The Nobel Prize in Physics 2021(nobelprize.org)
nobelprize.org
The Nobel Prize in Physics 2021
https://www.nobelprize.org/prizes/physics/2021/press-release/
112 comments
Parisi work on spin glasses already has some pretty mind bending mathematics. That continuous limit where the rank of a matrix goes to zero for example?
Can someone elaborate on on this?
Chapter 3 of this [0] might help a bit
[0] https://arxiv.org/pdf/cond-mat/0505032.pdf
[0] https://arxiv.org/pdf/cond-mat/0505032.pdf
+1 on the whole references as a nice introduction. I think the authors overstate the preparation of their hypothetical "pedestrian" (either that or they need to get away from the physics department a bit more often), but a great reference nevertheless. I also got a lot out of sections of Nishimori's textbook [1]. In particular it helps motivate problems outside of physics and provides some references to start digging into more rigorous approaches via cavity methods (which I think, incidentally, are also more intuitive). I am a novice in this area but am sort of crossing my fingers that some of the ideas in this area will make their way into algorithms for inferring latent variables in some of the upcoming modern associative neural networks. What I mean here is that it would be cool not just to have an understanding of total capacity of the network but also correct variational approximations to use during training.
[1] https://neurophys.biomedicale.parisdescartes.fr/wp-content/u... [2] https://ml-jku.github.io/hopfield-layers/
[1] https://neurophys.biomedicale.parisdescartes.fr/wp-content/u... [2] https://ml-jku.github.io/hopfield-layers/
Let me take a stab at this (I'll maybe take it halfway there). First of all we want to know what kind of matrix we are talking about.
Imagine that you have a whole bunch generative models (its best if you imagine a fully connected Boltzmann machine in particular, whose states you can think of as a binary vector consisting only of zeros and ones) that have the same form but different random realizations of their parameters. This is a typical example of what a toy model of a so-called "spin glass" looks like in statistical physics (the spins are either up down down, usually represented as +1/-1). Each of these models, having been initialized randomly will have their up particular frequency of a particular location (also called site) of the boolean vector being either a one or a zero.
If the tendency of a site to be either or one or a zero was independent of every other site the analysis of such a model would be pretty straightforward: every model would just have a vector of N frequencies and we could compare how close the statistical behavior of each model was to the other by comparing how closely the N frequencies at each site matched one another. But in the general case there will be some interaction or correlation between sites in a given model. If the interaction strength is strong enough this can result in a model tending to generate groups of patterns in its sequence of zeros and ones that are close to one another. Furthermore if we compare the overlap of the apparent patterns between two such models, each with their own random parameters, we will find that some of them overlap more than others.
What we can then do is to ask the question of how much, on average do the patterns of these random models overlap with on another in the full set of all models. This leads us to the concept of an "overlap matrix". This matrix will have one set of values along the diagonal (corresponding to how much a models patterns tend to overlap with themselves) and off diagonal values capturing the overlap between. You can find through simulation or with some carefully constructed calculations that when the interaction strength between sites is small that the off diagonal elements don't tend to zero, but rather a single number different from the diagonal value. This is perhaps intuitive: these models were randomly initialized but they are going to overlap in their behavior in some places.
Where things get interesting though is when you increase the interaction strength you find that the overlap matrix starts to take on a block diagonal form, wherein clusters of models overlap with one another at a certain level and at a lower but constant level with out-of-cluster models. This is called one replica symmetry breaking (1RSB). These different clusters of models can be thought of as having learned different overall patterns with the similarity quantified by their overalp. If you keep increasing the interaction strength you will find that this happens again and again, with a k-fold replica symmetry braking (kRSB) with a sort of self similar block structure emerging in the overlap matrix (picture is worth a thousand words [1]).
Now the real wild part that Parisi figured out is what happens when you take this process to the regime of full replica symmetry breaking. You can't really do this with simulations and the calculations are very tricky (you have a bunch of terms either going to infinity or zero that need to balance out correctly) but Parisi ending up coming up with an expression for the distribution of overlaps for the infinitely sized matrix with full interaction strength in play. The expression is actually a partial differential equation that itself needs to be solved (I told you the calculations were tricky right), but amazingly, it seems to capture the behavior of these kinds of models correctly.
Whereas mathematicians have a pretty good idea of how to understand the 1RSB process rigorously, the Parisi full replica symmetry breaking scheme is very much not understood and remains of interest both to complex systems researches trying to understand their models and applied mathematicians (probability people in particular) trying to lay the foundations needed to explore the ideas being explored by theorists.
Hope that helps a bit!
[1] https://www.semanticscholar.org/paper/Spin-Glasses%2C-Boolea...
Imagine that you have a whole bunch generative models (its best if you imagine a fully connected Boltzmann machine in particular, whose states you can think of as a binary vector consisting only of zeros and ones) that have the same form but different random realizations of their parameters. This is a typical example of what a toy model of a so-called "spin glass" looks like in statistical physics (the spins are either up down down, usually represented as +1/-1). Each of these models, having been initialized randomly will have their up particular frequency of a particular location (also called site) of the boolean vector being either a one or a zero.
If the tendency of a site to be either or one or a zero was independent of every other site the analysis of such a model would be pretty straightforward: every model would just have a vector of N frequencies and we could compare how close the statistical behavior of each model was to the other by comparing how closely the N frequencies at each site matched one another. But in the general case there will be some interaction or correlation between sites in a given model. If the interaction strength is strong enough this can result in a model tending to generate groups of patterns in its sequence of zeros and ones that are close to one another. Furthermore if we compare the overlap of the apparent patterns between two such models, each with their own random parameters, we will find that some of them overlap more than others.
