This paper proposes a methodology for optimally configuring multiple extreme fast-charging XFC stations in a distribution network. It first estimates the charging power demand of XFC stations using a Monte Carlo simulation tool. Then it designs the optimal energy capacity of the energy storage system, ESS, ESS rated power, and size of photovoltaic, PV, panels for multiple XFC stations in the distribution network. Finally, the optimal power flow technique is used to optimize the configurations of the XFC stations, ESS, PV panels, and distribution network. This article was authored by Jo Kwon-Woo, Pradeep Krishabat, and Bo Chen.


Not so fast, helmet. Meanwhile... Hi everyone, it is CryptoGroundz. Welcome back to another video. It has been a very long time since I posted a video on this channel, but I really needed to make a video on this topic because some people were getting confused on some topics regarding single tins. That's these guys, classes, these guys, and mono behaviors. So this video is going to be taking place on a whiteboard. I kind of drew everything out, explaining everything, and I will be talking through all of it. So I recorded this kind of last minute on my phone, so I'm really sorry if my quality isn't the best, but here it is. Okay, so I'm currently in a study room, and I have written everything up on this whiteboard. So right here is our class structure. So for now, let's just focus on this special controller class and this data class. So our controller looking at this is like the center of everything, right? You have settings, upgrade handler, achievements, you a handler, you name it, literally anything else will most likely want to refer to this control class. And I'm going to show an example later on. But for now, just to simplify things, you can see that this controller class has a data object. So it has an object, just an object in here, and I'm sure there's more going on, but just know that for now we need to only focus on this one thing, and it's just this object. This object is this right here. We create this data object, and this data right here includes any properties, fields, methods, and so on that is included in this data class. So in perspective, this is basically a blueprint for data, and right here we are creating an object for data. So now what we can do is that we can change anything that's public or that's legal, such as cars. So in this controller class, we can change, we can get, so get or set cars. You have other classes that are probably want to be accessing this data as well. So instead of just having a data object for every single class and somehow merge them all together, pass information around and all that, which would get messy anyways. Why don't we just have a single data object? Well, that's exactly what we do. Anyways, let's move on to this controller class. Let's get a little deeper look into it. So here is our controller class in a little more blown up picture here, but ignore the surroundings and just focus on this dotted box. So there are three things in this controller class. There is a static object called co, and its type is controller, which is literally the same thing as this up here. So you're creating right here, we are creating a static object of this class that it's in. And then in this private void awake method, I spelled that wrong, ignore that. This private void awake method, what we do is we set co equal to this. And awake is a unity special method that comes from mono behavior. Again, I'll get into detail in a second. And this is called before start. Okay, so this is called very early on when you start playing the game. Next, we have our data object, which I explained earlier. And okay, so let's explain what this mono behavior is. So controller derives from mono behavior. So mono behavior is a base class that provides methods such as start, awake, update, and so on. There are many other ones that you can find on the guide. And basically, in order to use the start, awake and update methods, we must implement this mono behavior base class. So without it, these are just normal methods. They won't start or awake, or this won't update every loop unless you somehow connected to another method or a special kind of method that we don't really use public static void main. But then again, that's we're not going to get into detail. But anyways, my point saying that these methods will not work properly. So let's say that we have a script called controller.cs, which includes a single class that implements mono behavior. We are able to add that script to a game object in the Unity scene. So in your hierarchy, however, if we got rid of this, if we were no longer implementing mono behavior, we cannot do that anymore. This class would no longer associate anything related to unity. It is just a plain C sharp class that implements absolutely nothing. And it just has all this. And it does nothing because there's no public static void main method. But we again, don't need to worry about that. So that's why we have this here, because we wanted to do something in Unity, right? We want something to happen on a week. We want to do something on start or update. Let's take a look at this one to the left, which is going to be our UI handler. This isn't doing anything related to UI at the moment. This could literally be any other class. It could be our settings, upgrade handler, achievements, and so on. Note UI handler does implement mono behavior because we want this script to update the UI in Unity. So that's text, images, other game objects, scroll rex, etc. We're not doing that in this example, but this is just to prove a point. So you see in our update method here, we're trying to do two things. We're trying to set a flow X and a flow Y. The first one being we're trying to access this cars variable. Well, we're doing that for both, but we're doing it two different ways. One is not right and the other is. So let's talk about our data class real quick or our data object that we're trying to reference. So that happens in controller. So here again, here's our object public data data. This notes is non static, but just know that what we're trying to do here is flow X equals controller. Okay, so first let's start a controller. So we do the same thing for both. So we are trying to access this controller class statically. Okay, whenever you try to access a class that isn't an object, you must use the class name. If we were to access the class for data, this would be capital D data instead and just ignore all that and we would just do what we want with that class. However, we're not doing that. We're trying to access the class controller and that must be done statically. So we have our controller up here and let's start the first one. So we have dot co. So we are trying to access the static controller object from our controller class. So it's co. Okay. So this is valid because co is a static object. So this is completely legal. And we want to access our non static data object from our controller. This static controller object contains this data. So then we access our cars variable, which is literally just from the data class. Okay. So first point I made this is good to access another object in another class that are both not static. We use singletons, which I will get to in point six. So let's talk about the second one. What's wrong with this? Why can't we just jump straight into accessing data? Well, here's our issue here. One, we start with this controller, right? This is good. However, since we are trying to access this class statically, data must be static. And in this case, it is not static. So this is not legal. If this was public static data, data. So if we had that static term right before data right here, this would be completely fine. Okay. This would be fine. And we would be able to access cars normally. However, since data, our data object in controller class is not static, this is not legal. Okay. I want to clarify that. Number two, this is illegal data and controller must be static in order to do this. So yeah, just as I explained. And I want to note for number three that this applies for literally any other class and this can be done anywhere else. This could be done in your settings class, achievements, et cetera. So for point four, data right here is not static. So we use single tens right here in order to access this non static variable. And we have to do this because we don't have a single 10. We can only access static variables like this. So we create a static object or a single 10 to bypass that. And since data is inside a controller, which is inside of this static object, this is perfectly legal. And I want to note that if this data object was static, we can use method two. We can use this one, right? However, I like to note that one thing I really like seeing is my variables in the inspector. I like to see what the numbers are behind the scenes while playing the game. If this was static, you can no longer view the variables in the unity inspector and that just sucks. So single tens one to one. This is what it is. This is a very, very basic single 10. It gets more complex, but this is just as basic as it can get. And that's honestly what I do for mine. So a few more things I want to point out is that this term right here, this is basically this instance. You're basically saying it as like this instance of controller. So this exact instance, which you assign to a game object in your unity scene. So if you dragged your controller script or added it as a component to a game object in unity, that would be this, right? That component in that game object is literally this, if that makes sense. It's kind of weird saying it, but it literally means that. Okay. Point number two, you can only have one class in your script that derives from mono behavior. You can literally have controller class in one script. You can add another class below it that doesn't derive mono behavior. Heck, you can even put classes inside another class that doesn't derive mono behavior. That is legal and that can be done in one script. However, you cannot have two classes that both implement mono behavior. Unity would get really confused and it just doesn't work that way. It's also the same reason why your script name must be the same name as your class that implements mono behavior. If it was different, Unity would get all confused and it will just break. And I want to quickly point out that I'm not encouraging you to add a bunch of classes within one script. I want you to split it up. For example, I have my controller class. I have upgrade handler. I have UI handler, achievement settings. These are all going to implement mono behavior. Each of these are one, its own class, two, its own script. One thing I've kind of failed on you guys is telling the difference between a class and a script. Because they're very different. I mean, a script contains a class or more. But again, it must follow the rules I explained earlier. I'm going to remind you, because this needs to stick, that each script must have zero or one class that implements mono behavior. Now note, if it has zero classes that implement mono behavior, just like a script called data, this cannot be added to your Unity scene. Or you cannot use Unity special methods such as Awake, Start, and Update as I said earlier. So you can have a script that is just data. This is fine. You can have a script that is just controller. You can also add other classes that don't implement mono behavior. And that will be in one script, and that is good. Just note, if you have two classes that implement mono behavior, things are going to be weird and not work properly. To kind of clear up this data, I probably should have mentioned this earlier, but this is an object. So you have your floats, doubles, right? Those are variables. This is basically a variable for a class. You can have as many of these as you want. You can have data one, data two, you can have different types of data, right? Not saying it's necessary, but just saying that our class is a blueprint and we can create as many of these as we want. This is just one object that is type data. So for how we set up our class, we can get set or read and write this variable cars because it's public. Last point, I'm going to make number six. So right here, this is our single 10. And I want to point out, I've probably already mentioned it, but I'm going to mention it again because it is important. It is static. It allows us to do controller.co. It allows us to access this static controller object and we only use the single 10 outside of this controller class. You don't use it inside yourself. There's no point in doing that. You can literally access data inside this awake method right now and you'll be just fine. However, if you want to access this non static object or any variable or possibly any public method outside of controller, you must use a single 10 just like this. So I am currently editing the video and I just want to jump in and explain why we use single 10s and how they actually work. So if we take a look at where we're at in the video, if we see this public static controller co static object, basically this is being assigned to itself. And this co is an object that is type controller. So this is the controller class and we are making a copy of it called co. Okay. So here's our class called controller. This controller has a non static object called data. And just, just like data includes a float variable called cars, controller has an object called data and it's type data. And so if we step back, controller.co.data. So we are accessing our static object by doing controller.co. And we are able to access or modify any type of variable objects or even call methods that are inside of the controller class. An example. And in our case, it would be the data object. So that's just how we do it. I hope that kind of, if you were still confused at this point, I hope that made a little more sense. Single 10s are strange initially, but once you use them more. And if you want to rewatch this a few times just so it clicks or if you want to do more research, that may help out as well. But they are very powerful and I personally use them all the time. So I know this was a pretty long video and I really hope this clears things up. I know these graphics are a bit confusing, but I wanted to clear this up. And yeah, anyways, thank you for watching. Hope this was really helpful and leave a like if you thought it was helpful. If you have any questions, let me know in the comments below. And I'll see you guys in the next one in the undetermined future. Goodbye.


