Search Results

Intro A few days ago I received, along with my colleagues in the physics department, an email referring to a paper posted on the scientific archive by an RIT student, Andrew Haverly. Andrew is a masters student in computer engineering at my university, and his preprint was titled 'Nuclear Explosions for Large Scale Carbon Sequestration'. The email I received was a forward from our department head of a request from Andrew for professional help from physicists in fleshing out the ideas in his paper. What caught my eye was his revelation that his original intention had been to just put the idea out there; but after posting the paper, he had been contacted by the Gates Foundation, researchers at MIT, and other physicists. They had asked him to elaborate on the work. A couple of days later I saw that Sabine Hossenfelder, the well known science popularizer had also picked up on his paper and posted a YouTube video on it (her channel has 1.6M subscribers). The Plan The main motivation behind Andrew's proposal is to remove (excess) carbon dioxide from the atmosphere. The path chosen is the known process of carbon capture from the atmosphere which occurs when rainwater interacts with silicate minerals in rocks like basalt; the carbon is stored in the form of carbonates during the process. This happens naturally during weathering and therefore the effects become noticeable only over geological timescales. If humans were to implement this carbon capture process on a timescale faster than geological using modern technology, the challenges would include the large scale mining, crushing and transportation of immense quantities of basalt. Andrew's proposal aims to accelerate the process by detonating a nuclear bomb placed inside seafloor basalt. This would make the oceanic water capable of sequestering large amounts of CO2. Aiming at addressing CO2 emissions from the last 30 years, Andrew estimates it would take a nuclear detonation a thousand times more powerful than ever implemented. In his paper he discusses the concerns regarding safety, ecology, politics, and finance that such a plan inevitably raises. To make things concrete he identifies a suitable spot under the Indian Ocean for the explosion. Conclusion The preprint is freely available (linked above), is about 5 pages long, and clearly written. It's worth a read, even if only for the amazingly large numbers involved (e.g. nuclear explosion yield in gigatons, project price in billions of dollars, human lives saved from climate related problems in tens of millions, etc.). I am not expert enough to say if the proposal is feasible, but this is certainly thinking on a grand scale.

Nowadays a scientific career is a substantial undertaking, requiring many years of training and preparation, resources from agencies, a relatively stable job at a university or research institute, etc. This post is about some scientists who gained eminence in science while their main employment was in another profession. One wonders if this is still possible today; in any case, here are some examples for inspiration: Leibniz: The co-inventor of calculus (along with Newton). Leibniz was a polymath who never held an academic position, serving instead mainly as an advisor to rulers and politicians. Ben Franklin : Inventor of the lightning rod and bifocals. He was a printer . Mendel : Gregor Mendel was the founder of modern genetics. He was a monk . Anton van Leewenhoek : The father of microscopy. He was a draper by profession . Einstein : Early in his professional career, Einstein was a clerk in the patent office in Bern, Switzerland. In this capacity, he published earth-shaking papers on relativity and the photoelectric effect. After seven years in the patent office, he became a professor at the University of Zurich. Fermat : Best known for his work in number theory (including 'Fermat's Last Theorem' proved by Andrew Wiles), Fermat's day job was that of a judge . His bachelor's degree was in law. He apparently 'bought' the position of a councilor in the Parlement de Toulouse, at which served until his end. Joule : James Prescott Joule has the unit of energy named after him. He was a brewer. Oliver Heaviside : Heaviside independently developed vector calculus, which he used to express Maxwell's equations in the compact form we currently know them in. Heaviside worked as a telegraph operator in his youth and never held an academic position. Ramanujan: One of the great exponents of number theory, among other fields. He was never formally trained in mathematics, and discovered many of his results while he was an accounting clerk . Yuval Ne'eman : Famous for his work in high energy physics (classification of strongly interacting particles). I have included him here because at the time he made his discoveries, he was not only a (somewhat older) graduate student in physics (working with Nobel laureate Abdus Salam), but also the Israeli military attache in London.