What we can then do is to ask the question of how much, on average do the patterns of these random models overlap with on another in the full set of all models. This leads us to the concept of an "overlap matrix". This matrix will have one set of values along the diagonal (corresponding to how much a models patterns tend to overlap with themselves) and off diagonal values capturing the overlap between. You can find through simulation or with some carefully constructed calculations that when the interaction strength between sites is small that the off diagonal elements don't tend to zero, but rather a single number different from the diagonal value. This is perhaps intuitive: these models were randomly initialized but they are going to overlap in their behavior in some places.
Where things get interesting though is when you increase the interaction strength you find that the overlap matrix starts to take on a block diagonal form, wherein clusters of models overlap with one another at a certain level and at a lower but constant level with out-of-cluster models. This is called one replica symmetry breaking (1RSB). These different clusters of models can be thought of as having learned different overall patterns with the similarity quantified by their overalp. If you keep increasing the interaction strength you will find that this happens again and again, with a k-fold replica symmetry braking (kRSB) with a sort of self similar block structure emerging in the overlap matrix (picture is worth a thousand words [1]).
Now the real wild part that Parisi figured out is what happens when you take this process to the regime of full replica symmetry breaking. You can't really do this with simulations and the calculations are very tricky (you have a bunch of terms either going to infinity or zero that need to balance out correctly) but Parisi ending up coming up with an expression for the distribution of overlaps for the infinitely sized matrix with full interaction strength in play. The expression is actually a partial differential equation that itself needs to be solved (I told you the calculations were tricky right), but amazingly, it seems to capture the behavior of these kinds of models correctly.
Whereas mathematicians have a pretty good idea of how to understand the 1RSB process rigorously, the Parisi full replica symmetry breaking scheme is very much not understood and remains of interest both to complex systems researches trying to understand their models and applied mathematicians (probability people in particular) trying to lay the foundations needed to explore the ideas being explored by theorists.
Hope that helps a bit!
[1] https://www.semanticscholar.org/paper/Spin-Glasses%2C-Boolea...
I work with many physicists. They are some of my most beloved colleagues. But man, physicists! Amirite?
>That continuous limit where the rank of a matrix goes to zero for example?
What the fuck?
What the fuck?
> The Nobel committee, in their infinite wisdom, suggest as much.
Usually this phrase is used ironically, as in “they don’t know what the [expletive] they’re doing,” but the rest of your comment reads genuine. Because people seem split on this and because I don’t fully understand any of it, can you clarify one thing: are you throwin’ shade?
Usually this phrase is used ironically, as in “they don’t know what the [expletive] they’re doing,” but the rest of your comment reads genuine. Because people seem split on this and because I don’t fully understand any of it, can you clarify one thing: are you throwin’ shade?
it was a bit of an innocent joke really, just to spice up the comment by alluding to the known fact that the committees are occasionally criticized.
Granting Nobel prizes for science is not an exact science :-)
Granting Nobel prizes for science is not an exact science :-)
I think this is the first time I have seen the term 'infinite wisdom' used unironically.
y' = x - y (life is good)
y' = x - y^2 (PANICC!!)
y' = x - y^2 (PANICC!!)
I first learned about Manabe's works from the wonderful "The Discovery of Global Warming" project. Looking at the Nobel prize citation, they seem to consider his work on climate sensitivity (2 degrees for doubled CO2, obtained in 1967) the most important, but I think his work on coupled model of atmosphere and ocean was equally important.
It is interesting to note his own view. On climate sensitivity calculation: "it is not advisable to take too seriously". On coupled model: "I am very proud of it".
https://history.aip.org/climate/GCM.htm
It is interesting to note his own view. On climate sensitivity calculation: "it is not advisable to take too seriously". On coupled model: "I am very proud of it".
https://history.aip.org/climate/GCM.htm
The linked page (and the whole site) is totally worth reading, but it is probably too long, so here are some quotes. On climate sensitivity calculation:
> Wallace Broecker, who would later play a major role in climate change studies, recalled that it was the 1967 paper "that convinced me that this was a thing to worry about". Another scientist called it "arguably the greatest climate science paper of all time", for it "essentially settled the debate on whether carbon dioxide causes global warming". Experts in a 2015 poll agreed, naming it as the "most influential" of all climate change papers.
So Nobel committee was right to cite it. On the other hand, the author's "don't take it too seriously" comment should be taken seriously. 2 degrees value is spot on, but knowing what we know now, it couldn't be the right value for the right reason. The most important is that 1967 model had no ocean. (Manabe went on to make the first successful attack with ocean in 1969.) Another is lack of data. The following quote is pretty funny:
> Until satellite measurements became available later in the 1980s, most models used data from the 1950s that only gave averages by zones of latitude, and only for the Northern Hemisphere. Modelers mirrored the set to represent clouds in the Southern Hemisphere, with the seasons reversed -- although of course the distribution of land, sea, and ice is very different in the two halves of the planet.
I mean, mirroring? It is obviously wrong, but what can you do? Other than waiting for satellites and noting the result shouldn't be taken too seriously, that is. Now we have adequate data and model, it is proper to acknowledge great effort went into these pioneering works.
The last quote on amount of computation used (for 1969 paper). It was truly AlphaGo-scale computaiton of its time! It is interesting to note AlphaGo Zero trained for comparable time of 40 days.
> Their costly Univac 1108, a supercomputer by the standards of the time... Manabe and Bryan were confident enough of their model to undertake a heroic computer run, some 1100 hours long (more than 12 full days of computer time devoted to the atmosphere and 33 to the ocean).
