Post by Nathan Shammah and Shahnawaz Ahmed.

Open-source scientific computing is empowering research and reproducibility. It forms one of the principles of the ‘open science’ movement, which aims to promote the spread of scientific knowledge without barriers. Open-source software refers to code which can be read, modified and distributed by anyone and for any purpose under the various open-source compliant licenses. This ‘open source way’ could extend beyond just software and is impacting quantum physics research in radically different ways.

Quantum-tech open source

Quantum computing represents a different computational paradigm from conventional computing: it exploits quantum mechanics at the algorithmic level. As quantum algorithms need to be run on quantum devices, advances in hardware development, currently underway, are crucial. At the same time also software for quantum computing needs to be developed for various purposes – compilation, control, noise modeling, simulation and verification. Open source is driving the development of the quantum computing software ecosystem [Fingerhuth18].

To some extent, the very structure of research in quantum technology is being reshaped by open-source projects to a new degree, for example allowing theorists to run quantum physics experiments from the cloud, without ever entering the lab (to the relief of experimentalists) [Zeng17]. In most cases, the tools are open source in a bid to involve the community of researchers and software developers to come together to build the next generation of software for quantum computing.

Beyond quantum computing there is also a broader area of quantum physics research that is being driven by open source. Some projects aim to provide a broad set of tools which can be used for quantum physics research, such as QuTiP, a Python toolbox for open quantum system simulations, which was started as early as 2011 [Johannson12]. Recently tools such as QuantumOptics.jl (a Julia package for quantum optics simulations) or Google-backed Open Fermion (simulating fermionic interactions and other chemistry problems) have been released for tackling different types of research problems. Other projects are purpose-specific, such as Pennylane (focussing on machine learning and quantum physics), ProjectQ (translating quantum programs to “any back-end”), and NetKet (Neural Network Quantum states for solving quantum many body problems). A community-maintained list of software can be found here.

 Factors contributing to the rise of scientific research with open-source software

Scientific progress is fueled by collaborations and development of ideas from others. In the same spirit, open-source is built upon the contributions of the community and there are several factors that are leading to its adoption beyond quantum physics research.

Firstly, open-source libraries allow fast reproducibility of results. By preventing the reinventing of the wheel and the need to start projects from scratch, they allow for a rapid development, testing and prototyping of ideas and extending previous work. This accelerates the rate of discovery, as new results can be investigated by other researchers tinkering with existing code.

Secondly, there are a variety of tools that increase productivity and collaboration. There is a general trend in scientific research in working in larger teams [Fortunato18] and open-source tools are helping in that. Github or Gitlab are websites that coordinate delocalized teams to work on the same coding project (similarly to Dropbox for file syncing and Overleaf for typewriting). One can also work interactively on code with solutions such as the Jupyter Lab computational environment, Google Colaboratory or CoCalc.

Then, there are well established tools for open-source software development from start to finish:  Travis CI, Anaconda, and the community-managed ‘conda-forge’ channel, can all be set-up easily to take care of testing, continuous integration and software packaging and distribution.

Finally, there are tools specifically crafted to better adapt to the modern characteristics of research publication, in which papers in journals have a background of data or software. Zenodo for example allows the publication of open-source software together with published papers and instantly attributes to it a DOI reference, without waiting for the (sometime lengthy) peer-review process. The crystallization of software is also a guarantee for reviewers and other researchers who might want to use the same code.

Python and machine learning as success stories for open source

 The benefits of the open-source approach can be clearly seen in machine learning, especially deep neural networks. Suddenly, it has become very easy to tinker and use even the most advanced methods in machine learning thanks to the availability of code and tools to modify and run them. With Google’s TensorFlow or Facebook-backed PyTorch, the power of deep neural networks reached the masses, leading to very creative applications.

As a result, we are also witnessing the impact of machine learning to all areas of natural sciences and tasks, from designing quantum experiments [Melnikov18] to detecting gravitational waves [Gabbard18].

An important factor for the wide adoption and use of machine learning tools is Python. It is an interpreted programming language that has seen a steady growth in adoption, based on a wide environment of modular independent software packages (libraries) that can be used together for numerics (SciPy), generating visualizations (Matplotlib), sharing code (Jupyter notebooks) and much more.

For some applications, Python’s limited computational performance (generally lower than C, C++ or FORTRAN) can be overcome by writing parts of the code in other languages and calling them from Python or using targeted solutions such as Numba or Cython to compile parts of the code into fast machine code.

