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The Most Beautiful Equation: How Wilczek Got His Nobel
Frank Wilczek was one of three recipients of the Nobel Prize in Physics in 2004 thanks to his work researching the so-called strong force.
Frank Wilczek is an American theoretical physicist, mathematician and a Nobel laureate. He is currently the Herman Feshbach Professor of Physics at the Massachusetts Institute of Technology (MIT). Wilczek, along with David Gross and H. David Politzer, was awarded the Nobel Prize in Physics in 2004 for their discovery of asymptotic freedom in the theory of the strong interaction. He is on the Scientific Advisory Board for the Future of Life Institute. His new book is titled A Beautiful Question: Finding Nature's Deep Design.
Frank Wilczek: There are four fundamental forces of nature as we now understand it. There’s gravity and electromagnetism, which are the classic forces, which were known already in prehistory and known in some form to the ancient Greeks, but which had mature theories in the case of gravity already in the 17th century with [Isaac] Newton and in the 19th century with [James] Maxwell and very beautiful descriptions and, in case of gravity, made even more beautiful with [Albert] Einstein’s general theory of relativity in the early 20th century. But in the course of studying subatomic physics and what goes on at very, very short distances, people found they needed two additional forces — gravity and electromagnetism aren’t enough. And the two additional forces are called the strong and weak forces. What I got the Nobel Prize for was figuring out the equations of the strong force. And equally important not just guessing the equations, but showing how you can test them and see that they were right. This was something I did as a graduate student. I was, of course, working very closely with my thesis advisor, a very, very gifted and powerful physicist named David Gross. What — so how did we go about doing it?
Well there were some — the experimental situation regarding the strong interaction was very confused, desperately confused. There was no theory even remotely worthy of standing beside Newton’s theory of gravity or Einstein’s or Maxwell’s theory of electromagnetism. There were just a lot of rules of thumb and a lot of confusing data. What we did was focus on one particular phenomenon and try to understand just that. Putting off all other aspects of this confusing situation. The phenomena we tried to understand seemed so paradoxical, so crazy that we thought if we could understand that, we could understand anything basically. And also because it seemed so profound and fundamental. Actually David thought that we could prove that it couldn’t — that you couldn’t understand it within the standard framework of quantum mechanics and relativity. And that would be a very important result too because it would tell physicists they had to go back to the drawing board. This aspect that we were trying to explain was the fact that quarks, which were somewhat speculative, but a pretty clear indication of reality at that time — when they get close together they hardly interact at all. Or when they’re moving at very high velocity relative to one another, high energy, again they don’t interact very much at all.
But if you try to pull them apart a significant distance, which means, in this case, 10 to the minus 13 centimeters or more, or if they’re moving slowly then they have very, very powerful forces. In fact you can’t extract single quarks from matter. They always exist bound to one another inside protons and neutrons. So we needed a force which gets weaker at short distances and grows as the distance grows. That’s a very paradoxical and difficult thing to imagine and make consistent with the other laws of physics that we know. Now there were powerful mathematical techniques for investigating that kind of question that had been developed for other purposes called renormalization group. So we were able to bring those techniques to bear and address this question. And they were very difficult calculations. It wasn’t entirely clear that they were consistent, that you could actually do this kind of calculation in the kind of theory that was most beautiful, that we wanted to investigate. But we insisted on hoping that the most beautiful equations would be the right equations. And we found out that a very, very special class of theoretical constructions with tremendous amounts of symmetry could give you this behavior. So that was — I compare that to Archimedes saying that if you give me a lever and a place to stand, I can lift the world. Based on that kind of leverage given by the sort of basic principles and faith and symmetry and beauty plus this one fact about the forces getting weaker, we were led to quite a unique proposal for what the equations of the strong interaction should be.
And we could develop some consequences of those equations and then propose to experimenters that they go out and check whether these consequences are correct. Now it took several years afterwards before it became clear that those consequences we predicted were correct, but they are. And in subsequent years it’s become more and more clear the theory has been used for a wide variety of applications now with great success. The kind of thing that in the early days was called testing quantum chromodynamics or testing asymptotic freedom is now called calculating backgrounds. So it’s gone from being a glamorous exploration of new worlds to kind of taking care of the garbage. So I think you could look for more interesting things. But well although it sounds, in a way, it’s kind of a step down. If I look at it in the big picture, it’s glorious that you have a theory that was originally very speculative and just something that existed in our minds. And it’s gone now to being an absolutely accepted and basic part of our understanding of nature and a very beautiful one.
Frank Wilczek was one of three recipients of the Nobel Prize in Physics in 2004 thanks to his work researching the so-called strong force. In this video interview, the MIT physicist details his work with David Gross and the pursuit of an equation to rival Newton's gravity and Maxwell's electromagnetism.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
Vaccines find more success in development than any other kind of drug, but have been relatively neglected in recent decades.
Vaccines are more likely to get through clinical trials than any other type of drug — but have been given relatively little pharmaceutical industry support during the last two decades, according to a new study by MIT scholars.