> Wallace Broecker, who would later play a major role in climate change studies, recalled that it was the 1967 paper "that convinced me that this was a thing to worry about". Another scientist called it "arguably the greatest climate science paper of all time", for it "essentially settled the debate on whether carbon dioxide causes global warming". Experts in a 2015 poll agreed, naming it as the "most influential" of all climate change papers.
So Nobel committee was right to cite it. On the other hand, the author's "don't take it too seriously" comment should be taken seriously. 2 degrees value is spot on, but knowing what we know now, it couldn't be the right value for the right reason. The most important is that 1967 model had no ocean. (Manabe went on to make the first successful attack with ocean in 1969.) Another is lack of data. The following quote is pretty funny:
> Until satellite measurements became available later in the 1980s, most models used data from the 1950s that only gave averages by zones of latitude, and only for the Northern Hemisphere. Modelers mirrored the set to represent clouds in the Southern Hemisphere, with the seasons reversed -- although of course the distribution of land, sea, and ice is very different in the two halves of the planet.
I mean, mirroring? It is obviously wrong, but what can you do? Other than waiting for satellites and noting the result shouldn't be taken too seriously, that is. Now we have adequate data and model, it is proper to acknowledge great effort went into these pioneering works.
The last quote on amount of computation used (for 1969 paper). It was truly AlphaGo-scale computaiton of its time! It is interesting to note AlphaGo Zero trained for comparable time of 40 days.
> Their costly Univac 1108, a supercomputer by the standards of the time... Manabe and Bryan were confident enough of their model to undertake a heroic computer run, some 1100 hours long (more than 12 full days of computer time devoted to the atmosphere and 33 to the ocean).
The most fascinating physics nobel prize for me in recent times was for gravitational wave detection using LIGO. I spent days learning and watching videos of the three of them. The ingenuity of the detector is fascinating and the fact that every year they simply got closer but ‘not there yet’ and the fact that it took more than two decades says that the goal was probably secondary but they enjoyed the journey far more. Of course they would have hoped to see the waves be detected in their lifetime but for Kip Thorne it was 50 years from the start. Most of the stories behind Nobel prize winners are mind boggling.
These three propositions are all simultaneously true (in my opinion):
1) Every person who has ever received a Nobel Prize in physics has richly deserved it;
2) Culture and politics influence the awarding of the Prize;
3) Several people who did not get the Prize would have if they had not been women.
(3) is a corollary to (2). One example is Jocelyn Bell Burnell, who discovered pulsars. The Nobel Prize for that was awarded to two men.
1) Every person who has ever received a Nobel Prize in physics has richly deserved it;
2) Culture and politics influence the awarding of the Prize;
3) Several people who did not get the Prize would have if they had not been women.
(3) is a corollary to (2). One example is Jocelyn Bell Burnell, who discovered pulsars. The Nobel Prize for that was awarded to two men.
But at least in the case of Jocelyn Bell Burnell, even though she put in a lot of the legwork, it was her supervisors who did much of the theoretical work to explain the discovery. Also of note is that she agreed with the Nobel committee decision. From her Wikipedia page:
"First, demarcation disputes between supervisor and student are always difficult, probably impossible to resolve. Secondly, it is the supervisor who has the final responsibility for the success or failure of the project. We hear of cases where a supervisor blames his student for a failure, but we know that it is largely the fault of the supervisor. It seems only fair to me that he should benefit from the successes, too. Thirdly, I believe it would demean Nobel Prizes if they were awarded to research students, except in very exceptional cases, and I do not believe this is one of them. Finally, I am not myself upset about it – after all, I am in good company, am I not!"
"First, demarcation disputes between supervisor and student are always difficult, probably impossible to resolve. Secondly, it is the supervisor who has the final responsibility for the success or failure of the project. We hear of cases where a supervisor blames his student for a failure, but we know that it is largely the fault of the supervisor. It seems only fair to me that he should benefit from the successes, too. Thirdly, I believe it would demean Nobel Prizes if they were awarded to research students, except in very exceptional cases, and I do not believe this is one of them. Finally, I am not myself upset about it – after all, I am in good company, am I not!"
Yes, (1) is true even in this case. It’s not that her supervisors didn’t deserve to share in the prize, it’s that she should not have been excluded.
I know of her statements about the incident. I think she’s being modest, and I disagree with her idea that awarding the Prize to someone who happened to be a student during the time of discovery would somehow demean the Prize. Her work was as crucial as theirs. It wasn’t just “legwork”, she discovered the regular signals and recognized them as something new and important.
I know of her statements about the incident. I think she’s being modest, and I disagree with her idea that awarding the Prize to someone who happened to be a student during the time of discovery would somehow demean the Prize. Her work was as crucial as theirs. It wasn’t just “legwork”, she discovered the regular signals and recognized them as something new and important.
As for (1), Dalén's 1912 physics Nobel Prize for a regulator for lighthouse illumination seems out of place.
Although it's factual, many people put their fingers in their ear and scream when you mention point (2). I would extend that point to any prestigious award.
At least (1) is still true. Contrast the Literature and Peace prizes, which have truly become bad jokes.
To argue a bit I'd say that the science prizes have it a bit easier.
Here's the criteria that Alfred Nobel set out in his will[0] for the literature prize (kinda badly translated from 19th century Swedish): "one part to whom in literature have produced the most excellent work in an ideal direction".
You have had 18 members of the Swedish Academy debating what the hell that means since forever.