This is a review of the book Musicophilia by Oliver Sacks . It was published in 2007, but I got to it just now. That's how long my reading queue is (!). A talk by Sacks based on the book is available here . The introduction is already interesting, as it points out that music seems to have only indirect evolutionary benefits (release of dopamine, bonding) for human beings. Birds, of course, use music (for mating and territoriality), but among the primates, humans are unique in being sensitive to music. This contrasts to the role music plays in the lives of many people, as a great number of people listen to, enjoy and are passionate about music: together, Taylor Swift and Beyonce have sold 300 million singles in the United States, just as an example. In his book Sacks discusses, by presenting a number of case histories, the connection of music with various medical aspects of the human organism. Some examples: Lighting strikes, tumor removals, and strokes have been reported to turn on musical passion, musical 'seizures' - even amazing musical abilities (savantism) - in human beings who previously were not remarkable in that sense. Sacks discusses the anatomical aspects of these phenomena, including a number of interesting cases in which music of some sort incessantly plays on in the patient's mind, sometimes even during sleep. From the book I learnt that techniques like MRI and dissection can identify a professional musician's brain anatomically (certain areas are more developed than in non-musical brains), while other professions are not so easy to recognize using this approach (maybe they are now, since the book was written more than fifteen years ago). Sacks also mentions the fact that increased sensitivity to music can occur even in the absence of overt medical events. An example of this is simply the process of aging. This I believe has happened to me - although I loved music even before that age, at around fifty I began to feel the emotions far more deeply than I had before, and found myself sensitive to a far broader range of musical genres than previously. Sacks briefly mentions a case like mine in his book. Another interesting aspect discussed by Sacks is the relation of speech to music. He mentions the case of a patient who lost his speech after experiencing a stroke, and speech therapy did not help at all, but musical therapy helped him regain his speech substantially. On the flip side, speech can also help music: the book mentions that musicians who already have exposure to tonal languages such as Chinese and Vietnamese are more likely to have perfect pitch [this study, I was pleased to note (sic!), involved students from the famous Eastman School of Music at the University of Rochester]. In his presentation of the effect of music on anatomical motion, Sacks gives examples to show that music can (encourage or) inhibit Tourette's Syndrome, relieve Parkinsonian symptoms, even overcome limb paralysis. Along with this are provided analyses of patients with synesthesia (association of colors and tastes with musical sounds). Another interesting aspect mentioned is the relation of music to memory: some people can memorize anything as long as it is set to music (an example is that of a student who memorized a professor's lecture notes by musicalizing them). In the book there are examples of music curing depression (the example is from William Styron's classic Darkness Visible ), and being used to alleviate PTSD. Musical ability is a complex skill, as evidenced by the variety of ways in which problems can occur. Among these, Sacks describes loss of melody, harmony, and stereoscopy (ability to infer depth of space through sound perception - the reason why we have two ears). Conclusion This is a substantial collection of case histories addressing the role of music in medicine. Sacks writes with authority and elegance, introducing the appropriate literary devices for engaging the reader, and making the technical aspects readable. An updated account of the research in this interesting field would be intriguing and welcome.

'Tis the season for reviewing graduate school admission applications (to PhD programs in physics to be specific to my case). Whenever I have served on the admissions committee in the physics department at RIT, I have always remarked how the applying students often have had rather diverse experiences before coming to a decision about what to study in graduate school. These journeys are usually described in their statement of purpose. Some students have spent time in a lab and decided it wasn't for them (they prefer thinking more to doing; a more sedentary lifestyle; perhaps late night hours). Some have worked through a theoretical project and decided physical movement and interaction with people was important to them. Some have dealt with abstract problems and decided to move closer to real data and its analysis. Some have been fascinated by the rise of AI and chosen to work in areas of physics which use its tools extensively. It is very nice to see how the students have set themselves up with various experiences and then used these experiences to guide their career. It reminds me of my own trajectory as a physicist, which was anything but straight. I became serious about physics in college. Not misleadingly, I was given the impression that to do theoretical physics one had to have very good mathematical skills. Mine weren't bad, but there were some real stars in my class. Academically, I was in the lower half of the class, a place from which only experimentalists were supposed to emerge. I followed the trend and in my senior year worked at a medium energy particle accelerator, essentially characterizing the efficiency of the silicon and germanium detectors. Then I joined graduate school intending to become a high energy experimentalist. Eventually, I found myself in an optics lab. This was very challenging, but also satisfying. After my PhD, during my first postdoc, I began realizing that the experiments in my field were becoming increasingly complex and therefore resource-intensive, and I was more inclined to working in theory. (I often joke that I found in theory if you fix something it stays fixed - in experiment you often find yourself fixing the same thing repeatedly). I changed over and became happier and more productive. However, I did not totally reject my training in the lab. In fact I used it whenever I could, especially in collaborating with experimentalists. Of course, I am hardly unique in having done this. Some recently prominent scientists have in fact gone the other way: Debbie Jin , for example, had a PhD in condensed matter theory and eventually a became a spectacularly successful experimental atomic physicist. Some scientists do both theory and experiment, if that is convenient in their discipline. For my part, I am actually grateful for the experimental training I received earlier. Of course, I might have learned more about theory if I had been trained from the beginning as a theorist. But the exposure to experiment gives me some tools distinct from a conventionally trained theorist: the ability to naturally understand and propose experiments, and to speak the language of the experimentalists. Advice for students Embrace your various exposures to different aspects of science. They will be of use to you later on.

