Hello and welcome to NewsClick. Media magnate Rupert Moldock's News International is in the news recently for the closure of its sensational tabloid News of the World. The tabloids phone hacking ways in the United Kingdom had created a massive public outcry and that forced the tabloid to close after a long run. So, to discuss with us Moldock, Moldock in the doc and Moldockization of the media in general we have with us, it is 79 million, the editor of the popular media watchdog website The Hoot. Thanks for coming on to NewsClick. In one sense Moldock's ways of sensationalizing news, his ways of dominating the media empire has been called into scrutiny after this news of the world scandal. But some say it's just a blip and soon it will be business as usual. Do you think so as well? No, see Moldock has a huge empire, all of which is not news. And his news empire, I think Britain was, even though it counts for very little financially, Britain was his biggest area of influence. In Britain certainly he will take a beating. His plans for television, just the fact that he has to call off his bid for B Sky B is a hit, it's a major hit. Also because of the 9-11 angle, his other influential news base was the US and we don't know how that's going to unravel in the future. But overall I think Moldock is too big and has to diversified an empire to be financially affected too much by this. What's more profound about this episode is that it's not just about paying of law enforcement agencies and so on and so simply the fact that Moldock has been able to buy off or rather threaten off political pressure or by the virtue of his papers being sold the most in the country and he's being able to set the agenda in some sense. That's true of what Moldock's news channels in America is doing for example. Not entirely, the three huge mainstream networks. Fox is simply a counter to them. But at the same time Moldock's networks actually push a very deeply right with the agenda. They push a conservative agenda. Yeah, especially in the UK for example and they have even been able to manipulate antagonistic political parties, the Labour Party for example by subverting it from within by supporting Tony Blair and so on and so forth. The question however is do you think such a trend is also visible in India or just an exaggeration? India is different, it's huge. There's no question of any one media empire having influence on any one ruling party. There are several which who are equally influential. Also in India, the political parties themselves have started majorly getting into acquiring media. So they don't depend entirely on the commercial media for their influence peddling. But the form of agenda building that we see in the UK and the US you think doesn't happen in Indian media? You know in the Indian media there's a huge amount of diversity. For every Hindu there is a pioneer. So there are ideological counterpulls. There's television which simply does its own market thing. So you can't influence it beyond a point. But having said that certain I mean except for honorable exceptions you know coverage of let's say the economic crisis from the point of view of Labour and the peasantry increase scrutiny on the corporates that seems to be lacking to a certain extent. No that's that it is true that they scrutinize politicians much more than they scrutinize corporates partly because largely because of the influence of advertising because all of our media is hugely dependent on advertising. But the fact remains that even that as you know it's every time something breaks then you can't ignore it beyond a point. So if there's a radio kind of episode then industrial houses will come under scrutiny and for every guy who doesn't scrutinize them somebody else will because we've had a huge growth and diversification of the media. Another aspect of the Muldakification you can use that term is that there is a blurring of the lines between news coverage, editorializing and advertisement that's at least visible in the Muldak press. Now in some sense some newspapers in the country do follow. See we don't have I don't think in India we had to look to Muldak to commercialize. I mean the Times Group has done its own thing you know if they commercialize or if they start selling news or they set any other trend which is highly questionable in terms of ethics then I don't necessarily think inspiration for that was got from Muldak I don't think selling news is done by you know. The way papers were structured is that news and editorial were different you know departments in one sense but you find in editorialization is creeping into news and the interest of the proprietor and the advertisers actually reflected in the editorial pages and so on and so forth. Now that necessarily might not be drawn from Rupur Muldak alone but he is seen as you know embodying that trend in one sense. He's seen as contributing to sensationalization. Foxification is I mean you know the Fox news brand is seen as where you turn very aggressive and you blur the line between comment and news. So all of that we are seeing here. We are seeing it in channels like Times Now and then we also have other channels which stick to a more basic news formula. Muldak I mean he is owner of a large media monopoly and we see certain I mean even though diversification is there in the Indian press and the Indian media there is also a trend towards monopolization in terms. There is cross ownership but and you know it becomes a problem in a place like Tamil Nadu where you have a political ownership which is highly influential and then he has newspapers as well as television as well as radio and so the scope for it is there at a national level it's unlikely to be simply because there's so many players and simply because the country is so huge and has so many regional dimensions to it. It is unlikely to be but we need to have cross media restrictions and law makers have not been able to come up with good solutions.  No for you know in regions you need cross media because you know the Sakshi TV in Andhra Pradesh you have TV you have newspaper they're huge they have a lot of money it's political. When you have TRS and you know Telangana again they have their own newspaper now and their own channel so partly because it's politically owned you certainly need cross media restriction. When you have a political party controlling various forms of this thing then you get bombarded with only one form of opinion. Then you have another political party but where is the space then for non-political news which can hold its own against the money that's being poured and everybody else is a viable media thing they don't you know they don't have other money. But is there also commercial danger I mean this is also danger from the commercialization of this process I mean in the sense that because of cross ownership because certain media groups are quite huge so they are able to subsidize other. Yeah I mean obviously times TV channels don't make money or at least certainly times now doesn't make money but you know the paper is so wealthy so when you yeah they are able to subsidize a voice in another media. So Mr. Murdoch by the way never made any money either you know on a lot of his newspapers you know. So what is the lesson that you think the Indian press gets out of this incident. Well first of all you must understand that the Indian press is not operating in a similar society we do not have red top tabloids in this country even if we have tabloids they are what is known as black top you don't have these kind of sensational things you don't have a society which permits prying or you don't have owners who would put large sums of money into hack anybody's phone or to buy off you know so we don't have that culture. So I think that we don't need to try and apply but yes the cross media thing is we've been reminded of it in other ways also we need cross media regulations and possibly in some centers if not all over.


