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.

 

Now I am become Bohmianism

1. About the title of this post:

Just before this Diwali, I had tweeted that I had made a resolution. The tweets went like this:

Let me note the text portions of these tweets (just in case I delete these some time later or so).

3:29 PM 13 Nov. 2020:

This year, Pune directly went from the monsoon air to the Diwali air. We seem to have tunnelled through the October heat!

3:55 PM, 13 Nov. 2020:

#Deepavali #Diwali #deepavali2020 #Diwali2020

[Diya lamp emoji, 3 times]

This is the *third* straight Diwali that I go jobless.

3:56 PM, 13 Nov. 2020:

My Diwali Resolution:

“Be a Bohmian (https://www.google.com/search?q=Bohmian+mechanics)

[Yes, there are going to be the usual New Year’s Resolutions according to the Western calender too!]

Alright.

We will come to the “tunnelling” part later. Also, the tweet related to my jobless-ness. [If the Indian IT industry has any sense of shame left at all, they would have prevented this circumstance. But more on this, too, later.]

For the time being, I want to focus on the last tweet, and say that, accordingly:

Now I am become Bohmianism.

As to the quaint grammar used in the expression, first consult this Wired article [^], also the Q&A at the Quora [^].

As to why I use “Bohmianism” instead of “a Bohmian”: Well, to know that, you have to understand Sanskrit. If you do, then refer to the Gita, Chapter 11, verse 32, the compound phrase “कालोऽस्मि” (“kaalo smi”). I just tried to keep a similar grammatical form. … But let me hasten to add that I am not a Sanskrit expert, and so, going wrong is always a possibility. However, I also think that here I have not.

Hence the title of this post.

Now, going over to the Bohmianism i.e. the Bohmian mechanics proper…


2. Material on the Bohmian mechanics (BM):

The following is a partial list of papers and other material on BM that I have downloaded. I am giving you the list in a roughly chronological order. However, my reading isn’t going to be in any particular order. I have not read them all yet. In fact, I’ve just got going with some them, as of now.

Also note, I expect that

  • Some of this material might have become outdated by now
  • I may run into some other related topics as my studies progress

Alright. On to the list…


2.1 Student theses:

Antony Valentini (1992) “On the pilot-wave theory of classical, quantum and subquantum physics,” Ph.D. Thesis, International School for Advanced Studies, Trieste

Caroline Colijn (2003) “The de Broglie-Bohm causal interpretation of quantum mechanics and its application to some simple systems,” Ph.D. Thesis, University of Waterloo.

Paulo Machado (2007) “Computational approach to Bohm’s quantum mechanics,” Ph.D. Thesis, McMaster University

Jeff Timko (2007) “Bohmian trajectories of the two-electron helium atom,” Master’s Thesis, University of Waterloo

Leopold Kellers (2017) “Making use of quantum trajectories for numerical purposes,” Master’s Thesis, Technische Universität München


2.2. Code:

Dane Odekirk (2012) “Python calculations of Bohmian trajectories,” GitHub, 12 December 2012. https://github.com/daneodekirk/bohm


2.3. Papers:

C. Philippidis, C. Dewdney and B. J. Hiley (1978) “Quantum interference and the quantum potential,” https://www.researchgate.net/publication/225228072

Berthold-Georg Englert, Marlan O. Scully, Georg Sussmann and Herbert Walther (1992) “Surrealistic Bohm trajectories,” Z. Naturforsch. 47 a, 1175–1186.

Robert E. Wyatt and Eric R. Bittner (2003) “Quantum mechanics with trajectories: quantum trajectories and adaptive grids,” arXiv:quant-phy/0302088v1 11 Feb 2003

Roderich Tumulka (2004) “Understanding Bohmian mechanics: A dialogue,” Am. J. Phys., vol. 72, no. 9, September 2004, pp. 1220–1226.

D.-A. Deckert, D. Dürr, P. Pickl (2007) “Quantum dynamics with Bohmian trajectories,” arXiv:quant-phy/0701190v2 13 May 2007

Guido Bacciiagaluppi and Antony Valentini (2009) “Quantum theory at the crossroads: Reconsidering the 1927 Solvay conference,” Cambridge UP, ISBN: 9780521814218 arXiv:quant-ph/0609184v2 24 Oct 2009 [Note: This is actually a book.]

