Thank you. So, hello to everyone. First of all, thanks to the organizers for organizing this nice event and for giving me this opportunity to present my work. And my today's presentation will be divided into two parts. In the first one, I will present that this poll which is a scheme for exact diagonalization of large sparse matrices. And in the second part, I will show how this scheme can be applied to phenomenon of manipulation. But let me start with introduction introduction. So, the field I'm interested in is the field of ergodicity of isolated quantum and about the systems. Like the basic setting one is interested in is a quenching experiment in which we have certain initial state and we want to see how the system evolves and whether it approaches some kind of equity build. So, an example of such state is plotted in here. This is a system of hardcore bosons. It was considered in this paper in 2018, 2008, and the system is prepared initially in such a way that half of the system is filled by hardcore bosons and the rest of the system is empty. So, if we think about some classical counter part of such an experiment, this would correspond to particles of gas gathered in the in half of the room and at the certain moment we start the evolution we allow them to explore the whole phase space and as we know in classical physics that particles will quickly fill up the whole volume of the of the container they are starting. Yeah, and, and this is, and then the thermal equilibrium is attained by by in such system so if we think about quantum isolated quantum and about the system actually quite similar thing is happening. If we look at some observables either occupation of the zero momentum mode or momentum distribution of those particles then we will see that initially, once the time evolution starts there. There are some changes in those in the values of those observables but then the particles fill the whole system and attain a uniform density profile, and then everything everything is time independent after after some some initial. And once this equilibrium this equilibrium status is is is reached by the system then the system can be obtained can be described by appropriate micro canonical or canonical ensembles. So, to see it in a little bit more details. Let us consider a certain many body quantum Hamiltonian age, which has its eigenstates psi m and eigen energies, em and consider arbitrary initial state, which can be expanded in the basis of Eigen states of this, of this many body Hamiltonian, if we now consider time evolution of an arbitrary local observable. And we look at its average value, then just the plug in the expansion in the of the initial state in the eigen states of the system will see that the observable at certain time is given by such a double sum. And now if we look at the average of this observable over a long time window, then only diagonal terms the m equal to n terms survived in this, in this sum, because of the long time average. And so so so so far this is just a general expression from from quantum mechanics. And now the main foundational hypothesis of the quantum quantum and the system quantum and the system is against the termization hypothesis, which states that the specific initial condition, which is encoded in those in those coefficients c m does not matter for the for this equilibrium average of local observable. And this value of this observable is just given by a sum over a certain microchemical ensemble which is determined by the initial state by its energy and its energy spread, which can be written in such a by such a thermal thermal average. And now this is the, this is the usual, the usual situation quantum and the body systems that they do approach this thermal equilibrium and they then they fulfill the against the termization hypothesis. However, they are, there are no exceptions to that, to that behavior and one of the exceptions exceptions is the phenomenon of many, many body localization, in which quantum anybody system is in the presence of strong disorder. So, so, so I'm going to describe an experiment which was done in 2015 it was an optical lattice with with fermions, which could help between adjacent sides of the lattice. They interact via spin up spin down density density interaction. And then there is the quasi periodic potential, and which plays the role of disorder in in such a system. And now we consider an initial state such that each even site of the lattices occupied by by a fermion and each outside is empty. And we consider a so called imbalance, which is an observable, which, which is roughly total population of the event sites minus total population of the outsides, and we look at its time evolution. So, there are two possibilities for small delta, the imbalance in Italy, there is some initial transient it is in balance is initially equal to one, and then it decays to zero very quickly if delta is small. This means that after some time of time evolution, the uniform density profile is reached by the system, and the system, then a full fuse the Eigen state termization hypothesis. However, if the this delta is strong is large, which means that the system system is in strong disorder, this is no longer the case. Even after a long time of time evolution, a non zero value of imbalance is present in the system which means that the initial state that the traces of the initial states, state are present in the system, even after a long time of time evolution, which the Eigen state termization is invalid, because, yeah, this average value of imbalance and codes, some information of the, of the initial state. But this means that the system is many body localized. Yeah, so so so that was that was a generic generic static setting in theoretical calculations the easiest systems in which one could can study. So many body localization easiest from the point of view of computational methods are spin chains because the onsite people places just two dimensional. And the standard model of MVL is exact Z spin one half chain, which has the spin flip part, there is a Z as the interaction and the disorder enters via a random onsite magnetic field and usually one assumes a box distribution from minus W to W where W is some disorder. And when one is looking from their perspective as such a model. One thing one one could do one could simulate time evolution of such a such model just simulating an experiment, however, in order to be really sure that the system is located or not. So we have to extrapolate the results to infinite time, which is the same as looking at the Eigen states of the systems of the system or also at the properties of Eigen values and the most straightforward probe which allows one to distinguish systems which are the same logic is level statistics through the so called gab ratio despite this variable air, which is quantity which is obtained from properties of Eigen values of our system, and the Eigen values which are taken into account in such conditions are Eigen values in the middle of the spectrum so they are associated with highly excited and Eigen states of the system rather than the, for example, something close to the grand state so we have generic Eigen states