Okay, so thanks a lot and let me also thank the organizers for the opportunity to speak about this work here My name is Roberto Verdel. I am a postdoc here at ICTP in the group of Marcelo Dalmonte and today I'm going to tell you about Some of our recent work where we explored the use of data-driven approaches to extract physically relevant information of many body problems and most of what I'm going to show you today is actually based on our recent publication on PRB that you can check out here and that was the result of a Really nice collaboration with all the people that you see mentioned here So let me begin by giving you some kind of Broke motivation to the topic of my talk and this really comes from the field of quantum simulation And I should say from all the amazing developments in this field Which has really opened a new door when it comes to the study of non-equilibrium quantum dynamics and the key aspects of Quantum simulators to make this realization possible is the capability to you know Prove quantum matter having control and Observation capabilities at the individual quantum level So what that means is that with current technologies and also thanks to the developments in imaging techniques Nowadays we can take essentially photographs of our quantum many body state Illustrated here from this figure taken from this recent experiment at work where what you see is three examples of such snapshots and in this case of linear chain of trap ions Where the ions represent the qubits and this simulator and what you see there each bright spot Essentially corresponds to a spin pointing down while the dark Squares is a spin pointing up Now this is really amazing because this kind of snapshots contain lots of information of your many body state of interest There are however a couple of remarks that one should make here the first one is that The number of degrees of freedom that you can probe nowadays with current quantum simulators is already quite large In the sense that the dimension that you can explore by a number of these Realizations is a still very small compared to the dimension of the full Hilbert space So that is to say that an approach like full quantum state tomography is just out of the game for a system like that and On the other hand by having these kind of single site resolution to the system That also makes them very special compared to other many body kind of systems like solid state Materials where of course we don't have this level of resolution So that brings us to the question as to what's the best way in which we can extract information out of these many body wave function is snapshots and Of course, perhaps the first thing that one could try is To do what we already know how to do that is for example Extracting these kind of few point correlators know like a local density to point correlation function and so on and This is an approach that is of course based on Physical assumptions and it works very well to describe very interesting physics in many situations and there are plenty of Also experimental works where such an approach has been carried out However from a data science perspective if you want What we are doing here is a kind of dimensional reduction the many body wave function snapshots on that side are really large objects and By only structing this kind of few point correlators We are reducing the dimensionality of the problem But in a way this could be a non-controlled dimensional reduction because we are not sure whether What we are throwing away is actually or could contain let's say physically relevant information of the system There are some other reasons why we would like to go beyond this kind of description and here I'm just showing you three examples of what I think represents quite well this point so the first one is systems for which we know actually that The physics is described in terms of no local correlations The best example here is systems that feature topological phases of matter where a local order parameter will not Tell you about the whole story of the system Another example of it in more broad terms is when you study non-equilibrium dynamics in a genetic interacting system It is not always obvious which quantities are the best in order to describe such such dynamics So here is another example where Utilizing the whole information content if you like of these many body wave function as snapshots could be of interest Finally, I think it's also clear with that if you want to benchmark the workings of our quantum device Probably you will need to go beyond computing these relatively simple observables that I was showing you before So all of these tells us that it would be highly Decidable to have a new theoretical framework That's really leverages on all the information content that these wave function snapshots contain So today, of course, I'm not going to Tell you the final answer to all the questions that I posed before Instead, I'm going to show you our effort Towards building such a theoretical framework if you like some kind of baby steps towards that final goal and the approach that we are putting forward here relies on the following realization that If you think about these wave function snapshots, they are simply data objects in fact There are classical data objects and therefore it's kind of natural to think of using data science tools to analyze the you know, what as I was saying the full information content of such objects and Importantly these tools that come from the field of data science are designed such that you don't need to do any physical assumption To analyze the data So here's an schematic representation of the kind of approach that I'm going to tell you about today So our starting point our collections of these wave function snapshots and at this point One should note that this could come really from an experiment from a quantum simulation or they could be Sample if you like also from a classical simulation so here what I will have in mind is that these Data sets are matrices Where the number of rows are the different? Realizations that we take the different snapshots and then the number of columns correspond to a different degrees of freedom that we have in the system As a second step, we will do this kind of what I call here exploratory data analysis with the idea of discover You know the hidden structure in the data without making any physical assumption and hopefully What you will learn from it will allow you to tell To say something about the physics of the system, which is the last step in this diagram And I should say it here that of course there are many works that in a way are complementary to the approach that I was showing you just now and Of course, I apologize if I didn't include all the relevant words in this respect so Now here's the outline for the rest of the talk I'm going to start by giving you some kind of little introduction to two of the tools that we use and then I will show you some examples where we apply these tools to extract information of some many body problems the first one involving a experiment with post-election condensates and the second is more recent work that we are Doing at the moment where we try to characterize transfer transport properties of Quantum spin chains Okay, so this is the kind the part regarding the methods So today I'm going to tell you about two methods that we utilize The first one is what we call the PCA entropy and as the name suggests this is something that is done within the framework of principal component analysis and Is essentially a tool that allows you to quantify the complexity of your data set In a way that I'm going to show you now So first of all a little reminder on PCA This method can be Formulated in several ways, but in the end it's about finding a set of orthogonal directions That successively maximize the variability of your data Once you project the data points onto those directions as illustrated here One can show that such an optimization problem boils down to actually linearizing square symmetric matrix this matrix sigma Over there Which you compute from your data matrix. That's the matrix X. So here X really represents for example one of these rectangular matrices there, okay, so Suppose that you have Solve the eigenvalue problem for that matrix sigma Then you get a set of eigenvectors and a set of eigenvalues the eigenvectors you Actually use in order to define the principal components in order to find these principal directions and the eigenvalues essentially they tell you a little bit of Like what's the spread of the data in the corresponding directions and here we will only utilize the the eigenvalues and We know that these eigenvalues Are all non negative and furthermore we can always normalize the set of eigenvalues by the total sum of them So in the end of the day what they define is not in both a probability distribution And finally we use that probability distribution to define the PCA entropy According to the Shannon formula that is in this square yellow square Okay, so here is how it works in pictures So suppose that your data set looks like that image over there, which is essentially white noise If you would do the PCA analysis and compute this entropy as I just told you You would get a number that is very large And in fact it's going to be a further log n where n is the number of degrees of freedom in your data set So and this is very intuitive for a for an entropy So the more random names you have the larger the entropy will be on the other hand if you would have a Extremely ordered data set and of course, this is just a kind of toy example. This doesn't correspond to anything But if you will have something like that Then essentially you just need a single principle component to explain the whole of your data And in that case the PCA entropy will be in fact zero So the more correlations you have in the data the smaller the entropy in The PCA entropy will be okay, so If yes Yes, that's actually a very good question. So We have a story the PCA entropy in a few different Kind of context But for example if you apply it to classical systems, let's say classical static systems at the equilibrium one can always define this PCA entropy with some normalization factors such that it coincides with a thermodynamic entropy in Certain limit for example at infinite temperature. So in that sense, it has a connection with a thermodynamic entropy and There is also a recent work by Carlo Bannonia and Vittorio Vitale where they analyze this kind of entropy for Quantum systems single particle quantum systems and then there show that In fact this quantity is an estimator for the participation entropy of those systems So there are certainly some some connections with physical quantities in some limits Good. So now I'll tell you about these other methods Which I think is very interesting, but perhaps is not so well known at least in the physics community And this is known as the information imbalance Which It's a method that will give you a tool to systematically find The most informative subsets of features in your data set and here by features I mean really the coordinates of your Snapshots so you can think of features snapshot as a data point in a highly dimensional space And the coordinates of that point are the features that I mentioned here So this method works by computing What is called distance ranks and it does so by So selecting two kind of Subset of features and those define two spaces which are here.  