OK, I think we can start. So hello, everyone. And welcome to the Latin American Webinar for Physics, number 54 of this series of these Latin American Webinars on Physics. So my name is Nicolás Bernal, and I'm from the University Antionariño in Colombia in Bogota today. So speaker today is Omar Miranda from CIMBE staff in Mexico. And he will talk about the perspective in physics beyond the standard model and coherent elastic-neutron-nucleon scattering experiments. And so we are super glad to have him today as our speaker. So first, let me remind you guys that you can be part of the discussion, writing questions and comments via the YouTube live chat system. And OK, now I'll hand you over to Omar. So are you there? Yes, yes, here I am. Thank you very much for the invitation. As Nicolás said, I would like to talk about these perspectives in physics beyond the standard model in the case of coherent elastic-neutron-nucleon scattering. The outline of the talk is the following. First, I will discuss what is this coherent elastic-neutron nucleonucleon scattering. And then I will talk about the perspectives that we have in some aspects of physics beyond the standard model. For example, nonstandard interaction and also the sterile-neutrino hypothesis and the reactor anomaly. If there is time, I will talk also about another aspect that is the neutrino-magnetic moment and with mixing angle possibilities. And finally, I will give my conclusions. As you can see here, I have advertised some of my work. So I think Omar, can you share your screen, please? Oh, sorry. Oh, I should start again, right? Sorry, sorry, sorry. Share. Is now correct or not yet? OK, share. Wow. Yes, now we should infinity. Yes, maybe I should start again. I think it's OK. You just have to select the right, exactly. OK, OK. So well, I will. I won't say the title again of the talk, but I would like to say that this is the outline. And also, here I mentioned the recent articles that I have been working on. But along the talk, I will try to cover more than just these three articles. I will talk about, especially about very important results by the Coherent Collaboration, a group of experimentalists that have done a very good job in detecting, for the first time, this scuttle. And I will also talk about a different work by other people that have also contributed a lot in this interesting topic. So these are just three articles, but I will try to be more general and to cover more information than this. And I will give, of course, all the references in any transparency. So let me start by this Coherent Elastic Neutrino-Nucleus Scattering and tell you what is the main idea of this Scattering. And the main idea is that if you have an incombinant trino that somehow heats an nucleus, you can have an scattering. But the point is that this nucleus is made of several protons and neutrons. However, if you go to a very low momentum transfer, then your wavelength somehow increased. And at some moment, you can see or the neutrino see and feels the nucleus as a whole. So in principle, there should be not only a recall of a proton or of a neutron inside the nucleus, but a recall of the nucleus as a whole due to this coherency. This was discussed more than 40 years ago by Friedman in this article. And this is just one way to present or to write the differential cross-section for this scattering. So as you can see here, there is a factor that is the nucleus mass. So this cross-section depends on the whole mass of the nucleus. And this makes that this cross-section is enhanced by this effect of coherency. So this is very attractive because in principle, you have a cross-section that is huge in comparison, for example, with a cross-section of an isolated proton. It's scattered off by a neutrino. This is very good, but of course, there is a problem that the maximum recoil of this nucleus depends on this formula that has this mass in the denominator. And that means that in reality, we are talking about very low energy regime, quite below a mega electron volt in the recoil. Therefore, this is quite difficult to detect. And somehow it was considered as an interesting result, but maybe not possible to realize at those times. However, later with the development of detectors, especially thanks to the dark matter problem, where many technologies to go to effectively to this low energy regime in order to detect dark matter candidates, this technology was making a lot of progress. And at some moment, it was realized that it could be possible to detect also this reaction. So maybe more than 10 years ago, it was realized that this was possible to really be detected in practice. Here is this cross-section I showed some coupling constants. And here, I have written down the specific values. So the actual coupling will depend on the spin of the nucleus. And there is this difference between the spin up and spin down here. So therefore, this actual coupling is negligible in comparison with the vector coupling. So it is expected that we only have a vector contribution. And of course, there is a form factor that depends on the nuclear physics. But in principle, for low q square, the dependence is very mild. And this form factor will tend to what? Depending on the energy. But in general, it is expected to have a very little influence. And if you see this, what is the expression for these two small g's here, you can see that gp depends also on the weak mixing angle. But this part is close to zero in comparison with this other part. So in principle, one can do some approximations and end up with this differential cross-section that also then also the important part is that you have this dependence on the mass of the nucleus. And this dependence on the recoil of the nucleus. So as I told you, for many g's, it was realized that this was possible. One of the maybe first ideas about how to, there were others, but one are very important. It was to use a cesium iodine detector that is sketched here. I took this from this report by Cohen in collaboration from a couple of years ago. And from the very beginning, they planned to put this detector in an expalation neutrino source. That is, there is a proton beam that hits a target produce pions that this pions decay, produce neon neutrinos. And later on, the neon also decays and then you have also a neon anti-neutrinos and electron neutrinos. So the proposal, as you can see, is not only that they will locate this detector, but several detectors along a corridor here. But this was the first detector. And as I told you this year in August, they presented in this article in Science the result of the first measurement of this coherent scatter. So here you can see the signal that it is expected to be made by these three neutrino types. So this is a great achievement by this collaboration. And as you can see, after more than 40 years, it was finally detected. And it was a big effort, especially to construct or to build a detector with such a low energy pressure. So the expected value from the computation was this in this dashed line with this error bar. And these are somehow the counts or the kind of scores that they found for the signal. So it is in good agreement with the expectation. So of course, just to detect this was a great achievement, but there are many other implications that come from this detection. At the moment, this error bar is big, as you can see. Sorry, I cannot listen to the question. No, that was not a question. Let's move back, sorry. OK, so I continue, right? So this was an achievement by this collaboration. There are many other collaborations that are also planning to detect this coherent scatter and also this coherent collaboration is planning to improve not only this detector, but to put other detectors in the spatial neutrino source. And as I told you, there are also many implications that come from this measurement. Since the errors are big, at the moment, the constraints that one can imply are maybe not so strong, but it is expected that it will improve a lot. So first, I will talk about the implications from nonstandard interactions. So in this nonstandard interaction picture, in general, one expects that besides the standard model Lagrangian, due to the effect of physics beyond the standard model, there may be additional contributions that are kind of similar in the structure to the standard model, model of Fermi constant, but also these corrections will be, in principle, small and modulated by this parameter epsilon. So in this picture, one tries to constrain phenomenologically any additional interaction that can appear in a process. And this interaction, in principle, can be translated into a specific model beyond the standard model later on. So for example, in solar neutrino data, it was found, well, we know that there is a resonance effect due to this relation, this MSW effect. But if one considers nonstandard interactions, there is an additional dependence on these nonstandard parameters. And this can even produce an additional solution to the usual LMA solution of the solar neutrino data. This was discussed more than 10 years ago. But this kind of situation continues. And there have been recent studies updating this result. And recently it was also proved that this problem was actually not possible to solve if one considered only neutrino oscillation experiments. And it was pointed out that the only solution for this could come if one can constrain these parameters, like this, but in experiments that are measuring directly the interaction of the neutrino. And therefore, this coherent scattering sounds as a very interesting place to test this interaction. So in that case, this differential cross-section, if we consider nonstandard interactions, is changed a little in the values of the coupling constants. And here, I put how these coupling constants are modified, depending on the different parameters that we consider. Since we have here several parameters, there could be a correlation or a degeneracy among them. So in general, there will be a linear dependence here between these two parameters. That depends on the number of protons and neutrons that the specific target contains. If one do two