There is a series of videos on YouTube labeled Nobel Minds, which involves all the Nobel laureates for a given year gathered around a table for discussion. Though the discussion is run by a moderator, and there is an audience of Swedish students, the conversation ends up being quite informal. It's a nice venue for discovering the way the laureates think, what is personally important to them, and the stories of their journeys. I watched a number of these videos, and was especially taken by the issue for 2019 , which included, among others, Esther Duflo and Abhijit Banerjee (they will figure later in the discussion), who were the laureates for Economics along with Michael Kremer. The moderator buttonholed every speaker asking them how the Prize had changed their lives and how they planned to use it. After stock replies about promoting science from several laureates, Sir Peter Ratcliffe (Medicine) said all sorts of people who did not used to reply to his emails or agree with him (including his family) were now writing him and agreeing with him. Next, the moderator described what each Prize was for. First she mentioned the Economics prize and the idea of using randomized control trials. Talking to Michael Kremer, she asked that if his work, where he found medicine was taken up faster by poor people if it was made totally free (and even a small price tag would lead to drastic reduction in population buy-in) was not 'blindingly obvious'. Kremer explained why it was not really obvious. A little later, Esther Duflo picked up the thread by saying that whenever we think something is obvious we should test it, because most of our intuitions are wrong. At some point Didier Queloz (Physics) commented that scientists had been doing that since the time of Galileo five hundred years ago, and that he was surprised to hear from the economists' discussions that this seemed so new. Prof. Banerjee leapt to the defense of the economists by saying that they were aware of the scientific method but their contribution was to break known facts into smaller pieces that were useful for making actionable plans. For example, he said, it is a fact that education is good and correlated with a high GDP. But that tells us nothing about what the curriculum should be or the classroom size, or number of teachers, etc. It's concrete information about the granular pieces that can help us determine policy. This was, of course, a lovely reply, but I felt within the pit of my stomach that Prof. Queloz had vastly underrated in his comment the factor of human ignorance and dare I say it, stupidity. Just because Galileo had started the scientific method 500 years ago it hardly means that human beings would now have overcome a million years of evolution and gotten over, as Prof. Duflo said, our misplaced instincts. In fact this goes back to Prof. Ratcliffe's quote above. Before he won the Nobel, his logical pleas fell on deaf ears, because human beings are just not that amenable to reason. After he won the Nobel, everybody listened to him because human beings understand power (collective endorsement in this case) much better. Looking at the state of the physics community and the way some people think, therefore, I hardly think it would be overdoing things to have a prominent scientist remind us each year that what we think is obvious is not so, and be awarded a Nobel prize for it -:). Bonus There is a heated (sic!) discussion of global warming towards the end of the video, plus a very entertaining exchange on exoplanets and life elsewhere in the universe, plus one of my favorite topics - the passion to do science till we die. Enjoy!

This is a collection of observations I have made about myself over time regarding the effect of my professional habits (as a physicist) on my everyday thinking and actions. Basically, they are intellectual patterns that have transferred themselves into my practical life. Quantify, quantify Physics deals a lot with what we can measure. So physicists tend to make, or ask for, measurements. During my graduate training as an experimentalist, I would have to measure things regularly (humidity and temperature in the lab, pressure inside my vacuum chamber, power emitted by lasers, current and voltage in circuits, flow rates through pipes, etc.). This habit has transferred itself to real life. I was telling my doctor about the daily patterns in my blood pressure. She looked at me suspiciously and asked why I was measuring my blood pressure so often. My reply ('Because I can') did not seem to douse whatever suspicions she might have had about my mental state. But of course, such measurements are increasingly becoming passé now that we have smartphones doing this literally all the time. As an extension of this habit, I order blood tests whenever I go to India, since they are cheap, the expert comes home to draw the blood, and the results are sent to me the same day electronically. So we can now track markers for liver, kidney, thyroid, etc. An Indian surgeon I know tells me his classmates who are now doctors in the USA and UK order CT scans whenever they come to India, as these tests are harder and more expensive to obtain in those countries. Estimate, estimate Where we cannot quantify exactly, physics teaches us to make 'order-of-magnitude' estimates. These are very useful to obtain a general idea of the situation, especially to decide which effects are likely to dominate. (Some of the more esoteric ones, such as guessing the number of piano tuners in Chicago, are known as Fermi problems - where coming up with the estimate requires some deep/creative thinking). But now the habit has become a reflex. So I find myself estimating all the time: the number of people in the mall; the average car velocity for a trip; the time it will take me to finish a book given the number and size of pages; the weight of the bag I am packing for a flight (to be checked against the meter later); the volume of liquid in a coffee cup, the number of effective months spent awake and working competently in an average human lifetime (hint: not that many). Scale, scale In physics scales set by nature or other situations matter crucially. For example, what is fast and what is slow may be decided (in free space) by comparison of the moving object's speed to the speed of light. So physicists are in the habit for asking for the scale of comparison when claims of 'light' versus 'heavy' or 'long' versus 'short' are made, for example. I find it very useful to carry this habit over to the arena of human experience. For example what some friend describes as 'cheap' might become 'expensive' when