and their values on them we calculate gab ratio, and then at small disorder. This gab ratio I think it's value which is, which corresponds to some random matrix theory, which means that the system is ergodic and once we increase disorders think this average gap ratio decreases, and once it acquires plus on value, which means that the energy levels of such systems are uncorrelated, then we know that the system is monobodylicized. However, although it is picture done for that model shows that it is not so easy to say where the transition happens for example because the crossing point at which one the data for different system sizes is moving within this system size to largely so this thing so it is not not clear for example where the transition is or even some people would argue that it is not clear whether the transition is there at all, or maybe this is just a finite size feature of this of this model. So if one looks at this Hamiltonian in the Eigen basis of the SZ operators, then there are two features of this Hamiltonian. First of all, it is matrix whose dimension is exponentially increasing with system size. This is just because the Hilbert space dimension is 2 to the L. So if one takes into account the total SZ conservation, then it is slightly larger but it is still exponentially large in system size L. However, this matrix is sparse in the Eigen basis SZ operators because the given spin configuration can be coupled by this Hamiltonian only to a configuration that differs from the initial configuration by single spin flip. Each spin configuration is at most coupled to L other spin configurations and consequently the Hamiltonian matrix is sparse. And now in order to be able to to get better and better results for this for this for this crossover and to have a better idea about man-made localization when one needs to reach as large system sizes as possible. So the question is how this sparsity of the matrix can be used in the most efficient way. So if one wants to calculate grand state or few low energy states or in general exterior Eigen pairs of such a system. So exterior meaning close to the grand state or close to the highest excited state. Then there is a famous lunches algorithm which is in a block version is shown in this blurry frame. So it is blurry because it is not so important. The only thing is that which is important is that this algorithm employs the sparsity of the matrix because the only thing which it does it considers certain initial vector and then acts with the Hamiltonian on the on that vector and performs then some linear algebra operations. Yeah, and the thing is the thing is that this sparse matrix times vector multiplication is the thing which can be done easily for sparse matrix. And this, this algorithm allows one to get the to transform the Hamiltonian to the diagonal form and then to obtain eigenvalues and eigenvectors at the ends of the spectrum of such Hamiltonian. The problem is that when we increase the number of eigenvalues we want to and eigenvectors we want to calculate with this method, then this then this algorithm becomes very inefficient. And one question is whether we could try to find a method which combines the good properties of this lunches iteration and uses the sparse pattern of the Hamiltonian matrix in in the most efficient way. One way to do that is to use the so called shooting method, which is more or less the state of the art method. Or at least up to recently, and the idea is to employ a spectral transformation and instead of Hamiltonian. My matrix one considers a transform matrix which is shifted and inverted Hamiltonian. And if we assume that the spectrum of our Hamiltonian is from minus one to one, the spectrum of the transform matrix is from minus infinity to in general to pass infinity. The thing is that the eigenvalues at the edges of that spectrum correspond and eigenvectors correspond because eigenvalues and eigenvectors of the R sigma of H matrix and H matrix are the same. And the eigenvalues are transformed. So the eigenvalues of R sigma at the edges of the spectrum correspond to eigenstates of the H matrix in the middle of the spectrum, which means that performing lunches iteration for this R sigma of H matrix. We can obtain the eigenvalues in the middle of the spectrum of this of the Hamiltonian. However, to perform this transformation to perform the lunches iteration one needs to act with matrix R sigma of H on vectors. And to do that, the only way is to calculate earlier the composition of the Hamiltonian. And the problem we value the composition is that it does not preserve the sparsity pattern of the matrix, which results in severe feeling of the matrix. And this is this was identified as the main bottleneck of this of this method, at least for the quantum many body systems. So, the idea of the pulver. So the abbreviation pulver comes from the polynomial polynomial filter exact diagonalization method. So the idea is to use spectra transformation, which is done by a order of high order polynomial. Instead of Hamiltonian we consider a high order polynomial of the of the matrix. And this Hamiltonian is chosen in such a way that it is picked strongly around certain certain energy. So if we are going to assume that spectrum of the Hamiltonian is from minus one to one, then it is picked around some some value some some value sigma. And to achieve that one can choose in various ways the coefficients in this, in this expansion for example one can use the coefficients of the expansion of Dirac delta around centered centered around energy sigma, which will give us strongly picked function around this around the And the idea is then similar one just uses the does the lunch was iteration for this transform transformer transform. And the good thing is that one avoids this bottleneck of the shipping method, because acting with high order polynomial of Hamiltonian on a vector is can be just translated to acting with the Hamiltonian, without ordinary Hamiltonian of vectors on vector and performing linear combinations of results of such of such of such calculations, which means that the sparsity pattern of the matrix is used in more efficient way in that in the approach. So the perfect algorithm. The words in the following way, following way, first we rescale the Hamiltonian, because generally the Hamiltonian has some grand state and some high as excited state, and we, which has certain energy energy, we rescale the Hamiltonian in such a way that its spectrum is from minus one to one. And then we find an order of the polynomial transformation, which has to be matched with the density of states of the Hamiltonian, and the number of eigenvalues we want to obtain in our in this, in this perfect, perfect algorithm. So the number of eigenvalues which is obtained is roughly shown in the by this green shade, sorry, gray shaded region. And knowing the value, the number of requested eigenvalues we and knowing the density of states of Hamiltonian which can be either obtained from some analytical and analytical estimate or can be calculated efficiently for sparse matrices. So we find the determine the order of this polynomial aspect of transformation, and then we just perform