So those are a space a and a space b Now, let's say that according to space a so according to these subset of features The point I and the point J are nearest neighbors So I encode that in that matrix are a by putting number one And that's the rank of these pair of points the distance rank of these pair of points But it could as well happen that if I use this other set of coordinates In the space b the same two points will be now third nearest neighbor So the corresponding distance rank in B in this case would be three and Then the information in balance is computed essentially by this conditional expectation value of the ranks in the In the space be conditioned to the points that are nearest neighbors in the space a So at this moment this quantity might look a little bit obscure But my claim is that what this quantity tells you is how well can a space a describe the structure? of a space B and There is a way to make this formulation, you know mathematically formal in probability theory and for the experts that's Essentially an application of what's known as sclar theorem but what is important to To to point out here is that these conditional expectation value really determines the full correlation structure between the two spaces Now a little bit more in plain words how it works Suppose that a space a and a space B are perfectly Correlated in the sense that the nearest neighbors according to a are the same as the nearest neighbors according to be In that case one can easily compute this conditional expectation and show that it's actually equal to 1 and Therefore this delta From a to b will vanish as 1 over nr nr here is a number of snapshots that we have a number of points On the other case on the other extreme of things if The two space are completely or perfectly uncorrelated meaning that the nearest neighbors in a have nothing to do what of With respect to what you call nearest neighbors in B Then one can also easily compute that conditional expectation value and show that it will actually be equal to nr over 2 And therefore with this definition delta is equal to 1 so this quantity goes from 0 to 1 and the closer it is to 0 and The better the space a explains the structure of the space B now You can perhaps already anticipate that this is a perfect method to do what is known as feature selection in the following sense Suppose that I call a space B the space of all the features that I measure and I take different subsets of features here I'm just showing you showing this for two subsets a one and a two and then I compute The information in balance in the way that I show you before and I get something like in this plot there then I could say that the subset of features a two are actually quite informative about the full set of observations and Here's a concrete concrete example of that suppose that You draw points from a three-dimensional Gaussian where the standard deviation in X is only one tenth Than of the standard deviation in Y and set So your data cloud is essentially in the Y set plane and then you call Space a one only the first coordinate X and you measure distance in that way And the space a two will be the second and third coordinate and you measure distance in this way Then essentially what this analysis will tell you is that if you determine distances using the Y and set component You can determine the full structure of your data because X in this case is just like some noise Okay, so now I'm going to show you some applications of this method, but maybe I stop here in case there is questions Yeah, that's also a good question. And actually at some point we were exploring precisely that question whether we could at least estimate the entanglement entropy from the SPCA It turns out that there is not a direct relation between these two quantities But it's more like I said before you can relate the PCA entropy to the participation entropy, which is you know the the Shannon entropy of the Probability density given by the wave function in that case But as far as as we know is we cannot relate it to the entanglement entropy Yes, I'm going to show you a concrete example just now And in fact it's going to be a little bit different from the beginning because I started by considering Snapshots in a lattice and now I'm going to go to the bulk So this is a kind of quantum simulator that it's of lattice And it was a collaboration with a group of Marcus Oberthaler in Heidelberg So what we did here was to analyze Data sets that had already been used in a different work that you can check out in that really nice paper Over there. So here. Let me just mention a few technicalities of the experiment So in this experiment they prepare a spin or both the Einstein condensate using rubidium atoms and These are put in a trap that has this Enlogated shape. So it's almost one-dimensional system And then in the experiment what they basically perform is a quench dynamics. So they Initially prepared all the atoms in The hyperfine manifold with f equal to one and substrate with mf equal to zero So you can think of this as a spin one system and then by tuning some lasers in the experiment they basically Perform this kind of quench dynamics So essentially what in pictures what it happens is you start by putting all the atoms in this Substate and by doing this kind of quench to bring this level into resonance with the other two levels and that You know drives some kind of spin changing collisions in the condensate and drives it out of equilibrium So and then in this experiment they can take these state selective especially resolve snapshots of atomic Populations or densities in the on in all the relevant levels and these are the kind of snapshots that We were going to on that we are going to analyze here Where you see these kind of gray? Rows over there corresponding to different levels And like I said, these are just atomic densities at different In the different relevant levels Now there is of course a lot of work on this type of systems and it's understood based on physical arguments heuristic arguments that a good quantity to describe This condensate is what is known as a transverse a spin of the of the condensate And it can be shown that this Can be computed from those measurements by taking the imbalance of different populations as showing here so the first question that we ask here is Whether such kind of dimensional reduction It's a good one in the sense that I explained at the beginning Namely whether we would obtain a compatible description if we analyze these Kind of data in a blindfolded manner if you like so without reliant on any heuristic arguments So this is just to show you how these data sets look like so essentially they measure these Densities at different times and in the different sub states and On the so the different rows again correspond to different Realizations and the different columns correspond in this case to different spatial locations where they sample these densities So this is just to say that by simple inspection, of course, you are not going to see any kind of correlation between different between different observables Good. So first we apply the PCA entropy to such data sets and we do this as a function of time so for each time we have Six matrices for the six different observables and we compute their PCA entropy And what we see is that as the system evolves There is a clear separation between two groups of observables and there is clearly four Observables that develop a smaller PCA entropy. So in that sense They are more relevant because they seem to capture more of the correlations across that time-space evolution of this of this system We went one step further by asking ourselves which Concrete combinations of these observables could be more informative so what we do here is literally concatenate the different data sets in the As schematically showing there and we compute again the PCA entropy for all the possible combinations Here I'm just showing you for combinations with two observables And what we found is that By doing this analysis, there is clearly two specific combinations that develop a smaller PCA entropy and those combinations actually Which are indicated there correspond to what it was known Based on physics arguments that would be like the relevant combinations So finally once we have identified these pairs of Relevant or these kind of relevant pairs of observables We can go one step further and try to really define new operators that would be in the most informative ones So here I'm just showing you for three particular combinations And again what we found is that the difference of these observables Has a lower PCA entropy and therefore we interpret it as more relevant and that it's in perfect agreement with This physically motivated kind of answers Good so at this point we were quite happy But you know when you use PCA you have to bear in mind that you are kind of assuming that your date is well described by a Best fit in subspace So there is always this kind of linearity assumption that you're making so we wanted to cross check Whether this analysis was also true using other kind of methods and here's where we use this information in balance So remember that you have to compute to do this information in balance You have to compute distant ranks in two spaces. So in this case our reference space be Would be the space of all the different features that are measured for the six observables So it's so you can imagine that each data point has a further 1200 coordinates in this case and Then as a space a we take only a subset of those coordinates that correspond to the features for each of the different Observables and so we ask which of those observables describe better the structure of the full space of observations So very quickly here. I'm showing you the results again doing the three steps that I show you before and The labels here. I'm sorry that I'm not showing it showing them, but they correspond to the same levels as before so again, we see that The four observables that had the lowest PCA entropy in this case. They also have the lowest Information in balance. I remember that an information in balance close to zero tells you that those coordinates Can describe quite well the full structure of your space So in this sense, they are