[0] https://www.nobelprize.org/alfred-nobel/alfred-nobels-testam...
Here's the criteria that Alfred Nobel set out in his will[0] for the literature prize (kinda badly translated from 19th century Swedish): "one part to whom in literature have produced the most excellent work in an ideal direction".
You have had 18 members of the Swedish Academy debating what the hell that means since forever.
[0] https://www.nobelprize.org/alfred-nobel/alfred-nobels-testam...
Hmmm. OK, that’s quite something to have to interpret.
Summary Pr. John Wettlaufer https://www.youtube.com/watch?v=Ezsbf42_RTA&ab_channel=Nobel...
Physicists developed a whole bunch of tools to find the base energy levels of spinglasses, which were repurposed in the past 10 years as general purpose solvers for NP hard combinatorial optimization problems (by converting them to QUBO format, which is equivalent to the Ising format in spinglasses). There are pros and cons to them, but it opened a whole new area in optimization, currently multiple companies are building custom hardware QUBO solvers (D-Wave, NTT, Fujitsu, Hitachi, ...)
Nice thread on Giorgio Parisi by Montanari: https://twitter.com/Andrea__M/status/1445405295811960841?s=2...
Manabe (and a lot of other people!) really figured out the control dials on climate back in the 1970s The basic science on carbon dioxide and climate was settled by 1979, and ExxonMobil's scientists agreed internally, as recent revelations demonstrate (1). Everything since has mostly been fine-tuning and improved resolution due to computational technology advances. There has been a huge political effort to discredit this science ever since, by the fossil fuel industry and affiliated interests, since they have huge finacial interests in maintaining the current energy supply system - so, the science got politicized.
Let's take a look at the general concept though, from Manabe et al.'s 1975 paper (2):
> "The atmospheric part of the model incorporates the primitive equations of motion in a spherical coordinate system. The numerical problems associated with the treatment of mountains are minimized by using the “sigma” coordinate system in which pressure, normalized by surface pressure, is the vertical coordinate. For vertical finite differencing, nine levels are chosen so as to represent the planetary boundary layer and the stratosphere as well as the troposphere. For horizontal finite differencing, the regular latitude-longitude grid is used. To prevent linear computational instability in the time integration, Fourier filtering is applied in the longitudinal direction to all prognostic variables in higher latitudes such that the effective grid size of the model is approximately 500 km everywhere."
So, let's note that this general approach is applicable to planets like Mars and Venus as well as Earth. There is no ocean on those planets, however, but the atmospheric radiative-convection model approach is identical. Mars has something like 1% of Earth's surface pressure, Venus has 90X that pressure, but the same approach works. It's even applied to the gas giants. Note that 9 layers in the model is quite simple relative to modern models.
> "For the computation of radiative transfer, the distribution of water vapor, which is determined by the prognostic system of water vapor, is used. However, the distributions of carbon dioxide, ozone and cloudiness are prescribed as a function of latitude and height and assumed to be constant with time. The temperature of the ground surface is determined such that it satisfies the condition of heat balance."
Here's another key point - water vapor is modeled as a feedback, CO2 is modeled as a forcing. About 2/3 of radiative forcing in the atmosphere is due to water vapor, but that water vapor increases due to CO2 forcing (which has greatest effect higher in the atmosphere, closing windows that would allow IR to escape to space). This was verified by the Pinatubo explosion incidentally, in which predictions about water vapor feedback were highly accurate (3).
> "The prognostic system of water vapor includes the contribution of three-dimensional advection of water vapor and condensation in case of supersaturation. To simulate moist convection, a highly idealized procedure of moist convective adjustment is introduced. The prediction of soil moisture and snow depth is based upon the budget of water, snow and heat. Snow cover and sea ice are assumed to have much larger albedos than soil surface or open sea, and have a very significant effect upon the heat balance of the surface of the model."
So, that's the albedo effect, and as the poles melt albedo drops and you get more warming. You also get polewards heat transfer. Thus these scientists predicted warming at poles would be much faster than warming at equator, and that's been proven as well. Cloud feedbacks introduce a certain degree of variability, but definitely don't change the overall conclusions (see MIT's Richard Lindzen for that worn-out fossil-hyped argument if you like).
Now, I'll stop here but note that Manabe's other great contribution was linking the atmospheric model to the rather more difficult ocean circulation model. This allowed quantification of the lag effect, i.e. ocean warming absorbs a great % of the atmospheric forcing but warmer oceans warm the atmosphere and so on.
Incidentally, none of this would be at all controversial if human civilization had exhausted global fossil fuel reserves by 1980 and renewable adoption had been forced by necessity.
It's rather interesting though - science was once completely accepted by industry, but then scientific advances began undermining business profits - the discovery of industrial carcinogens, the discovery of fossil-fueled global warming, etc. really changed the dynamic and accurate science became as much of a threat to established interests as it was a boon.
[edit sources]: 1. https://www.climatefiles.com/exxonmobil/1978-exxon-memo-on-g...
2. https://journals.ametsoc.org/view/journals/phoc/5/1/1520-048...
3. https://www.science.org/doi/pdf/10.1126/science.296.5568.727
Let's take a look at the general concept though, from Manabe et al.'s 1975 paper (2):
> "The atmospheric part of the model incorporates the primitive equations of motion in a spherical coordinate system. The numerical problems associated with the treatment of mountains are minimized by using the “sigma” coordinate system in which pressure, normalized by surface pressure, is the vertical coordinate. For vertical finite differencing, nine levels are chosen so as to represent the planetary boundary layer and the stratosphere as well as the troposphere. For horizontal finite differencing, the regular latitude-longitude grid is used. To prevent linear computational instability in the time integration, Fourier filtering is applied in the longitudinal direction to all prognostic variables in higher latitudes such that the effective grid size of the model is approximately 500 km everywhere."