brogue lunches iteration for this, for this transformed Hamiltonian, which converges after certain numbers of iterations of this lunches procedure, which and the main. The lunches procedure is again few linear linear algebra operations. The most important one is this action of the transformed transformed Hamiltonian on on matrix of vectors. And then there are few organization steps which are less time consuming less less important. And during, actually during execution of this popular algorithm, the number of converged eigenvalues is shown in here as a function of the number of steps for few values numbers of the requested eigenvalues. Because the number of because the eigenvalues is 100 and here 200,000 and 2000. And we see that roughly after two times number of steps, two times larger than the number of requested eigenvalues, the algorithm converges, and then the eigenvectors to which it converges and eigenvectors of the initial Hamiltonian to the eigenvalues which are in the middle of the spectrum of this of this original And this this perfect algorithm has few features. So first of all, it then most time consuming step is the action of this high order polynomial on matrix of vectors. This can be parallelizing two ways. First of all, if this QQJ is matrix of vectors that is some, and it is for example, let's say 20 vectors in there then we can do action of this polynomial on each of the columns of this matrix in parallel and then each of the products can be parallelized on its own. But the vectors which are obtained in this action of the of the transform Hamiltonian on the on some initial initial vectors, they have to be stored during the time during the execution of the of the of this algorithm. As we saw only two or three time more eigenvector vectors kept to be stored on the eigenvectors that the number of eigenvectors you want to calculate. And the matrix in which we can form them dominates the memory conception of this of this program and this is much much lower cost down in the other ways of considering eigenvalues and eigenvectors in the middle of the of the spectrum. Finally, there are two to further further classes of this of this method. One advantage is that time consumption increases only linearly with increasing number of non zero elements of this of this Hamiltonian age, which is not the case for other people who want to do this shift and then we will see that the this time consumption increases much much more rapidly with the increasing number of non zero elements of this of this Hamiltonian. Finally, it has also a nice feature that the only thing the only thing which is needed in this in this pulver execution is action of the higher the polynomial of the matrix on the on eigenvectors which means that it can be used for example for flocket systems in which the flocket operator. If we only can find a good way of an efficient way of acting acting with flocket operator on vectors, then we can use the similar ideas to obtain eigenstates of flocket systems, which was, which is hard to do with other methods and the total flocket operator doesn't even have to be the doesn't even have to be a sparse matrix. Benchmark on the disorder pin chain is shown in in this plot in this slide. And this is benchmark of the pulver method around and the shift and that method, which was, which is state of the art method. So, for the most standard. Exit pin chain, as we see that time execution as a function of system sizes quite similar in pulver and in the student in that however memory consumption is orders of magnitude smaller for for for for for example, for the l equal to 26, 26 spins, the pulver needs like 500 gigabytes of RAM memory, whether the sheet and invert needs like more than to 10 to five gigabytes of memory which makes calculations with the sheet and the method very very challenging. And the second plot to be run on very large supercomputers. With both of the, I, one can calculate things, even on few, few notes of some super computer. The second plot show more or less the similar similar story, when the number of non zero elements is increased, then the performance of both of these, even, even better as compared to the as compared to the sheet and invert. All right, so this concludes my, in my description of the pulver method, and now I will come back to this problem of many of the localization. I consider either the exit this pin chain or j one j two model, which is very similar. The only difference is that I have in j one j two model I have captains between the neighbors pins and neighbors. And the whole problem with analyzing the many of the localization transition is that it is, there are very strong finite size effects at this at this transition. And this is, this can be exemplified on such a such a problem shows some property. This is this kind of bipartite entanglement entropy of eigenstates in the middle of such system, which is expected to be close to unity for ergodic system or to decrease like one over L for localized system as you see that there is in the end for value disorder strength. Thanks. And there is a gradual change, change between the two behaviors. However, in the middle, there is some kind of non monotonic re entrant behavior in which the systems first flows towards something which is which looks localized because with increasing system size, the scale entanglement entropy is decreasing, but then at certain length scale, it starts to increase. And the same stories can be obtained from this average gap ratio, which which is obtained just from the eigenvalues. So, to analyze this crossover, I have considered the following disorder, disorder strengths. Wt and W star and Wt of L is deviation from the ergodic behavior and it is obtained for given system size L at the point at which the average gap ratio crosses this red dashed line, which is which is taken to be a little bit smaller than the value expected for the ergodic system. And W star of L is an estimate of the transition at given system size, it is just crossing point of the data for two system sizes. And now if one looks at such a crossover and plots the two disorder strengths as a function of L, or rather as a function of one over L, one obtains plots like that. So horizontal axis shows the vertical axis shows one over L, which means that the thermodynamic limit is here. And the horizontal axis shows disorder strengths and the two plots are for the either J1J2 or XXZ model. The two models behave in a very similar way. And this crossing point can be very nicely described by one over L behavior, which suggests that the systems do become minimally localized and one could extrapolate this one over L behavior to infinity, obtaining some estimate of critical disorder strength. However, the story is not so simple because this WT deviation from the ergodicity behaves linearly in L for the system sizes which can be obtained with numerical method accessible at the moment, which means that the two skilings are in fact incompatible because one has to have WT smaller than W star at all system sizes just by definition, which means that either of the skilings must break down at value smaller than the L equal to 50, which is obtained from the extrapolation