also the relevant observables according to the information in balance and This was fully consistent with the results that we got with the PCA PCA entropy analysis So in a way was a nice Form to cross-check the results that we were obtained Okay, so in the last part of my talk I'm gonna show you some ongoing to work and here really the main Character has been the vendora Bakuni who has a poster in the poster session And I also like to advertise the poster by Cristiano who is working on similar aspects, but for a classical static systems So here We are going to chain again a little bit the setting so we go back to the lattice so we have in mind, you know quantum spin chains and The question that we are after is whether we could say something about, you know, the transport properties of such systems So the scheme that we are going to follow is the same as I presented at the beginning And here are a few results So first of all the the setting that we have in mind is One typical setting to probe transport. Namely, we are going to study the unitary dynamics generated by some Hamiltonian with some conserved quantities And we prepare the system initially in a way that it has a kind of kink in one of those conserved quantities schematically shown there And this is for example Motivated by some recent experiments like the one showing here where they study spin transport in the Heisenberg model and in particular they are able to probe Super diffusing super diffusive regime that actually falls into the KP set kind of physics So we apply the same Kind of setting about utilizing these PCA tools And only relying on these snapshots that we are taking from our many-body wave function So here all that I'm going to show is results from classical simulations so the first part corresponds to this spin transport and What I'm showing here on the first row is The growth of the PCA entropy as a function of time So at each time we have in this case an MPS representation of the many-body wave function We can sample it efficiently using for example perfect sampling And then we do this PCA analysis we compute the entropy and we plot that as a function of time And we do we do it here for three different values of the anisotropy parameter which Has been shown in previous numerical works that they correspond to ballistic transport Super diffusive transport and diffusive transport as well. So What we found is that the growth of these PCA entropy captures or is in a way Go burn by the dynamical exponent corresponding corresponding to the different types of transport and On the right panel We show these for different values of the number of realizations and it's quite remarkable that already for a few hundred of these snapshots You can Recover a signal that allows you to extract the dynamical exponent with a very good accuracy On the lower row we plot a different quantity which is essentially The difference of the largest eigenvalue when you do this PCA analysis on the left half of the system Versus on the right half of the system So this was motivated by the physical quantity that was analyzed in this experiment this polarization transfer What we see is that again this Recover or is governed by the same kind of dynamical exponents and in fact if you plot it together with a polarization transfer is basically on top of feet and The one of the nice things of PCA is that actually you can understand very well the math that you're doing So it's only linear algebra So in this case we could understand based on some singular value the composition theorems why this quantity Was essentially computing the polarization transfer So okay, you could say very well, but in this case, you know that the system in this system the magnetization in the set Direction is conserved. So you are taking the snapshots in the in that basis So in a way is not so surprising that you can capture, you know all the transport properties And based on this observation we try to do something a little bit more challenging, which is To study energy transport So here we took three systems with different kinds of energy transport and this has been a story again in previous works And in particular we took system where the energy is Transported in a diffusive way in a ballistic and a super diffusive manner And what is shown in the lowest row is a kind of energy transfer That of course you can compute from these numerical Calculations, but you cannot as far as I know you cannot measure in experiments And on the top panel is really this analysis based on the snapshots that those you can take Certainly in the experiments and where we compute again the spreading of this PCA entropy or how information is spread as measured by the PCA entropy and what we see and I think this is really kind of remarkable is that The way in which the information is spreading is again governed by the relevant Dynamical exponents and again, I emphasize that this is only taking snapshots in one single basis Okay, so with this I'm in the end of my talk and let me just Thank all my collaborators for these works, and I thank you for your attention Thanks Robert for the nice tag. Is there any question? Yes, just one question about this Actually last remark that you did that Actually, you only measure in the Z basis. So in fact, it's not the whole wave function Do you have an intuition why it is sufficient to extract this information because in general should not be the case Yes, so At least what I think here is that as long as you know, your any energy functional has some kind of overlap on the measurement basis that you are taking It seems that that's enough to For the information that is being spread in that representation to be governed by the same dynamical exponents But that's certainly a question that we are exploring at the moment to try to put on a more solid ground Yeah, so the it's the PCI entropy if you took just some let's say the first or the component of the PCI analysis of the Snapshot then it wouldn't work. I mean, I guess it's related to the fact how this PCI entropy is connected What you mentioned briefly. Yeah. Yeah, that's also a very good point In fact for the spin transport We also check when you know to do actually something very drastic and you throw away all the eigenvalues except the first one so you compute the kind of Shannon entropy for the first eigenvalue and in that case it also captures correctly the the dynamical exponent But also if you look at the PCI spectrum in this case, you see that it is Quite drastic separation between the first eigenvalue and the rest of the spectrum For the energy transport, that's not so clear and here actually I don't remember if we try Computing this quantity only with a few of these eigenvalues but in general If you have the separation between some part of your spectrum and the rest You could as well just use You know the the most important eigenvalues I would say But I mean doing this kind of analysis is very cheap So you can in principle consider all the spectrum and get the information the full information out of it without and this deviations at later times is a problem of your I don't know how you Get the Snapshots, it's not the problem of them. You mean the saturation. Yeah, it's going Yeah, yeah That would be Kind of finest size effect that I think and yeah, it's one should also note that the saturation for example on this Energy transfer occurs at later times in general with respect to this PCI entropy, but I think yeah, we don't expect to capture the full Information about the the energy transferred by only taking measurements in a single basis, so Yeah Yeah, thanks, so I have a question to the to the first part the Heidelberg data basically So in in the regime where you evaluated this I mean data was still I mean the state is still time evolving So there's also still dynamics happening Could you could you also get information from the structure of the eigenvectors? Basically from the PCI analysis that you get and not only the eigen So can you say something about the relevant structure? Maybe spatial structures or so? Yeah, that's a good question. Actually in this case, we didn't look at the eigenvectors We did Look at a different Kind of description of the system, so if you look at the physics of the system, there is a regime where it actually Exceeds itself similar dynamics And our original target was to describe that from the data science perspective as Kind of simplification of the data structures that that you are getting and that's more or less What you see when you look at the first plot there You see that in general the complexity as measured by this PCI entropy decreases as a function of time So we analyze a different quantity, which is known as the intrinsic dimension to measure precisely this and in that case we could also kind of extract the Universal regime for the dynamics that is revealed by a kind of plateau in this intrinsic dimension But in terms of PCI we didn't look at these eigenvectors So I cannot tell you more about it That thing kinks show you the eyes that can go there, please You mean in the second part? Yes I have a next Next please. Yes that can simulate the topological defects in the initial states So what we do here is We I mean the precise protocol that we follow here is we compute The ground state of the left part of the chain with a corresponding Hamiltonian And we put that left part in the ground state and then for the other half of the system We compute the highest excited state So minus the ground state of the other part and that generates a kind of energy kink when you look at the Initial energy density profile. So it would be something like this You have one half of the chain that has a larger energy compared to the other half And then we just do the unitary evolution of that initial state But that that things can be compared to topological defect in the initial state And since do we have one wall that divided two parts to phase in the system Yeah, essentially the question that we are asking in this setting is how the conserved quantity Is sort of redistributed when you start from this in homogeneous initial state? I don't know if you can relate it to the notion. I mean for sure There is the notion of a topological defect But I don't know if you can express it in terms of, you know the spraying of such topological defect or something like that Let's thanks Roberto again