So, let's note that this general approach is applicable to planets like Mars and Venus as well as Earth. There is no ocean on those planets, however, but the atmospheric radiative-convection model approach is identical. Mars has something like 1% of Earth's surface pressure, Venus has 90X that pressure, but the same approach works. It's even applied to the gas giants. Note that 9 layers in the model is quite simple relative to modern models.
> "For the computation of radiative transfer, the distribution of water vapor, which is determined by the prognostic system of water vapor, is used. However, the distributions of carbon dioxide, ozone and cloudiness are prescribed as a function of latitude and height and assumed to be constant with time. The temperature of the ground surface is determined such that it satisfies the condition of heat balance."
Here's another key point - water vapor is modeled as a feedback, CO2 is modeled as a forcing. About 2/3 of radiative forcing in the atmosphere is due to water vapor, but that water vapor increases due to CO2 forcing (which has greatest effect higher in the atmosphere, closing windows that would allow IR to escape to space). This was verified by the Pinatubo explosion incidentally, in which predictions about water vapor feedback were highly accurate (3).
> "The prognostic system of water vapor includes the contribution of three-dimensional advection of water vapor and condensation in case of supersaturation. To simulate moist convection, a highly idealized procedure of moist convective adjustment is introduced. The prediction of soil moisture and snow depth is based upon the budget of water, snow and heat. Snow cover and sea ice are assumed to have much larger albedos than soil surface or open sea, and have a very significant effect upon the heat balance of the surface of the model."
So, that's the albedo effect, and as the poles melt albedo drops and you get more warming. You also get polewards heat transfer. Thus these scientists predicted warming at poles would be much faster than warming at equator, and that's been proven as well. Cloud feedbacks introduce a certain degree of variability, but definitely don't change the overall conclusions (see MIT's Richard Lindzen for that worn-out fossil-hyped argument if you like).
Now, I'll stop here but note that Manabe's other great contribution was linking the atmospheric model to the rather more difficult ocean circulation model. This allowed quantification of the lag effect, i.e. ocean warming absorbs a great % of the atmospheric forcing but warmer oceans warm the atmosphere and so on.
Incidentally, none of this would be at all controversial if human civilization had exhausted global fossil fuel reserves by 1980 and renewable adoption had been forced by necessity.
It's rather interesting though - science was once completely accepted by industry, but then scientific advances began undermining business profits - the discovery of industrial carcinogens, the discovery of fossil-fueled global warming, etc. really changed the dynamic and accurate science became as much of a threat to established interests as it was a boon.
[edit sources]: 1. https://www.climatefiles.com/exxonmobil/1978-exxon-memo-on-g...
2. https://journals.ametsoc.org/view/journals/phoc/5/1/1520-048...
3. https://www.science.org/doi/pdf/10.1126/science.296.5568.727
As with the NP for Med/Physio it is unfortunate that the trope of "saving the planet" has such a vile revival. And if I'm not for the one team I'm for the other.
Irrespective of that this years NP in Physics is an achknowledgment of a "young" (in terms of NPs) but promising field.
For anyone interested, I found this podcast very informative:
https://www.preposterousuniverse.com/podcast/2020/08/17/110-...
Irrespective of that this years NP in Physics is an achknowledgment of a "young" (in terms of NPs) but promising field.
For anyone interested, I found this podcast very informative:
https://www.preposterousuniverse.com/podcast/2020/08/17/110-...
The climate and environment are critically important, as everyone knows from daily front page disasters that will increase.
I have a PhD in physics and have made sustainability my mission. I wish I didn't have to as fixing problems past generations stuck us with isn't my first passion, but I can't change the past.
As important as the science was to get us here, we have to move to the next stage, which is leadership. I don't mean just passing laws. Even prior to our twin problems of overconsumption and overpopulation, the damage we're suffering is the physical manifestation of our values, especially material growth, extraction, efficiency, externalizing costs, and comfort and convenience. Technology, innovation, laws, and markets augment those values. As long as we hold them as a culture and individuals, we will innovate technologies, laws, and markets that exacerbate the problem.
I will always support more research and value these scientists' work that enabled us to get past the science to restoring our values of stewardship: personal growth, enjoying what we have, humility to nature, resilience, responsibility for how our behavior affects others, meaning, purpose, and the satisfaction of a job well done. With those values, we will innovate solutions that increase Earth's ability to sustain life.
Again, as important as the science is, we must restore our personal and cultural values to solve the problems science revealed. That's leadership and teamwork. We can all act immediately. Since systemic change begins with personal transformation, the fastest, most effective way to change governments and corporations is to act here and now, learn from the experience, act more, and lead others to join.
I have a PhD in physics and have made sustainability my mission. I wish I didn't have to as fixing problems past generations stuck us with isn't my first passion, but I can't change the past.
As important as the science was to get us here, we have to move to the next stage, which is leadership. I don't mean just passing laws. Even prior to our twin problems of overconsumption and overpopulation, the damage we're suffering is the physical manifestation of our values, especially material growth, extraction, efficiency, externalizing costs, and comfort and convenience. Technology, innovation, laws, and markets augment those values. As long as we hold them as a culture and individuals, we will innovate technologies, laws, and markets that exacerbate the problem.