of the two skilings. They cross and it's clear that one of them has to cease working. So there are actually two possible scenarios. Either this W star one over L scaling works and then this WT linear scaling in system size adapts to it at a certain length scale. Or it's the other way around. The W star of L ceases to be one over L but starts to be in this linear with system size, which would mean that there is no manual localization. So, trying to understand this scaling is quite interesting. So, motivated by this picture, we looked at other class of pin chains in which one can actually get data for larger system sizes. And those class of spin chains is motivated by recent experiments with Rydberg atoms. And in for such chains of Rydberg atoms one can enter blockade regime in which the Hilbert space is effectively constrained in such a way that there are no two spin up states at distance smaller than than alpha, where alpha is the blockade range. Usually the blockade range is one and then one obtains the PXP model, which is the famous model in which the quantum and the body scars were first observed and then understood. But this alpha in this talk will be just a parameter which can be also larger than one and then I will get a class a family of of constant spin chains with the property that it's Hilbert space dimension is increasing more and more slowly with increasing range of this blockade regime. So, for alpha equal to zero no blockade then the Hilbert space is just two to the L and for alpha equal to one it's 161 and then for larger values of alpha this value which is then taken to the L power is smaller and smaller, which allows one to get larger and larger system sizes for increasing blockade radius. And if I now so I look at this at this system, so I have the system with constraint and I added disorder and to look at the similar things as I did for the for this standard spin chains in which many body localization is is well studied. And when I did the similar extraction of WT and W star, I obtained the results which are shown in here. Now the system size is shown on the horizontal axis and the disorder strengths are shown on the vertical axis. Yeah, and the main thing is that what we observe is that sufficiently large system sizes we observe just linear bridge of this disorder strength, which suggests that those systems aren't really monodolar price even though at given system size we do see a crossover between ergodic and localized behavior. The interplay of this, of this, the change of this crossover with increasing system sizes such that it just shifts to larger and larger disorder strengths, more or less linearly with system size, essentially are system sizes, which means that there is no man able to localization in the in such such systems. So, trying to understand this. And one, one thing is that for for those constant models, one is able to get much larger system sizes so 26 for alpha equal to one but once we have constant values equal to two, then we are able to reach like that is four spins and for alpha equal to five we can reach 50 spins, which is larger systems, larger system. However, the properties of the fox plays are quite different. Yeah, so if we look at the Hamiltonian of the system, and first forget about this term the eigen states of this term are just the eigen states of s i z operators so these are certain spin configurations. So let's try to do if we can assume that this is large and this is a perturbation. This will be just a perturbation which couples certain spin configuration to other other configurations. And one can introduce a quantity called, which we call the radius of Hilbert space in such a way that assume that we have certain spin configuration. If we are to the kinetic part of the Hamiltonian, then we obtain a certain number of spin configurations. And now if we are to the Hamiltonian on all of those configurations then we obtain larger and larger and larger number of spin configurations and the number of times with we with which we act with the kinetic term of the Hamiltonian operators on given spin configuration until we reach the whole Hilbert space is a certain variable are, are, and then if we average this variable are over various initial spin configurations then we obtain quantity which characterizes this this particular space of the constant systems. And one can expect that if this radius is small, which means that small number of actions of the kinetic term is sufficient to reach all of the spin configurations for from the given spin configuration then we expect that the system will be prone to the localization because this term will be acting more efficiently. So, if we, if we look at this order pxp models with and plot the radius of Hilbert spaces function of system size for values radius of constraints we see that with increasing values, radius of constraints, the radius of Hilbert space is much much much much more slowly increasing the system which means that that the localization those systems is not so unexpected, it might be just traced back to the fact that this, this term is just much more is becoming much more effective within decreasing, sorry, increasing the radius of constraints. So this brought us to consider another class of constant spin chains in which you also have a disorder on site disorder term. And we have the same kind of constraint, which prevents us from having to spin up or sorry, or in the language of particles to party to occupied sites at the distance smaller than alpha. And, but now we have just a hopping hopping term which means that we have a certain number of particles. And this model has the property that the Hilbert space radius is increasing linear with L for arbitrary alpha. Just because of this is so just because of the different nature of the committee. We consider some some symmetry and some total as Z or some number of particles in the in the system so something is some certain feeling. And what we obtained from the same analysis is that this model is again becoming delocalized in large L limit for at least for large for significantly sufficiently large radius of constraint. And that was quite surprising for us. And then we talked about thought about the one proper one interesting property of the system with concert number of particles. If you look at this Hamiltonian and forget about this other term. Then those particles are actually behaving as a particles with radius. And this maybe maybe maybe it is maybe visible in this in this figure so few sites are occupied by green particles. The particles can have hope to adjacent sites, and they cannot hope to a site. If a particle is in the neighborhood to that site this is for a radius of constant equal to unity. This means that with each of the particles I can associate an excluded volume I can, for example, which for alpha equal to one I cannot associate with each particular site left right to it, and say that this is a new particle. And then if I and then I can shrink the whole whole chain, which means that I obtain from a system constraint I obtained system which is unconstrained. And as you see the hopings which are possible in in this chain are the same as hopings in this