But for all the best content on the planet, that's free. No banner ads, banner free, and always a fun place to get all the data and information. And I'm here with Mark Manson, industry analyst, elusive, omnipresent, guru, Twitter influencer. Welcome to theCUBE. Thank you. So tell us what your impressions are, I'm only kidding about it, you are influential. But we were chatting last night about big data. What are you seeing right now at the end of the show day two, or day one, officially the big day, but really day two of the actual conference we've been broadcasting. What are you seeing, what are your thoughts? What's the big trends that are popping out at you? Well, I think the big trends that are popping out are probably the shift from the early stage startup scene to the much broader enterprise IT market. I think that the era of startups selling technology to other startups is ending and the runways run out on the free cash from the VCs. Now it's a, oh, enterprise is wanted by this stuff and they have the money and the startup scene is run out of money, we better move. So that's my nutshell. Okay, let me just, we have some time to talk about that, so we don't want, okay, that's the end of our interview. Thank you. So let's talk about that. So we just had John's dog deal on, and he said, and big data is coming to the enterprise through the front door, and it's coming fast. So let's unpack that a little bit. So, you know, the rubber's meeting the road, okay? The VCs are funding quality and business value. So you got to have some tech to enter the market, so you got to have some chops. Not a lot of, hey, I launched a company, I'm done. You know, celebrate, get my VC funding, get some VC funding, some scrutiny right now on a lot of things, product market fit and the go-to-market path. So with respect to that, where are you seeing that business value connection on the product market fit and the go-to-market for these companies? To do the business value equation, because no one's going to buy the hype that's just too much noise right now. Yeah, there's a boatload of noise. So I would think that what you have a lot of right now is technology searching for a solution, or, you know, it's like, I have this technology, what can I solve with it? As opposed to people actually asking for it, and that's a big problem if you're a tech company, you know, it's a push. And in some areas, it's a pull from departments because they're frustrated with IT. So a lot of the big data messages been around get us in your data warehouse, get rid of databases, do this, do that, it's faster, it's agile, it's easier, which it may or may not be. Or it's a part of the underserved. And when you look at things like transactional data, databases do it well. Time series, databases don't do it well. Networks, databases don't do it well. So what are you going to do? Well, you're going to have to turn to something else. And so we're seeing a lot of big data as applications sneaking into other parts of the organization. And what's that called? What kind of effect is that causing when you're seeing? And obviously some confusion, but also some impact. It's causing some change, right? Yeah, it's causing change because you've got the IT people being disrupted. You've got a part of the IT organization that never dealt with data, developers dealing with data. And you have the data people being left out because they don't have the technology to support what these guys want. And so we're in this one world's collide period where developers on one side, data guys on the other, each one trying to talk the other's language. So what are we people doing? I mean, what's your sense of the, obviously people can get stuck, right? They can break through it. What are you seeing that the action right now on today's marketplace? I mean, is it just, okay, everyone's got the pause button, is it evaluation time? I mean, there is confusion. I mean, I was just talking to someone out there that's like, I don't know who to call. I walk into the exhibit hall and I see all this noise. I don't know who to call. I saw EMC's in the news, maybe I'll call them. So there's a lot of, I don't know who to talk to. Yeah. What are you seeing there? Because of the confusion in the market, I think we've got a situation of disambiguation that has to happen and this is probably the year that it does because people say it's an analytic solution. Well, maybe, maybe SAS is good enough. It's a database solution. Well, maybe database. And there, I think that you're seeing right now the strawman being thrown up by the vendors who are threatened, right? The Oracle or the IBM or the Informatica are your choice in the sort of, in the EMC as, yeah, definitely in the store. The green plume announcement yesterday. Terra data. Everybody's being threatened. IBM. So let me ask you a question. Let me ask you a question. Terra data versus EMC, green plume. Who has, who's going to, what's going to happen there on the BI side or data warehouses side? Because the green plume came out with a very focused, we're going after the data warehousing. SQL on Hadoop, Hadoop is a nice little Hadoop wash there. Come in, ride that. You talking about Hawk? Yeah, Hawk, yeah. And you've got Terra data that's already out there. You think they'll put a dent in Terra data or? At this point, probably a very small dent, but EMC has a lot of feet on the street. So maybe, but you really got to roll back a little bit. Yeah, you have to roll back a little bit and look at what does Terra data do? What does EMC do in this Hawk thing? And how are they different in terms of both implementation and what you can accomplish with them? And it comes down to worldview. If you believe the world is going to gravitate towards the database wrapping things like it has for the past 20 years, then Terra data might be the way. If you believe that bringing things like SQL to Hadoop and building out that world and migrating it closer to the enterprise data world, then it's the green plum side. And so, I don't really know, to be honest, because they're both potentially viable futures right now. Well roll back a little bit more if you would. So where I was going with that was, you had Vertica, Natesa, Green Plum attacking, essentially Terra data when they came out, the MPP guys. And they made a little bit of traction. They got good exits, but Terra data did fine. Okay, now the big data thing comes on, it's like wave two of attack on Terra data, which brings us forward to your last comments. But I want to flip it now, because you consult to both the vendor community and the IT community, the practitioners. And so my question, you've already answered it, but I'm going to ask it anyway, is my data, I'm an IT practitioner, is my data warehouse a dinosaur? It's not a dinosaur, but what you really have to do is look at the uses of information in an organization. And data warehousing is designed around assumptions of stability. Things don't change a lot. Core transactional data, essential financial pieces of information about the business. Customer data, behavioral data, external signal, never part of that inside the firewall transactional apps. And so you've got the monitoring, see exceptions, and maybe do some analysis of those exceptions. Figure out the root cause of what's going on. Choose amongst three different choices, like I could make a decision to do X, Y, or Z, which one is going to lead to the best outcome, and what are the downstream implications of that? Or forecast or predict this outcome? Data visualization stuff can't really run effectively off a data warehouse, because it's in human interactive time and data warehousing, the eye tools are not. And so how do I convince you that you need to change this thing and we need to take this to the CEO and get it approved as a business project? And so convincing, educating, elucidating, laying out problems and explaining, all of that is part of a spectrum and the data warehousing market drew a little tiny box around the first piece which was monitor and identify exceptions and it's a very stable thing that very rarely changes. That's where we are. Yeah, you described it very well.  Every month a little bit changes. Add some new data, whereas this new world is, hey, let's redo everything. Yeah, well that's Cloudera. So I like that world view because it's kind of like Democrat-Republican, pick your religious view and you only know it'll play out based upon what happens on the street. The market will spin in whatever direction. Is it that though? Or is it Democrat, you can make a case for either side. You could play for my counterpart. Well, let's think what he was saying about the wrapper though, that there are use cases but there'll always be these niche deployments but what's going to really, when the world spins to whatever preferred environment, use cases developed at scale in terms of corporations. Right, so. That'll be defined by the solutions and if wrapping it and that's the package, a container if you will. But if the, what do you want to call this new way? Big data way, whatever.  This new world delivers much more corporate productivity on a growth trajectory, almost like the microprocessor revolution, then it's not like, it's almost not a win or lose. It's like this is the area that's going to now consume everybody's attention and get all the investment. It's a classic headroom, right? It's a headroom argument, right?  So what do you think? Or there's foreclosure, you know? Yeah, I'm thinking about it. You're the expert, right? So John and I are sort of peripherally involved. I suspect that having lived through the first set of BI and data warehousing wars when we were telling main framers that those reporting systems that they had been designing were the wrong way to do it and there was this data warehouse architecture and it was a new way. You ended up with, oh, OLTP is an IT architecture. It has its whole systems architecture and philosophy around it and we renovated that in the whole Web 2.0 sort of stateless scale out stuff. Then you take the data delivery side of the equation, the business intelligence data warehouse market to date and that was all about getting data in and getting it out to eyeballs. And now you've got a third piece which is both that and machine to machine like recommendation engines or whatever or automated detection and management systems. I think you're seeing the evolution of a third piece of architecture which is processing, right? Because databases are for storing and retrieving data. They're not for processing. OLTP is for recording transactions and sort of storing it in that way but for the execution of tasks. And now we have a third leg of an IT system architecture evolving which is the processing of data at low or high latencies, at large or small scale, in real time, in batch, it doesn't really matter but it's a different beast. And so you've now got something that offers you new capabilities. So it doesn't supplant the data warehouse any more than the data warehouse supplanted the mainframe or the ERP system. Right. Now at the same time, sort of back to what I said before who sort of driving the most corporate productivity being the traditional, let's call it the traditional BI data warehouse, failed to deliver in my opinion on a lot of the promises that were made. That's 360 degree view of the business, the predictive analytics, it was just. That's called hype. It was hype but they didn't live up to it, right?  