monotonic sort of behaviour is simply not to be expected here.

Indeed, if you ask me, these are pretty good trends, even if they are only for the hydrogen atom.

Note, for the helium atom, my new approach would require giving eigenvalue computation calls thousands of times. So, at least on this count of atomic radius computation, the fact that even the coarse or mid-level mesh refinement results didn’t vary much (they were in the range of 5.25 to 5.6) was very good. Meaning, I don’t have to sacrifice a lot of accuracy due to this one factor taken by itself.

For comparison, the atomic size (diameter) for the hydrogen atom is given in the literature (Wiki), when translated into atomic units, comes out variously as: (1) 0.94486306 using some “empirical” curve-fitting to some indirect properties of gases; (2) 4.5353427 while using the van der Waal criterion, and (3) 2.0031097 using “calculations” (whose basis or criteria I do not know in detail).

Realize, the van der Waal measure is closest to the criterion used by me above. Also, it is only expected that when using FDM, due to the numerical approximations, just the way the FDM ground-state energy values should come out algebraically greater (they do, say -0.49 vs. the exact datum of -0.5), the FDM \psi-max measure should come out smaller (it does, say 0.52 vs. the analytical solution of \approx 0.56), similarly, for the same reasons, the rough-and-ready estimated atomic size should come out as greater (it does, say 5.25 to 5.67 as the domain size increases from 10.0 to 40.0, the. van der Waal value being 4.54 ).

Inline update on 2021.02.02 19:26 IST: After the publication of this post, I compared the above-mentioned results with the analytical solution. I now find that the sizes of the sub-cubes found using FDM, and using the analytical solution for the hydrogen atom, come out as identical!  This is a very happy news. In other words, making comparisons with the van der Waal size and the other measure was not so relevant anyway; I should have compared the atomic sizes (found using the sub-cubes method) with the best datum, which is, the analytical solution! To put this finding in some perspective, realize that the FDM-computed wavefunctions still do differ a good deal from the analytical solution, but the volume integral for an easy measure like 95 \% does turn out be the same. The following proviso’s apply for this finding: The good match between the analytical solution and the FDM solution are valid only for (i) the range of the domain sizes considered here (roughly, 10 to 40), not for the smaller box sizes (though the two solution would match even better for bigger boxes), and (ii) only when using the Simpson procedure for numerically evaluating the volume integrals. I might as well also note that the Simpson procedure is, relatively, pretty crude. As the sizes of the sub-cubes go on increasing, the Simpson procedure can give volume integrals in excess of 1.0 for both the FDM and the analytical solutions. Inline update over.

These results are important because now I can safely use even a small sized domain like a 10.0-side cube, which implies that I can use a relatively crude mesh of just 51 nodes per side too—which means a sufficiently small run-time for each eigenvalue function call. Even then, I would still remain within a fairly good range on all the important parameters.

Of course, it is already known with certainty that the accuracy for the bonding energy for the helium atom is thereby going to get affected adversely. The accuracy will suffer, but the numerical results would be on the basis of a sweet-zone of all the numerical parameters of relevance—when validated against hydrogen atom. So, the numerical results, even for the helium atom, should have greater reliability.

Considerations like conformance to expected behaviour in convergence, stability, and reliability are far more important considerations in numerical work of this nature. As to sheer accuracy itself, see the next section too.


6. Putting the above results in perspective:

All in all, for the convergence behaviour for this problem (eigenvalue-eigenvector with singular potentials) there are no easy answers. Not even for just the hydrogen atom. There are trade-offs to be made.

However, for computation of bonding energy using my new approach, it’s OK even if a good trade-off could be reached only for the ground-state.

On this count, my recent numerical experimentation seems to suggest that using a mesh cell-side of 0.2 or 0.25 should give the most consistent results across a range of physical domain sizes (from 7.5 through 30.0 ). The atomic size extracted from the simulations also show good behaviour.

Yes, all these results are only for the hydrogen atom. But it was important that I understand the solver behaviour well enough. It’s this understanding which will come in handy while optimizing for the helium atom—which will be my next step on the simulation side.

The trends for the hydrogen atom would be used in judging the results for the the bonding energy for the helium atom.


