On Satyendra Nath Bose

But Bose’s real story is actually far richer. His life and career reveal a complex, deeply human scientist who navigated intellectual passions and colonial-era challenges to make his historical mark. The narrow focus on his ‘accidental’ discovery overlooks the breadth of Bose’s pursuits and the context that shaped him. Bose was a true polymath, fluent in multiple languages and immersed in literature and philosophy, and a dedicated teacher who believed science should be accessible to everyone, not just an elite few. Crucially, he achieved all this while working under the British Empire, facing the hurdles of a colonised scientist: limited resources, isolation from international peers, and the pressures of life under foreign rule. Acknowledging Bose’s context doesn’t diminish his achievements; instead, it casts them in a more illuminating light. His groundbreaking work was not the result of mythical serendipity alone, but rather the culmination of perseverance, intellect and a willingness to think differently from the heart of a colonial world.

Bose was born on 1 January 1894 in Calcutta (now Kolkata), then the capital of British-ruled India. He was the only, eldest son (among seven children) of a lower-middle-class Bengali family. His father, Surendra Nath Bose, was an accountant with the East Indian Railways who had a knack for mathematics and science. His mother, Amodini Devi, although barely formally educated, managed the large household. Surendra Nath harboured nationalist sympathies; in 1901, he left his secure railway job, a position with the colonial government, to start a small chemical and pharmaceutical venture with a friend. Hence, Surendra Nath’s quiet defiance of colonial structures, and his turn towards Indian scientific enterprise, likely created a family world where a nascent nationalist milieu could thrive. This, I believe, left an enduring mark on his son.

The Bose family belonged to the Bengali Kayastha caste, which was traditionally excluded from the highest echelons of scholarship. By the late 19th century, however, social reforms of the Bengal Renaissance were loosening such barriers and opening up higher education to non-Brahmins. In this milieu of rising opportunities, young Bose demonstrated exceptional talent in mathematics and science, coming top in his classes at university.

Bose launched his academic career just as a new era in physics was dawning, but also during the tumult of the First World War, which cut off direct intellectual contact between British India and the German scientific centres pioneering quantum theory. Bose, however, was determined to keep up with the latest developments. He taught himself German and, with the help of mentors and colleagues, obtained copies of cutting-edge European research. He devoured papers by the physicists Max Planck and Arnold Sommerfeld, and studied advanced texts, such as James Clerk Maxwell’s and J W Gibbs’s treatises on statistical mechanics. Immersing himself in these resources, Bose stayed abreast of the new quantum ideas, even as some Western scientists remained sceptical of concepts such as the light quantum (the photon). Later in life, Bose reflected that working from the ‘periphery’ helped him think independently; the prevailing orthodoxies of the European establishment didn’t bind him.

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By the early 1920s, quantum physics had emerged as a radical new field, offering Bose intellectual freedom from colonial strictures. As I argued in my book The Making of Modern Physics in Colonial India (2020), embracing the quantum provided ‘a great intellectual escape from the hegemony of scientific colonialism’ that defined the British-dominated scientific establishment in India, which focused on teaching classical physics in universities and exploring applied science that benefited colonial interests.

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Notably, Bose was not a traditional firebrand political agitator; he did not lead rallies or write polemics against British rule. His form of nationalism was expressed through intellectual sovereignty. He showed by example that Indians could innovate at the highest levels of physics, even under the constraints of colonial rule. Moreover, by choosing to develop his career in India and by communicating science in an Indian language, he undercut the notion that one must go abroad or use English to be a successful scientist.

Beyond his famous work in quantum statistics, Bose led a rich and varied scientific life. Upon returning to Dacca after his European sojourn, he threw himself into new projects. One of his significant contributions was in the field of X-ray crystallography. With the know-how he gained in de Broglie’s lab in Paris, Bose established one of India’s first X-ray crystallography laboratories at Dacca University in 1926. Under his guidance, the lab’s students and technicians constructed advanced instruments. By the 1930s, they had built a Weissenberg X-ray camera, a sophisticated device for crystal structure analysis, in the department’s workshop. This was cutting-edge equipment for an Indian institution at the time, and it turned Bose’s Dacca lab into a regional hub of research activity. Not only his students used it, but students from other universities (including some from Calcutta) would travel to Dacca to conduct experiments. In an era when Indian scientists often struggled for resources, Bose’s initiative created rare opportunities for hands-on training within his home country.

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True to the label ‘polymath’, Bose’s interests were never confined to physics alone. His lifelong love of literature, music and philosophy complemented his scientific pursuits. Bose was fluent in several languages, including Bengali and English, as well as French, and had a working knowledge of German from his student days. He enjoyed reading the original works of Western philosophers and actively engaged in the cultural and intellectual debates of his time. Friends and colleagues recall that he could discuss the poetry of Rabindranath Tagore or the essays of Bertrand Russell with equal ease, as he could the latest findings in quantum mechanics.

- More Here

What Is Entropy? A Measure of Just How Little We Really Know

But despite its fundamental importance, entropy is perhaps the most divisive concept in physics. “Entropy has always been a problem,” Lloyd told me. The confusion stems in part from the way the term gets tossed and twisted between disciplines — it has similar but distinct meanings in everything from physics to information theory to ecology. But it’s also because truly wrapping one’s head around entropy requires taking some deeply uncomfortable philosophical leaps.

As physicists have worked to unite seemingly disparate fields over the past century, they have cast entropy in a new light — turning the microscope back on the seer and shifting the notion of disorder to one of ignorance. Entropy is seen not as a property intrinsic to a system but as one that’s relative to an observer who interacts with that system. This modern view illuminates the deep link between information and energy, which is now helping to usher in a mini-industrial revolution on the smallest of scales.

Two hundred years after the seeds of entropy were first sown, what’s emerging is a conception of this quantity that’s more opportunistic than nihilistic. The conceptual evolution is upending the old way of thinking, not just about entropy, but about the purpose of science and our role in the universe.

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Notions of entropy developed in disparate contexts thus fit together neatly. A rise in entropy corresponds to a loss in information about microscopic details. In statistical mechanics, for instance, as particles in a box get mixed up and we lose track of their positions and momentums, the “Gibbs entropy” increases. In quantum mechanics, as particles become entangled with their environment, thus scrambling their quantum state, the “von Neumann entropy” rises. And as matter falls into a black hole and information about it gets lost to the outside world, the “Bekenstein-Hawking entropy” goes up.