I mean, I guess the internet lived up to its hype, right? So sometimes it happens. We'll see, with big data, the practitioners that you talk to in the data warehouse, the business intelligent world, they're constantly trying to figure out how to make what they have better. They're chasing chips, they're maybe bringing in the latest and go, oh man, the tease is here, let's try that. They're always trying new things. It maybe helps a little bit for a while and then deluge of data and they're back chasing their tails. So that cycle is not going to change anytime soon, right? And they're still playing now a vital role within the organization that's tied to the processes they're locked in to the organization. But at the same time, that traditional world is being dragged into Hadoop. So those two worlds are coming together. Right now it's like the Hadoop tail wagging the dog. Do you see that flipping? I mean, it's a different version of the question that you said I don't really know on before but I'm going to ask it anyway. I'm just going to give you the same answer. Well you said you couldn't be pinned down so I'm trying to pin you. The thing is, I don't see either or I see both because Korean retrieval is one half of a problem. Think about it like Web 2.0, right? Web 1.0 was a publishing metaphor.  Along comes HTTP, RPC, and suddenly REST based web services develop and now we have read write web. That's a different, it changes architectures, it changes what you can accomplish. The big data stuff, not specifically Hadoop but all the processing plus the low latency which we don't have in the database world because you can't store data and then act on it in real time, you have a new way. And part of that is that, what does Hadoop? It's a storage system and a processing engine. It's not an ETL tool, it's not a pipe, it's not a database. And so I have a read write system. That's a different set of infrastructure. It's not optimized to get data out real fast for query but with that read write system, I can change so much of what I've done with information as opposed to IT being the arbiters of taste and I talk to you and then I cook up a meal and then I serve it up to you. Well, now with sort of the big data tech you're starting to give people the kitchen. Mark, what's your thoughts on sort of the structure of the industry? I've said many times that we live in this world that's almost, it's an oligopoly, right? You've got five, six, maybe seven companies controlling the chessboard. Oracle goes and buys a company, they own Java, they own MySQL, right? The list goes on, EMC could make big moves, they have made some moves with VMware. So it's almost as though the sort of innovative startup, their objective is to get, have an exit. Maybe there's an IPO in it for some of them, some small minority. But generally, I don't see that changing. And so, and I wonder if you agree or disagree with that but the question I have is, do you feel, do you agree with that? And do you feel as though those whales could continue to control that chessboard, make moves and then morph into this new world pretty, without too much disruption, you know, they'll cross the chasm. I think they've figured out how to do that. Do you agree or disagree? I agree in principle, but it could play out differently.  And they've just essentially outsourced their R&D function and their risk-taking functions.  IBM, Oracle, SAP, they've all digested companies and poorly executed on the promise that those companies were expected to deliver. All these database companies, the netizas and the verticas and then this and then that, how much have they actually done for those vendors? The answer is it varies. Really, they just become more price book entries for people to throw at the wall. And there's some point where you can't just be solving things by buying product. You have to have rethinking of architectures and those vendors are not because they have lines of business that are drawn up specifically around things. They don't want to cannibalize their own thing. We saw that like Cisco was a great example.   They do know how to swallow a company, but operationally, they're buying lines of business. But you're right. We ever talking all week about old way, new way and fundamentally this data platform is a new architecture and some of the things just aren't invented yet. And I think the entrepreneurial community is ripe with innovation in the sense that you got guys beavering away out there saying, hey, you know what? I don't want to go work for the big company. I got 15 years experience doing data warehouse business intelligence, data management, or whatever, I'm just going to build my own system and bring that to the market. So you're right. There is a little bit of picks and shovels Dave right now. But the database is particularly tricky. Well, database is interesting. What unstructured data gives a program sort of a bit more programmatic freedom, right? So you have, you're not schema bound, right? So you now can have some range, right? So I think, you know, our concept of data as code building off our infrastructure as code riff this morning was interesting because infrastructure as code is changing the cloud and business. Because you're talking about simultaneous deployment of code data and teams. I'd say there's a second piece to this too, right? There's the buyer side, the IT audience. Think about what's happening in IT. You mentioned cloud, right? All these business departments are running around buying apps to serve their department and it's shifting to SaaS and it's shifting to cloud and IT's role is becoming not the guys who have to do everything. It's become sort of all administer the app in a light remote way. And so what does IT's role become? They're really, the main thing is data. The data to connect to the Salesforce app, to the CRM app, to this other app, to this internal thing which may be hosted, which is my ERP solution, plus all of these other bits and pieces. Plumbing and data. And that is totally different than the role of IT in the past in many ways. It's interesting, you mentioned main frames and talking about the data warehouse in the old days and all that. The old app systems and stuff and kind of jolting on that. One thing that's very, very interesting and this is kind of popped out of my head when I saw it over and over here in that same term, data processing. Now, remember back in the textbooks 1970s, data processing was a discipline. Yeah, and data processing was punch cards, right? So the DP department, so now we're in data processing. So here we go. Here we go, we're back into data processing. So, okay, data pipelines, data processing, data management, data stewardship, we're seeing this kind of coming back. Again, coming back to your other point, the riff on is architectures. Yes. And I hate the word software main frame and I know that's been talked about with Paul Moritz all the time, but I don't like it, but I don't have another term. If data processing is going to be a discipline again, okay, in a new architecture, what do you think it's going to look like? And obviously, you know, I don't think any vendor really has the answer yet. And I will give Cloudera props. I mean, what they're proposing with Impala is academically and theoretically and being executed as a multi-resource platform that enables resource-based data processing, meaning no one vendor can do anything. You know, but Morton, we're all the same thing. So what was your take on all this? Well, I think trying to say that an architect is something that a vendor can sell you is a mistake. I don't think vendors sell architecture. They sell products and products fit into larger architectures. And I think what we're like, let's use the term data platform because that's what I like to call it.  And you have to start thinking about where do you draw the boundary lines between platform and application in a new and different way? And that gets so little attention. I think that the vendors don't even understand it because part of it is you have to remove the old frame of reference. The old frame of reference says, here's a box and here's a box and here's a box and here's this thing. I'm going to shove it into a box. And preserve special interest, right? So, you know. Exactly, the gardeners and foresters of the world, they have their waves and their quadrants. That's how they make their money. We have a new report coming out called the Magic Kingdom. Yes. And the Magic Kingdom will be, I tweeted that one, it's got a lot of, why can't I see the Magic Kingdom report? Well, it's kind of bigger than the quadrant, but we haven't released it yet. No, I mean, but yeah, it was slow, but that's the magic quadrants for people who aren't paying attention, right? So, they need to see things in. I think that it actually is a sign of the difference between a stable market and an unstable market. And I look at IT markets as periods of punctuated equilibrium. We had a nice period of reasonable stability on the data side. The web stuff was going crazy. But now, all of a sudden, just like 1992 or so, this part of the market's going insane. And it's going to be chaotic for the next few years, the data side of the market. Not the, I'm taking and doing transactions, but the data infrastructure, data management, data storage, data retrieval, data delivery, all of those things because we've had several orders of magnitude of technology change and capability and the software architectures have not shifted to match. Just like in Web 2.0, software architectures went from app servers on centralized grids to stateless architectures and browsers. There's no doubt that this decade is a lot more interesting than last decade. I mean, there was some cool stuff with mobile for sure, but I mean, from an enterprise standpoint, it was compliance and I mean, it sort of gave a nice boon to the BI business. Thank you, Enron. But you're right, this is a much more disruptive and volatile. Okay, we are wrapping up day two. Mark Madsen, great way to end it and kind of reading of tea leaves, kind of stepping back, looking at the worldview, kind of riffing out here, kind of like a bunch of musicians playing our notes on the marketplace, looking at what's happening. And I think it's a really good perspective. I think, you know, the summary of this conversation is one of great innovation opportunity, great disruption, disruption kind of a lot of things coming together at the same time, multiple theaters as they say, but the platform really is the focus and we're going to be covering it all day tomorrow. Stay tuned. This is theCUBE at the Stratoconference at SiliconANGLE.com's exclusive coverage of Stratoconference and we'll be right back for a wrap right after this short break.