7. The discussed “optimization” of the numerical parameters is strictly for my laptop:

Notice, if I were employed in a Western university or even at an IIT (or in an Indian government/private research lab), I would have easy access to supercomputers. In that case, much of this study wouldn’t be so relevant.

The studies regarding the atomic size determination, in particular, would still be necessary, but the results are quite stable there. And it is these results which tell me that, had I have access to powerful computational resources, I could have used larger boxes (which would minimize the edge-/size- effect due to the finite size of the box), and I could have used much, much bigger meshes, while still maintaining the all-important mesh cell-side parameter near the sweet spot of about 0.20 to 0.25. So, yes, optimization would still be required. But I would be doing it at a different level, and much faster. And, with much better accuracy levels to report for the helium atom calculations.

Inline update on 2021.02.02 19:36 IST: Addendum: I didn’t write this part very well, and a misleading statement crept in. The point is this: If my computational resources allow me to use very big meshes, and then I would also explore cell-sides that are smaller than the sweet-spot of 0.20 to 0.25. I’ve been having a hunch that the eigenvalue solver would still not show up the kind of degeneracy due to very deep PE well, provided that the physical domain size also were to be made much bigger. In short, if very big meshes are permissible, then there is a possibility that another sweet-spot at smaller cell-sizes could be reached too. There is nothing physical about the 0.20 to 0.25 range alone, that’s the point. Inline update over.

The specifics of the study mentioned in this post was largely chosen keeping in the mind the constraint of working within the limits of my laptop.

Whatever accuracy levels I do eventually end up getting for the helium atom using my laptop, I’ll be using it not just for my planned document but also for my very first arXiv-/journal- paper. The reader of the paper would, then, have to make a mental note that my machine could only support a mesh size of only 131 nodes at its highest end. For FDM computations, that still is a very crude mesh.

And, indeed, for the reasons given above, I would in fact be reporting the helium atom results for meshes in between 41 to 81 nodes per side of the cube, not even 131 nodes. All the rest of the choices of the parameters were made keeping in view this limitation.


8. “When do you plan to ship the code?”

I should be uploading the code eventually. It may not be possible to upload the “client-side” scripts for all the trials reported here (simply because once you upload some code, the responsibility to maintain it comes too!). However, exactly the same “server”- or “backend”- side code will sure be distributed, in its entirety. I will also be giving some indication of the kind of code-snippets I used in order to implement the above mentioned studies. So, all in all, it should be possible for you to conduct the same/similar trials and verify the above given trends.

I plan to clean up and revise the code for the hydrogen atom a bit further, finalize it, and upload it to my GitHub account within, say, a week’s time. The cleaned up and revised version of the helium-atom code will take much longer, may be 3–4 weeks. But notice, the helium-atom code would be giving calls to exactly the same library as that for the hydrogen atom.

All in all, you should have a fairly good amount of time to go through the code for the 3D boxes (something which I have never uploaded so far), run it, run the above kind of studies on the solid grounds of the hydrogen atom, and perhaps even spot bugs or suggest better alternatives to me. The code for the helium atom would arrive by the time you run through this gamut of activities.

So, hold on just a while, may be just a week or even less, for the first code to be put on the GitHub.


On another note, I’ve almost completed compiling a document on the various set of statements for the postulates of QM. I should be uploading it soon too.


OK, so look for an announcement here and on my Twitter thread, regarding the shipping of the basic code library and the user-script for the hydrogen atom, say, within a week’s time. (And remember, this all comes to you without any charge to you! (For that matter, I am not even in any day-job.))


A song I like:

(Hindi) दिल कहे रुक जा रे रुक जा (“dil kahe ruk jaa re ruk jaa”)
Lyrics: Sahir Ludhiyanvi
Music: Laxmikant-Pyarelal
Singer: Mohammed Rafi

[Another favourite right from my high-school days… A good quality audio is here [^]. Many would like the video too. A good quality video is here [^], but the aspect-ratio has gone awry, as usual! ]


History:
— 2020.01.30 17:09 IST: First published.
— 2021.02.02 20:04 IST: Inline updates to sections 5. and 7 completed. Also corrected a couple of typos and streamlined just a few sentences. Now leaving this post in whatever shape it is in.