different experiments with two different relations for protons and neutrons, then you are somehow moving in different lines. And therefore, you can remove the degeneracy. So the coherent collaboration already put a constraint on these parameters, that is this blue line. You can see this, as I told you, this dependence, this linear correlation here along this line. But you have this very good constraint that is already a first result that was published in the same article by Cogin collaboration and has been also studied in more detail in these other references. But as you can see, there is this correlation of this dependence. It was also pointed out that if you use different detectors to go to different targets, for example, these two lines will be tilted, one line here until they are a little bit tilted. And then you can remove the degeneracy. And in this, we did this for a very hypothetical case of a very streamed resolution, very good resolution. But you can get very good constraint and remove the degeneracy of this correlation. This was also discussed later on by Solver. And it has been re-analyzed for different targets. And somehow the result is more or the expectation is more or less the same. That in future, especially using different detectors, they can constrain these parameters and therefore get a very good constraint, very competitive with any other experiment just by combining these different detectors using the same coherent reaction. So for example, here is the reference. There is another reason one here, more or less in the same direction. And this shows how these experiments are a good complement to other experiments like oscillation experiments. So this is the expectation for non-standard interaction. And there are other applications, like sterile neutrinos, for example, that can be analyzed. So also recently, there is another prepping where they try to get some constraint directly from the recent coherent signature. The constraint is not very good for sterile neutrinos for the region, but it is already a first constraint that is a good result. And I would also like to discuss the perspective for future experiments that can use reactor anti-neutrinos in combination with coherent scattering detectors. So a little bit about the reactor anomaly, just to remind, many people have already discussed about this problem. There are very nice reviews about this. And as you know, there is a kind of discrepancy between the expected or theoretical anti-neutrino flux from reactors and the measurements at very short distances. Here I show, for example, this article by Carlo Gionti. And this is a more recent analysis where, again, there is a region where probably this discrepancy, this few percent discrepancy, can be explained due to an oscillation of the electron anti-neutrino into an sterile state. There are many experiments using inverse beta decay that are trying to test this region. Dan's already have some result. And in general, they use inverse beta decay to test this. And actually, another possibility is that this problem can be solved not by the sterile hypothesis, but also it can be solved if one considers, if one from how to normalize, let's say, or recalibrate the anti-neutrino flux. For example, this uranium-235 fuel can be decreased just by a factor of 5%. And then you maybe can solve this problem. These are the two options. So in any case, the current status is that the sterile signature is there. And it needs to be approved of discard. So most of the experiments use inverse beta decay, but maybe we can use also coherent scattering in a different energy regime with a different technique to also test this problem. So we can consider this usual probability, survival probability in the presence of an sterile mass-against state, and compute the expected number of events for a given detector located at some distance from a reactor. So we have done this for different experimental proposals. For example, Connie is a collaboration that already has some detectors in Angra II reactor in Brazil. They are considered a threshold of very low, as you can see here, the threshold, very low, threshold of 28 electron balls. And they already are running at 30 meters from the reactor. But they are running with a kind of prototype. But still, they plan to increase this detector and get up to a kilogram of CCD detectors, solution, would be the target. And you can see here that this is the best fit for this sterile signature. And you can see here that, depending on the efficiency, they can be sensitive to this point. But for sure, if they really get to this kilogram detector, they can put a constraint on at least a part of this region. So this is very promising experiment that is already running. And also, there is another collaboration, this red-hundred collaboration, that uses a very different technology with a synod detector. This is, again, a technology that comes also from these dark matter experiments. And they have this plan to put this detector in the Kalinin nuclear power plant. The threshold is relatively high. But still, they can be sensitive to at least a part of the reactor spectrum. And they expect to have a huge mass. So this will be a very good point for them to have a good statistics and maybe be sensitive to the whole region. Here I put two different distances because they plan to put this again in a corridor. And therefore, they can move this detector in principle to different distances, like these two. And you can see the spectatives in this case are also very promising. Also, there are another collaboration, one of the first proposals in this direction, that is the texano collaboration in Taiwan, that also plans to detect coherent scattering using a germanium detector with maybe a hundred electron volts of a threshold. And again, depending on the details of the detector, they could be more sensitive or less sensitive if in this pessimistic case. But in general, they can also test the interesting region for the sterile signature. And the same happens for a different collaboration, this minor collaboration, that is planning to use a non-commercial reactor. And the interesting point here is that this reactor is different. And therefore, they can put the detector at a distance that is very close to the reactor. And since it is very close, they will have a different signature in the sense that the distance is different. And also, the flux can be increased. And also, they have the sensitivity. And the sensitivity will depend, of course, on the efficiency, let's say, but also on the distance that they finally determined to use. OK, but as I told you, maybe the solution to this problem is not that we have an sterile signature, but we have just a correction in the, for example, in an overall factor of 5% here for some of the fuel. So what would happen in that case for these experiments? Here I show some blue dots that are here, this and this, for example, or this here there is another one. There are three blue dots here, and two here, and there are other blue dots here. They represent the rate in comparison to the usual theoretical flux, the rate that would be detected in the case that there is a correction in this factor, or only a 5% decrease of a particular fuel. In that case, it is natural to see that irrespectively of the distance that we locate, where we locate the detector, the rate will be constant. Here, here, for example, and here. However, if we have the sterile signature as the solution, this rate will be different depending on the location of the detector. So in principle, for example, in the case of this Red Hundred experiment, if you really can't put the experiment and run the experiment in two different distances, obviously you can be more sensitive to the sterile signature, or to disprove the signature. So in that case, it would be also interesting that these experiments could also give additional information about this sterile problem. So if you notice here, this is again the sketch of the coherent collaboration plan for future. And here you can see that they also plan to use different detectors located at different distances. So in principle, the same exercise could be done for this coherent proposal for the future. Let's see. So I will comment just a little bit about the magnetic moment that is also another aspect that can be improved through a coherent scattering. So in principle, this neutrino magnetic moment in the standard model is quite small. But there are some models of physics beyond the standard model that could enhance the value of this neutrino magnetic moment. And currently, the constraints are at the order of 10 to the minus 11 for magnetons here. So any signature of a neutrino magnetic moment of a relatively large neutrino magnetic moment would be somehow a signature of new physics. And in general, the cross-section for this neutrino magnetic moment is inversely proportional to the recoil of the nucleus. Therefore, these low energy experiments are somehow the right place to look for constraints. So in the case of coherent scattering, for example, for the coherent collaboration, we made some time ago the spectatives for a combination of different detectors that they could use in this corridor. And you can see that there are some spectatives to really get some constraint. From this published result, some people, maybe Cosmos and Papulias, already put some constraint. But it is still not in this region. But it is already possible to constrain something. The weak mixing angle that is an important parameter in the standard model could be also tested in these proposals. Although the errors here are big, in comparison, for example, with, I don't know, with LEF or other collider measurements. However, it is important to notice that these measurements are in the low energy regime where there are not so many measurements in this parameter. So it could be interesting also. This is the same spectative of the measurement for the weak mixing angle, but for the case of the germanium detector in a reactor flux. So you can see here that there are different directions where this coherent scattering can be useful. So there are recently more articles that are getting