I will always support more research and value these scientists' work that enabled us to get past the science to restoring our values of stewardship: personal growth, enjoying what we have, humility to nature, resilience, responsibility for how our behavior affects others, meaning, purpose, and the satisfaction of a job well done. With those values, we will innovate solutions that increase Earth's ability to sustain life.
Again, as important as the science is, we must restore our personal and cultural values to solve the problems science revealed. That's leadership and teamwork. We can all act immediately. Since systemic change begins with personal transformation, the fastest, most effective way to change governments and corporations is to act here and now, learn from the experience, act more, and lead others to join.
"I have a PhD in physics and have made sustainability my mission. I wish I didn't have to as fixing problems past generations stuck us with isn't my first passion, but I can't change the past."
Somehow, I don't think you'd have a PhD in physics had the industrial revolution never occurred.
Somehow, I don't think you'd have a PhD in physics had the industrial revolution never occurred.
It's encouraging to see that the second part to Parisi (completely unrelated to the first) is still non-political.
The first is hardly political either. Most people simply don't want to admit that the science of carbon dioxide and climate was figured out by the late 1970s and everything since has been fine-tuning the models and improving their resolution.
meister0(4)
Can anyone with more insight into the three researchers explain if this is a political statement or if their work really represents the best physics research? I am genuinely asking as I don't know much about their research.
Is it unreasonable to suggest that maybe it could be both a reflection of politics and world class scientific achievements?
To suggest that the prize is given simply in order to make a political statement seems like an insult to both the academy and the laureates. Besides, wouldn't it be just as bad to avoid awarding a prize that is politically sensitive, even though the actual science may well be prize worthy?
It's fine to not consider a laureate a worthy winner, for sure, but it's not like they gave the Nobel prize in physics to Greta Thunberg..
To suggest that the prize is given simply in order to make a political statement seems like an insult to both the academy and the laureates. Besides, wouldn't it be just as bad to avoid awarding a prize that is politically sensitive, even though the actual science may well be prize worthy?
It's fine to not consider a laureate a worthy winner, for sure, but it's not like they gave the Nobel prize in physics to Greta Thunberg..
It's a defensible suspicion given the other prize that shares the name "Nobel."
High profile prizes will always be political. That said, Syukuro Manabe built the foundation for a lot of modern day computer-based climate simulation. I can't speak for the others but I'd say that's Nobel worthy.
I don't know how you would meaningfully rank physicists without resorting to subjective value judgements. The notion of importance exists only in relationship to our ability to accomplish our goals, and goals are subjective.
The same can be said of any attempt to measure 'merit'. Whatever is called 'meritorious' is simply so because of cultural and historical happenstance.
> computer-based climate simulation
I'm no scientist by any stretch of the imagination, the last time when I read something related to higher physics was ~20 years ago, in college, but I have to ask how is that topic related to modern physics. You're correct, it sounds like like a worthy Nobel for an Earth Sciences Nobel, or a Meteorology one (to be more direct), if those two things existed (maybe they should), but, again, don't know how meteorology (what computer-based climate simulation basically is) is the same thing as higher physics.
I'm no scientist by any stretch of the imagination, the last time when I read something related to higher physics was ~20 years ago, in college, but I have to ask how is that topic related to modern physics. You're correct, it sounds like like a worthy Nobel for an Earth Sciences Nobel, or a Meteorology one (to be more direct), if those two things existed (maybe they should), but, again, don't know how meteorology (what computer-based climate simulation basically is) is the same thing as higher physics.
As a physicist, I try to avoid the snobbery of limiting myself to "higher physics". A wide variety of physical systems are interesting, not just fundamental particle physics. Physics contains multitudes; graphene, giant magnetoresistence, fiber optics, and systems more complex.
But then again physics risks following the (wrong) road taken by economics a while ago, when it decided that almost all modern human-activity can be in fact studied through the economics lens.
Surely studying the climate, i.e. a physical system, is completely in the realm of physics. Certainly, it is closer to whatever definition of physics you may have, than education or kidney donation (to take two examples) are to economics.
Meteorology is a sub-branch of physics.
There is a level of politics that shreds credibility though. I am just struggling to see how someone gets a physics Nobel for modelling a climate system. Climate isn't new, climate models have been getting better for decades and will continue to. The work may be important and well done, but it doesn't sound like it is pushing the boundaries of physics.
The tag line sells it really poorly.
The tag line sells it really poorly.
Below is a quote from the press release we are discussing:
> In the 1960s, he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.
As far as I understand (I am not a physicist), you're right: climate is not new, and climate models have been getting better for decades. And that's (in part) because of this guy's work, half a century ago. It sure pushed the boundaries of physics at the time, didn't it?
> In the 1960s, he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.
As far as I understand (I am not a physicist), you're right: climate is not new, and climate models have been getting better for decades. And that's (in part) because of this guy's work, half a century ago. It sure pushed the boundaries of physics at the time, didn't it?
It doesn't sound like it from that tagline either, it makes it sound like he discovered that sunshine makes air move around. Which is also not news on the scale of the Physics nobel.
Obviously he discovered something a lot more noteworthy than that, but these one line summaries are doing a terrible job of hinting at what.
Obviously he discovered something a lot more noteworthy than that, but these one line summaries are doing a terrible job of hinting at what.
Manabe contributed many pivotal works to the broad domain of planetary and atmospheric physics in the 1960's. The word "model" in reference to his work is substantially more than just computer simulations; really, it's referring to some of his seminal contributions providing "models" in the sense of physical frameworks for understanding the responses and evolution of planetary atmospheres (broadly speaking - with relevance far beyond the terrestrial atmosphere) to particular forcings. See Manabe and Weatherald (1967) [1] for perhaps one of the most critical contributions that he made.