What entropy consistently measures is ignorance: a lack of knowledge about the motion of particles, the next digit in a string of code, or the exact state of a quantum system. “Despite the fact that entropies were introduced with different motivations, today we can link all of them to the notion of uncertainty,” said Renato Renner (opens a new tab), a physicist at the Swiss Federal Institute of Technology Zurich.

However, this unified understanding of entropy raises a troubling concern: Whose ignorance are we talking about?

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In September 2024, a few hundred researchers gathered (opens a new tab) in Palaiseau, France, to pay homage to Carnot on the 200th anniversary of his book. Participants from across the sciences discussed how entropy features in each of their research areas, from solar cells to black holes. At the welcome address, a director of the French National Center for Scientific Research apologized to Carnot on behalf of her country for overlooking the impact of his work. Later that night, the researchers gathered in a decadent golden dining room to listen to a symphony composed by Carnot’s father and performed by a quartet that included one of the composer’s distant descendants.

Carnot’s reverberating insight emerged from an attempt to exert ultimate control over the clockwork world, the holy grail of the Age of Reason. But as the concept of entropy diffused throughout the natural sciences, its purpose shifted. The refined view of entropy is one that sheds the false dreams of total efficiency and perfect prediction and instead concedes the irreducible uncertainty in the world. “To some extent, we’re moving away from enlightenment in a number of directions,” Rovelli said — away from determinism and absolutism and toward uncertainty and subjectivity.

Like it or not, we are slaves of the second law; we can’t help but compel the universe toward its fate of supreme disorder. But our refined view on entropy allows for a more positive outlook. The trend toward messiness is what powers all our machines. While the decay of useful energy does limit our abilities, sometimes a new perspective can reveal a reservoir of order hidden in the chaos. Furthermore, a disordered cosmos is one that’s increasingly filled with possibility. We cannot circumvent uncertainty, but we can learn to manage it — and maybe even embrace it. After all, ignorance is what motivates us to seek knowledge and construct stories about our experience. Entropy, in other words, is what makes us human.

You can bemoan the inescapable collapse of order, or you can embrace uncertainty as an opportunity to learn, to sense and deduce, to make better choices, and to capitalize on the motive power of you. 

- More Here

What Can We Know About That Which We Cannot Even Imagine?

What can we know about that which we cannot even imagine? paper by David H. Wolpert of Santa Fe Institute. 

Read the whole thing. It is meant to make us all humble. 

In this essay I will consider a sequence of questions, ending with one about the breadth and depth of the epistemic limitations of our our science and mathematics. I will then suggest a possible way to circumvent such limitations. I begin by considering questions about the biological function of intelligence. This will lead into questions concerning human language, perhaps the most important cognitive prosthesis we have ever developed.

While it is traditional to rhapsodize about the perceptual power provided by human language, I will emphasize how horribly limited – and therefore limiting – it is. This will lead to questions of whether human mathematics, being so deeply grounded in our language, is also deeply limited. I will then combine all of this into a partial, sort-of, sideways answer to the guiding question of this essay: what we can ever discern about all that we cannot even conceive of?

 

Teleporting Quantum Information Within A Diamond

Science enables humans to satisfy their needs. It does nothing to change them. They are no different today from what they have always been. There is progress in knowledge, but not in ethics. This is the verdict both of science and history, and the view of every one of the world's religions.

- John Gray, Straw Dogs: Thoughts on Humans and Other Animals

Please read on if you understand the above wisdom from John Gray. 

Teleporting quantum information is big deal and researchers have successfully done it now but please don't confuse this scientific progress with moral progress. We will still continue to cause pain to animals, kill each other in wars, abuse children, and die/kill nonsensical myths. 

From Good News Networks: 

Researchers have successfully teleported quantum information securely within the confines of a diamond – and the study has big implications for quantum information technology, the future of how sensitive information is shared and stored.

The researchers from the Yokohama National University published their results earlier this week in Communications Physics.

According to the American Physical Society’s physics page, quantum information is spy-proof. When an eavesdropper attempts to intercept a message encoded in a quantum state, the message is altered by the eavesdropper’s measurement. Quantum bits, or “Qubits”, also cannot be copied – any attempt to do so instead creates an entangled state.

“Quantum teleportation permits the transfer of quantum information into an otherwise inaccessible space,” said Hideo Kosaka, a professor of engineering at Yokohama National University and an author on the study. “It also permits the transfer of information into a quantum memory without revealing or destroying the stored quantum information.”

The “inaccessible space”, in this case, consisted of carbon atoms in diamond. Made of linked, yet individually contained, carbon atoms, a diamond holds the perfect ingredients for quantum teleportation.

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“Our ultimate goal is to realize scalable quantum repeaters for long-haul quantum communications and distributed quantum computers for large-scale quantum computation and metrology,” Kosaka added.

The National Science Foundation says that quantum effects have already been used to create unbeatable codes. Previous studies have also shown that the defects in a diamond’s atomic structure could be used to store vast amounts of data similarly to how CDs and DVDs store information on their discs.

Since one of a diamond’s atomic defects measuring just billionths of a meter wide could be used to store data, researchers say that diamonds could very well be the future of computer storage – and now with the research from Yokohama National University, they could be the future of cyber security as well.

 

The First Cell - On Why Questions, Data And Future Treatments (Part 3 of 3)

We all are going to die one day. Eventually, Max too would have died of old age. But why he has to suffer from cancer even after spending trillions of dollars for half a century with no understanding of the root causes nor cure? Why? 

Judea Pearl, father of causal inference in his book The Book of Why: The New Science of Cause and Effect instills a meditative-mental anchor in our minds: 

Ironically, the need for a theory of causation began to surface at the same time that statistics came into being. In fact, modern statistics hatched from the causal questions that Galton and Pearson asked about heredity and their ingenious attempts to answer them using cross-generational data. Unfortunately, they failed in this endeavor, and rather than pause to ask why, they declared those questions off-limits and turned to developing a thriving, causality-free enterprise called statistics.

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My emphasis on language also comes from a deep conviction that language shapes our thoughts. You cannot answer a question that you cannot ask, and you cannot ask a question that you have no words for. 

Not only statistics but multi-disciplines failed in this endeavor by working in silos, parochialism - lack of collaboration across disciplines, funding, and more importantly no incentive for bright students to get into the field. 

This is part 3 of my lessons from Russ's latest episode with Dr. Azra Raza, author of the new book The First Cell: And the Human Costs of Pursuing Cancer to the Last.