chain for example the third particle can hope only to the right cannot hope to the left. So this is the unconstrained case because of the constant radius equal to alpha in the unconstrained case, just because there is particle to the left of it. And then the particles are hard to do so. This effect actually gives us mapping between a constant model and unconstrained model, which allows us to translate each of the states of the of this constant spin chain so so this is just a state which means that the this is Fox state this representation of state in Fox space. So this shows us which of the sides are occupied in the constant model, then if we add zero at the end of this of this of this state, and then take zero which is after each occupied side in this in this constant model and we forget about the zero we we attach it to the particle. Then we obtain unconstrained model, which tells us that n particles on L sites in a model of constant with constant radius alpha and open conditions can be exactly map to n particles on L minus alpha times n minus one sites in unconstrained model and this is exact mapping, mapping between the Hamiltonians because the hopings are the same in the constant and unconstrained cases, which means that in the absence of this, this term that this model is actually non interactive. However, I, as I was saying, I, if we have non zero value of W, I was observing a crossover between ergodic and, and localized behavior and ergodic behavior can be obtained only if the interactions are in the system which means that this disorder term actually introduces interactions to the system. And this can be seen in the via this, this, the same mapping. So the, the, the mapping is repeated here. And now if we look at if we introduce disorder to the system, and we look at the constant model with each of the particle is is experiencing a field with the number which corresponds to the site at which the particle, at which the particle is. If we do the mapping, then the energy of such state must be the same, which means that the first particle has fields potential h one, the second particle is potential h three, and the last particle is potential h seven, which means that the mapping between the potentials is affected is is change is changing in a non trivial way by this transformation. And so actually this particular screening potential h three, even though it is on the sites site number two if we start numbering the sites from zero, just because there is one particular the left of the of it. And this particular fields potential h seven, even though it is on the fifth, on the fifth side. Which means that there are there are correlations between the, the particles the particle fields potential which is shifted if they there is certain number of of particles to its, to its left and this can be this just means that the disorder term in the, in the constant model can be written as a disorder term plus all to all interactions of infinite range between particles in the constant model, which somehow explains why there is no border localization in the system. It is just because the interactions are of infinite range, and they, their strength is increasing the disorder strength with disorder strength. And, and we believe that that is why we do not see localization in this in this model, which also means that one has to be careful when one identifies disorder. In this system, disorder term is actually also introducing interactions to a representation in which the particles move in a constant way. And that's why the models are not localized. So this brings me to my conclusions. So first of all, Paul Fett is a method which utilizes the sparse structure of Hamiltonian matrix to efficiently obtain highly excited Eigen states, which are needed in studies of systems out of equilibrium, for example, in trying to obtain informations about the localization and or about the city of, of isolated quantum and the systems. And the other take home message is that at the moment, at least from the numerical perspective it's hard to reach an ambiguous conclusions about the localization transition and the constraints models, which we consider because we thought that we can access larger system sizes actually are not many body localized, even at strong disorder states. And this is due to peculiar way, peculiar interplay between disorder term and the and constrain term, constrain terms which actually introduce interactions to those systems. Okay, so, so that this, that would be it. Thank you for your attention. Thank you for the nice talk. We'll have plenty of time. So it's a good time to ask questions or give some comments. Okay, maybe I stop. I probably just to miss to this part about the final size effect in many body localization. Can you go there? This one? Yeah, this one, I think as well. One slide before. This one, let's see. As you said, there is a decrease in the increase. Yeah, but is it not done yet? Up to 50, as you said. This is what is not known. So, the problem is that once we know that there is such kind of behavior in the system, then it is a certain term that these sort of things. Then we can always be worried that if we look at the largest disorder, and we see that we've increasing size size, our, our entanglement is decreasing. Then we can always be worried that at some point it starts to increase. To somehow see how monotonic this behavior is, I looked at those crossings. So, actually, if you think about it, the crossing for various system sizes happens if there is, if the curve in here is flat. This means that the entanglement entropy for L equal to 10 and L equal to 12 is equal to each other, which means that for such data there is crossing. So, so tracing the minima of those curves is the same as tracing the crossings of those curves and tracing those crossings gives you this data. Quite clearly one changing like one over L, which would suggest that there is no number of localization, which is also the trend is quite clear. Yeah, however, there is this problem that the other part of the crossover is not really adjusting to this, to this, to the scaling that each, at least, at least at the system sizes, we can access enumerate. So, to really see whether this, this part of the crossing is WT this deviation from the, from the GOE, from the ergodic behavior is adjusting to this behavior of crossing points then one need to, then one would need larger system sizes and this is not, not accessible currently. Yeah, but the hope is that there is. Yeah, this for me is that the one can find models in which this, let's say this crossing happens a smaller smaller system size because it could be that for the different types of models. This crossing happens at smaller length scales that can be actually reached in numerous. Yeah, and also the problem is that the, all of the other approaches to manualization are somehow inspired by new made so it is quite important what we see in the medics. So, besides the various first approach to manualization which was that they keep argument. This is, this is because. Maybe another question about the last part of your talk and constraints. I used, well, when you actually it was very nice version that the effective side of the change is reduced because I used to have like one side particle but now you have inside particles. And initially I thought, yeah, here. I thought there will be like, if this one, then you have a particle of size to, but it's also trivial. There is, it's constrained how the course of this expectation that they can come close to each other, but they can still share this memory size. Yes. So, so, so that's, that's how I think about it. So I think about each of the part of us, but for alpha equal to one of the particular radius tool.  