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What is science, how to begin a scientific journey and what constitutes scientific discovery along the journey?

From The Beautiful Cure: The Revolution in Immunology and What it Means for Your Health by Daniel M. Davis (Professor of Immunology with a Ph.D. in physics):

 “Science is many things. A method, a journey, a route to power, a body of knowledge, a thing you loved or hated at school, a jigsaw puzzle with an infinite number of pieces, a force for good and bad which has produced both food and bombs. Arguably, its greatest success has been, and will be for some time to come, in curing diseases.” 
 “How does anyone begin a scientific journey? By following tracks other have left behind, then branching off.” 

György Buzsáki Professor of Neuroscience:

“Major scientific discoveries typically become discoveries post hoc, after a long scrutiny by the community. Tools and methods are of course different; they have an instant impact. But recognizing the importance of critical insights and synthesizing thoughts require long incubation and maturation because they are not immediately clear to others and they are so easy to steal.”

What is "scientific method" and why it took so long (two thousand years after the invention of philosophy and mathematics) to discover it?

From The Knowledge Machine: How Irrationality Created Modern Science by Michael Strevens Professor of Philosophy:

 Scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens' book calls this scientific code the “iron rule of explanation,” and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “The iron rule of explanation,” by which modern science has accrued its enormous power,  requires scientists to settle arguments by empirical testing, imposing on them a common language “regardless of their intellectual predilections, cultural biases or narrow ambitions.” Individual scientists can believe whatever they want to believe, and their individual modes of reasoning can be creative and even wild, but in order to communicate with one another, in scientific journals, they have to abide by this rule. The motto of England’s Royal Society, founded in 1660, is “Nullius in verba”: “Take nobody’s word for it.” 
 Much of scientific research takes place under conditions of “intellectual confinement” — painstaking, often tedious work that requires attention to minute details, accounting for fractions of an inch and slivers of a degree. Strevens' book gives the example of a biologist couple who spent every summer since 1973 on the Galápagos, measuring finches; it took them four decades before they had enough data to conclude that they had observed a new species of finch. This kind of obsessiveness has made modern science enormously productive, but Strevens' book says there is something fundamentally irrational and even “inhuman” about it. Another example is discovery of thyroid-stimulating hormone (TSH) released by the brain to help control the thyroid gland, for which  1977 Nobel Prize in Physiology or  Medicine was awarded to Guillemin and Schally. Guillemin was working with 5 million hypothalamic fragments from sheep, and Schally with the same amount of material but from pigs. After years of struggle, during which the two groups established a formidable race, they stood there one day with 1 mg (!) of TSH.  “Nobody before had to process millions of hypothalami,” Schally said. “The key factor is not the money, it’s the will ... the brutal force of putting in sixty hours a week for a year to get one million fragments.” Strevens' book points out that focusing so narrowly, for so long, on tedious work that may not come to anything is inherently unappealing for most people. The single greatest obstacle to successful science is the difficulty of persuading brilliant minds to give up the intellectual pleasures of continual speculation and debate, theorizing and arguing, and to turn instead to a life consisting almost entirely of the production of experimental data. It is partly by generating data on such a vast scale that the  “iron rule of explanation” can power the knowledge machine—opinions converge not because bad data is corrected but because it is swamped.
Rich and learned cultures across the world pursued all kinds of erudition and scholarly traditions, but didn’t develop this “knowledge machine” until relatively recently. The same goes for brilliant, intellectually curious individuals like Aristotle, who generated his own theory about physics but never proposed anything like the scientific method. In 1713, Isaac Newton appended a postscript to the second edition of his “Principia,” the treatise in which he first laid out the three laws of motion and the theory of universal gravitation. “I have not as yet been able to deduce from phenomena the reason for these properties of gravity, and I do not feign hypotheses,” he wrote. “It is enough that gravity really exists and acts according to the laws that we have set forth.” What mattered, to Newton and his contemporaries, was his theory’s empirical, predictive power—that it was “sufficient to explain all the motions of the heavenly bodies and of our sea. Descartes would have found this attitude ridiculous. He had been playing a deep game—trying to explain, at a fundamental level, how the universe fit together. Newton, by those lights, had failed to explain anything: he himself admitted that he had no sense of how gravity did its work or fit into the whole; he’d merely produced equations that predicted observations. If he’d made progress, it was only by changing the rules of the game, redefining wide-ranging inquiry as a private pastime, rather than official business. And yet, by authorizing what Strevens calls “shallow explanation,” the iron rule offered an empirical bridge across a conceptual chasm. Work could continue, and understanding could be acquired on the other side. In this way, shallowness was actually more powerful than depth.”
Without the  “iron rule of explanation,” physicists confronted with a theory like quantum mechanics would have found themselves at an impasse. They would have argued endlessly about quantum metaphysics. Following the iron rule, they can make progress empirically even though they are uncertain conceptually. Individual researchers still passionately disagree about what quantum mechanics means. But that hasn’t stopped them from using it for practical purposes—computer chips, MRI machines, GPS networks, and other technologies rely on quantum physics. It hasn’t prevented universities and governments from spending billions of dollars on huge machines that further explore the quantum world. Even as we wait to understand the theory, we can refine it, one decimal place at a time.