compared to my salary. What some colleague describes as an 'easy' problem might become 'very hard' when normalized by my intellect. What some acquaintance as 'cool' might be 'avoidable' when normalized by my personality. But even physical comparisons can be quite illuminating. It is sobering to realize the difference between crashing into a lamppost while driving at 30 miles an hour (relative velocity 30mph) versus crashing into another car coming the other way also at 30 mph (relative velocity 60 mph). The total energy of collision is 4 times larger in the latter case. Predict then Test Scientists (especially theoreticians) like to make predictions and then test to see if they are true. Since we live in an era in which life is changing before our very eyes (new electronic models every few months, viral videos every few weeks, new news practically every second), pre-empting the future almost becomes a necessity. The more of our predictions come true, the better our understanding of our system. The exercise is also fun as a kind of futurism. Some trivial examples: For quite a while Google maps did not show the speed limit of the road on the navigator. It was not hard to predict this improvement would be made, and it was. There was a time when there were personnel sitting in booths to collect highway toll. It was not hard to predict that these jobs would be automated, and they were (recently, at least in New York state). With the coming of AI, we can certainly make and test a lot of predictions. A prediction that I hope will come true: as soon as I tell my AI assistant my dates and locations of travel, it books the tickets, sends Ubers at the right times to the right places (where it tells me to go), books and directs me to hotels in case of flight delays, clears me with airport security and immigration, arranges for luggage checkin and tagging, and injects me with the right medicine so I can overcome jetlag dynamically and stay current in whatever time zone I am passing through. Ok, maybe not that last one.

This post looks - for inspiration - at some cases in science where an individual picked a problem (which had been set aside by the community, because it believed the problem to be too difficult to solve), and achieved a breakthrough by solving it. In each case, the scientific community responded variously: with ridicule when it learnt that someone was trying to take on the problem, with unwillingness to accept the solution even when it had been established, with puzzlement when the details of the solution were not revealed initially, with complaints that the individual should have shared out their partial progress instead of surprising the world with the final answer. Before I present the list, in no order of time or importance, the famous quote on the topic: "Problems worthy of attack prove their worth by fighting back." Nakamura . Shuji Nakamura invented the blue LED for which he received the 2014 Nobel prize in physics. This device is crucial to LED lighting. I heard Nakamura talk live during a visit to the GlobalFoundries campus north of Albany some years ago. At the time of his invention, it was not believed that GaN (Gallium Nitride) could be used to make such an LED marketably. Nakamura recounted how he would give talks on his project to mostly empty sessions at conferences. Once he overheard two professors saying 'some crazy guy is giving a talk about blue LEDs' ; later both of them ended up working for him. Nakamura accomplished his aim by basically moving in with his MOCVD (Metalorganic Chemical Vapor Deposition) machine, which made the LEDs, for a year or so. He said his family hated him for doing that, but he knew he was on to something very important. He later successfully sued his then employer Nichia for hundreds of millions of dollars for the invention proceeds. He is now a professor at UC Santa Barbara. Lars Onsager : Onsager (Nobel prize in Chemistry 1968) famously exactly solved the two-dimensional Ising model, which was the first model to analytically show a phase transition (these transitions are said to occur when water changes to ice or steam, for example). Before that it was not clear that the subject of statistical mechanics could handle phase transitions. Before Onsager, physicists like Lenz, Bethe and Peierls found approximate results but no one came even close to solving it exactly. Onsager was notoriously cryptic, and just wrote the answer down on the blackboard at a conference. C. N. Yang (Nobel Prize in Physics 1957) later worked out the details, calling it the longest calculation he had ever done. Dan Schechtman . Schechtman (Nobel Prize in Chemistry 2011) discovered something called the icosahedral phase, which opened up the field of quasi(periodic)crystals , which are ordered but not periodic. When Schechtman initially showed his data, no one believed him since his results contradicted the standard textbooks which said all crystals are periodic. He was fired from his research team. He encountered special resistance and ridicule from Linus Pauling (Nobel Prizes in Chemistry 1954 and Peace 1962), who famously said "There are no quasicrystals, only quasiscientists." Pauling passed away by the time Schechtman was proven right. Schechtman said after a point he enjoyed every moment of the dispute with Pauling, knowing that Pauling was wrong. Andrew Wiles . Wiles proved Fermat's Last Theorem, one of the longstanding challenges (>350 years) in mathematics, after 7 years of working in secret and simultaneously maintaining a funded research program in another topic. After Wiles initially presented his proof, it was found to contain a gap. Wiles tried for a year to fix it without success. He was about to give up when he got a revelation and found the solution. Even great mathematicians like David Hilbert had given up on the problem as a lost cause; Wiles' words about proving the theorem being like finding your way in a dark house are haunting . Grigori Perlman . Perlman proved the Poincare conjecture , a result of great importance in topology, and a prominent problem that had been unsolved for a century. Perlman also proved the famous Thurston conjecture (made by the topologist William Thurston, brother of my departmental colleague George). Perlman wanted no part of the ensuing media hype. He gave up his research position at the Steklov Institute, and refused the Fields Medal (the equivalent of the Nobel prize in mathematics) as well as the $1Million Clay Millennium Prize. He has apparently subsequently withdrawn from active mathematical research. Conclusion Get that garage side-project going!