But what really sets it apart its intrinsic code-writing efficiency and speed of developing prototypes, as one can more easily debug software on the go. As pointed out by Guido Van Rossum, the creator of Python, in a recent video interview for the MIT AI lecture series, scientific research through numerical means is usually a trial-and error creative approach, where the very investigative process benefits from an interactive feedback loop. The faster the loop, the faster the distillation of code.

Can quantum physics and quantum computing follow in this path by going the open-source way, accelerating the discovery of physical phenomena? Below we provide an example drawn from our recent experience.

PIQS: an example of open source package for physics research

 A major drawback in the development of quantum technology is the emergence of stronger noise as the system size grows, a process generally referred to as decoherence. The quantum system is never completely isolated, like Schrödinger’s cat inside the box, but is ‘open’ to interactions with the environments. The theoretical description of such coherence-averse processes in many-body quantum physics dynamics is itself problematic. This is because the very computational space grows exponentially with the number of qubits N, faster than 2^N (actually a daunting 4^N even if major assumptions simplifying the possible correlations of the open system are made).

We have recently released an open-source library, the permutational invariant quantum solver (PIQS) [Shammah18], to simulate a broad range of effects with an exponential advantage over the straightforward simulation of the open quantum dynamics. With PIQS, it is possible to include local effects in the noisy dynamics and energy dissipation, as well as the incoherent influx of energy from an external source, such as that mediated by a pumped cavity field by intermediate Raman processes in clouds of atoms illuminated by laser light [Baumann10,Bohnet12].

PIQS is quite versatile and addresses a series of open questions in the thermodynamics of quantum systems. This library can describe a broad range non-equilibrium effects in large systems of qubits, or ensembles of two-level systems, such as Dicke superradiance, which is the cooperative emission of light from an ensemble of identical two-level systems, in presence of sub-optimal experimental conditions, such as in solid-state devices, in which inhomogeneous broadening and local dephasing spoil the simple textbook picture of coherent light-matter interaction [Shammah17].

Due to the universality of the mathematical language in which quantum mechanics speaks, this tool can also describe spins in solid state materials and more generally, qubits engineered on a broad variety of platforms, from lattices of atoms to defects in diamond [Bradac17,Angerer18,Rainò18]. The use of permutational invariance has been crucial for the exponential reduction of the system space. The PIQS library joins other numerical investigations and libraries leveraging on symmetries in Lie algebras in tensor spaces [Kirton17,Gegg17].

By integrating the PIQS library into QuTiP, the quantum optics software in Python first released in 2011, this purpose-specific tool is now accessible to a wide community of users already familiar with this other well-established open-source software. This agility is another example of the modularity not only of the Python ecosystem, but of modular libraries themselves.

QuTiP itself is the example of a flexible library, which is used by theorists to test ideas or explore new physics, but also by experimentalists, who might want to analyze data or obtain predictions for how to tune the knobs of their experiments, including those involving the first error-prone quantum computers.

The future of quantum open source

 Open-source libraries like PIQS and QuTiP and the community of developers-researchers seem a key drive to the development of quantum technologies, as they offer the opportunity for creative interactions and novel solutions, as well as the capability to tinker with open problems.

Training more theoretical physicists and experimentalists on how to code collaboratively and develop open-source tools is another important aspect to train the next generation of future quantum programmers. At the same time, making this process easy and efficient, so that it can complement fundamental research, is paramount.

Involving the wider open-source community to use the knowledge and skills of expert software developers can also help to develop better simulation techniques or tools, for example for running simulations on GPUs or clusters. The two communities can learn from each other: one can help to adopt the best software development techniques and the other can demystify quantum quirkiness to facilitate the search for new and creative applications.

Finally, we look forward toward the development of institutional avenues to open-source quantum computing. Currently, only private ventures offer researchers cloud access to quantum machines [Zeng17], due to the costs of hardware development and software engineering infrastructure. As the community and tools of open-source software develop, we can envision in the future of quantum computing — and broader quantum technology research — also a network of scientific and institutional laboratories providing cloud access to experiments. This would contribute to reshape and possibly accelerate the rate of discovery in basic quantum physics research.

References

[Fingerhuth18] Mark Fingerhuth, Tomáš Babej, and Peter Wittek, Open source software in quantum computing, PLoS ONE 13 (12): e0208561 (2018).

[Zeng17] Will Zeng, et al. “First quantum computers need smart software.” Nature News 549.7671 (2017): 149.