M. D. Towler and N. J. Russell (2011) “Timescales for dynamical relaxation to the Born rule,” arXiv:1103.1589v2 [quant-ph] 27 Sep 2011

Michael Esfeld, Dustin Lazarovici, Mario Hubert, Detlef Dürr (2012) “The ontology of Bohmian mechanics,” preprint, British Journal for the Philosophy of Science

Travis Norsen (2013) “The pilot-wave perspective on quantum scattering and tunneling,” m. J. Phys., vol. 81, no. 4, April 2013, pp. 258–266. arXiv:1210.7265v2 [quant-ph] 9 Jan 2013

Travis Norsen (2013) “The pilot-wave perspective on spin,” arXiv:1305.1280v2 [quant-ph] 10 Sep 2013

Kurt Jung (2013) “Is the de Broglie-Bohm interpretation of quantum mechanics really plausible?,” Journal of Physics: Conference Series 442 (2013) 012060 doi:10.1088/1742-6596/442/1/012060

Samuel Colin and Antony Valentini (2014) “Instability of quantum equilibrium in Bohm’s dynamics,” Proc. R. Soc. A 470: 20140288. http://dx.doi.org/10.1098/rspa.2014.0288

W. B. Hodge, S. V. Migirditch and W. C. Kerr (2014) “Electron spin and probability current density in quantum mechanics,” Am. J. Phys., vol. 82, no. 7, July 2014, pp. 681–690

B. Zwiebach (2016) “Lecture 6,” Course Notes for MIT 8.04 Quantum Physics, Spring 2016.

Basil J. Hiley and Peter Van Reeth (2018) “Quantum trajectories: real or surreal?,” Entropy vol. 20, pp. 353 doi:10.3390/e20050353

Oliver Passon (2018) “On a common misconception regarding the de Broglie-Bohm theory,” Entropy vol. 20, no. 440. doi:10.3390/e20060440


2.4. Advanced papers:

Asher Yahalom (2018) “The fluid dynamics of spin,” Molecular Physics, April 2018, doi: 10.1080/00268976.2018.1457808. https://www.researchgate.net/publication/324512014, arXiv:1802:09331v1 [physics.flu-dyn] 3 Feb 2018

Siddhant Das and Detlef Dürr (2019) “Arrival time distributions of spin-1/2 particles,” Scientific Reports, https://doi.org/10.1038/s41598-018-38261-4

Siddhant Das, Markus Nöth, and Detlef Dür (2019) “Exotic Bohmian arrival times of spin-1/2 particles I—An analytical treatment,” arXiv:1901.08672v1 [quant-ph] 24 Jan 2019


2.5. Nonlinearity in the Bohmian mechanics:

To my surprise, I found that a form of non-linearity has been found to come up in the Bohmian mechanics too. I am sure it must have come as a surprise to many others too. [I will comment on this aspect quite some time later. For the time being, let me list some of the papers/presentations I’ve found so far.]

Sheldon Goldstein (1999) “Absence of chaos in Bohmian dynamics,” arXiv:quant-ph/9901005v1 6 Jan 1999

S. Sengupta, A. Poddar and P. K. Chattaraj (2000) “Quantum manifestations of the classical chaos in an undamped Duffing oscillator in presence of an external field: A quantum theory of motion study,” Indian Journal of Chemistry, vol. 39A, Jan–March 2000, pp. 316–322

A. Benseny, G. Albareda, A. S. Sanz, J. Mompart, and X. Oriols (2014) “Applied Bohmian mechanics,” arXiv:1406.3151v1 [quant-ph] 12 Jun 2014

Athanasios C. Tzemos (2016) “The mechanism of chaos in 3-D Bohmian trajectories,” Poster Presentation, https://www.researchgate.net/publication/305317081

Athanasios C. Tzemos (2018) “3-d Bohmian chaos: a short review,” Presentation Slides, RCAAM, Academy Of Athens

Athanasios C. Tzemos (2019) “Quantum entanglement and Bohmian Mechanics,” Presentation Slides 17 July 2019, RCAAM of the Academy of Athens