( Belated Merry Christmas and best wishes for the New Year to all readers !!) This list is personal, and claims to be neither complete nor comprehensive. Neither is it in any justifiable sequence. Obviously I am not an expert in all - any? - of the mentioned areas. Solar eclipse : This happened in April and although we were in the path of totality in Rochester, cloud cover shortly before to after denied us a view of the full spectacle. Still, watching - feeling - the darkness come and go was amazing. The Nobel prizes in Physics and Chemistry : The physics award to Hopfield and Hinton moved the boundaries of physics closer to AI. The chemistry award to Baker and Hassabis was for protein structure design, also AI-related. Nobel prize in Physiology/Medicine : This award went to Ambros and Ruvkun for their work on gene regulation, which enables cells, all of which contain exactly the same genes to develop into specialized tissues (nerve, muscle, etc.). Fruit fly connectome : The complete map of the wiring between the 140,000 neurons in the brain of the fruit fly was assembled. Doing the same for the human brain is still some distance away - it has about 100 billion neurons. Largest prime number found : I can't write it down here, as it has 41,024,320 digits. Primes are interesting to pure math (number theory) and used to encrypt (e.g. internet) data. Geometric Langlands Conjecture Proved : Robert Langlands had made the conjecture in 1967. The Langlands program is a set of conjectures relating geometry to number theory (it is sometimes described as a Grand Unified Theory of Mathematics). The geometric Langlands theorem considers a generalization of Fourier theory. I can't write down the proof here - even if I could understand it - because it is more than 800 pages long. Transparent mice : Injection with the right kind of food dye (tartrazine, found in Doritos and Mountain Dew) can make skins of mice transparent . If extension to humans can be realized, it may lead to easy detection of tumors, etc. (Maybe the next thing in body bling after the tattoo). Mimicking Exercise Effects with a Pill : This will help people who cannot exercise: ageing human beings or those facing muscle loss, etc. The inventor also talks about the benefits of the pill to people who are lazy, like himself. Edible ants : Depending on the species, the flavors can be nutty, vinegary, or caramel-like. The chemicals responsible were analyzed using chromatography. Reminded me of the time I was offered some cookies which I found had ants crawling over them. When I pointed that out, the cookie-offeror, a doctor, said "Ants are good for you." Not sure she was familiar with this research, though. The Ig Nobel prizes : Can't miss this one. Awarded yearly to research that is amusing. Consider the ones for chemistry (using chromatography for telling sober worms from drunk worms) and demography (establishing that reports of supercentenerians come from areas with no birth certificates). Afterword See you next year!

This post is a review of the book Invisibility: The History and Science of How Not to be Seen by Gregory G. Gbur . (Full disclosure: Greg is a colleague and a friend; we overlapped in graduate school). There is a lot of public curiosity about this topic (invisibility) and the book is well poised to address it. Here are some pressing questions the book answers: Can an object be perfectly hidden, according to the principles of science? Short answer : it's not clear. Long answer : it seems to be almost impossible if the object is made of natural materials (this is what the theorems say). On the other hand, it seems to be possible if the object is a substance specially designed by human beings ( metamaterials ). This is what the experiments show. In any case, all concrete demonstrations so far have involved some kind of conditional invisibility - the object disappears only when viewed from a certain angle, or using only certain colors of light, or only when it is made of a certain kind of material. Are there different types of invisibility? The book broadly categorizes these into two types. 1. Active invisibility : This indicates invisibility caused by some device which measures as well as generates light to create the illusion. Examples include those by Susumu Tachi (he made an invisibility cloak which recorded the scene behind the wearer using a camera and then projected it from the front) and Alaina Gassler's prize-winning use of similar ideas to remove the blind spots due to the A-pillars in her family car. (I think all cars should have this). The book does not deal much with this kind of invisibility. 2. Passive invisibility : This indicates invisibility caused by some device which only guides the light illuminating the object. Examples are (refractive index matching) such as when pyrex glass is made to vanish in mineral oil , beads disappear in water, and refraction through calcite is used to cloak the background. This is mainly the kind of invisibility that the book describes. What is the scientific basis of invisibility? Light can be thought of as consisting of waves or rays. Invisibility can be thought of in terms of waves. Things become visible by scattering light (like when we shine a torch on them). So the way to stop visibility is to avoid light scattering. This can be done using the fact that light is made of waves and can show destructive interference. Greg's book traces the history of this line of scientific research starting with Ehrenfest's paper on accelerating but nonradiating electric charges (for the experts - remember quantum physics had to be invented because point charges, i.e. electrons in atoms, could not keep to stable orbits around the nuclei - they would radiate away their energy; Ehrenfest found extended charge distributions that accelerated but did not radiate). Among others, the book describes the relevant contributions of Emil Wolf (Greg's PhD advisor, who also taught me Complex Analysis) on light scattering (the theorems mentioned above). Finally the book arrives at the work of Veselago, Pendry and Leonhardt, who basically