Part 1 of my lessons are here, part 2 here,  and you can listen to the full interview here:

Azra Raza: And, by the way Russ, let me stop here and tell you one other thing. We are talking a lot about immune therapies these days, and there are multiple kinds of immune therapies. But, the most dramatic ones are those that use bodies' own immune cells to activate them and attack the cancer. You might have heard of CAR-Ts [Chimeric Antigen Receptor Therapy]. Nowhere do investigators point out that while CAR-T cellular therapies, the most dramatically effective form of killing every last cancer cell in the body. I acknowledge all of that. It is a fabulous feat of scientific achievement.

Incredible achievement to take the body's own T-cells, which are a kind of immune cells, and engineer them in such a way that they are now carrying part of a B-cell, which is another lymphoid immune cell. And it's activated to kill any cell it means that is expressing a B-cell receptor, CD-19. This is the most common CAR-T therapy used for B-cell lymphoma or leukemia.

But, nowhere do investigators point out that these T-Cells also cannot differentiate between a normal cell and a cancer cell.

So, what they actually do is kill the whole organ. But specifically that organ. Still there are off-target effects, which means other cells in the brain or somewhere else which are expressing the same marker. These engineered cells are so effective they will seek out and kill every cell that even has a molecule of that receptor being expressed.

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Azra Raza: Russ, one of the big problems we have faced in cancer is that, despite looking for 60 years, we have not been able to find molecules that are expressed only by cancer cells and not by normal cells.

In other words, we can't find the address, the unique zip code, of a cancer cell so far.

So, at best what we are trying to do is basically kill cells more effectively irrespective of whether their cancers are normal. When you ask me that, 'Will this immune therapy be applicable to other cancers?' Absolutely. It should be applicable.

But, right now it is not so because if we try to kill liver cancer cells with this kind of CAR-T therapy it will destroy the whole liver, not just liver cancer cells. Or, it will destroy the whole GI [Gastro-Intestinal] tract, the whole colon. So, the entire organ would be killed because normal cells are expressing the same markers as the cancer cells.

However, when we learn to identify by means of whatever biomarkers we develop, in the future as technology is evolving, then not only would we be able to specifically target cancer cells, but the other thing is that we would be able to use these therapies in earlier stages.

So, that right now, when we give these therapies, the only patients who respond are the ones who experience the most severe side effects, called the cytokine storm, which basically puts the patient's life at stake. That, if they survive it, they will enter remission. Those patients who don't experience this horrendous cytokine storm, they don't even eventually respond to this kind of therapy.

In other words, what I am saying is that we are going in the right direction. We have made some significant, dramatic advances in these kinds of immune therapies, but the way they are talked about, the hyperbolic language that is used minimizing not just the financial toxicity but actual physical toxicity of immune therapies.  

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So, now it comes to two issues. One is that we have patients today for whom we need treatments and we need to invest resources to try and improve those treatments and find better ones. I'm saying that the other half of resources need to go to improve the technology we have for earlier detection, which means a really serious, thorough, overall analysis of cells, RNA, DNA, proteins, metabolites from serially, sequentially studied actual human samples, not animal models.

And, the last thing I want to say about this is that this is where real and large-scale studies will have to evolve to provide the sample size for machine learning and artificial intelligence.

Since 1984 when I turned my attention towards studying pre-leukemia and following these patients as they are either died of MDS or developed leukemia, I started banking bone marrow and blood samples of my patients.

Today, Russ, this may sound like a very ordinary thing; but I have now collected over 60,000 samples from thousands of patients. Not one cell in my tissue bank has come from another investigator. All of these patients mean something to me because I've personally taken care of them. Most of them I have done with my own hands. This is a tissue repository where, today, I can go in, look at the cells, look at RNA, DNA, proteins, and metabolites in a serial fashion--as the patient progressed from pre-leukemia to acute leukemia.

This is how we can work our way back and then ask the question, why did some patients get pre-leukemia? What were the risk factors that made this individual or these people susceptible to getting pre-leukemia, even? And, this will take us then to identify a group who is at high risk of developing pre-leukemia and then we can start monitoring those individuals, healthy individuals who are at high risk, in a targeted fashion.

So, I can do this for pre-leukemia and acute myeloid leukemia. The resources are needed. I'm making this appeal to everybody that we should not rely on any one test done annually which was developed 50 years ago. Rather, we need to develop using the latest scanning, imaging, biomarking, genomic, proteomic, metabolomic technologies to find maybe 500 different tests that can be amassed in a bar code fashion or can be done rapidly, quickly, to identify individuals in the earliest stages of cancer.

The resources, half the resources, go to treating current cancer patients and developing and improving treatments for them. The other half must be invested towards early detection through the latest technology and prevention and nipping the cancer in the bud.

This is very depressing news... even targeted gene therapy doesn't differentiate between good and cancer cells. It does make sense since we never found the root causes of cancer. 
I am not as optimistic as Dr. Azra is when it comes to AI and Machine Learning. Nevertheless, AI can help us go from zero to 60 or even 80 easily. But the key here is we need data. 

The data needs to come from people like you and me in the form of samples. For the last two decades, Max and I have donated our genes, microbiome, and other samples from home for research. 

Trust me, there is no "John Corner" version of Max and me from the future came nor coming. We self-immolate ourselves by refusing to give out samples. Free samples from each one are more precious than donating billions and science cannot provide an alternative to samples. A piece of great news for animals is that a lot of animal testing in cancer and current medical research doesn't work - which means non-human animal samples don't go too far. 

People believe in magic and assume "they" are working on a cure. One of the biggest lessons I learned as I am getting older is that there is no "they". 

"They" is nothing but collective humanity. So if you want to find the root causes of cancer and cure for cancer - volunteer to give samples. Wearing a yellow bracelet and walking for "pink" in NYC doesn't move mountains expect feeding one's virtue signaling or self-deception. These help to raise money but money will do no good without good samples via your blood, DNA, microbiome, and other samples. 

This is exactly what I said the day Max was cremated. You can check out the responses I got in part 1. I cannot comprehend the idiocy of this without thinking most of us are deluding ourselves that "magically" we will escape cancer or we will be cured. Humans do baffle me. 

We as a society lost the art of asking questions. I cannot think of a better person than Richard Feynman who taught the art of asking the proper "Why" questions:. 