more constraints or more information thanks to this new measurement. I could not cover all of them. But the main idea is that finally this reaction has been observed by this coherent collaboration. There are already some information that can be obtained from this. And there will be more measurements by coherent collaboration, by other collaborations. And in the future, they will give, of course, more and more information that could be complementary and very important for neutrino physics and will be an additional information besides the oscillation experiments. So that is the main idea that I wanted to tell you. I hope it was interesting for you. So thank you for your time. Thank you, Omar, for this super interesting talk. This is a round of questions. But first, I will remind you guys that you can ask questions to Omar via the Google Q&A system and via our YouTube website. So I don't know if there are questions. Let's start with the audience here. OK, well, I have a question for you, Omar. If you go back, for instance, to your slide, I think it was 37 or something like this. Yeah, exactly. For this kind of plot, I was kind of confused. So how can I read this plot? So these two lines, 100% and 50% are the efficiencies? Yes, yes. Somehow we don't, this is a proposal for the future. And we don't know exactly how well they will measure the signature. So in order to have an idea for, let's say, to put a very optimistic and a kind of pessimistic case, we just put two different efficiencies that translate into different statistical errors. And this will make that the constraint will be better or worse. So somehow we should expect that the constraint will be somehow in the middle. We don't know where, but somehow here. Sorry, this moves. And since you asked this, I will also talk about this other case where we, here again, we have these efficiencies. But also there is another interesting point and also kind of problematic for these experiments that sometimes it's difficult to translate the measure recall energy into a kind of recall energy that you really control and know in detail. So in general, in many of these cases, you know very well the recall of the electrons, but not the relation of these with the energy recall of the nucleus. So sometimes this collaboration, for example, reports this electron equivalent. A measurement that you don't know very well how to translate into the recall energy of the nucleus. So this recall could be 100 or, for example, 4 or 500 electron volts. And this blue line here, that is kind of even worse case, taking into account that not only the number of events can be different, but also the threshold can be not so optimistic as in the original proposal. So at the end, since the experiment is not running yet, you don't know where will be the constraint, but you expect that it will be somewhere in this region. OK, thanks a lot. So are there more questions? Herman? OK, let me ask a question. So I was wondering if this measurement will, at some point, give any info on the axial mass appearing in neutrino quasi-elastic scattering. So I don't know if there can be any kind of interplay between the types of scattering. So you say the axial mass, right? Sorry, could you repeat me the question because I got a little bit. Yeah, no, no. So I mean, basically, I more or less understand that when you consider quasi-elastic neutrino scattering, you have this issue of determining this axial mass for the scattering model. So I was wondering if this could provide any valuable info. Honestly, I haven't thought about it, and I don't know the answer. So maybe I will think about it, and I will, in any case, I'll do a message too. OK, thank you. So another naive question because it was a completely naive question. Here's another one. So usually when you do oscillation experiments, you take for granted that there is a model for the Earth density, right?  So I was wondering if these measurements can provide any information for these Earth density models. For the moment, these here, the distances are in the very short baseline. So we are talking about one meter to 30 meters. So in that case, it is expected that there is no dependence somehow on any matter effect for these particular experiments. So therefore, there is no information in this case. So of course, this is kind of, how to say, any experiment has some advantages, but also some disadvantages. So one of the disadvantages here is that you don't have this Earth effect, or you don't have any information about oscillation other than this sterile case. OK, thank you. You're welcome. OK, can you hear me now? Yes. Yes. OK, well, my question that actually the question, maybe the first one is very stupid, from these experiments, I don't know if you infer that all the neutrinos need to have mass. Because you measure differences in masses, but not sure if you can have one mass less than three in all of them, because it always is between two, no? Yeah, yes. In these experiments, I think you don't have any sensitivity to the absolute mass. Only in the case of the sterile, you can have sensitivity to the difference, to the square mass difference. And I have another question. And it's regarding, well, you use these nuclear power plants for the source of the neutrinos. But how reliable is the number of neutrinos that you produce? I mean, because, well, maybe this discrepancy system. Yes. They control this number. Yes, that is a whole issue in this problem. Somehow, people is now thinking about this. And in that sense, the idea of having a detector that you can move to different distances or different detectors in different distances can be maybe more reliable in some sense than the theoretical prediction of the flux. Because you are right that this prescription for the flux, it has been a theoretical effort. But maybe we are not understanding the flux quite well. So because of that, one way to discriminate this problem of the flux with the sterile signature could be just to have different distances in order to calibrate somehow. And this is an idea that is also being used by Dan's experiment, that they are also discrepancy in a power plant. And they are using a corridor also to move the detector and somehow get a result that is independent of the uncertainties in the flux. OK, thank you. You're welcome. Excellent. Are there more questions? I have one question. Yes. OK. Hi, Omar. You discussed neutrino magnetic moments, right? Yes. And at the beginning of your talk, you were also the collaboration has measured this coherent elastic neutrino scattering, right? Yes. So what is the impact of this new measurement on what we know about the neutrino magnetic moments? Ah, OK. Yeah, for the moment, this collaboration made a first measurement. And as you can see here. No, I cannot see it. Wait, where? The error is still big. So for the moment, there is a constraint recently. It has appeared maybe last week. But it is not a very strong constraint yet. But it is a second. Is there a constraint on what? Sorry? On the neutrino magnetic moment. But maybe it is 10 to the minus. I don't remember. It's maybe 10 to the minus 9 or 10 to the minus 8 for magnetons. That is not competitive yet with the current constraints. But of course, it is expected that in the future, with more data, the constraint will be better. OK. Then I have a second question. Yes? So along the same lines. So I mean, it's known that if neutrinos are majorana particles instead of dirac, then the magnetic moments satisfy some inequalities. So how far are we from testing this with this experiment? I guess very far. But just to have an idea. Yes. Yes, somehow I think that to test these inequalities, what we would need somehow will be to really detect a signature of neutrino magnetic moment. So in that case, you can maybe have an idea of the majorana nature. But of course, we are far because first, we need to have the positive result, let's say. I think this is my impression. I have not studied any qualities in detail. But my impression is that first we need to have some really kind of result in order to say something about the nature. But this is really one of the interesting points of the neutrino magnetic moment that they can have information about the dirac or majorana nature of the neutrino. Thank you. Maybe we have now a last question. So it doesn't seem to be the case. So I get a normal question. So let's thank Omar again and all our viewers. And we'll meet next week for another Latin American webinar on physics that will be next Wednesday. OK. So thanks a lot. Hope to see you next week. Bye, guys. Bye.


Russia wants to mine grain corridor in the Black Sea. The United Kingdom has stated that following their intelligence information, Russia intends to install sea mines in the path of civilian vessels carrying Ukrainian grain for export. It is noted that Russia may continue to target civilian shipping in the Black Sea, including laying sea mines on the approaches to Ukrainian ports. The UK believes Russia is trying to endanger civilian vessels passing through the Ukrainian humanitarian corridor to deter Ukrainian grain export, allowing Russia to pressure the Ukrainian economy. Russia aims to refrain from openly causing the sinking of civilian vessels instead, falsely laying blame on Ukraine for conducting any attacks on civilian vessels in the Black Sea. The UK published information on the land mines to prevent any such incident. We are committed to ensuring Ukraine can continue to export its agricultural produce through all appropriate routes, including its humanitarian corridor, overland and via the Danube, UK said. The world is watching, and we see right through Russia's cynical attempts to lay blame on Ukraine for their attacks. We and our allies stand united against Putin and his attempts to harm Ukraine and thus harm the rest of the world. UK Foreign Secretary James Cleverly said, The UK authorities noted that Russia damaged 130 port infrastructure facilities in the cities of Odessa, Charnomarsk and Rennie after withdrawing from the Black Sea Grain Initiative. The Russians destroyed nearly 300,000 tonnes of grain that would be enough to feed over 1.3 million people for a year.