In this lesson, we will be looking at much the same material as in the last, but with the purpose of discovering sources of harm or value that can be the basis for change. We will be looking at our investment potentials as the ultimate owners of our nation and its economy. Empowerment in this arena will face a common challenge inherent in our modern study of economics. It provides a well-valued and readily available knowledge base that would redirect economic concerns from what we value to what the economy does. It has an established focus on economic operations with a good concentration on cause and effect knowledge that provides a basis for leaders who would act to run the economy for our benefit. It favors those who would run the economy, those in authority who claim to take actions on behalf of owners. The performance alternative is what an economy can accomplish for us as its owners and for us as the ones who can benefit from its operation. We the people are this nation. The purpose for having an economy is our purpose. It has no other purpose. Its function is one of converting what we put into our economy into what we both value and receive back from its operation. What we put in is our personal time and effort and performance skills along with the resources of the nation and economic energies that we ultimately own. What we put in is our life energies and resources. Our commitment to these is partly choice and there is great personal value in having those choices. What we receive and get to value is food, shelter and companionship support for family. These are things that preserve life and meet our personal wants and needs and we receive for another value support for our personal decisions on what we choose to receive. We also receive economic freedom that we can value as prosperity. And in this we are both the owner of the economy and are its only real customer. We are the only ones who are to be served by its operation. In another aspect we are also individual people with needs and wants. We do not have different needs and wants as owners than we have as customers. We are singular units. As owners we give purpose to our economy as customers we evaluate what we receive. We the people are truly the only party in interest. There is nobody else to be served by our economy. Where others are served it will be at our expense it will be waste. From use of the black box we have the definition of economic waste and it is value that is redirected from the performance cycle. Waste is output delivered to non-citizens or output that we do not value. Waste is cost placed on us to serve someone else's purposes. We improve the value cycle by eliminating that waste. If we just stop expending our resources on waste we still get just as much from the economy at less personal cost. If we just stop delivering economic goods and services to non-citizens the cost of operating our economy will drop without affecting what value it does deliver to us. Public charity can have value but only as we are able to value it, valuing the notice of its delivery. Also as a review our modern science of economics is firmly focused on the internal operation of the economy.  It does not address performance only activity. The science of economics is designed to provide technical support for those who would run our economy for us. Modern economic science is useful for many things but not performance. Our focus must be on its black box performance on converting what we put into the economy into what we receive and value as its output. Purpose is a challenge as we are individual human beings. Our purposes can vary widely. Our purpose as children is quite distinct from our purpose as working adults or as seniors. And we are still just one person. Our purpose as wealthy citizens is different than our purposes as those who are impoverished. Our purpose as women is not always our purpose as men. We seem to have almost endless variations. Our purpose even shifts as we are able to satisfy needs and wants. Once either is satisfied our personal purposes shift to other needs and wants. What we do share is basic humanity. We value having choices and results and that is freedom. We value economic freedom. We value economic choices and results and that is prosperity. Prosperity includes having sufficient economic value that we have choices in what we are able to gain from committing or buying with it. Prosperity is having sufficient options for our purchases that there are things that we value, valued opportunities. We value our interaction with other people and especially our effectiveness in dealing with them. The key is trust and we value our ability to trust one another as in the family. We value society with others. Once again we value these because they are human values and we are human beings. These are the values that we do share with other people. These are the values where we as people who own the economy and who receive a productive output can find natural agreement on the values we receive. It is where we can come to agreement that we can exercise the power and authority of citizen ownership over our economy. In the positive sense increasing our freedom, prosperity or effectiveness in society with one another will be a common source of value that can bring us to agreement on what the economy is to do. In the negative sense recognizing interferences with our freedom, prosperity or effectiveness in society with others will provide a common cause to eliminate that interference as waste. We also need to recognize that all our needs and wants cannot be satisfied by economic products. There are other human purposes that can be a basis for agreement among people. There are common needs to maintain our physical and emotional health. There are common needs to bring up the next generation as effective people. There are common needs to address the value of senior citizens who become increasingly needy as they age. We value rest and relaxation, the ability to temporarily cease our efforts to regenerate our persons or our bodies. We also value other things like the companionship of pets. We have some values in objects of beauty or pleasure, artwork of both physical objects and presentations by people of skill and talent. Many such needs must necessarily remain unfocused as specific products will be valued by segments of we the people instead of all humans. Still the knowledge that they are valued in general, promotion of the arts and human sciences can be a matter for agreement. We can come together for assuring the economic choices of human entertainment, even though we may not be together in which entertainment is most valuable. We can come together for supporting the education and training of our next generation or the maintenance of ourselves as senior citizens. These are common values because we all start out as children and then all hope to continue living. We are both complex and variable. The things that bring us together today may be replaced by something else tomorrow. The only true focus that we share is our basic needs and wants as human beings. Our ability to come together to assure a valued result is most easily focused on freedom, prosperity and society. But there are other matters that are worthy of our time and effort. There are things that we value because they are valued by others in our environment. We value the welfare of our family members. We value the people in our immediate presence. We value human membership in our divisions of society. We are being daily urged to waste, giving of ourselves for important matters from which we receive nothing. Perhaps the most alluring is doing things for the good of following generations or for the good of our future society. The flag should go up immediately for those in this course. Family is how we care for our next generation. The same people who would secure our world or our environment from us for the benefit of future generations will also secure it from future generations for the same reason. If nothing comes to you, then you have no good basis for valuing it.  Quite simply, when and where our economy is not serving us, it is not serving society and is not serving the public. We are the society. We are the public. There is no other society or public to be served. There will be no future society that is in any different than ours unless we are the ones who create it. And the value for change does not belong to leaders. It is our value that counts. What is it that you must do for the good of the nation or the economy or the environment or some people in a country 5,000 miles away? What is so important that you have to surrender your children to military training and transport to the scene of battle? The first performance question for you as owner and customer is, what will you receive from such efforts that you will value? We have learned that hard lesson of customer relations. Only those who receive are able to effectively value what they receive. Only the customers have real purchase decisions. We have also learned that companion lesson of the willingness of leaders to limit or remove personal choices that might interfere with the way they have learned to run things. We also have an observation of human character that is appropriate. You will make personal decisions based on your own expectations of cost and benefit. If you have to be ordered to do something, it is likely to be something you would not do, except someone else is able to enforce consequences. The dark side of this rule is that those things that someone has to order you to do under penalty of law is not representing you or your interests. It is regulating your choices to meet criteria that are valued by others. It is likely to involve waste. You are also the public calling on some directive as being for the good of the public is just one more cause for concern. If public officers have to order the public to do it, it is not effective representation of the public. Such regulatory orders and laws are common examples of political misrepresentation. In government management of our economy, we are addressing massive waste created by leadership trying to meet goals and objectives of public leaders. In this lesson, we are addressing those specific directives that require the time, effort, and other resources of citizens without delivering or like return for them to value. Consider real estate taxes. These are commonly collected from those who own property. The performance question is one of what the taxpayer both receives and values that is secured through this taxation. When we expend on police and fire protection services, that value is clearly there. But then we are left with the nagging question of why it has to be collected by threatening legal consequences upon those who fail to pay. Is funding police and fire protection somehow not worth what it costs to citizens? On even asking the performance question, we are challenging the privilege of those who are set into positions of authority. Taxing us commoners is a privilege of rule. Property taxes also fund the county administration, which does its best to run things. It can fund public parks and roads. It also funds the county schools who return nothing to the taxpayers for the considerable expense that this incurs. It provides resources for a large number of services that may or may not produce anything for the taxpayer and public to receive. Consider the process of selling your property to another citizen. You both get real estate attorneys to represent their interests. The sale is accomplished through real estate professionals. The public support service you receive is so bad that you have to hire professionals at your own expense to deal with the government entities. You have already paid for it with your tax dollars. And then you add the additional fees and requirements for your transfer. Instead of service, you receive massive costs and burdens of requirements just to deal with your own property. Instead of service, you get additional waste. These demand, time, effort and resources that you have to expend just to exercise your personal ownership of your property. The waste is incredible. It is punishment delivered to the landowners instead of services that citizens might value. We have come far enough in our performance studies to see the direction of solution. And it is to identify what value the government's land management and taxation services can deliver to the citizens who pay for it. From another perspective, it is how the public service can team with property owners in getting what they value. Of course, teaming with citizens is unlikely to be pursued by public leaders. Teaming with citizens to do things is not considered as a proper way to run things. If anything, the preferred public direction is empowering the right side of any issue to prevail over