But the problem, you see, when you ask why something happens, how does a person answer why something happens? For example, Aunt Minnie is in the hospital. Why? Because she went out, slipped on the ice, and broke her hip. That satisfies people. It satisfies, but it wouldn’t satisfy someone who came from another planet and knew nothing about why when you break your hip do you go to the hospital. How do you get to the hospital when the hip is broken? Well, because her husband, seeing that her hip was broken, called the hospital up and sent somebody to get her. All that is understood by people. And when you explain a why, you have to be in some framework that you allow something to be true. Otherwise, you’re perpetually asking why. Why did the husband call up the hospital? Because the husband is interested in his wife’s welfare. Not always, some husbands aren’t interested in their wives’ welfare when they’re drunk, and they’re angry.

And you begin to get a very interesting understanding of the world and all its complications. If you try to follow anything up, you go deeper and deeper in various directions. For example, if you go, “Why did she slip on the ice?” Well, ice is slippery. Everybody knows that, no problem. But you ask why is ice slippery? That’s kinda curious. Ice is extremely slippery. It’s very interesting. You say, how does it work? You could either say, “I’m satisfied that you’ve answered me. Ice is slippery; that explains it,” or you could go on and say, “Why is ice slippery?” and then you’re involved with something because there aren’t many things as slippery as ice.

We outsource some of the precious things in life such as our food (by letting corporations cook for it), our thoughts (letting the morons on TV and Radio implant an ideological virus in our heads). 

In the end, what then is precious to humans? 

Crazy as it sounds, we think our "choices" we make while outsourcing is what we think is precious! 

These choices become our habits, "culture", part of our vocabulary, and endowment effect sets in. Yes, we defend the "precious" bullshit we eat and the morons we watch. That pretty much sums up our life outside of our work life and super cuddly family! 

Democracy cannot operate and sustain with such attitudes leave alone giving samples to find the root cause of cancer and finding a cure. 

The worst part of all of it is when you have a personal conversation with a meat-eater or someone refusing to understand the importance of giving samples - they will in ways gaslight you by using your passion against you. They are smart enough to turn the personal conversation into general one by using phrases like people, belief, goodness, busy, work, and such filler bullshit. And the final straw which usually ends the conversation would be acting the victim game. Not sure how they are victims while they are funding animal sufferings and not giving out samples that would help cancer research. They will maintain an unbelievable calmness and soft-spoken the entire conversation but their passions would flare for 10 min traffic job or being a helicopter parent, drop in a few dollars in the stocks. 

These attitudes make me sad. Even after watching Max suffer, the bond we had - they cannot comprehend nor think outside of their ideological walls and habits. This is just a dog and a guy who loved the dog because of lack of relationships he had while he was a kid. This the story they tell themselves and probably would live and die in that belief. 

My Max had to suffer and die of cancer because of collective choices we make every day by voting with our dollars and refusing to give any samples when we are healthy nor when we are unhealthy nor when we are dead - all because of some abstract concept of liberty, individualism and in most cases by lack of caring until shit hits their home. With omnipresent bad luck, you and I might die suffering for the same reason. 

Distilling all my noisy rant and to summarize what can a good person do:

• Always ask the why question. Why we haven't made any progress in finding the root causes of cancer? 
• Never settle for the status quo when it comes to science and answers regarding the world around us. 
• Open up your heart and mind to give out samples of your DNA and microbiome. 
• Data on your eating habits, daily activities (workout, walking, etc.), diversity of life inside your house, your ecological choices (laundry detergent, soap, etc.) 
• Cook your own food with no ingredients made from corporations. They don't understand complex systems nor will they attend your funeral. 
• Don't outsource your thinking to morons on TV and Radio. 
• Vote. Elect representatives who talk less and do more. They are not our leaders but they are our workers. Elect representatives who have a sense of gratitude, are humble,  understand the complexities of science, and don't believe in magic. 
• Make time to read all the bill's that matter to you which are due in the senate. Read the bills which have already passed as well. 
• Understand and follow all the nuances FDA does. 
• There is a brand new "field" named Exposome - We think about all health and illness as a combination of genes and the environment, and now it really is time to fill out the environment side of that equation. Limit and eliminate chemicals in your life. You need to bring to the surface the invisible choices you make in everyday life. 
• Every school, every university, every office, and every household should learn about complex systems. You do too. 
• Repeat all of the above. Understand - democracy, civilization and the life of earth depend on that. If that doesn't convince you - this will help minimize suffering during your final months and days. 

This interactive quiz from the BBC on how much of your body is your own? is a good place to understand the complexities inside "I" and how little of "I" is actually in "I".

One might feel overwhelmed by the little list above. But our brains love when we unleash them on things that matter. The hard part is to get started and persists. Garret Hardin comes to our rescue.

Garret Hardin in his book Filters Against Folly: How To Survive Despite Economists, Ecologists and the Merely Eloquent identifies three major filters against the folly that we citizens can use against blindness, short-sightedness, and sheer idiocy that so often comes disguised as eloquence or expertise.

Hardin contends that most of the major controversies of our time can be better understood as the result of the participants relying too much on any single one of these three filters. Since no one filter by itself is adequate for understanding reality and predicting the consequences of our actions, Hardin devotes the rest of the book to a discussion of the strengths and weaknesses of each of the three filters (my notes here)

• The first filter is literacy - "the ability to understand what words really mean."
• The second is numeracy - "the ability not only to quantify information but also to interpret it intelligently."
• Hardin calls the last filter ecolacy - "the ability to take into account the effects of complex interactions of systems over time." 

Hardin goes on to explain more on his ecolacy concept: 

More comprehensive development of ecolacy - the ability to ask and answer the question: and then what? so that the effects of the interactions of systems over time can be taken into account - is necessary if we are not to fall victim to the forces we unleash and are unwilling or unable to control. 

Some ecologists have tried to draw attention to the interrelatedness of our world by stating that everything is related to everything else (sometimes called Barry Commoner's first law of ecology).  This statement has been criticized by many scholars because while it is valuable as a warning it is useless as a guide to action. 

While all things in the environment interact they interact in different ways. The ecologist Garrett Hardin restated this important ecological understanding in the following language so that it can serve as a guide to action: WE CAN NEVER DO MERELY ONE THING which is now known as Hardin's Law. The language that we have used to describe the effects of our actions demonstrates the reality that Hardin's Law draws our attention to. We talk about the effects and side effects, products, and wastes. Hardin contends that since we cannot do just one thing we must always ask and answer the question and then what? 