Okay Okay, so I've got to stay here frozen in place So I wasn't quite sure what to present At this meeting, but I think that especially given what Stephanie will be talking about later on this afternoon Where she's presenting some results about how looking at the archaeological record can inform our current thinking About how to go forward. I thought it might be worth presenting some results that I did several years ago now With my great collaborators there my price Tim Kohler Brendan Tracy. I'm Hedgemer Schmauer and J1 Shin On looking at a data set that was actually collected by somebody else Peter Turchin who's somewhat a big controversial figure and Analyzing it a bit more carefully there were comments made this morning about you know, the old platitude that All models are wrong, but some are useful There are some important consequences of taking that kind of message to heart that I'll be presenting in this talk And if there's time remaining at the end, I would like to Basically point at a bunch of approaches a bunch of mathematical tools That Stephanie is also involved with that have that would provide hopefully a way and we think to go much much more Much much more sophisticated in terms of these analyses and could also be applied a far far more wild are widely Okay, and so I'm actually more comfortable if people ask me questions during the talk so long as it doesn't get out of hand So if there's anything here that's not very clear, please let me know so First off, I'm Peter Turchin with a group of about 51 other Archaeologists got together about five years ago to collect a data set to Create a data set by collecting data that Extends over ten thousand years all six inhabited continents all civilizations and just start analyzing it Ultimately he Peter does have motivated reasoning He's got a he has a hypothesis about what is driving history that he wants to use this data to actually confirm He and he's recently come out of picking up with a paper in science advances That's using a little bit more sophisticated and a little bit more updated version of this data set Where that's one of the major lessons that he is drawing But credit where credit is due this on project this data set that he Curated and brought together is an amazing thing and they did a very good first statistical analysis but there's a lot of Extra things that one can discern from the data and that's what we'll be talking about today So first I'm going to go into what this data is and then later on I'm going to be talking about a more this You got more information from this data Here's the PNAS paper as you can see as I promised. It's about 50. I think 51 maybe Archaeologists these are people who had expertise in different specific civilizations in different times so one of them is a expert in the Khmer civilization for example another one is an expert in Peru ancient Peruvian civilizations There's another one who's an expert in Latium the Latium plane and so on so forth. So they there was a consensus reached on how exactly to quantify a set of about 45 characteristics of The civilization that is their expertise Every single one of them came up with these 45 numbers for the civilization that's theirs expertise and then the data was brought together and There was these are the civilizations. They were total of 30 that they ended up Putting it together into this data. You can see here are their locations all across the planet and What they did was they took the original those what they call those natural geographic areas there's lots of Crude attempts to correct for statistical biases and how they formed this data set in the first place They threw out a lot of data to try to actually make there be things like uniform coverage To a Bayesian to someone who's anal retentive about such things like I am you never ever no matter what throw out data All data is at worst Useless, but if you're careful in your statistics, it'll never actually be something that you don't want to know about But in any case it makes sense to be quite honest for a first approach, but they did so they settled on those 30 national geographic areas, which I just showed you a hundred year time slices From the beginning of the agriculture Far back is 9600 BCE depending on the actual quality in question to very very close to the modern period And so what you had here is very very important is longitudinal data sets. It's not cross-sectional It's longitudinal you can watch different civilizations. The reason that's so important is that different civilizations? So to speak had different birthdays So if you just take a cross-section of a group of people who have very very different ages and try to discern something about Dynamics of an individual Humans lifetime you're basically screwed you want to be able to track individual humans And that's what they were doing in this data set and they called it the session data set They are one thing that they did. I think it's on this next slide Yes, so they took the 51 Different variables and they then here's one of the first hacks They actually Collapsed them down to what they called nine complexity characteristics These were the nine variables that they then I'm sent it to their Subsequent statistical analysis and you can see here what those nine variables are so for example in infrastructure They were a bunch of binary that variables And do you have markets or not? Do you have full food storage now? But a lot of these variables actually had small number of numeric Values for example, it could be ports. How big was your port? Irrigation different ways of quantifying the sophistication of the irrigation and so on and so forth They had substantial problems that they had to finesse because a lot of there were things like not only choosing which There is to ignore as I mentioned but also to deal with missing data They know civilization can you actually fill all 51 variables to all these one century time slices? So they use as technique that standard and statistics, but it's frankly junk called imputations And what I'll be pointing to at the end of the talk. Hopefully is how you can use Fitting of data sets with the longevity on dynamics that completely circumvents that issue. So anyway Then the okay, so here's the way that they started I can carp about it, but the truth be told it's a very reasonable first pass of what you're going to be doing with this data set All these decisions that they made Then they got a result which frankly I was 100% convinced has to be wrong Every historian ever knows that this is junk, but it was true They did just a principal component analysis The dumbest possible thing you can do to the entire data set in the space of a nine complexity characteristics and They found that the first principal component so it's people who don't know that's just your visit fitting a single Gaussian to your data and The first principal component the major ellipse of this Gaussian Which is actually about equally loaded on all of those nine complexity characteristics. So it's not just ending up being one of them It explains over 70% of all the variability So you can just look at that one direction in nine-dimensional space essentially Point to yourself and this is like a historian's version of that T-shirt with a picture of the Milky Way galaxy saying you are here. You can just point to where you are on that one axis and say this is where your civilization is and Civilizations all moved from low PC one values from low values of that principal component to higher ones Absurd this is like the revenge of Toynbee or something like that. Everybody knows this can't be true So the first thing that I did was I tried to dive into the data and find mistakes, but it's legit Here's as I say the loading of that first seven principal components again in the nine-dimensional space Here is some cross-validation kinds of things that they did one of the rather powerful natural experiments as economists some we'll talk about instrument of variables is something called the Atlantic Ocean You can compare New World to Old World and in these Times that this data is collected from you're pretty sure that they were completely independent And you can actually see that the same phenomenon is going on in the New World in the Old World So this is actually human civilizations The experiment was done twice Okay, let's see what we got here. Yep. That's as I was just saying the held out data for in the North America And for those of you who are history junkies It's actually you can just spend it hours and hours looking at the actual data and what it's showing So here are just some examples to sort of wet your appetite Here's the years and here is that principal component that first one that explains almost everything and here is upper Egypt and the middle Yellow River Valley and as you can see there are obviously fluctuations and here are some other civilizations Susiana the catchy plane. I think that's actually Kyoto narrow Latium that's much of a contains where we are right now, but it's certainly Rome So Diana so Oxford River civilization and so on and as you can see there are many major fluctuations down fluctuations Well, whether the fluctuations or not there are many Dips downward in PC one with time So it's not that PC one exactly equals time But nonetheless it does seem to be something that basically you can view it as a measure of the complexity of A civilization, you know, this is something that sociologically you are not supposed to say that one Society is more developed than another one, but to be quite honest the PC one value plays that role a lot So and here's just how they go with time Alright, so now I'm going to be taking those results of Peters, which so I went through this paper Confirm that boy. It really does seem to be legit. How can we take it further? So principal component analysis Here is an example It's a simple sine wave and if you were to do a principal component analysis So you're going to try to fit that data with a single Gaussian You will find that the first principal component is this red line and the second one is the green line This red line is going to explain almost all the variability You'll be pretty sure that yep. This is just a single Gaussian Notice that you're missing a hell of a lot of important structure So, okay, given that What we're doing? Do we actually maybe have this kind of a structure underlying the PCA? Underline the data set. Yes, we do This is PC2. This is the second most important principal component and this is PC1 It actually looks just like that sine wave This is the data. We've dev a sliding window here. That's what these error bars are reflecting and you can see all civilizations This is our history folks We seem to be going down in PC2 as we grow in PC1 Then we hit this point a hinge point We called it and you now start increasing and