And in such, and then if you shrink those particles, then they just moves as, move exactly as ordinary, ordinary hardcore boson so for example, because this particular radius tool, then it cannot hop on top of this particular. And so, so this is how how the constraint works. And this is what allows one to do that mapping the in the systems without this disorder between the constraint and unconstrained case and the spectrum of the constraint. However, the it is not all the features are the same because the mapping is not, not fully, not fully local, which means that for example the entanglement could be changed. So on the previous slide that increasing radius of your constraints, you can increase radius of your length of your chains, but in some sense, you just, it's just rescading of going to the larger radius of hardcore boson. You are talking about this one. Yeah, like 616. So, so that is important distinguish the distinction between this model which conserves the number of number of particles, and then you really can think about particles which do hope. And between this model, which does not concern the number of particles. So, if you translate it by the transformation to hardcore bosons, then you will see that this time is just a plus a dagger. Yes, means that you can excite you can create an annihilate occupation. Particles just just like that, which is probably like, for example, in superconductor superconductors. The interesting thing is that when you can do that when you are allowed to change the number of particles, then you get this problem with the decreasing radius of feedback space with increasing radius of constraint constraints, which is not the case for the, for that model because then you like, for example, in such a system with large constraint to get, and if you have certain spin configuration, you can just be excited, be excited all of the spins to spin downstate and then excite whenever you want the spins, and you can reach in few steps, all of the, all of the states, this is not the, this is not the case for the system with with concept number of particles because then the particles have to hope between the adjacent sites, which means that there is there is many actions of the kinetic term needed in order to reach all of the states from given for space configuration. Other questions or comments.  Yeah, yeah, exactly. So, so, so we claim that there is no no MPL in those systems, because we see linear drift of the of this crossing point so if there was a localized face then we would expect the saturation of this of this curve with increasing health and such saturation to critical and that and most probably if you also want to have just a transition, then we would also want to have this line to approach the WT to approach W star and to merge at some point in the critical in the critical point in such a way we would obtain a step function which would be something expected for the transition right, we want to have the deviation from from the ergodic value, and then we want to abruptly decrease value of the of our observable to to the localized localized value. So, so, so saturation saturation of this curve and approach of the WT to the crossing points. This is what would be seen for a system which which is becoming localized. And in the bottom curve that this crossing will not be there. You mean those funds. So, so they are also here. Yeah, exactly. So, so, so, so these are different, different, different variables. So, so in here, L is increasing if you go to in that direction vertically. So, so we have learning for the localization then we would expect that this curve in the thermodynamic limit so one over L going to zero reaches some some reaches some finite value of W and this curve. This is WT adapts to it at some point. And then also reaches the same, same. These are the things for a key change. Does that mean, and does this. Yes, yes. And does this depend on the kind of observable that you're studying. Yeah, good question. So, so, so actually there are two, two observations shown here, which I didn't mention so I can do such analysis of the crossover. Right there for this gap ratio, which is just pure level statistics I don't do not look at I can stay at all, or I can look also at properties of entanglement entropy of, of eigenstates. And then if I normalize in such a normalize this entanglement entropy of eigenstates in such a way that it is equal to unity in ergodic regime, then I get very similar crossover. So this is one of these scales entanglement entropy as function of disorder strength, and I can really analyze it with the same disorders scales. Sorry disorder states, and these W star are the blue blue points are from this entanglement entropy so as you see the two observables either the orange points which are from these. The blue points are from entanglement entropy and blue points which are from the gap ratio, give you very similar behavior so this is what would be. Yeah, so so so those two observables are consistent. So I would expect that other observables are consistent as well. Okay, okay. And they do change. These transitions and do change in this continuous manner in terms of. The last question for me. Okay, there is another question, please go ahead. Okay, I mean, is there a model where like you get all these points exactly cross each other. Like this. So so if I want to have a model in which I have ergodic phase and I have localized phase and if it is in the interactive model then I do not have at the moment I do not have a model in which I have clear evidence for for either of the behavior that closest model. In some sense close to many of the localization and close to. Yeah, but but simpler is Anderson model on random regular graphs and this model can be studied analytically and it is known to have critical disorder strength like equal to 18.1 which is for certain certain properties of this random regular graph. And this shows the similar figure as I was showing you before for that model. So, so what is what is obtained for this system. So I again get the crossover between the localized phase ergodic phase and the localized phase. So I analyze it in terms of these crossing points and increase of this WT, and I obtained the following behavior. So this is the one over lock two of anywhere, and is the size of these random regular gap. So thermodynamic game is again at zero as a function of disorder strength I see such behavior, and then if I extrapolate this behavior now it is not like one over L but like not one over this variable but there is second order in this variable, then I get something close to the critical disorder strength. And