[Johansson12] J. R. Johansson, P. D. Nation, and F. Nori: “QuTiP 2: A Python framework for the dynamics of open quantum systems.”, Comp. Phys. Comm. 184, 1234 (2013); J. R. Johansson, P. D. Nation, and F. Nori: “QuTiP: An open-source Python framework for the dynamics of open quantum systems.”, Comp. Phys. Comm. 183, 1760–1772 (2012)

[Fortunato18] Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., … and Vespignani, A. Science of science. Science, 359, 6379, eaao0185 (2018).

[Melnikov18] Alexey A. Melnikov, Hendrik Poulsen Nautrup, Mario Krenn, Vedran Dunjko, Markus Tiersch, Anton Zeilinger, and Hans J. Briegel, Active learning machine learns to create new quantum experiments, PNAS 115 (6) 1221 (2018)

[Gabbard18] Hunter Gabbard, Michael Williams, Fergus Hayes, and Chris Messenger, Matching Matched Filtering with Deep Networks for Gravitational-Wave Astronomy. Phys. Rev. Lett. 120, 141103 (2018)

[Shammah18] Shammah, N., Ahmed, S., Lambert, N., De Liberato, S., and Nori, F, Open quantum systems with local and collective incoherent processes: Efficient numerical simulation using permutational invariance. Phys. Rev. A 98, 063815 (2018)

[Baumann10] Kristian Baumann, Christine Guerlin, Ferdinand Brennecke and Tilman Esslinger, The Dicke Quantum Phase Transition with a Superfluid Gas in an Optical Cavity. Nature 464, 1301 (2010)

[Bohnet12] Justin G. Bohnet, Zilong Chen, Joshua M. Weiner, Dominic Meiser, Murray J. Holland and James K. Thompson, A steady-state superradiant laser with less than one intracavity photon. Nature 484, 78 (2012)

[Shammah17] Nathan Shammah, Neill Lambert, Franco Nori and Simone De Liberato, Superradiance with local phase-breaking effects. Phys. Rev. A 96, 023863 (2017)

[Bradac17] Carlo Bradac et al, Room-temperature spontaneous superradiance from single diamond nanocrystals. Nat. Commun. 8 1205 (2017).

[Angerer18] Andreas Angerer et al. Superradiant emission from colour centres in diamond. Nature Physics 14, 1168–1172 (2018)

[Rainò18] Gabriele Rainò, Michael A. Becker, Maryna I. Bodnarchuk, Rainer F. Mahrt, Maksym V. Kovalenko and Thilo Stöferle, Superfluorescence from lead halide perovskite quantum dot superlattices. Nature 563, 671 (2018)

 [Kirton17] Peter Kirton, and Jonathan Keeling, Suppressing and restoring the Dicke superradiance transition by dephasing and decay. Physical review letters 118, 123602 (2017).

[Gegg17] Michael, Gegg, and Marten Richter, PsiQuaSP–A library for efficient computation of symmetric open quantum systems. Scientific Reports 7, 16304 (2017).

Post by Cliò Agrapidis — read the graphic novel here.

Being a female PhD student in theoretical condensed matter physics, I am part of a growing number of women in STEM. Being part of this group has made me aware of several initiatives related to it: from groups forming to reunite women scientist and/or to inform the public about women in STEM (500 women scientists, Women in research), to specific funding programs for women (like the one from the L’Oreal Foundation). Major journals (including Nature) publish editorials and data on the current situation for women in science and I find myself reading and sharing them almost daily. Being part of this group makes me feel invested in talking about this and other academia-related issues, acknowledging them among my peers and my colleagues and whoever is patient enough to listen to me.

This is how I found myself at the Lucca Comics&Games, the largest comics fair in Europe, talking about mental health in academia to a cartoonist, while other cartoonists and publishers were at our same table. Having finished with that, a young member of the BeccoGiallo publishing house asked me about the women in science issue, if it is something in which I am interested. After my affirmative response and some more small talk, he explained to me that he and a younger collaborator were launching a new comics website, with the intention of publishing short graphic journalism stories about current events but also, more in general, as a platform for informing the public about broader modern issues. They asked me whether I would write biographies of women scientists, with the intention of ‘going beyond Marie Curie’. I accepted and so I started collaborating with STORMI, an Italian online magazine dedicated to graphic journalism.