then you start going down again Okay Well, what's going on notice? This is all model free really in a certain sense or it's put another way through again Point to that earlier talk This is taking the original model which is a single Gaussian and saying well, not only is it wrong? It also might be a little bit misleading. Let's go into the data a little bit more But it's still model free in the sense that there's no at this point Well, I'll show you so far. There's no underlying thesis about this is the way human cultures work This is just raw collecting of the data material. Sorry David. So how much? Variance does the PC2 explains? How much does it explain after the PC1? Yeah, let's see. I don't know the number of hand it would go back to This right there So this is the amount That's explained and so PC1 is up there just under 70% PC2 It's actually very very close to a bunch of the other PCs. All right, so this point I've not said anything about humans really. This is just raw time series analysis This could have to do with populations of frogs and a pond or what have you and that's not completely glued by the way Huck upon I've been talking off and on about applying some of these techniques to ecosystem modeling but now I'm going to actually dive into some Social science kinds of hypothesizing about what's going on here So, well, let's look at those nine complexity characteristics. These are the this is what they are for the top two PC components This is the population of the polity the territory of the polity The population of the capital number of levels of the government the government type and so on and then over here is the Infrastructure how developed it is Writing there's bit various kinds of writing all the way up to ultimately I think they was listed here as the most sophisticated writing would be alphabets But I'm how widespread texts are money. There's of course many kinds the most quote primitive money is barter You can end up going all the way to fiat money Thanks to a Yuan China civilization. Actually, I think it was town but in any case and So here actually is the answer directly to Mateo's question 77% of the variability and 6% now if you look at what these are I'm going to be very very crudely Refer to these ones here. These have to do with the information processing in the polity in the civilization These ones have to do with just how damn big it is how fat That polity is so this one is sometimes called in archaeology scale It's called a scalar value not to be confused with what everybody else would mean by the word scalar and this one sort of Expanding a little bit beyond what the true data necessarily justifies We're going to be referring to this as the computational capabilities of the civilization It's how much information processing it can actually do Viewing a civilization as a computer in essence Okay, so Given that there's these two values here notice by the way PC to flips from having negative loading On the first components to having positive loading over there Moreover because PC one is positive and by definition PC to must be orthogonal. We know it has to be that case So it's got to be the case that is PC one is going up some PC to components are going down and other ones are going up and if you use that and apply it to this particular data set here is the actual sum of The PC to components and here is just looking at the negative loading ones and the positive loading ones so what we're seeing here to interpret this for you is that up until this point right here the The size characteristics of the polity are increasing Without much change in the information processing capabilities You're getting bigger and bigger and bigger, but you're still dumb ass Eventually you get up to a sufficient hinge point a threshold and all of a sudden you say wait Now I'm actually pretty big The causality who knows it might be that you can't grow bigger without developing more information processing capabilities Or maybe only now are you able to but whatever you tend to stop growing? Physically, but instead start developing greater and greater information processing capabilities your computer stops us adding more and more Slow memory and now it's getting a bunch of GPUs added to it until eventually you get up to a sufficiently sophisticated My information processing capability and now you can start growing and getting fatter and fatter again That's us. That's humans folks Who knows what it would be with some alien civilization? But that seems to be us and who knows why this is happening, but this is just what the data seems to be saying minimal modeling There's many many other patterns in this data This is actually the data shown the the time series this is PC to this is PC 1 These are all the it's color coded the color is just to try to distinguish the trajectories of the different polities But there's all kinds of Properties in this data set first of all notice that this huge regions of PC 1 PC 2 space Where nobody's there? Why? What's wrong about those regions of PC 1 PC 2 space? Also notice here's PC 1 and so time tends to be going left to right What seems to be happening and this can actually be quantified now with techniques I'm not going to be showing here is that societies all start to spread apart But then they start to to use a biological term. They start to canalize Over here. It seems like everybody's getting on the same highway and we're all going in the exact same direction and we're converging to the same spot and Interestingly, these are the two hinge points So this is the one where you now start developing information processing capabilities And you start going everybody in all which directions and then once you have sufficient information processing capabilities everybody starts homogenizing and Of course, this is all there've been many many things Remarked in this talk about things like loss of language diversity Worldwide and so on and so forth That's all part and parcel of this kind of a trend in human civilization in that case of the global scale Okay, but other things to notice These patterns they hold are mostly for old-world societies. Those are the blue ones New world societies is not so clear that they do This might be the fact because to use very very loaded language New world societies never actually got as developed as old-world societies. They never got over here in the PC 1 space But that's to be determined. These are the kinds of things one can start to actually tease out of the data Yes So as you asked for questions during the talk, and you just said new world societies never got as civilized as old-world ones How about things like the Aztec and my own society? I flipped through that let me be more careful in my language The new world societies that are recorded in the session data set So this is actually things like a Oaxaca and I think Monta Alban Inca was not here Tenochtitlan is not in here Teotihuacan is not in here I think the Maya were the Maya were in fact. Yes, I'm sure of that, but that's about the extent of it So based on the data that you have and given that you're seeing that dissimilarity How representative do you think these patterns genuinely are of all trends if You know that they're not representing all stages of development in these societies So very very good and this is gets to the issue that I was emphasizing before you never ever throw out data They did because they wanted to try to get essentially uniform coverage over the world And they also want to try to pick early stage middle stage and late stage what they going in before even analyzing the data viewed as Early middle and late stage civilizations So they just did that as a first pass to try to de-bias it because obviously there's a hell of a lot more data in say Latium than there is in say something like sub Sahara Africa So completely and and there's a lot try to point to at the end of the talk How long how much time do I have I have 20 minutes? Okay, and I'll try to point at the end of the talk There are some techniques that have been developed in machine learning Let me actually point to it now Do you know What fucker Planck dynamics is laundry von dynamics stochastic differential equations? Okay stochastic processes there have been some techniques that have been developed in machine learning recently on Fully Bayesian approaches to actually fitting a fucker Planck dynamics So a stochastic process To a data set where you can have missing data. You can have completely you can have missing fields You can have all the data in there You don't it's there are no biases that come in by having extra data points This is very very powerful machinery Well very very importantly the fucker Planck dynamics the was close to cast a differential equation It is not varying in time, but it's allowed to vary in space So it's allowed to vary across this entire system here And that is the proper way to address your questions and a whole hell of a lot as well But that's not here and it's also not in this paper Where we did this initial analysis? So that's probably more than you want to know but none of us David maybe Just one other question. So why do you call this second component information? It looks like it's It's a measure of the amount of interaction or exchanges that are occurring Well, I Don't I don't know it look one couldn't see that it is I mean these are certainly if you do want to view a society as a computer and insert here all the cliches about how every scientific era likes to view Other physical systems in terms of whatever the sexy thing is in that scientific era And so viewing societies as computers is maybe a silly thing to do But nonetheless if you do want to do it This makes sense as this is the information processing capability if you have an alphabet Your writing system is first of all it's going to be much much greater literacy And in general you're going to have many many more kinds of text early writing Pre-alphabetic writing was first only scribal classes could ever read it or write it So it's a very very limited part of your actual society more over there's in many early societies Where you work had very very early scripts most of what was written was actually just Bookkeeping there was almost nothing in terms of what we would consider Either the sciences or the arts because it was very very practically oriented. That's not completely true for example Chinese Chinese Calligraphy that that actually originated by divining the future by looking at cracks on the shells of tortoises and things like this But by and large for example the more sophisticated the writing the far greater It is possible to actually use writing for society as a whole to develop itself Some people say that Gutenberg's printing press is one of the most important inventions ever because it basically unleashed the virus of the fifth of the Early