Klaus von Bloh (2020) “Bohm trajectories for the noncentral Hartmann potential,” Wolfram demonstration projects, https://www.researchgate.net/publication/344171771 (August 2020)

G. Contopoulos and A. C. Tzemos (2020) “Chaos in Bohmian quantum mechanics: a short review,” arXiv:2009.05867v1 [quant-ph] 12 Sep 2020


3. What happens to my new approach?

It was only yesterday that a neat thing struck me. Pending verification via simulations, it has the potential to finally bring together almost all of my research on the spinless particles. I’ve noted this insight in the hand-written journal (i.e. research notebook) that I maintain. I will be developing this idea further too. After all, Bohmians do study mainstream quantum mechanics and other interpretations, don’t they?

Due to the RSI, the simulations, however, will have to wait further. (The status is more or less the same. If I type for 2–3 hours, it’s easily possible that I can’t do much anything for the next 2–3 days.)

OK. Take care and bye for now.


A song I like:

(Hindi) देखा ना हाय रे सोचा ना (“dekhaa naa haay re sochaa naa”)
Singer: Kishore Kumar
Music: R. D. Burman
Lyrics: Rajinder Krishan

[Another song I used to love in my high-school days—who wouldn’t? … And, of course, I still do! A good quality audio I found is here [^]. I had not watched this movie until about a decade ago, on a CD (or may be on the TV). I’ve forgotten the movie by now. I don’t mind giving you the link for the video of this song; see here [^]. (In any case, it’s at least 3 orders of magnitude better than any so-called Lyrical Video Saregama has released for any song. The very idea of the Lyrical is, IMO, moronic.)]

 

 

A recruiter calls me to talk about a Data Science position in Pune…

A recruiter calls me this morning, from Hyderabad, all unexpectedly. No emails beforehand, no recruiter messages at a jobs-site, no SMSs, nothing. Just a direct call. They are considering me for a Data Science position, in Pune. She says it’s a position about Data Science and Python.

Asks about my total and relevant experience. I tell: 23 years in all, ~12 years in s/w development. She asks about my Python experience. I tell: Familiarity for, may be, 10 years if not more; actual use for, may be, 5–6 years. (Turns out to be since 2006, and since at least 2013–14 times, in connection with scripting while using the open-source FEM libraries, respectively.)

She then asks me about my data science experience.

I tell that I’ve been into it for about a year by now, but no professional, paid experience as such. Also add that I do understand kernels from the Kaggle competitions. (In fact, I can think of bringing about meaningful variations in them too.)

She asks about my last job. I tell: Academia, recently, after PhD. (She sounds a bit concerned, may be confused. She must be looking at my resume.) But before that, I was in the software field, I say. And now, am now looking for a Data Science position. I then add: In the software development field, my last job was as a Systems Architect, reporting directly to the CEO. … By this time, she must have spotted this software experience listing in my resume. She says “OK,” with just a shade of a sense of satisfaction audible in the way she sounds.

She then again asks me about my Data Science experience. I now tell her directly: Paid experience, 0 (zero) years.

Hearing it, she keeps the phone down. Just like that. Without any concluding remarks. Not even just a veneer of a courtesey like a hurried “OK, if you are found suitable, we will get back to you” etc. Nothing. Not even that. No thanks, nothing.

She. Just. Keeps. The. Phone. Down.


It must be a project for one of those companies from America, especially from California, especially from the San Francisco Bay Area. Only they can be as dumbidiots* as that. And, they could very well be one of those “Capitalist”s, esp. Indians—there and here. “You are just as good as your performance on your last job!” Said sternly. And, the quote taken literally. In the current context, it is obviously taken to mean that I am as good as zero, when it comes to Data Science positions.

Dumbidiots*. Zeno’s descendents. They don’t deserve to hire me.

But these stupididiots* do amass a lot of money for themselves. Help build the nation. Etc.

Rich idiocy.


*By the rules of the Sanskrit grammar, this “sandhi” is correct. English is an Indo-European language. So, such a “sandhi” should be allowed. The jointed word means something like “k’mt’om” [^] “moorkha”. (You look up “moorkha”.)


A song I like:
(Hindi) “hum the, woh thee, aur, samaa rangeen…”
Singer: Kishore Kumar
Lyrics: Majrooh Sultanpuri
Music: S. D. Burman