The next step I took was to write down a list of important female scientists from the past that not everyone knows. The first confirmation that many of these women are not widely known came when I showed the list to my partner, who is also a physicist: he did not know more than half of the people on the list. I sent the list to the two editors of STORMI with a short subject for the biography of Maria Goeppert-Mayer and a first suggestion for the order in which I would work on the list. As I expected, they did not know the names of the dozen scientists I had written down, but this is the core of the project: showing people how women have been part of science, not in big numbers as men (mostly because of regulations that did not allow women to do science), and how we, the public, have forgotten them: it is time we remember.

Comic as a medium has the advantage of using pictures. You can say a lot without too many words. For example, in Maria Goeppert-Mayer’s biography, one of my favourite illustrations is the one depicting Maria’s movements around the U.S.A. Sure, one can make a list, but it will not immediately show the distances she actually covered.

Another idea, which came from the illustrator I collaborated with, the talented Eliana Albertini, is to use different colors for different life periods. Again, one can divide the text in paragraphs, or chapters, but it does not have the same visual effect.

There was another problem that was very clear to me: the website is in Italian, but the language of science is English. So, I translated my own text into English and even asked my partner to make a German translation. That way, the comic is now available as pdf in three languages, and can reach a much broader audience.

I started with writing about a woman physicist because physics is my field and because when we ask people to name any female scientist they will most probably say Marie Curie and stop there. But there was another woman who got the Nobel Prize in Physics, and now we finally have a third one (which made our comic obsolete, but made us very happy). I will not restrain myself to physics: I have already written the text for Emmy Noether’s biography, my never-tired editor Mattia Ferri has contacted an illustrator, and we hope this story will be available soon. But there are other scientific fields to cover: biology and informatics, for example. I am now focusing on prominent female scientists of the past, but my hope is to be able to write stories about living scientists, maybe a graphic interview, in order to show to the public, but also to some fellow scientists, that science is not a men’s affair: women have been there, they are there, and they will be.

Post by Igor I. Smolyaninov, Department of Electrical and Computer Engineering, University of Maryland.

How to build a ‘multiverse’ in a lab

Many physical properties of our universe, such as the relative strength of the fundamental interactions and the value of the cosmological constant appear to be fine-tuned for the existence of human life. One possible explanation of this fine tuning assumes the existence of a multiverse, which consists of a very large number of individual universes with different physical properties. Intelligent observers populate only a small subset of these universes, which are fine-tuned for life.

While this point of view may not be falsifiable based on astrophysical observations, one possible way to ascertain its viability may rely on macroscopic electrodynamics and condensed matter physics. In particular, the ‘optical spacetime’ in electromagnetic metamaterials (artificial structures patterned on a subwavelength scale to achieve unusual materials parameters) may be engineered to mimic the landscape of a multiverse that has regions with different topology and effective dimensionality. Nonlinear optics in metamaterials in these regions mimics Kaluza-Klein theories with one or more kinds of effective charges [1].

Another closely related model of a cosmological multiverse may be based on the electromagnetic properties of ferrofluids [2]. When a ferrofluid is subjected to a modest magnetic field, the nanoparticles inside the ferrofluid form small hyperbolic metamaterial domains, which from the electromagnetic standpoint behave as individual ‘Minkowski universes’. Microscopic spacetime defects and inflation-like behaviour appear to be generic within these individual Minkowski domains. It is remarkable that these non-trivial effects are accessible to direct experimental visualization using optical microscopy. Here I summarize several metamaterial systems that capture many features of cosmological models and offer insights into the hypothesized physics of the multiverse.

Electromagnetic metamaterials and transformation optics

The unconventional functional behaviors of the electric permittivity ε and magnetic permeability μ in metamaterials in the physical space lead to the creation of unusual ‘optical spaces’ that can be designed and engineered at will, opening the possibility of controlling the flow of light with nanometer spatial precision. Moreover, in a special class of hyperbolic metamaterials the optical space behaves like an ‘optical spacetime’, in which one of the spatial dimensions assumes a time-like character [3]. Hyperbolic metamaterials are extremely anisotropic electromagnetic materials, which behave like a metal in one direction and like a dielectric in the orthogonal direction. Hyperbolic metamaterials are typically composed of multilayer metal-dielectric or metal wire array structures. While in ordinary media all components of the ε tensor are positive, in hyperbolic metamaterials they have opposite signs in the orthogonal directions across quite broad hyperbolic frequency bands. Light can still propagate in such materials, but the direction of negative ε becomes time-like, so that the normally Euclidean optical space behaves more like a Minkowski spacetime at these frequencies. Light rays in this situation start to behave like evolving ‘world lines’.