European version of what we would now call the internet revolution that once you had the printing press Literacy was now much more widely and distributed many many more texts could be written You didn't have to have these silly monks and monasteries Writing down things very very tediously. This was a similar thing. So and that's true for money Certainly as well one of the major uses and economists will tell you of money is to try to essentially be a hyacin Construct that allows the market to be the computer and so on if you don't have fee up money If you just got barter money, you're not going to really be getting there So it does make sense. I think to view these as Whether that's the reason they're important or not who knows but they are actually variables that enable a information processing abilities of the actual society so I mean, I've got a lot of questions around these that can wait for later you stated that the Information spreading often comes in when societies reach a certain size and obviously I mean I think of the Victorian era and when we started to evolve ways of dealing with ways But What it makes me think of is some of these ancient societies collapse because of what we think may be Related to disease and pandemics or as evidence to suggest that for some of the Latin American civilizations and the climate civilization Has it ever been examined to see if there is a lack of information transfer when they hit that Significant size that you actually see other factors coming in that could lead to the extinction of those societies So there are many things that can happen to a society That do not have to do it just directly these variables for example volcanic eruptions Pandemics coming through the Justinian plague Take your pick. I'm terra erupting Maybe or maybe not having to do with the crops the minimum civilization One of the things that the stochastic process modeling techniques Provide is the following I Can look at a data set Hit it with a stochastic process Say that okay look at this particular event right here though How probable would it have been? Under this long-term stochastic process that seems to gen to govern the dynamics of human civilizations If the answer is very very Improvable Then that is great evidence that you've got an external perturbation on your system So I that's not the subject of this talk But going to stochastic process modeling where everything is probabilistic is Extremely powerful. There's lots of things you can do with it Some of them are to adjust the very very question that you just raised Unknown unknowns. When are they actually which big glitches? I'm seem to be due to the unknown unknowns in the sense of not being recorded in the data set Okay All right, so Yeah, oh Probably the way that they Normalize their numbers. I don't know. I'd have to go back and dig into it. Um, there are Whenever you dive into data sets you always find there are going to be some glitches and I should say That's such that in those recent science advances paper. They have developed it further There's now more than 51 variables and they got a lot of pushback mostly from archaeologists. There are big fights About the way that they were collecting their data and so on and basically they won those fights But nonetheless, they've modified a lot on how they are signing numbers in like such that version, too Let me actually give you an example of a fight and In the small amount of time I have left so this is an interesting Topic in almost sociological sociology of science There has been this hypothesis kicked around. I'm Joe Heinrich and others are one of the major proponents that a Necessary condition for a society to get sufficiently complex is that you have to have a religion based upon moralizing high gods It's tied up with people who believe in things like the axial age, which by the way is junk Um Peter church and actually is a great paper that he just basically takes that to shreds The notion of a why a moralizing high god is necessary is the following. It kind of makes sense as a cartoon Go back to the standard deities, you know say Greco-Roman deities. These were essentially Zeus Apollo all them The dudes and a couple of the dudettes.  Moralizing gods the Abrahamic religions Notionally some of the Hindu deities and if you want to actually say Hindu wisdom is religion Um Potentially you could view wisdom this way um the moralizing gods said no no no no none of that for you to actually get the benefits of The religious realm you've got to be moral and good Why would might this make um any kind of difference the cartoon is that well if Everybody is now being incentivized to be good Rather than just my chop up enough of their firstborn sheep That means that they are much more likely to actually have engaged in reciprocal altruism They are going to be much nicer to people that they don't happen to personally know if They think that you're being watched by the big dude in the sky Who's going to really slam on you if you're not nice to people just because they happen to be from a different tribe That's the cartoon Peter and so as I say I'm Joe Heinrich and many others We're saying that this is in fact true that you need to have moralizing high gods before you can have a jump in complexity in civilizations Peter I Understand why he did this I would have as well or I would have possibly He was very very eager to mine the sesh at data set just after came out So he actually came up with a nature paper. He and his was published in nature Nature nature not nature of human behavior. It was later. They have to actually retract it but For for other reasons besides this one what they tried to do is to use the sesh at data set to address this question Are moralizing high gods a precondition for societies to have a jumping in complexity? The way that they tried to do it is out for each society in sesh at they did a simple time series analysis of the PC One values to find the large jumps Interpret those as jumps of complexity and then said well Did they pre-see the onset of moralizing gods and they concluded in fact that moralizing gods always occur after a jump in complexity? So the causal arrow they said if there's anything the other direction Okay, well We've got other measures of complexity here Besides just PC one We realize that well, we can actually use these hinge points as measures of complexity. So let's see what that says because There's actually a major statistics flaw in what Peter Adalia. We're doing that nature paper in order to actually Carry out their program of doing this time series analysis You need to have PC one data in society from before the onset of moralizing gods to after Do that you have to and so what they did throwing out on data that All over the place they excluded societies from their analysis where they didn't have such data This is very statistically biased Because it's basically going to be much more societies that have the moralizing God onset much more recently a much more likely to Satisfy those conditions It was realizing this that led us to say well Maybe we can use the hinge points instead and so what we found So anyway, as I was saying Alternative that we investigate was to see whether PC one of society has reached its first hinge point That's how we are assessing social complexity and see where the moralizing God onset is compared to that Anybody here want to make predictions of what we found? basically Moralizing gods are irrelevant There's too much other stuff going on not completely irrelevant presumably they have some role to play But here's what we found remember the first hinge points right about there and There we found that there are some onsets of moralizing gods that are before the first hinge point and some of them are after You know, maybe you might want to say that there's more after than before But you would have to be careful about your statistical biases and when you can actually measure the onset of moralizing gods But to a first pass No, it's just a nice cartoon, but it's not really got anything to do with anything Okay, so many many other things to go through I should probably start to Finish up. Okay. Let me skip this. There are no surprise some statistical artifacts we found Having to do with their use of imputations One thing that I should point out is It's actually a very subtle kind of a stochastic process In this kind of a data set there's actually two stochastic processes that you're going to be see that's going to be going on One of them is just the dynamics if I'm a civilization and I'm here in my Non-complexity characteristics. Where am I likely to go in the future? That's the dynamics stochastic process But especially because remember, this is longitudinal. That's a big power of this data set Rather than just being cross-sectional There's another very very important stochastic process, which is when were you born and There's presumably If you look early very early the probability of any given Civilization being born then is very very small and it grows with time These two stochastic processes come together to actually distort the kind of data sets you see we found That in fact it looked like there were two Gaussians Remember PCA assumes a single Gaussian. We thought that they're well my god If you look at the data looked like there's actually two Gaussians and maybe it's a mixture model But then when we really dug into it We saw that because of these two stochastic processes going on You could get a pretty crude fit to it by just modeling the birth process Plus a simple Markov chain dynamics. It's these kinds of issues the stochastic processes going on here are very subtle Where the where do we go from here? That's pretty much the end of what I've got to present here as I mentioned we Mami and some collaborators And I've been talking with Huckabee and so on about playing this to other data sets I'm like microeconomic data and so on why is any of this relevance to this conference Based upon what we Are experienced as an analyzing session We've now taking these tools that have been developed in machine learning Which allow you to be a much more first-principled much more powerful Stochastic process analysis of a data set Where you can do things like detect was there a perturbation from outside the system another kind of thing that you can do Asking very loaded questions Is it a good model to say that India right now is just where Japan was 30 years behind? We can actually start to address those kinds of questions You can actually apply these kinds of techniques that we're developing to macro system Dynat to macroeconomic dynamics. You can also apply it to climate dynamics Basically, it's very very agnostic Modeling fully Bayesian where you don't put any interpretation in and yes every model is only in approximation No model exactly correct, but there's lots of great