When we try to ascertain the benefits and costs of proposed courses of action on both the individual as well as social levels. The ecological systems' way of thinking employs modern scientific theories and knowledge to study a world of interlocking processes characterized by many reciprocal cause-effect pathways. The ecological systems' way of thinking has to become an integral part of the thinking of the well-educated person if we are to adequately control technology rather than fall victim to the forces we generate and are unable or unwilling to control. Ecological systems thinking provides well-educated persons with the opportunity to act more rationally because they have learned a more comprehensive and more accurate way of estimating the probable costs and benefits of their actions.

We as individuals need to develop an ecolacy way of thinking. A habit of ecolacy thinking helps one not to get lost in a myriad of details and it helps develop meta-level thinking. Nurturing meta-level thinking helps detect bullshit a mile away and helps decipher the essence of progress in any domain without getting lost in details.

I will close with a brilliant philosophical Tamil song from 1964 - the essence of the song might get lost in English translation but it's worth pondering. 

There is no life without asking the why question 

No human with me, me, and me attitude lived a good life 

General knowledge was born only because of asking questions

All the liberties were earned only because of having emotions

Let thousand years pass until the meaning of our patience is understood

Let future generations sing that we are not salves 

There is no life without asking the why question 

No human with me, me, and me attitude lived a good life 

Progress happens only because all the work of those who work 

All the duties are followed because of the wants for freedom 

Good Bye Freeman Dyson

Technology is a gift of God. After the gift of life it is perhaps the greatest of God’s gifts. It is the mother of civilizations, of arts and of sciences. 

- Freeman Dyson

You were the last man standing from the classic physicists. Thank you sir for all the wisdom and discoveries. We will all prerish but you will be remembered for centuries to come.

In his memory, let's cherish and not abuse technology.

Wisdom Of The Week

Through his career, Hilbert was interested in the ultimate limits of mathematical knowledge: what can humans know about mathematics, in principle, and what (if any) parts of mathematics are forever unknowable by humans? Roughly speaking, Hilbert’s 1928 problem asked whether there exists a general algorithm a mathematician can follow which would let them figure out whether any given mathematical statement is provable. Hilbert’s hoped-for algorithm would be a little like the paper-and-pencil algorithm for multiplying two numbers. Except instead of starting with two numbers, you’d start with a mathematical conjecture, and after going through the steps of the algorithm you’d know whether that conjecture was provable. The algorithm might be too time-consuming to use in practice, but if such an algorithm existed, then there would be a sense in which mathematics was knowable, at least in principle.

In 1928, the notion of an algorithm was pretty vague. Up to that point, algorithms were often carried out by human beings using paper and pencil, as in the multiplication algorithm just mentioned, or the long-division algorithm. Attacking Hilbert’s problem forced Turing to make precise exactly what was meant by an algorithm. To do this, Turing described what we now call a Turing machine: a single, universal programmable computing device that Turing argued could perform any algorithm whatsoever.

Today we’re used to the idea that computers can be programmed to do many different things. In Turing’s day, however, the idea of a universal programmable computer was remarkable. Turing was arguing that a single, fixed device could imitate any algorithmic process whatsoever, provided the right program was supplied. It was an amazing leap of imagination, and the foundation of modern computing.

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There’s a wrinkle in this story. Deutsch is a physicist with a background in quantum mechanics. And in trying to answer his question, Deutsch observed that ordinary, everyday computers based on Turing’s model have a lot of trouble simulating quantum mechanical systemsResearchers such as Yu Manin and Richard Feynman had previously observed this, and as a result had speculated about computers based on quantum mechanics.. In particular, they seem to be extraordinarily slow and inefficient at doing such simulations. To answer his question affirmatively, Deutsch was forced to invent a new type of computing system, a quantum computer. Those quantum computers can do everything conventional computers can do, but are also capable of efficiently simulating quantum-mechanical processes. And so they are arguably a more natural computing model than conventional computers. If we ever meet aliens, my bet is that they’ll use quantum computers (or, perhaps, will have quantum computing brains). After all, it’s likely that aliens will be far more technologically advanced than current human civilization. And so they’ll use the computers natural for any technologically advanced society.

This essay explains how quantum computers work. It’s not a survey essay, or a popularization based on hand-wavy analogies. We’re going to dig down deep so you understand the details of quantum computing. Along the way, we’ll also learn the basic principles of quantum mechanics, since those are required to understand quantum computation.

Learning this material is challenging. Quantum computing and quantum mechanics are famously “hard” subjects, often presented as mysterious and forbidding. If this were a conventional essay, chances are that you’d rapidly forget the material. But the essay is also an experiment in the essay form. As I’ll explain in detail below the essay incorporates new user interface ideas to help you remember what you read. That may sound surprising, but uses a well-validated idea from cognitive science known as spaced-repetition testing. More detail on how it works below. The upshot is that anyone who is curious and determined can understand quantum computing deeply and for the long term.

- Quantum Computing for the Very Curious

How Conglomerations Of Stars Are Born & Die

Shortly after its birth, the universe was filled with gas, mostly hydrogen. Over time, here and there, gravity pulled the gas into clouds which turned into galaxies and in which stars ignited. Stars shine by thermonuclear burning of the gas; of those that die in explosions, some blow the gas back out of the galaxies. Out in intergalactic space, the gas cools and gets denser, until gravity pulls it back into the galaxy where new stars form. The process repeats: Gravity condenses gas into galaxies and stars, stars blow up and kick the gas out, gravity cycles the gas back in and makes new stars.

In time, any given galaxy begins to run out of recyclable gas. Without gas, it can’t form new stars; the old stars live out their lives and die, and eventually the galaxy dies too. Galaxies sit in a bath of gas, the medium from which they were born and which fuels them. The galaxies breathe gas in and out, and their stars burn until their gas is gone.

This is theory. The problem with verifying it has been that astronomers’ instruments could barely detect signs of gas, let alone map its comings and goings. With more sensitive instruments and dogged surveys, astronomers now know more. Convincing evidence suggests that the intergalactic medium is rich in gas, which fills the universe and seeds galaxies. Less-convincing and sometimes puzzling evidence in the circumgalactic medium shows that galaxies live by recycling gas into and out of stars. And astronomers have only preliminary evidence supporting arguments for how galaxies might run out of gas, stop forming stars and die.

- More Here

Wisdom Of The Week

First, we have three families (we call them generations) each consisting of four matter particles: two quarks and two, so-called, leptons. In the first family we find our by now familiar up-quark, down-quark and electron, as well as a fourth particle, the electron neutrino. This is an almost massless particle that is produced in huge quantities in the sun but mostly passes right through ordinary matter. The pattern of two quarks and two leptons is repeated twice more, so that there are twelve matter particles in total, grouped into three generations. Apart from being heavier, the particles in the latter two generations have exactly the same properties as those in the first. This is a rather strange state of affairs, but it seems to just be that way.