started the field of artificial (human-made) substances that allowed for cloaking better than what was available in nature. These substances are called metamaterials . Invisibility, in these arrangements, can be explained by thinking of light as consisting of rays. In these designs, light rays flow like water around an obstacle so that downstream it is not possible to infer of the existence of these obstacles. As we all know, rays are deflected when light goes from one medium to another (this is why straws look bent as light from it exits from water into air); what changes at the interface is the refractive index. So refractive index engineering, aimed at bending light appropriately, can be used to create invisibility. The general field is now called Transformation Optics: it involves warping space to govern light flow (if this reminds you of general relativity, you are bang on - the mathematics is the same). Outlook According to the book, research on invisibility cloaks has been extended to interesting applications like thermal cloaks (e.g. to prevent heat loss), sea cloaks (to protect oil rigs, etc. from rogue waves in the ocean), acoustic cloaks (for noise cancellation purposes, etc.), and seismic cloaks (to protect buildings from earthquake waves). All of these involve the manipulation of waves and creation of their destructive interference. I thought it was interesting (though in hindsight perhaps inevitable) that Greg also discusses the 'anti-cloak' - a device that cancels a cloak, and makes the object visible. There is also now a field of ' illusion optics ' which replaces the real object by a desired illusion. Summary Overall a great read and handy reference. The prose is direct and the scientific technicalities are handled very well. The book covers the history of the subject nicely, including ancient myths, references in the popular literature and film . Interestingly, no magicians are mentioned. Bonus As a special treat the books ends with two appendices, one for building your own invisibility device, and the other, an 'invisibibliography' (Greg's word) - a list of invisibility stories from the literature.

(This is my 100th post – thanks to all the readers who have stayed with me thus far!!). What is endsemesteritis? Endsemesteritis is a disease that faculty and students at a university catch twice a year. It typically infects people when the final exams have to be made up, proctored and taken; when all-nighters are pulled by students before the exams and by the professors afterwards (to finish the grading before the registrar’s deadline); when projects have to be submitted and evaluated; thesis defenses have to be made and attended; service committees have to summarize their work, travel plans have to be put into motion (to finish packing in order to catch that international flight that you booked with only a day’s gap between the end of the semester and the break – this may involve grading electronic submissions from a major flight hub); when you already have one eye on getting ready for the next semester’s course which you have never taught before and for which you need to prepare the lecture notes; when holiday receptions and house parties have to be attended. It's a busy time, often followed by an exhausted prostration of both students and faculty. The pace of the semester The climactic pace of work at its end makes me think of the unforgiving pace that the academic semester sets for both the teachers and the taught. My commitments - to prepare lectures, post lecture notes and practice problems and solutions, make up and grade homeworks and exams, and maintain office hours - keep me quite busy. Quite often the penetrating questions asked by the students leads me to examine my own understanding of the subject and to uncover issues and topics previously unknown to me – the attendant trailing through the literature can absorb large chunks of time. But as professionals, teachers are expected to, and indeed can, take on that load. Penalties for slipping I am more often concerned about students who are pushed through an increasingly punishing pace as the semester gathers momentum. Quite often, I find that the academic system is geared to reward efficiency, time management and error avoidance, perhaps even more than creativity, intelligence, depth or persistence. I find the top grades often go to students who can organize their time efficiently, avoid fatal errors, and recover from mishaps quickly. A high GPA at the end of college is almost certainly an indication of good organizational skills, apart from anything else. But I have seen, for example, slower, but solid, thinkers left behind by the breakneck speed of the assignments and deadlines. These students look promising in the beginning, ask great questions in class, initially hand in thoughtfully worked out homeworks. But towards the end, the last few homework submissions from them may be missing or incomplete or carried out in haste. This may happen because of time demands made by some project which carried perhaps a greater number of academic credits, or some other competing course. I often see students going around sleep deprived in the last few days of the semester from the intense pressure of their academic commitments. I consider myself a slow learner/thinker and remember being similarly overwhelmed in college by the required pace. I always felt I was playing a (losing) game of catch-up. I have also seen students who start the semester in stellar fashion and then – maybe they had a family emergency or caught a transient infection – go off the rails because recovering from that slip gets harder as time passes and the classes rush on. Another way to teach and learn? One wonders if some margin could be introduced for taking pause in the middle of the rat race and ‘recover’ these students. Unfortunately, the logistical aspects of the educational system seem to block this path: the added cost for prolonging or adding semesters to the academic degree, the uncertain availability of professors to be around to teach once the formal semester is over (many