the nice feature of this Anderson transition randomly like that is that this ergodic boundary is already starting to adapt to this, this crossing points. So the dashed line black dashed line show the linear behavior and it's sufficient in our system says there is the deviation from this linear behavior, the increase of this WT is slower and and that curve starts to adapt to it but as you see they are still quite far from each other and yeah, so, so, so there is another crossing point now of this modified modified extrapolated point and then to really see whether if they are not crossing each other then one need to reach system sizes again roughly 50, which is by 50 I mean two to 50 the size of the random regular graph which is again not not not accessible, but for this model it is known that there is the transition so so this actually is a kind of check whether my method of extrapolation has any sense so so it does because it gives you roughly sensible value of critical disorder strength as compared to the value which is known Okay, thank you. Other questions or comments. So that's the case. Then, again, thank you for behalf of all the participants for this great talk. And I can call this session by thinking Adriana here and they see before making this very nice possible. And I keep for the floor to appear and join in case they want to make some kind of remarks. Thank you very much Andre. So, Adriana, do you want to do the closing remarks. Yeah. So, first of all, also on behalf of Pierre I'm pretty much of this. I wanted to thank everybody that participated both the speakers the panelists of chairman the audience for just, you know, taking your time to sit down with us and show us your work show us what you do. One of the reasons why we wanted to do this is that we really wanted to try and fix the fact that it's very very common that we don't know what the guy that works next door to us does, which is something that we should really try to avoid this is our little, you know, stepping stone towards trying to avoid something like this. I also wanted to thank the large number of people I was actually really really surprised by this that took the time in their talks to start with introductions about their fields introductions about what they do and explaining things to people that were not specialists into their topics and into the, the subject of their research. This was a really good effort that I felt should be acknowledged, because not all of us as specialists in everything and so it really helps. If we start if we go in steps and we explain what we are doing before going in with you know the interesting stuff and Pierre and I are very pleased to see the amount of questions the amount of interactions that have been going on. Hopefully this will also bloom into something more only time will tell, but this was also one of the intense of our conference so we were pretty satisfied about this. And that pretty much concludes what I wanted to say now to know if Pierre wants to say something more. No, I think you you summarized my feelings quite well. So we really hope that you got something out of this conference scientifically and also perhaps in terms of connection with as Adriano was mentioning the person next door that maybe you have been eating with but you may not have known the content of his or her work now now you And we hope that with both the knowledge and let's say networking that you did during this conference you will be able to to use it in the in your career in the future. But in the meantime, I thank every speakers I think every spectacular every participant. And I wish you all a good. A good Eastern holidays if you take some, and I wish you farewell until the next time. Goodbye. By the way, next year we won't be one last thing and next year we won't be here neither Pierre nor right to organize this thing but we've already received questions about can we do a next year. So if somebody wants to step up and organize the thing, please do and maybe call us. We will try and see what we can do. If you need some tips. Otherwise, Godspeed everybody. Bye bye. Bye bye. Bye.


Hello everyone. I'm going to talk about the new source to image feature in OpenShift 3.2 that allows you to customize the official image that is shipped by OpenShift for adding your configuration, plugins, and other stuff to the Jenkins image. So how does it work? The source to image processing OpenShift is a mechanism that allows you to point at a source code of certain things, could be your application, in this case it's a configuration of Jenkins. It takes that configuration, it layers it on top of the Jenkins official image, downloads the Docker image from registry, layers those stuff on top, and creates a new image, container image containing the official image, your configuration and push that into the registry. We can use that as the base image of creating Jenkins instances on OpenShift. Why do we do that? Because we want the Jenkins image that we start with, we want to have all the plugins that are required in my team already configured in it, all the jobs that I need for different kinds of things, the credentials for connecting to things, and the configuration of the required Jenkins. I have every time that stand up Jenkins instance, I go reconfigure everything, I go manually add those kind of stuff. So it really simplifies customizing Jenkins image so that I can stand up new ones, pre-configure everything like follows the immutable infrastructure principle. On top of that, we're going to do one more thing that is also available in OpenShift 3.2. We're going to use Jenkins pods for running the slaves in Jenkins. You can run Jenkins in this sort of manner. Then you want to run many jobs, you want to have more instances of Jenkins available to just delegate the actual running job to those instances running job and get the result and show it in Jenkins master. In OpenShift 3.2, we can instantiate pods on demand, run the job and terminate them after the job is finished and show the result on Jenkins master. How would that work in this demo? We're going to have a job that looks at Git repository for an application, it's a Java application, it's a list of tests, expose the REST API for that. So Jenkins talks to OpenShift. It asks to create a new slave pod for Jenkins. Then it starts that job, it's a Maven job, builds the application and package it on that slave pod. It's going to pull down the Java, the Maven dependencies that it has from a Nexus that I have also running on OpenShift. And after the job is finished, it collects all the results, collects all the reports and removes that slave pod so that it saves resources for the next job. So let's switch to the demo and see some of this stuff in action. Okay, Jenkins is up and running, so far so good. Let's switch to Jenkins and look at our job. I need to login, the default password is password. You can customize that in the template provided. So we have the task field job already pre-configured as if you can see in the master in GitHub, I had already a task field configuration with conflict XML so that is laid already on top of this Jenkins image and it has pre-configured a job for us. If you