Next, there are four, so-called, gauge bosons, of which the photon is one. The gauge bosons are associated with three of the four fundamental forces of nature: the gluon corresponds to the strong nuclear force, the photon to the electromagnetic force, and the W and Z bosons to the weak nuclear force. (The fourth fundamental force is gravity – more on this in the followup articles.)

Finally, there is the Higgs boson, world-famous since its discovery at the Large Hadron Collider at CERN in 2012 . The Higgs boson is perhaps the strangest of the known fundamental particles (even stranger than the aptly named strange quark). If you followed its discovery, you may recognize the claim that particles gain mass through their interactions with the Higgs boson.

The particles shown in the table above, together with Einstein's theory of gravity, account for every observation ever made in physics, with only a small handful of exceptions (mostly in astronomy, you can read more in the final article). In particular, all of the things we encounter in our regular lives ultimately arise from these particles interacting with each other; the interactions individually are rather simple, but together adding up to all the complexity we observe, like a complex machinery where each component on its own behaves according to simple rules.

- Our theory of very nearly everything: the particles

Wisdom Of The Week

Feynman was also a renowned educator. Those lucky enough to have attended his lectures have the best sense of how his agile mind operated. He taught a first-year course at the California Institute of Technology (Caltech) in Pasadena: ‘Physics X’, in which students would ask him anything and he’d think on his feet. Feynman loved to astound, and often refused to provide solutions, to spur students on intellectually. The careful notes of attendees have been published as books and articles, bolstering his reputation as a master lecturer. One such from Caltech was the three-volume The Feynman Lectures on Physics (1964). Another, 1959’s The Theory of Fundamental Processes, is based on notes taken by Peter Carruthers and Michael Nauenberg, two students at Cornell University in Ithaca, New York, when Feynman was a visiting lecturer there in 1958. Nauenberg told me how, during the first lecture, Feynman walked in, glanced at the blackboard, wildly erased the equations on it and declared that they would all learn the whole of physics from scratch. Within a few weeks, the course proceeded from elementary quantum mechanics to Feynman’s rules for particle-physics calculations. The Character of Physical Law (1967), another of Feynman’s works, emerged from lectures he delivered at Cornell six years later.

Feynman’s books urge us to explore the world with open-minded inquisitiveness, as if encountering it for the first time. He worked from the idea that all of us could aspire to take the same mental leaps as him. But, of course, not every ambitious young magician can be a Harry Houdini. Whereas other educators might try to coddle those who couldn’t keep up, Feynman never relented. The essence of his philosophy was to find something that you can do well, and put your heart and soul into it. If not physics, then another passion — bongos, perhaps.

- Richard Feynman at 100

Quantum Questions Inspire New Math

Mathematics has the wonderful ability to connect different worlds. The most overlooked symbol in any equation is the humble equal sign. Ideas flow through it, as if the equal sign conducts the electric current that illuminates the “Aha!” lightbulb in our mind. And the double lines indicate that ideas can flow in both directions. Albert Einstein was an absolute master of finding equations that exemplify this property. Take E = mc2, without a doubt the most famous equation in history. In all its understated elegance, it connects the physical concepts of mass and energy that were seen as totally distinct before the advent of relativity. Through Einstein’s equation we learn that mass can be transformed into energy, and vice versa. The equation of Einstein’s general theory of relativity, although less catchy and well-known, links the worlds of geometry and matter in an equally surprising and beautiful manner. A succinct way to summarize that theory is that mass tells space how to curve, and space tells mass how to move.

Mirror symmetry is another perfect example of the power of the equal sign. It is capable of connecting two different mathematical worlds. One is the realm of symplectic geometry, the branch of mathematics that underlies much of mechanics. On the other side is the realm of algebraic geometry, the world of complex numbers. Quantum physics allows ideas to flow freely from one field to the other and provides an unexpected “grand unification” of these two mathematical disciplines.

It is comforting to see how mathematics has been able to absorb so much of the intuitive, often imprecise reasoning of quantum physics and string theory, and to transform many of these ideas into rigorous statements and proofs. Mathematicians are close to applying this exactitude to homological mirror symmetry, a program that vastly extends string theory’s original idea of mirror symmetry. In a sense, they’re writing a full dictionary of the objects that appear in the two separate mathematical worlds, including all the relations they satisfy. Remarkably, these proofs often do not follow the path that physical arguments had suggested. It is apparently not the role of mathematicians to clean up after physicists! On the contrary, in many cases completely new lines of thought had to be developed in order to find the proofs. This is further evidence of the deep and as yet undiscovered logic that underlies quantum theory and, ultimately, reality.

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How Life (and Death) Spring From Disorder

There’s a thermodynamic cost to storing information about the past that has no predictive value for the future, Still and colleagues show. To be maximally efficient, a system has to be selective. If it indiscriminately remembers everything that happened, it incurs a large energy cost. On the other hand, if it doesn’t bother storing any information about its environment at all, it will be constantly struggling to cope with the unexpected. “A thermodynamically optimal machine must balance memory against prediction by minimizing its nostalgia — the useless information about the past,’’ said a co-author, David Sivak, now at Simon Fraser University in Burnaby, British Columbia. In short, it must become good at harvesting meaningful information — that which is likely to be useful for future survival.

You’d expect natural selection to favor organisms that use energy efficiently. But even individual biomolecular devices like the pumps and motors in our cells should, in some important way, learn from the past to anticipate the future. To acquire their remarkable efficiency, Still said, these devices must “implicitly construct concise representations of the world they have encountered so far, enabling them to anticipate what’s to come.”

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Entropy maximization has long been thought to be a trait of nonequilibrium systems. But the system in this model obeys a rule that lets it maximize entropy over a fixed time window that stretches into the future. In other words, it has foresight. In effect, the model looks at all the paths the particles could take and compels them to adopt the path that produces the greatest entropy. Crudely speaking, this tends to be the path that keeps open the largest number of options for how the particles might move subsequently.

You might say that the system of particles experiences a kind of urge to preserve freedom of future action, and that this urge guides its behavior at any moment. The researchers who developed the model — Alexander Wissner-Gross at Harvard University and Cameron Freer, a mathematician at the Massachusetts Institute of Technology — call this a “causal entropic force.” In computer simulations of configurations of disk-shaped particles moving around in particular settings, this force creates outcomes that are eerily suggestive of intelligence.