Ethics in science

  • Categories of unethical behavior in science:
    • Plagiarism.
    • Falsification of data.
    • Redundant (duplicate) publication.
    • Drawing far-fetched conclusions without hard data, for early publicity.
    • Gift authorship (receiving as well as giving).
    • Ghost authorship.
    • Not giving sufficient attention and consideration to scholars and postdocs.
    • Self promotion at the cost of team-members.
    • Treating colleagues (overall all juniors) in a feudal way.
    • Machiavellianism (cunningness and duplicity in general conduct and push to positions of power and pelf).

Physics & Astronomy journals

News & Views

General Science

General Physics


Applied Physics

Nanoscience & Nanotechnology

Astronomy and Astrophysics

Space and Plasma Physics

Mathematical and Computational Physics

Physics Pedagogy

Navigating scientific literature via citations

Physics and Astronomy conferences and workshops

Major conferences repeated every year

Examples of summer schools and workshops

Student membership in professional organizations

Writing scientific papers

 Scientific writing is crafted using precise words and specialized terms tempered by fine subtleties that make each statement precise and nuanced. It 
is aimed to be read by other scientists (see Lecture 2 above), and therefore it often appears difficult and dense to general public. 

N. D. Mermin

LaTeX templates

LaTeX packages

  • Overleaf (Online LaTeX)
  • MikTeX (LaTeX implementation for Windows)
  • TexStudio (TeX Editor for Windows, Linux, or Mac OS)
  • JabRef (organizer for BibTeX references)
  • Beamer (LaTeX alternative to PPT)
  • QuickLaTeX (prepare LaTeX equation images for inserting into PPT talks)

Submission and peer review of scientific papers

Scientific presentations: Talks and posters

Designing talks

Giving talks

Designing posters


Cognitive psychology and cognitive neuroscience to keep in mind when giving talks and lectures

“Cognitive research shows that the amount of new material presented in a typical class is far more than a typical person can process or learn. 
People’s brains function in a way somewhat analogous to a personal computer with very limited random-access memory. The more things the brain is 
given to process at the same time – the cognitive load – the less effectively it can process anything. Any additional cognitive load, 
no matter what form it takes, will limit people's abilities to mentally process and learn new ideas. This is one of the most well-established and 
widely violated principles in education, including by many education researchers in their presentations. Cognitive  load  has  important  implications  
for  both classroom  teaching  and  technical  talks.  To  maximize learning, instructors must minimize cognitive load by limiting the amount of 
material presented, having a clear organizational  structure  to  the  presentation,  linking  new material  to  ideas  that  the  audience  already  
knows,  and avoiding unfamiliar technical terminology and interesting little digressions.”