 Modeling time with metamaterials: metamaterial models of the Big Bang

The nature of time has been a major subject of science, philosophy and religion. Our everyday experiences tell us that time has a direction. On the other hand, most laws of physics appear to be symmetric with respect to time reversal. A few exceptions include the second law of thermodynamics, which states that entropy must increase over time, and the cosmological arrow of time, which points away from the Big Bang. While it is generally believed that the statistical and the cosmological arrows of time are connected, we cannot replay the Big Bang and prove this relationship experimentally. However, it appears that electromagnetic metamaterials may provide us with interesting tools to better understand this relationship and, maybe, the physical origins of time itself. For example, an experimental demonstration of the behavior of a world line near a toy Big Bang in an expanding metamaterial universe as a function of a timelike radial r coordinate can be seen in Figure 1.

Figure 1 : (a) Atomic force microscopy image of a hyperbolic metamaterial structure. (b)  Light rays increase their separation as a function of a timelike radial coordinate. Light scattering at the edges of the structure is partially blocked by semi-transparent triangles. (c) Schematic view of world lines behavior near the cosmological Big Bang.

Light rays are launched into the hyperbolic metamaterial near the r=0 point via the central phase matching structure (marked with an arrow in the figure). Similar to the world line behavior near the Big Bang (Fig. 1c), light rays or ‘world lines’ indeed increase their spatial separation as a function of a ‘timelike’ radial coordinate. This experimental model may illustrate the relationship between the statistical and the cosmological arrows of time if disorder is introduced in this metamaterial structure [3].

Metamaterial multiverse experiments in ferrofluids    

Let us now turn our attention to self-assembled hyperbolic metamaterials made of ferrofluids, which share some common features with the class of cosmological models of the multiverse based on the loop quantum gravity [4]. This analogy relies on the fact that a modest external magnetic field aligns most of the individual magnetic nanoparticles in the ferrofluid into long parallel chains, so that the ferrofluid becomes a self-assembled hyperbolic metamaterial [5]. It appears that both loop quantum gravity models and the hyperbolic metamaterials may exhibit metric signature phase transitions [4], during which the spacetime metric used to describe the system changes its signature. Moreover, the metric signature transition in a ferrofluid leads to separation of the optical spacetime into a multitude of intermingled Minkowski and Euclidean domains, giving rise to a ‘metamaterial multiverse’ [2]. Inflation-like behaviour appears to be generic within the individual Minkowski domains (Fig. 2). Thus, studies of the optical spacetime in ferrofluids may illustrate the potential existence of parallel universes and shed some light on the ‘measure problem’ in a multiverse, which has to do with making probabilistic predictions of some particular measurement outcomes in a multiverse setting. All these effects may be studied in ferrofluids via direct microscopic observations.

Figure 2: (a) This magnified image of the Minkowski domains in a ferrofluid illustrates inflation-like expansion of the optical spacetime near the domain wall. (b) Measured and calculated  dependencies of the spacetime scale factor on the effective time.

Microscopic observation of spacetime melting in ferrofluids

Recent developments in gravitation theory provide numerous clues that strongly indicate that classic general relativity is an effective macroscopic theory, which will be eventually replaced with a more fundamental theory based on yet unknown microscopic degrees of freedom.  Unfortunately, these true microscopic degrees of freedom cannot be probed directly.  Our ability to obtain experimental insights into the future microscopic theory is severely limited by the low energy scales available to terrestrial physics and even to astronomical observations. In order to circumvent this problem, it is instructive to look at various examples of emergent gravity and analogue spacetimes [6] that appear in solid state systems such as superfluid helium, electromagnetic metamaterials and cold atomic Bose-Einstein condensates.

As discussed above, ferrofluids subjected to an external magnetic field have emerged as an interesting example of an electromagnetic metamaterial, which exhibits gravity-like nonlinear optical interactions, and which may be described by an emergent effective Minkowski spacetime. Unlike other more typical metamaterial systems, such a macroscopic self-assembled 3D metamaterial, they may also exhibit physics associated with topological defects and phase transitions. In particular, effective Minkowski spacetime melting may be observed and visualized in these metamaterials. If the magnetic field is not strong enough to hold nanoparticle chains together, the optical Minkowski spacetime gradually melts under the influence of thermal fluctuations. It may also restore itself, if the magnetic field is increased back to its original value. Such a direct microscopic visualization of Minkowski spacetime melting is depicted in Figure 3.