[1]: https://journals.ametsoc.org/view/journals/atsc/24/3/1520-04...
[1]: https://journals.ametsoc.org/view/journals/atsc/24/3/1520-04...
The Nobel Prize does not — and cannot reasonably — highlight the "best" physics research, because it is not possible to directly say one discipline is superior or more important than another. Rather, the Nobel features different disciplines in different years.
In this context, it's important to recall that the development of modern climate science is one of the most significant developments of 20th-century physics, and before this year, no Nobel Prize had been awarded for climate science. Similar prizes were awarded for the development of the integrated circuit and the light-emitting diode, and in these cases almost nobody finds it to be in the slightest untoward that the Prize is awarded in relation to the social impact of the work. (There are always a few crotchety purists, but more people pretend to be so when it suits them.)
So yes, awarding the Nobel for climate science is a political decision. Not awarding the Nobel for climate science would also be a political decision. In this context, it appears that the recipients are two of the most influential early theorists of climate science, who did their work decades ago.
The Nobel committee has no choice but to be politicized when science is politicized. They handled it admirably.
In this context, it's important to recall that the development of modern climate science is one of the most significant developments of 20th-century physics, and before this year, no Nobel Prize had been awarded for climate science. Similar prizes were awarded for the development of the integrated circuit and the light-emitting diode, and in these cases almost nobody finds it to be in the slightest untoward that the Prize is awarded in relation to the social impact of the work. (There are always a few crotchety purists, but more people pretend to be so when it suits them.)
So yes, awarding the Nobel for climate science is a political decision. Not awarding the Nobel for climate science would also be a political decision. In this context, it appears that the recipients are two of the most influential early theorists of climate science, who did their work decades ago.
The Nobel committee has no choice but to be politicized when science is politicized. They handled it admirably.
Hasselmann deserved it. Hasselmann model is stochastic climate model that explains red noise. https://onlinelibrary.wiley.com/doi/10.1111/j.2153-3490.1976...
I don't know much about Manabes work but he is a pioneer in climate modelling.
ps. Climate science is political only because those who don't believe in science politicize it.
ps. Climate science is political only because those who don't believe in science politicize it.
Politicizing it has almost nothing to do with whether or not it is believed, it is politicized when it has value on a political scale. Saying Country A has lower impact on the climate than Country B and therefore A should limit its production of weapons and infrastructure that rely on factories and industries that produce harmful chemicals is very obviously of value to a politician
The fact people think anyone should believe in science speaks to how political many scientific subjects have become so political.
Imagine if scientists just "believed" science and never tried to reproduce. Belief is an awfully terrible trait to have in science.
Imagine if scientists just "believed" science and never tried to reproduce. Belief is an awfully terrible trait to have in science.
> Imagine if scientists just "believed" science and never tried to reproduce.
You're mixing up scientists-as-individuals with scientists-as-a-whole.
Scientists-as-a-whole should certainly reproduce results, both to check new claims, and to teach/learn/demonstrate old knowledge.
Scientists-as-individuals need belief, since there's no way to indivudally reproduce everything. For example, climate models rely on decades of measurements from Earth-observation satellites; if scientist shouldn't "believe", how would they go about reproducing those measurements for themselves?
Even if individual climate scientists began each of their projects by building and launching their own satellites to take decades of observations (which would lag behind existing data, in any case), how would they calibrate the instruments on those satellites (e.g. without "believing" in the zeroth law of thermodynamics)?
You're mixing up scientists-as-individuals with scientists-as-a-whole.
Scientists-as-a-whole should certainly reproduce results, both to check new claims, and to teach/learn/demonstrate old knowledge.
Scientists-as-individuals need belief, since there's no way to indivudally reproduce everything. For example, climate models rely on decades of measurements from Earth-observation satellites; if scientist shouldn't "believe", how would they go about reproducing those measurements for themselves?
Even if individual climate scientists began each of their projects by building and launching their own satellites to take decades of observations (which would lag behind existing data, in any case), how would they calibrate the instruments on those satellites (e.g. without "believing" in the zeroth law of thermodynamics)?
Individuals have to trust scientific community.
In principle, every individual could spend 10 years to learn the subject, then comb trough the evidence in one particular detail. That's not possible in reality.
Even climate scientists have to trust other climate scientists in details they are not experts in. Climate chemist has not checked 3D computational model and vice versa.
It is said that Thomas Young (1773 – 1829) was the last man who knew everything. He was a polymath who had studied most of human knowledge in detail.
In principle, every individual could spend 10 years to learn the subject, then comb trough the evidence in one particular detail. That's not possible in reality.
Even climate scientists have to trust other climate scientists in details they are not experts in. Climate chemist has not checked 3D computational model and vice versa.
It is said that Thomas Young (1773 – 1829) was the last man who knew everything. He was a polymath who had studied most of human knowledge in detail.
Isn’t that the problem? Because for most people, believing in it is the only option? They don’t have the tools or the ability to either refute nor confirm it.
Isn't trying to reproduce a part of believing science? It seems that you're loving less than half of it otherwise
No, verification is not belief. You can believe in the methodologies I suppose, but that is not what is being said when people say "believe in science". They are saying "believe in the findings from people you haven't met who have credentials", which is nothing more than a nonsense appeal to authority.
If a subject is important to someone, they should try their best to understand the research and to more fully understand a claim, one would do well to research with a heavy dose of skepticism in everything, especially things that affirm their own bias.