travel for research purposes), etc. seem to prohibit any chance of allowing ‘learning at your own pace’. In fact, I have always been curious about the way courses are taught at university: certain topics at certain times during the day and the week, in units of an hour or so. I suspect some people learn better and more effectively when they are allowed large chunks of time around a certain subject, until they naturally lose interest and wish to move on to something else (essentially learning driven by natural curiosity). I wonder how the learning outcomes would change if we took a single topic and discussed it for a whole day once a week. There could be a much deeper and more free-ranging exchange with the students, with all sorts of questions being asked, more space to emphasize the unifying principles, and more time to digest the material between successive classes. Maybe quantum physics on Mondays, classical physics on Tuesdays, etc. In the current style I often find myself obliged to go ahead with the course, where looking back at and making connections to the material already taught would be more beneficial. Conclusion As far as I know there is only one way around this problem: you have to survive your formal education and then become a professor (since they kick you out of school after your get your PhD, the only way to stay is to become an academic). Then you can ‘learn at your own pace’ and to your own satisfaction. This was in fact one of my major motivations for becoming an academic. I often tell my students that the real reason they come to university is to educate the professors. Then I have to duck out before they ask me why they have to pay tuition in order to do that. [1] The Slow Professor: Challenging the Culture of Speed in the Academy, M. Berg.

A phenomenon that is common in undergraduate as well as graduate physics education: a student who is quite competent comes across a classmate who is brilliant, and takes that as a signal that (s)he should quit physics, because only the brilliant classmate has what it takes to 'succeed' in the field. I rather suspect this happens in every field of human endeavor, but I will stick to physics which is where I have faced this phenomenon in person, have been told about other cases by colleagues, and have tracked publicly available confessions by people I do not personally know - see below for the example of Jeff Bezos. This post is aimed at gathering thoughts about the phenomenon, without judging anybody to be right or wrong, and making some suggestions that students might find useful to consider before quitting physics, even though their final decision might be unchanged. Have you examined your career aims? If you are completely in love with physics (as an intellectual discipline) and desire nothing more than the privilege of practicing it every day, you will likely not be stopped by the brilliance of others (you may in fact be inspired by it). If love of the subject is not the prime motivation for doing physics, then the sort of interaction described at the beginning of this article may indeed lead you to choose to excel in a different field, where brilliance comes to you more naturally. A famous example is Jeff Bezos , who decided to leave theoretical physics at Princeton (and eventually start Amazon) because a classmate from Sri Lanka was able to solve a particular differential equation in a few minutes, something that Bezos (and his roommate) had been stuck at for three hours. Whether you choose to change your field will depend on the kind of person you are. Some people are naturally ambitious for success and recognition (not a bad thing) and would like to take the path that leads them there most naturally (though this might prove difficult too - remember the saying 'I had to work half my life to be an overnight success'?). Others are looking for a challenge from something they are not easily good at, and do not care about (external) success. In my opinion the world needs both kinds of people. Have you considered that brilliance may not be necessary for success in physics? At the undergraduate and graduate levels brilliance might consist of solving homework problems faster or more economically, of already knowing what the professor has to say, of reading ahead in the scientific literature, of thinking faster, etc. (It does not consist in proposing an original problem, or solving an outstanding puzzle in physics - except in very rare cases). In my opinion, it is not wise - though it is all too human - to be intimidated by these qualities, which I will club under 'technical brilliance'. This is because in physics research, speed usually does not count for much, unless there is a close competition to reach a suspected conclusion, and even then papers which are received weeks or months apart are usually published back-to-back, i.e. simultaneously. More importantly, the real problems worth solving are usually not the ones which many people know how to solve and where you beat other people out by using speed. They are often the problems that nobody knows how to solve and that require persistence - and time - to be cracked open. I personally tend to believe that anything that can be done quickly has an equally short shelf life in physics. Fashionable today, forgotten tomorrow. (Having said that, I am sometimes guilty of being fashionable myself). Also, physics thinking requires some maturity and exposure before you can become good at it. Your 'brilliant' classmate may have had a head start on you on this (maybe his mother is a physicist; Bezos' Sri Lankan friend knew of a related problem which he had solved earlier). But you can catch up, in some sense, given time. Then his thinking no longer seems so magical or overpowering. In other words, give yourself a chance. Have you considered that physics requires many kinds of talents? This is related to the previous point. Technical brilliance (which I consider to be the mastery of complexity, just as creativity is the mastery of simplicity) is not the only quality, nor even a necessary quality, in my opinion, required to do