Figure 3: Magnified quasi-3D images taken from a movie of the effective Minkowski spacetime melting in a ferrofluid. A small region in the third frame, which remains in a microscopic Minkowski spacetime state (while the rest of the original spacetime has already melted) is highlighted by the yellow circle.

Outlook

The mutually related fields of electromagnetic metamaterials and transformation optics are experiencing extremely fast progress. While most of the experimental and theoretical work in these fields is devoted to revolutionary practical devices, such as super-resolution microscopes and electromagnetic invisibility cloaks, I have tried to show that they also have enormous potential in helping to shed light on some of the most fundamental problems of philosophy and science, such as the nature of time or potential existence of alternative universes. While the metamaterial systems considered here may or may not have anything in common with the real physical universe, they may still teach us a lot about the fundamental physics governing it.

References

1. I. I. Smolyaninov, Journal of Optics 13, 024004 (2011)
2. I. I. Smolyaninov, B. Yost, E. Bates, V. N. Smolyaninova, Optics Express 21, 14918 (2013).
3. I. I. Smolyaninov, Y. J. Hung, JOSA B 28, 1591 (2011).
4. M. Bojowald, J. Mielczarek. J. of Cosmology and Astroparticle Phys. 08, 052 (2015).
5. V.N. Smolyaninova, et al. Scientific Reports 4, 5706 (2014).
6. C. Barcelo, S. Liberati, M. Visser, Living Rev. Relativity 8, 12 (2005).

A guest post by Alak Ray and Prajval Shastri.

After seventy years of the government of independent India nurturing scientific enterprise, even in the face of criticism of its investment in the fundamental sciences, it is a good moment to review the story of what many regard as the prized jewel of them all – the Tata Institute of Fundamental Research (TIFR), which was founded in 1945 by the physicist Homi Bhabha with the help of the Dorabji Tata Trust. We are treated to a visit of this famous institute and its history in the book Growing the Tree of Science, Homi Bhabha and the Tata Institute of Fundamental Research (Oxford Univ Press, New Delhi 2016) written by Indira Chowdhury. The reference to a growing tree in the title came from a Presidential Address by Bhabha in 1963 at the National Institute of Sciences of India: “A scientific institution… has to be grown with great care, like a tree.”

The history of the Institute is distilled from years of effort by Chowdhury to set up the institutional archives of TIFR. She explores the early efforts of scientific institution building around the time of India’s independence in 1947, when science was envisaged as being serviceable to the nation and a tool of nation building, but the need was also recognized to nurture institutional spaces without borders.

The campus of Tata Institute of Fundamental Research around the time of inauguration of its new buildings in January 1962 in south Bombay (now Mumbai). Photo courtesy of the Archives of Tata Institute of Fundamental Research.

Bhabha undertook this nurturing with enthusiasm, even when within a few years of founding the Institute multiple responsibilities left him little time for research. He concentrated on creating the conditions for conducting good research, and sought to entice stellar scientists to visit, and to recruit established scientists who could lead various programmes. A largely unknown initiative by Bhabha was his invitation in 1952 to Richard Feynman “to spend a couple of years or more here as a Professor of Theoretical Physics”, which Feynman declined.

A poignant story of Bhabha’s sense of science without borders concerns the Chinese mathematician S. S. Chern. During the intense civil war in China (1948), Bhabha wrote to Chern at the Mathematical Institute of the Academia Sinica at Nanking, which Chern himself had founded in 1946 after returning from Princeton. Bhabha wrote, “Although we know the patriotism which prompted you to prefer to work in your own country despite the many attractive offers from abroad, we realise that the present conditions must make work in your neighbourhood extremely difficult, if not impossible… I am therefore, writing to you to offer you the hospitality of this institute… to spend one year in the first instance as a Visiting Professor?” By this time Chern had already accepted J. R. Oppenheimer’s offer at the Institute of Advanced Study at Princeton, but was deeply grateful “for the concern of my foreign friends, which has never failed me”.