what others want. The proper way for privileged leaders to do things can be horribly wasteful. Consider the business of justice. The very purpose for government is stated in our Constitution. It includes assuring justice. If you want justice in today's courts, you have to hire an attorney. Justice is at least partially for sale. Performance? Consider that the entire system is built on advocacy, on taking sides in a contest. It is straight out of King Arthur and the Knights of the Round Table. This is for adversaries to pick their champions to do battle with the idea the most virtuous side will surely be able to prevail. Competition creates drama, not performance. Justice is not something secured by a contest. It is to be a service provided by government. What we have requires further expense, which often has to be partially covered by those who seek legal justice, just to have a cause heard for resolution. It is a same old system of privilege, assigning judicial responsibility for implementing the law that legislators and authority direct for use. We have assignment in place of service, exercise of authority in place of serving a purpose. Those with the authority of privilege will not change anything. We have the same basic court system that existed in England before the Revolution. It is proud to be doing the right things and to be doing these things as well as they can be done. Again, we have been developing the vision that will open our understanding of what we are not receiving from our economy and government. We can see where we get punitive costs for demanding government services even after we have been required to pay for them. When we address what we can do about it, then we will be looking for those things that can be presented to others that will bring agreement on a course of correction. Until then, we continue in frustration. We currently have something like 125 million taxpayers. The first task is to apply our analytic tool to see where we apply the cost of taxation. It is immediately obvious that we have to be ordered to pay tax. We do not value it. We pay it in order to have a working government and we pay it under threat of public prosecution. Well then, the tax dollars go in. How are they productively used? Again, those who govern use our tax dollars as they feel to be most appropriate. The dollars are redirected from the productive efforts of the economy to fund government. What we have is support for government and it provides us some services but it also expends on its internal operations that deliver nothing to people like us for value. We have tax dollars that are removed from the working economy altogether. As to our economic performance cycle, they are waste. There may be government services but they are not part of the economic value cycle. We also want to zero in on the specific cost the time and effort required for us to pay our taxes. It includes the time and effort of employers to track, collect, and pay employer taxes on behalf of employees. That becomes an operating cost that has to be covered by those who own or are customers of the employing business. It also includes the time and effort people must put in to understand what citizens do or to pay separately for someone else to prepare taxes. It includes the time and effort required to produce and deliver tax documents. I estimate that effort at equivalent of eight man hours of effort per taxpayer per year. That is an annual cost of eight hours in paying taxes for each of 125 million taxpayers or one billion man hours expended from our economy without any return at all. This is equivalent to a government operating a full time and unpaid tax force of 500,000. The kindest word is unpaid employment which is the effect temporary slavery. For cost we have to also add on the people who are employed by the IRS to take part in this no value effort. They have to be paid too and that cost has been over $11 billion a year. There is no value return to the citizens for this expenditure. The cost for our method of taxation which is in addition to any taxes paid is approaching half a percent of the productive capacity of the nation. And why is this expense set upon us? It appears to be just so our leaders can proclaim they have not taxed us unfairly. On the performance side there are flags all over the field. The people who are empowered to serve us are issuing orders instead of providing service. Those orders are issued under threat of public enforcement and that really gives definition to the nature of us and them that is currently supported by our privileged leadership. Why are we taxed? The common answer is that this provides for the operation of our government. Let's try to define the performance for this. Is there a difference between success and failure in our government's operation? That of course is the performance question. What measurable results does our tax system have to accomplish that defines its successful operation? Is there even a difference between its success and its failure other than doing the right things? There is nothing that is to be gained by the taxation effort. It is not only unmanaged but effectively unmanageable. So what about funding our government? We just find a new and higher us and them wall. It is in the form of a massive public debt. The efforts of the IRS are not able to fund the government of the United States. It is not even accomplishing that. It is unable to meet any reasonable purpose. Can we fix this? Can we change things so that the IRS can fund government? One most unhelpful answer is that Congress is a body of privileged leaders engaged in ruling over common citizens. It is commoners who do the productive work and privileged leaders get to harvest it. It is the old feudal model that is still with us. No, the answer is no. There is no fix through congressional action. The strength of privilege is in its stability not performance. Any change is resisted. The known cure for failed management is to apply the missing management. This cure is likely to require public action to direct the appropriate changes. Those will be the changes upon which we, as citizen owners of the United States, can agree upon as personally valuable to us. Until then, we get to be economically abused by the existing system, watching it waste our time, effort, and much of our resources as it collects. We do have the Constitution on our side. What we earn is ours, and we have property rights in it. We have the protection of private property that is seized by government. Even that's seized for a valid public purpose. Our leaders can be held to account for providing just compensation for what is taken. And that is just compensation that comes to us, what we both receive and value, not some vague good of the nation result. When doing something about it becomes a priority, we have this one possible starting point. The general rule is simple and to the point. If the output from government actions does not come to us, it can have zero public value. We only get to value what we receive. That turns out to be absolutely scary to modern leaders that they have to produce something for the people they would rule over. Consider public secrecy, securing information from the public. There is no value to the public. It is denial of even the concept of representation in favor of rule. The generation of information that is withheld from the public and even worse from our representatives is the cost incurred through denial of public purpose. If such things are simply terminated, there would be no difference at all. Secrecy is the exception, not the rule. It is only to be supported where it is necessary for the effective operation of our government. We the people are the ones who set purpose on our government, not some privileged employees. We set that purpose on office holders, both elected and hired, through the agreement by and among ourselves as to what government was to accomplish. There is no value in withholding public products from the public, denying delivery as voluntary waste that can be eliminated. Also, it is embezzlement, a felony to direct money collected to operate our government to the benefit of foreigners. If you, as both owner and customer, would not expend what you earn on an effort, then any spending on it certainly does not represent you and you are the public. It is right back to that simple and potent rule. If it does not come to us, then it has no public value. It is the nature of privilege that it invents its own purposes and then serves those purposes. It is generally termed public charity serving the special needs of some people and claiming this as the right thing to do. And if that form of public charity is not offensive enough, modern leaders are willing to use tax dollars to give special support and services to the citizens of other nations who come among us without permission. It is equivalent to raiding the bank account of a homeowner to the benefit of someone who has broken into their home and tried to stake out a place for themselves. Our challenge is reinforcing the meaning of representation. The one who assumes privilege in his or her actions is not representing anyone except themselves. Again, as owners, all these provide us with opportunities. When it comes to official management by regulation, the rule is that there is waste whenever people have to be compelled by law. Quite simply, you do not have to order people to do what they want to do anyway. If you have to direct people to do or not to do something, you are establishing an us and them relationship. There will be no teaming. There will be waste. In another perspective, if the leaders have to order people to do or not to do some action, you can be pretty sure they are not representing the people. This becomes doubly problematic when most of the people are ordered to act or to stop action for the benefit of some small number of people who have special needs or situations. It is when leaders would rather represent those in greatest need instead of representing the public. Such leaders will create great waste. They feel justified in spending other people's money on good causes, on doing the right things, serving leader goals and objectives. Modern political leaders are perfectly willing to impoverish the people they lead and destroy their lives if they accept that they have a good cause. We have the harshest of witnesses to how maniacal they can be that lesson of our civil war. That war was not caused by slavery. It was caused by the worst sort of misrepresentation and total rejection of law to do something that should not have been done in the first place. The cause was slavery and leadership took sides for and against it. It was so important to leaders that they rejected the very concept of representing we the people. The very idea that some law banning or mandating slavery would represent the people was so obviously an error that it never should have been considered for a government action claiming the representation of the people. The war was the price of having leaders who are willing to take sides of some people in their dispute with others. It is leadership who have no interest in the Constitution's mandate to create a union. Their economic correction was to seize private property to slaves as a public purpose but to refuse to pay for them. It was to trash the Constitutional mandate when it would not serve their political goals. Nobody wins a war. This is leadership at its worst, working to divide the people against each other and focusing on their divisions to the point where the unity of the nation is denied. The result was dead Americans, the worst sort of waste. The cost was piles of dead Americans who were supposed to be protected and represented by our elected leaders. And as a final insult, modern leaders point to the Civil War as one of the greatest accomplishments and economically ruin South and impoverish North and dead citizens. Political leaders do not change. They have learned nothing. Their efforts create stability, not improvement. In addressing the larger economy with government as a means for servicing the economy for our benefit and our purpose of prosperity, we bring focus on the unity of our purpose in seeking prosperity and our personal and public support that government is duty bound and legally required to deliver to us. In our next session, we will be addressing that singular business we recognize as a stock market. It was initiated as a timely service to a growing nation and has been wonderfully successful at what it does. It has also become a major source of waste that is fueled by support for privileged people who have become an effective part of the operation of this business, even though not part of what it was set up to do. Government interference has just increased the challenges of operational waste.