In one case, a large disk was able to “use” a small disk to extract a second small disk from a narrow tube — a process that looked like tool use. Freeing the disk increased the entropy of the system. In another example, two disks in separate compartments synchronized their behavior to pull a larger disk down so that they could interact with it, giving the appearance of social cooperation.

Of course, these simple interacting agents get the benefit of a glimpse into the future. Life, as a general rule, does not. So how relevant is this for biology? That’s not clear, although Wissner-Gross said that he is now working to establish “a practical, biologically plausible, mechanism for causal entropic forces.” In the meantime, he thinks that the approach could have practical spinoffs, offering a shortcut to artificial intelligence. “I predict that a faster way to achieve it will be to discover such behavior first and then work backward from the physical principles and constraints, rather than working forward from particular calculation or prediction techniques,” he said. In other words, first find a system that does what you want it to do and then figure out how it does it.

Aging, too, has conventionally been seen as a trait dictated by evolution. Organisms have a lifespan that creates opportunities to reproduce, the story goes, without inhibiting the survival prospects of offspring by the parents sticking around too long and competing for resources. That seems surely to be part of the story, but Hildegard Meyer-Ortmanns, a physicist at Jacobs University in Bremen, Germany, thinks that ultimately aging is a physical process, not a biological one, governed by the thermodynamics of information.

- More Here

Quote of the Day

I’m sick and tired of this block universe, I don’t think that next Thursday has the same footing as this Thursday. The future does not exist. It does not! Ontologically, it’s not there.

- Avshalom Elitzur, A Debate Over the Physics of Time

AI Learns & Recreates Nobel-Winning Physics Experiment

The experiment the AI performed was the creation of a Bose-Einstein condensate, a hyper-cold gas, the process for which won three physicists the Nobel Prize in 2001. It involves using directed radiation to slow a group of atoms nearly to a standstill, producing all manner of interesting effects.

The Australian National University team cooled a bit of gas down to 1 microkelvin — that’s a millionth of a degree above absolute zero — then handed over control to the AI. It then had to figure out how to apply its lasers and control other parameters to best cool the atoms down to a few hundred nanokelvin (i.e. a billionth of a second), and over dozens of repetitions, it found more and more efficient ways to do so.

“It did things a person wouldn’t guess, such as changing one laser’s power up and down, and compensating with another,” said ANU’s Paul Wigley, co-lead researcher, in a news release. “I didn’t expect the machine could learn to do the experiment itself, from scratch, in under an hour. It may be able to come up with complicated ways humans haven’t thought of to get experiments colder and make measurements more precise.”

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Wisdom Of The Week

On April 6, 1922, Einstein met a man he would never forget. He was one of the most celebrated philosophers of the century, widely known for espousing a theory of time that explained what clocks did not: memories, premonitions, expectations, and anticipations. Thanks to him, we now know that to act on the future one needs to start by changing the past. Why does one thing not always lead to the next? The meeting had been planned as a cordial and scholarly event. It was anything but that. The physicist and the philosopher clashed, each defending opposing, even irreconcilable, ways of understanding time. At the Société française de philosophie—one of the most venerable institutions in France—they confronted each other under the eyes of a select group of intellectuals. The “dialogue between the greatest philosopher and the greatest physicist of the 20th century” was dutifully written down.1 It was a script fit for the theater. The meeting, and the words they uttered, would be discussed for the rest of the century.

The philosopher’s name was Henri Bergson. In the early decades of the century, his fame, prestige, and influence surpassed that of the physicist—who, in contrast, is so well known today. Bergson was compared to Socrates, Copernicus, Kant, Simón Bolívar, and even Don Juan. The philosopher John Dewey claimed that “no philosophic problem will ever exhibit just the same face and aspect that it presented before Professor Bergson.” William James, the Harvard professor and famed psychologist, described Bergson’s Creative Evolution (1907) as “a true miracle,” marking the “beginning of a new era.” For James, Matter and Memory (1896) created “a sort of Copernican revolution as much as Berkeley’s Principles or Kant’s Critique did.” The philosopher Jean Wahl once said that “if one had to name the four great philosophers one could say: Socrates, Plato—taking them together—Descartes, Kant, and Bergson.” The philosopher and historian of philosophy Étienne Gilson categorically claimed that the first third of the 20th century was “the age of Bergson.” He was simultaneously considered “the greatest thinker in the world” and “the most dangerous man in the world.” Many of his followers embarked on “mystical pilgrimages” to his summer home in Saint-Cergue, Switzerland.

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Bergson found Einstein’s definition of time in terms of clocks completely aberrant. The philosopher did not understand why one would opt to describe the timing of a significant event, such as the arrival of a train, in terms of how that event matched against a watch. He did not understand why Einstein tried to establish this particular procedure as a privileged way to determine simultaneity. Bergson searched for a more basic definition of simultaneity, one that would not stop at the watch but that would explain why clocks were used in the first place. If this, much more basic, conception of simultaneity did not exist, then “clocks would not serve any purpose.” “Nobody would fabricate them, or at least nobody would buy them,” he argued. Yes, clocks were bought “to know what time it is,” admitted Bergson. But “knowing what time it is” presupposed that the correspondence between the clock and an “event that is happening” was meaningful for the person involved so that it commanded their attention. That certain correspondences between events could be significant for us, while most others were not, explained our basic sense of simultaneity and the widespread use of clocks. Clocks, by themselves, could not explain either simultaneity or time, he argued.

If a sense of simultaneity more basic than that revealed by matching an event against a clock hand did not exist, clocks would serve no meaningful purpose:

They would be bits of machinery with which we would amuse ourselves by comparing them with one another; they would not be employed in classifying events; in short, they would exist for their own sake and not serve us. They would lose their raison d’être for the theoretician of relativity as for everybody else, for he too calls them in only to designate the time of an event.

The entire force of Einstein’s work, argued Bergson, was due to how it functioned as a “sign” that appealed to a natural and intuitive concept of simultaneity. “It is only because” Einstein’s conception “helps us recognize this natural simultaneity, because it is its sign, and because it can be converted into intuitive simultaneity, that you call it simultaneity,” he explained.5 Einstein’s work was so revolutionary and so shocking only because our natural, intuitive notion of simultaneity remained strong. By negating it, it could not help but refer back to it, just like a sign referred to its object.