Bhabha smoothly and successfully recruited the mathematician K. Chandrasekhar in 1948 and the physicist M.G.K. Menon in 1955, though he failed with astrophysicist S. Chandrasekhar. In 1962, he offered George Sudarshan an Associate Professorship. Sudarshan had worked in TIFR’s emulsion group earlier (1952-1955) at the Old Yacht Club. Then, while on leave from TIFR at the University of Rochester, Sudarshan, with his thesis advisor Robert Marshak, worked out the universal V-A theory of weak interactions, for which they were nominated for the Nobel Prize multiple times. But the effort to repatriate Sudarshan failed because Bhabha tried putting Sudarshan on par with others who stayed on in the institute and did their research in India. Indeed, Chowdhury writes about Bhabha’s notion of “self-reliance which had instilled in him an unswerving faith in the scientists who had trained at his institute”. She elaborates, “It was this group that had been responsible for growing the roots of the tree of science and Bhabha the master gardener was unwilling to carry out any process of grafting a foreign branch which could potentially disturb the stability of the tree itself.” Chowdhury asks, “The institutional model itself had an unresolved paradox at its core – was it national or international?” She opines that the “ambiguity at the heart of Bhabha’s grand vision presented a troublesome dilemma – how to be international and national at the same time”.

The idea of using modern science for social transformation has been debated among the Indian elite since social reformer Raja Ram Mohan Roy’s time in the 1820s. The debate has touched on questions such as: What are the priorities for development? What types of scientific activities are most appropriate for a developing country like India? How can a scientific community be best established within a traditional society? How can scientists working in such a society keep their loyalty to the internationalism of science and at the same time deal with the more local and immediate needs of their own countries? [see “India’s Scientific Development”, William Blanpied, Pacific Affairs, vol 50, 91,1977)]. In the first two decades after India’s independence the international network that Bhabha built worked together with India’s nationalism and was happy to contribute to the development of institutions for a newly independent India. (The most notable scientist in this network was Nobel prize-winning experimentalist P. M. S. Blackett – see “Empire’s Setting Sun?”, Robert Anderson, Econ. Pol. Weekly, vol 36 (39), 3703, 2001). Chowdhury points out, “The sense of national self-realisation and an awareness of international cooperation went hand in hand.”

Bhabha also successfully drew a strong connection between fundamental science and technology development. Bhabha in his letter to the Sir Dorabji Tata Trust in 1944 wrote, “It is absolutely in the interest of India to have a vigorous school for research in fundamental physics, not only in the less advanced branches of physics, but also in the problems of immediate practical interest to industry. If much of the applied research done in India today is disappointing and of very inferior quality, it is due to the absence of sufficient numbers of outstanding pure research workers who could set the standards for good research.”

Growing the Tree of Science paints the picture of TIFR and its journey of undertaking science in a newly developing nation on a wide canvas. The story however is somewhat less richly textured for the period after Bhabha’s death. Chowdhury does discuss the beginnings of molecular biology, radio astronomy and other disciplines in TIFR with the recruitments of the geneticist Obaid Siddiqi in 1962 and the radio astronomer Govind Swarup in 1963. Her story is however mainly concentrated in the earlier phase of these groups. The hits and misses of the Bhabha era affected TIFR’s later development and the future it looks into. One wishes that a deeper appraisal of the era that followed could be put together in greater detail.

About the authors:

Alak Ray is a Raja Ramanna Fellow at the Homi Bhabha Centre for Science Education (TIFR). Prajval Shastri is a Professor at the Indian Institute of Astrophysics, Bangalore. As young physicists they both arrived at TIFR’s south Mumbai campus in 1981, fifteen years after the Bhabha era.

Guest post by Charlie Ebersole, a social psychology graduate student at the University of Virginia.

Graduate school has been both a wonderful experience and incredibly challenging. When I will later look back on this period in my life, I’m sure that my memory will fail to accurately capture what it was like to be a graduate student. I’ll remember the highs, and more lows than I care to admit, but will likely lose some of what the day-to-day experience was like. If I have graduate students of my own someday, I want to have a more complete picture of what graduate school was like so that I can give them a better experience. With that goal in mind (and with some great suggestions from Twitter folks), I compiled the following list for my future self.   

Things to remember for when you have graduate students
Gentle reminders from past you to help current you give your students a better experience 