If a subject is important to someone, they should try their best to understand the research and to more fully understand a claim, one would do well to research with a heavy dose of skepticism in everything, especially things that affirm their own bias.
That's not true. On the "believing" side, Al Gore certainly politicized it.
No, Gore merely made a movie that a lot of people saw, the politicisation (in the sense of wilfully ignoring science results for partisan reasons) was started in the 1990's by oil companies and republicans looking to kill they Kyoto protocol.
You can say so only if you believe that reality is constructed, like some French postmodernist philosophers do.
If you think there is some ground truth in hard sciences, and science community provides best approximation of it, then "other side too" argument is not valid. Al Gore educated, only climate dentists politicized.
If you think there is some ground truth in hard sciences, and science community provides best approximation of it, then "other side too" argument is not valid. Al Gore educated, only climate dentists politicized.
Here is a nice summary: https://twitter.com/thePiggsBoson/status/1445334496857841668
Rather than reading what tech/science writers can summarize on a lap (remember, they only learned the laureates' names a hour ago or so), I prefer to simply head over to YouTube and look for a lecture given by a laureate themselves. Most likely, Nobel is not their first prize and they have given a lecture summarizing their lifetime contributions before. Plus, it's always more pleasure to listen to nice people than reading Twitter :)
You can also find a nice PDF summary of their contribution on the Nobel Prize website itself, including a popular version : https://www.nobelprize.org/uploads/2021/10/popular-physicspr...
I don't know the other two, but Parisi is definitely a star in his field.
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The fact that you think that climate change is a "political" topic speaks volume about the success of the right wing propaganda machine.
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It is obvious that the committee decided they wanted the prize to be about climate change this year before the selection process began, or it never would have shaken out this way.
How is it obvious?
I guess first stathibus defined that anything that indicates the reality of climate change is part of one big conspiracy, and then "obviously" this event is part of that?
Tell me you're way out of your depth without telling me you're way out of your depth
Looks like this part is political:
“for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming”"
And this part is actual science: “for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales”
And this part is actual science: “for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales”
> Looks like this part is political: “for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming”
All this is saying is that the predictive models they devised were proven correct given climate behavior today, e.g rise of temperatures and a general uptrend in severe weather activity that followed.
All this is saying is that the predictive models they devised were proven correct given climate behavior today, e.g rise of temperatures and a general uptrend in severe weather activity that followed.
He predicted 0.57C of warming by the year 2000, and we saw 0.54C of warming. So accurate at least according to that.
https://twitter.com/hausfath/status/1445359093905084417
https://twitter.com/hausfath/status/1445359093905084417
nope.
before you ask me for sources, you haven't provided any, and you're quoting from a release with sources.
before you ask me for sources, you haven't provided any, and you're quoting from a release with sources.
Taking a look at Syukuro Manabe on Google scholar, one will find that his most cited work is decades old. They could have given him the prize years ago or years from now. Climate change being the biggest topic currently certainly was a contributing factor to the decision.
Manabe's work was predictive. It's only in recent years when we've started seeing those predictions come true.
Less "politics" and more "hey his models were right."
Less "politics" and more "hey his models were right."
That's how the scientific Nobel prizes work. The average delay between discovery and award for recent Physics prizes is over 25 years, and gaps of 40+ years are not uncommon.
That is often the case with the Nobel prize though. Higg's most cited paper was also many decades old before he got the Nobel prize.
The point your comment makes is one I imagine you have not grasped - the basic science of climate and CO2 was figured out by the late 1970s. Everything else since has been fine-tuning.
For example, if you go back to the early 1950s this was not well known, and you had theories about how variations in the tides controlled climate and so on.
P.S. Exxon scientists knew in 1978 that the science was accurate, and yet their executives spent millions of dollars for decades lying about it - and are still at it.
For example, if you go back to the early 1950s this was not well known, and you had theories about how variations in the tides controlled climate and so on.
P.S. Exxon scientists knew in 1978 that the science was accurate, and yet their executives spent millions of dollars for decades lying about it - and are still at it.
Psychohistory by Hari Seldon
It's not politically motivated, it's "existentially" motivated.
Especially when world leaders ridicule the problem and dismantle efforts to fight it [1].
[1] https://www.bbc.com/news/world-us-canada-51213003
Especially when world leaders ridicule the problem and dismantle efforts to fight it [1].
[1] https://www.bbc.com/news/world-us-canada-51213003
These are worthy winners of the Nobel Prize, but it also seems like we’re starting to see the science Nobels enter the Culture War.
Say rather that the climate denialists have used politics to attempt to discredit science, thus politicizing, for their own purposes, the results of research.
Two of these awards seem like virtue signaling for climate change and global warming, topics which exploded in media and politics this year.
I personally believe that global warming and climate change are the most pressing issues facing humanity, but I oppose the politicization of prestigious award platforms. It's simultaneously obnoxious and unfair to the other candidates.
We see the same thing happen in racially-charged atmospheres for artistic awards.
I personally believe that global warming and climate change are the most pressing issues facing humanity, but I oppose the politicization of prestigious award platforms. It's simultaneously obnoxious and unfair to the other candidates.
We see the same thing happen in racially-charged atmospheres for artistic awards.
The work of Parisi (and quite a few others) in the eighties (non-linear systems, chaos theory, attractors, universality of power laws etc) have given us a first glimpse of what lies beyond, but a true revolution is still in the future and will require some pretty mind-bending mathematical inventions.
Making serious progress is not just intellectually challenging, it is also of immense practical relevance for us understanding and moderating our impact on the biosphere. The Nobel committee, in their infinite wisdom, suggest as much.