powers of using some of these more recent techniques To actually do the analysis rather than a conventional time series Delay embedding time series where you would need massive amounts of data to get anywhere So Thanks David very interesting talk so many You know such the whole arc of history there First of all I really like to hear that you said you're thinking of applying this to ecosystem data as well too because our work in Ecosystems are that they go from stages of growth and scalar Increased to development and focusing on information and all of that so that I see that fitting very nicely With that which then brings me back to those nine characteristics. None of them were natural resources based and That seems to be a problem unless it's just implicit that the city couldn't start unless it already had something like that But it would be nice to maybe try to consider that. Oh, yeah, it's a big problem There are many many things to go forward with this whole approach People should be joining. I mean that's one kind of a thing that could come out of this kind of a meeting Have people with data sets in all kinds of fields related to sustainability Throw it all together get into one big data set That you could then just use stochastic process fitting to that data set and just see what the hell comes out You'll be able to see I expect fully just like the hinge points Which we didn't anticipate that there will be things that we don't anticipate about climate human behavior interactions Almost guaranteed. There's things that nobody in this room is thinking of that are actually very important That such a data set would actually uncover for you and something I should actually emphasize that's so powerful about these new techniques If you go to anybody who's an expert right now in nonlinear time series analysis Based upon delay embedding. It's called people are familiar with this armor models or Or the regressive models are a linear version of this to be able to Do any kind of a reasonable fit to something and say even just a nine dimensional space You would need probably depends but on the order of hundreds of thousands of data points To do it with these recent techniques because it amounts to assuming that you've got a Markovian dynamics That is allowed to vary across your space the such that data set none of the time series Contained more than several tens of data points So especially when you're data poor Or just anything other than hugely data rich These new techniques that these people have been developing are Extraordinarily powerful. They should be used essentially all sciences. I would think Rather than or in addition to standard nonlinear time series analysis in addition to the fact that they can tell you things like External perturbations and you don't need to use imputations to deal with missing data and just so when women win Characteristics, okay, just as a follow-up question to this one So all your analysis depend on basically this predetermined pre-specified nine complexity characteristics, right? Can we ever imagine, you know having a society to develop to and you know information to a point where you have such Information present capacity that you have so many more complexity classes So basically just can we even study or talk about the emergence of a new complexity characteristics or something like that? Or are we sure that these are actually, you know constructing with societies and it's just done there's I've done a lot of work my day on machine learning for Customers business customers or engineering customers like when I was at NASA There are several mantras one of them is you never throw out data The other one is you're not going to get very far without trying to use domain experts Quote-unquote people who really know what the things mean Don't be full of yourself.  These are people exploit them. They really know what they're talking about Sometimes they're wrong, but really you've got to understand them That's in essence what was done here. It was domain experts who came up with those nine complexity characteristics You could have Alternately just worked in the 51 dimensional space directly. They didn't want to do a PCA in that 51 dimensional space But what you should probably be doing is not PCA. You should be doing what's called manifold learning You couldn't even imagine using what's called topological data analysis If you were to do something like manifold learning to actually just find what is the low the lower dimensional manifold That everything reduces to these the important ones and then look at the dynamics there One could very easily imagine that certain things are emergent You would need to be sure that whatever is emerging is not being it has to be at least somehow captured in the data set There was nothing in these data sets that said does this civilization have the internet or not? If you don't have that in your data set, you're not going to be able to see the onset of the internet But nonetheless, you could very easily imagine things like these complexity characteristics for a weird kind of a statistical hack Change with time one could imagine how sensitive are these results to some methodological changes like if you change the imputation method or if you read If you use a different way of standardizing some variables or if you exclude some variables rather than others, you know when you when you up Study these data sets you have to take tones of methodological choice has anybody do you have a sense of how robots are, you know, if you are the end results to Variations of these choices. So Peter used cross-validation and I am a very very firm believer I think that's the under Difference Presentation would be that cross-validation is really the scientific method. I would say Quantified made formal he used that with things like the Atlantic Ocean as I mentioned So that is one version of testing exactly what you're saying if you were one of the advantages if one wants to What we view it that way of having these nine complexity characteristics is that if you throw out one of your 51 variables You'll still have nine complexity characteristics the also the fact that the PC one was Equally loaded on those nine complexity characteristics means that even if you got rid of one of those nine complexity characteristics PC one would still be aiming in a pretty much the same direction that being said No civilization Had a complete history without any gaps in the data Archaeological data is just very very holy so to speak In a class a couple of senses and so they did use these ugly things called linear imputations very very hideous and They weren't aware of it, but introduced to the school artifacts. You can see them right here This was we were trying to figure out why the two Gaussian peaks And so then we did we went into really deep dive into their data Which they had pre-processed with these imputations which are a very ugly way of trying to fill in missing fields And we noticed these streaks We concluded that these streaks are not themselves directly relevant But nonetheless they are there one of the advantages to keep on evangelizing of Using these new stochastic process models is that it would be very robust against these kinds of things. It's Bayesian all The way through so not only do I get a stochastic process But I also tell you how confident you should be in the parameters of that process David just quick. I wish we didn't use the word complexity in any of this, but that's an aside, but I the I mean what you're finding is this peculiar Collapse of dimensionality right and is that a sort of operational definition of a civilization where all its various Factors become correlated Um in essence, that's what the mat if they had used or we should anybody who's Got the resources to be quite honest be blunt about it Which I right now don't to go after this should do it's up Like manifold learning where one would see exactly what you're saying what you're pointing to Where you would see as you know all of the data it really it's not spread out I mean notice I'm recall that I said one of the big mysteries way back here Was How come there are all these gaps? Well, if we if you look at things in nine-dimensional space, there's gonna be presumably much larger regions This this is going to be some kind of a weird sheet in that nine-dimensional space and that is exactly Reflective of the kinds of collapsing of all these different Features down to actually only one underlying variable Here's another way of putting it the the physicist in me and there is still a little bit of one Wanted to be able to take this dynamics and to be honest Try to actually model it as though it's actually a physics system where you use what's called a Hem holds decomposition to say can we view this as like a gravitational field? With all societies are being moved with noise according to that gravitational potential Turns out it doesn't quite work, but that's essentially it would amount to what would be so cool by that kind of thing Which is relate to what you were saying is that we would then discover this would be like Kepler We would be discovering the laws That govern human society dynamics purely from the data It would then be some kind of Newton further down the road who would figure out the why But we would exactly Tycho Brahe I guess would be better than analogy than Kepler We would then actually be discovering by doing exactly what you're saying What the dynamic laws are that seem to govern humans in a certain sense in a certain Okay, thank you very much David. Okay. Thank you. I think we need to move


even saw. I even saw one of the greatest games I've ever seen played. Right? One of the greatest games I've ever seen played. I saw the United States play against Brazil on July 4th in San Francisco. What a game. What a game. The United States played a phenomenal game.  One of the Brazilian, I believe that was a game, one of the Brazilian players got a red card for smacking the American player in the jaw and he broke this jaw. The Americans were, I believe that was a game. Was that the game? No, maybe it wasn't the game. Maybe I'm confusing a couple of different, because I've watched a lot of World Cups, right? But the Americans, man, the energy they put out was amazing. They had the drums out, they were loud. What a phenomenal feeling in that game.


Millions of people have been told to stay at home as one of the worst storms in decades. Stom Eunice hits the UK. Rare red weather warnings, meaning there is a danger to life from flying debris, have been issued by the Met Office covering much of southern and eastern England and south Wales. Hundreds of schools are closed and travel networks are experiencing cancellations and major disruptions as power cuts have left more than 50,000 properties in south west England and south Wales without power.