1. 1. There are a lot of little ways that you can make their lives easier. For instance, if you suggest a literature for them to search, try to give them some citations as a starting point. That way, they don’t have to guess which articles you were thinking about. Little things like this can really add up in the long run.
   2. Although class grades might not matter as much in grad school, your students got into grad school, in part, because they were good at getting good grades. That drive won’t go away immediately. Same goes for deadlines. Be patient while they figure out priorities.
   3. Tell your students: Wanting to look competent is natural and useful in some settings. However, it’s also important to admit when you don’t know things. Acting like you know more than you do stifles opportunities for others to teach you new things. This is probably going to be an ongoing struggle; that’s ok. Let me know how I can make it easier for you to say when you don’t know things.
   4. Remind them that they have/will develop expertise that will surpass you. Take opportunities to learn from them so that they recognize this.
   5. Remember that shielding your students from their weaknesses will hurt their development. Also remember that hearing critiques from your advisor can be hard.
   6. It’s hard to know when you’re doing well as a grad student. Be sure to tell students when they’re doing well and point out what you see as their strengths. That can help balance when you need to do #5.
   7. Things from outside of work will affect work. Try to create an environment where students feel comfortable letting you know those things. As an example from your time in grad school: Brian regularly asking about your life outside of work (e.g., “how was your weekend?” at the start of each meeting) made it easier for you to bring up struggles when they were affecting your progress.
   8. Sometimes fighting for your students is as important as the outcome. You’re not going to win everything (or, frankly, most things), but showing that you care enough to stick up for them goes a long way.
   9. Grad students don’t make a lot of money. They might not have a lot saved either. Keep that in mind. Things that might not seem like much to you (like being a few hundred dollars in debt while waiting to get reimbursed for conference travel) might be a serious strain for them.
   10. Finally, you were really bad at writing when you started grad school. It’s probably just good to keep that in mind when looking at your students’ writing.

Post by Michael Paolillo.

Without hardware there is no science. Equipment, reagents and consumables are all paramount for the execution of experiments, collection of new data and generation of new knowledge. Coupled with the movement for open science, many groups and initiatives are pushing to make Open Science Hardware the new norm in labs worldwide. We interviewed one of the founders of one such initiative, Prometheus Science, that is working to develop easily accessible and usable open science hardware starting from published academic research.

Can you introduce yourself and tell me what are Prometheus‘ goals as a company?
I am André Maia Chagas and I have been with Prometheus since the first tinkering phases. I work on this project with Dr. Maira Bertolessi. Together, we aim to increase the availability of science and education tools by creating affordable, open-source, scientific-grade equipment. We are heavily involved in the open-source and do-it-yourself movements. We are proud to say that our product, the FlyPi, can now be found across the world in more than 10 countries, such as Chile, Argentina, Nigeria, USA, Sweden, France and Germany.

Picture courtesy of Pierre Padilla

You mentioned the FlyPi, what is that?
The FlyPi is our ‘proof of principle’ product, started as a collaboration with the NGO Trend in Africa. It is an open-source compact modular imaging system built out of 3D-printable parts and off-the-shelf electronic components. It is highly modular, so it can be adapted to unique experimental conditions. We have published work demonstrating that the FlyPi can be used for diagnostics and state-of-the art methods in neuroscience, such as optogenetics, calcium imaging, behavioural tracking and fluorescence imaging. As far as the price goes, even after building all the modules, it is still 10−20 times cheaper than traditional systems.

Tell me more about the open-source movement.
Well, the open-source movement started a while ago, mainly with software. The basic idea is that all plans/blueprints describing a piece of software, a protocol, a recipe or a piece of laboratory equipment are made freely available for people to comment, share, modify, improve and customize. This leads to the creation of communities where everyone can build off each other’s ideas and creations. We have held workshops in various countries in Europe and Africa to teach people how to build and use the FlyPi. We also focus on showing people how to use the available open-source technology out there to build their own scientific equipment. It has been an inspiring experience to see how access to a dynamic and powerful new tool like the FlyPi can transform a community and inspire a group of young scientists. We believe that by empowering people with these scientific tools we can increase access to science education and improve the way research is done. For example, we now have an online forum consisting of people from around the world who are develop tools to improve upon the FlyPi’s design.

Can you tell us about what your plans are now?
Of course. There are a lot of published scientific papers describing new open-source equipment, but  normally the researchers who publish the articles are not interested in bringing the tools to a wider market. This is due mostly to the large time commitment and to the fact that academics’ main concern is to do more research. This is a problem, since many people do not have the necessary skills to build these tools from the original blueprints, or have time to spend doing so. This is what we at Prometheus want to do next. We aim to identify interesting open-source equipment described in the literature and to work with the researchers to find a way to bring their designs to market. Researchers interested in bringing their designs to a wider audience can contact us directly at andre[at]prometheus-science.com.

Where can we learn how to get involved with Prometheus?
You can find us at prometheus-science.com and we welcome conversations with open arms on our forum. Come check us out!

Michael Paolillo is a PhD student in Biochemistry and Neuroscience in Tübingen, Germany and he is passionate about science communication. He also created the website Neuromag.net, a science communications website that accepts interesting articles about science around the world.

Picture courtesy of Aga Pokrywka