physics successfully (professionally), although it is a very useful trait to have (if you don't have it, you can hire people who do). The history of physics shows that other qualities like depth, solidity, risk-taking, networking and creativity are also very important. In this context I am reminded of Einstein's quote: "I have no special talent. I am just passionately curious." I am also reminded of James Watson's article, available online, where he gives some rules of thumb for succeeding in science. One of them is about networking, specifically about how both his (and Crick's) competitors for deciphering the structure of DNA failed to win the Nobel because they were isolated: Rosalind Franklin by her distaste for small talk; Linus Pauling because no one dared to disagree with him. Have you considered that being around brilliant people may be good for you? Both throughout my undergraduate and graduate days, I was academically never top of the class, sometimes not even close. Yet, I appreciated how much I learned from the top students. Even day, twenty years after the fact, I can trace back specific tricks and techniques and ways of thinking that I learnt from them, and then molded to my needs. Surviving their academic company also gave me useful confidence that even if there were tigers in the jungle, I could find enough food to survive (i.e. endure the competition). Have you considered that the physicist you consider brilliant may not even stay on in physics? Keep in mind that the person who made you quit physics might not end up being a physicist. One of my brilliant topper classmates moved to Wall Street, another to being a Public Policy expert in the energy sector. 'Brilliant' people can be quite capricious in their choices. One remembers the meeting of Harish Chandra (who had trained in theoretical physics under Dirac ) and Freeman Dyson (who grew up as a mathematical child prodigy). Harish Chandra told Dyson he was going over to mathematics because he found physics to be too messy. Dyson replied that he was going the other way, because he found mathematics to be too messy. They both succeeded in their careers. Summary Think (at least!) twice before quitting.

(Hope everyone had a Happy Thanksgiving!) This post is a review of The Impossible Man , a recent (2024) biography, by the science writer Patchen Barss, of the Nobel prize-winning physicist, mathematician and science popularizer Sir Roger Penrose . The book, in my opinion, is rather well written. The writing flows, the technical aspects are handled at an acceptable level of popularization, and I did not feel like skipping the text anywhere. Among other things, I like the fact that the book is not too long (300 pages - compare e.g. Alan Turing's bio at 736 pages). The book begins with a brief but compelling description of a world class intellectual battling the age-related decay of his mental and physical abilities (macular degeneration has made Penrose almost blind; rage against the dying of the light!) and his recent divorce from his wife of thirty years. Reading on will reveal: How a sundial (and subsequently a telescope) played a triggering effect in his scientific curiosity just as a magnetic compass did in Einstein's childhood. How he initially struggled at math in school, but imbibed at home his father's passion for mathematical puzzles. How his father was not afraid to go against the prevailing intellectual dogma (a trait manifested by Penrose many times in his scientific career) but was also socially gregarious, inviting all kinds of artists, scientists and literary people, who not only came home for dinner but often stayed on for months (!). Young Roger was surely stimulated by this company. How his childhood rivalries (in math, music, games) with his siblings played a major role in formulating his intellectual strategies and analyses. How he was stimulated by the radio broadcasts of Fred Hoyle , the popular books of George Gamow , and the art of Maurits Escher . Escher later made drawings based on Penrose's mathematical ideas; their one in-person meeting is described in the book. That his mature intellectual pursuits were shaped by Dennis Sciama (who was also responsible for introducing him to Stephen Hawking) and lectures from Bondi (general relativity), Dirac (quantum mechanics) and Steen (mathematical logic). How his defining scientific collaborations with Ted Newman and Wolfgang Rindler emerged organically. That Penrose was an evaluator of Stephen Hawking's PhD thesis. That Penrose does not like competition (see 4 above) and avoids hotly contested fields. Interesting insights like the one Penrose draws from Godel's incompleteness theorem, which says there are truths in any mathematical system which cannot be proved to be true within the rules of that system. Penrose takes that to mean that understanding cannot be fully described using rules, and thus computation cannot fully model human intelligence (seems relevant in the age of AI!). Why he ended up suing one of the world's biggest toilet paper companies (they used his tiling on their paper, because the tiles were nonperiodic and kept the paper from folding - the case was settled out of court). How another brush with tile trauma occurred when Daniel Shechtman was awarded the Chemistry Nobel for discovering quasicrystals. The prize ignored Penrose's earlier prediction of the phenomenon. Interestingly, examples predating Penrose's work by centuries exist. A fascinating two-word 'ambigram' on page 289 which Douglas Hofstadter made and sent to Penrose after the Nobel announcement. Right side up, it reads 'Roger Penrose' upside down, it reads 'Nobel Prize'. Very creative, clever and needless to say, appropriate. The overall success of the book in conveying the mathematical obsession with geometry that led Penrose to many of his pioneering discoveries. The contributions as well as conflict introduced by Penrose's relationships with the women in his life vis-a-vis his work. This includes his two failed marriages, the second with a student thirty four years younger than him. Overall a satisfying read!