Bergson had been thinking about clocks for years. He agreed that clocks helped note simultaneities, but he did not think that our understanding of time could be based solely on them. He had already thought about this option, back in 1889, and had quickly discounted it: “When our eyes follow on the face of a clock, the movement of the needle that corresponds to the oscillations of the pendulum, I do not measure duration, as one would think; I simply count simultaneities, which is quite different.”6 Something different, something novel, something important, something outside of the watch itself needed to be included in our understanding of time. Only that could explain why we attributed to clocks such power: Why we bought them, why we used them, and why we invented them in the first place.

- This Philosopher Helped Ensure There Was No Nobel for Relativity, Henri Bergson’s debate with Albert Einstein reached and swayed the 1921 Nobel committee

Why Do Living Things Die?

One of the best best piece I have read in a long long time - Physics Makes Aging Inevitable, Not Biology:

Four years ago, I published a book called Life’s Ratchet, which explains how molecular machines create order in our cells. My main concern was how life avoids a descent into chaos. To my great surprise, soon after the book was published, I was contacted by researchers who study biological aging. At first I couldn’t see the connection. I knew nothing about aging except for what I had learned from being forced to observe the process in my own body.

Then it dawned on me that by emphasizing the role of thermal chaos in animating molecular machines, I encouraged aging researchers to think more about it as a driver of aging. Thermal motion may seem beneficial in the short run, animating our molecular machines, but could it be detrimental in the long run? After all, in the absence of external energy input, random thermal motion tends to destroy order.

This tendency is codified in the second law of thermodynamics, which dictates that everything ages and decays: Buildings and roads crumble; ships and rails rust; mountains wash into the sea. Lifeless structures are helpless against the ravages of thermal motion. But life is different: Protein machines constantly heal and renew their cells.

In this sense, life pits biology against physics in mortal combat. So why do living things die? Is aging the ultimate triumph of physics over biology? Or is aging part of biology itself?

Wisdom Of The Week

Born was after a unifying theory to relate all the fundamental forces of nature. He also wanted a theory that would explain where these constants came from. Something, he said, to “explain the existence of the heavy, and light elementary particles and their definite mass quotient 1840."

It might seem a little bizarre that Born worried about a couple of constants. The sciences are full of constants—one defines the speed of light, another quantifies the pull of gravity, and so on. We routinely use these numbers, flipping to dog-eared tables in reference books, and coding them into our software without much thought because, well, they are constants. But the weird thing about such constants is that there is no theory to explain their existence. They are universal and they appear to be unchanging. So is the case with the masses of protons and electrons. But time and time again, they are validated through observation and experiment, not theory.

What Born and so many others were after was a unifying theory that would demonstrate that there could only be one unchanging value for a constant. Without this theory, scientists resort to testing limits of a constant. Measuring the constant is a good way to verify that theories using them make sense, that science stands on firm ground. Error from the measurements can be a huge concern. So, instead of validating the masses of protons and electrons, it's useful to measure the ratio of their masses, a number that is free of the burden of units.

The search for a unifying theory continued. Two years after Born's lecture, his Cambridge colleague, Paul Dirac, wondered in a Nature paper whether the constants were indeed constant if one were to look at the entire history of the cosmos. Measurements on earth are useful but it is a tiny blue dot in the vast universe. What Dirac asked decades ago is what physicists continue to ask today. Is it a constant everywhere in the universe? Why is it a constant? How constant? The question lingered even as the decades rolled on. “The most exact value at present for the ratio of proton to electron mass is 1836.12 +/-0.05,” wrote Friedrich Lenz in a 1951 Physical Review Letters paper. “It may be of interest to note that this number coincides with 6pi^5=1836.12.” That was the entire paper.

- Are the Constants of Physics Constant?

What I've Been Reading

In non linear systems-and the economy is most certainly nonlinear-chaos theory tells you that the slightest uncertainty in your knowledge of the initial conditions will often grow inexorably. After a while, your predictions are nonsense.

Complexity: The Emerging Science at the Edge of Order and Chaos by M. Mitchell Waldrop. I read this book last summer but was thinking for past four months on what to write. Still date, I have no idea how to summarize the importance of this book.

This is an unofficial biography of Santa Fe Institute - I learned so much from this book that it will me many life times to work on those ideas. This is one book, I have to re-read every few years.

“Here was this elusive "Santa Fe approach": Instead of emphasizing decreasing returns, static equilibrium, and perfect rationality, as in the neoclassical view, the Santa Fe team would emphasize increasing returns, bounded rationality, and the dynamics of evolution and learning. Instead of basing their theory on assumptions that were mathematically convenient, they would try to make models that were psychologically realistic. Instead of viewing the economy as some kind of Newtonian machine, they would see it as something organic, adaptive, surprising, and alive. Instead of talking about the world as if it were a static thing buried deep in the frozen regime, as Chris Langton might have put it, they would learn how to think about the world as a dynamic, ever-changing system poised at the edge of chaos.” 

When Can Quantum Annealing Win?

We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10**8 times faster than simulated annealing running on a single core. We also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This is a method designed to emulate the behavior of quantum systems, but it runs on conventional processors. While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 10**8.

While these results are intriguing and very encouraging, there is more work ahead to turn quantum enhanced optimization into a practical technology. The design of next generation annealers must facilitate the embedding of problems of practical relevance. For instance, we would like to increase the density and control precision of the connections between the qubits as well as their coherence. Another enhancement we wish to engineer is to support the representation not only of quadratic optimization, but of higher order optimization as well. This necessitates that not only pairs of qubits can interact directly but also larger sets of qubits. Our quantum hardware group is working on these improvements which will make it easier for users to input hard optimization problems. For higher-order optimization problems, rugged energy landscapes will become typical. Problems with such landscapes stand to benefit from quantum optimization because quantum tunneling makes it easier to traverse tall and narrow energy barriers.

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Ten Laws of the Physics of People

6. The Uncertainty Principle

The more you know about one topic, the stupider you become. Or, as my mom used to tell me, "never trust someone who has all the answers, especially yourself." Experts are dangerous, if they are not balanced by naive laymen. Diversity is more valuable than expertise.

Lesson: diversity is not a political slogan. It's the basis for collective intelligence.

7. Zipf's Law of Power Distributions
20% of any system always has 80% of the power. It applies to cities, languages, earthquakes, and economies. And organizations, and software systems. You'll spend most of your effort on a fraction of the software. Over-engineering code that isn't in the critical path is a waste of time.

Lesson: if shitty code solves the problem, it's not shitty code.

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