look at it, it's cloning the task application from GitHub. It's a normal Java application, nothing complicated on that. Okay, so how am I going to say that this needs to run on those particular pods on OpenShift, the JDK8 pod, so we use restrict where this project can run and say this project can run on a pod that is labeled as JDK8. And the platform will recognize there are no nodes defined but there is one cloud node provider, OpenShift, that supports this type of label. I saved this. Let's run this side by side. All right, let's start this build and see what happens. So a new build is instantiated, it's queued, it's waiting to find an executor to find a node. Now it's going to talk to OpenShift as you see a new pod is instantiated, it brought up based on the JDK8 Jenkins slave that we built. Now the job has started running on that particular image that we created, it's normal build, it's going to clone the source code, it's going to run the build, takes a few seconds, run the Maven build package and after this is succeeded, it's going to remove that pod. If you start several of these jobs at the same time, you're going to have several of those pods standing up, right, to allow us to own parallel builds on separate environments, just creating them on demand and remove them as the job finishes. Okay, the job was finished, the pod you see disappear takes about 30 seconds, 40 seconds to build a job and it was a sunny, green build was successful. We can verify also through looking at the logs, there's a Maven build, all good, and build successful and success. So that's about it. Jenkins is trying to be able to allow us to customize the official Jenkins image and also at the same time using the Kubernetes plugin, allows you to on demand to create a slave pod on OpenShift and run the jobs on it and remove them when they are needed, not needed in the model. Thank you very much for listening.


From Hollywood, California the Lux Radio Theatre presents Frederick March and Florence Eldridge in The Outsider with Douglas Montgomery Lux presents Hollywood. This program made possible because of your friendship for our products. Tonight brings you Frederick March, Florence Eldridge, Douglas Montgomery, Donald Crisp and Marcel Corday in the stage and screen success The Outsider. Also behind the footlights of our theatre here on Hollywood Boulevard are two special guests. Miss Anne Barkens, who tells us how motion pictures are edited and Milton H. Berry, who like the central figure of our play, is devoting his life to an amazing treatment for cripples. Our conductor, Louis Silver. And now, here is our producer. Ladies and gentlemen, Mr. Cecil B. DeMille. Greetings from Hollywood, ladies and gentlemen. The banks in recent years have had their ups and downs, but they suffered their severest loss when Frederick March became an actor. A surgeon removed Fred's appendix and his desire for banking at the same time. Up to then he'd sat behind a desk at the National City Bank of New York, but during his convalescence he realized that he'd rather be behind the footlights. Even before then, Fred had longings for the theatre. Of all the laurels he accumulated at the University of Wisconsin, where he was honor student, manager of the football team and class president, none meant as much to Fred as the University Voderville Cup, which he won for putting on the Best Variety Act. He met and married Florence Eldridge while they were playing together in stock. Then as tonight they were co-starred. Lovers of the legitimate theatre will be delighted to learn that this fall, Frederick March and Florence Eldridge will leave their Beverly Hills home for a while and return to the New York stage. Mrs. March entrains for the East a week from tonight. And she can blame me for holding her husband here. At the moment, Fred is up to his nautical boot-tops starring for me a journal of feet in the buccaneer. Tonight, however, he sheathes his cutlass, turns his back on the swamps of Louisiana and becomes Anton Ragazzi in Dorothy Brandon's melodrama, The Outsider. His lovely wife is heard as Le Large Sturdy. Our all-star supporting cast features Douglas Montgomery as Bessel, Donald Crisp as Dr. Sturdy and Marcel Coday as Madame Clost. Curtain time. Our stars enter. The footlights clash on and the Lux Radio Theatre presents Frederick March and Florence Eldridge in The Outsider.  A heavily shaded desk lamp throws deep shadows on the whitewashed walls. Behind the desk sits Anton Ragazzi.  Somewhere a clock strikes three. And from the shadows on the other side of the room comes a low moan. A woman lies there strapped to a table.  The table, like a modern instrument of torture, gleams brightly in the darkened room. She moans again and Ragazzi comes softly to her side. Here, here, here, here. What's the matter? My legs, they hurt tonight. They feel as if they're being thrown from my body. Stop it. You wish to walk again, do you not? Yes. You must bear the pain. You must grit your teeth and clench your hands and say over and over to yourself, I have faith in Anton Ragazzi. I have faith. I have. But it's been so long now. So many days and weeks. And months, yes. The rack works slowly, very slowly. Who'll soon be over? How soon? Tonight, I hope. Tonight? Tomorrow morning, Madam Plast. You will take your first step. I'll walk again. Quiet. You must rest. Hysterical patients are bad patients. You must take no chances. Hello? Trafalgar 6840, please. Hello? St. Martha's Hospital? I would like to leave a message for Dr. James Sturdy. Tell him his patient, Madam Plast, whom he discharged as a hopeless cripple, has been cured. Tell him the rack, which he said was useless, has straightened her hips so that tomorrow she will be able to walk. Tell him if he will call his staff of physicians together at 10 o'clock. I will be pleased to give a demonstration. This is Anton Ragazzi speaking. No, no, not Dr. Ragazzi. Just Anton. Gentlemen, gentlemen, please. Dr. Sturdy, in my opinion, we should recognize this Ragazzi. He has a machine, a rack as he called it, that will cure a lateral curvature. I'd like to know about it. You'll have your opportunity, Dr. Ladd. He's coming here at 10. But I may tell you, frankly, I shall not be here. I have no faith in this man. Nor have I. He has no degree. He has no medical background. He's obviously a charlatan. But he has cured cripples. His facts prove it. Ladd, I think you mistake the issue. We are all deeply interested in giving our patients the best treatment possible. But we cannot expose our patients to the risks of a cure, which has not been tested and proved by competent physicians and surgeons. That's intolerant. Do you really believe I'm intolerant? Perhaps I ought to tell you why. That's hardly necessary, Dr. Sturdy. I'm intolerant because I've learned the mischief that cracks can do in the person of my own daughter, my own child. You know her, some of you? Yes, yes, of course. You know that she's beautiful, talented. You also know that from her hips down she is a hopeless and helpless cripple. She wasn't born that way. There was some slight dislocation, but I never knew it. Her mother died when she was born and I refused to look at my child. I sent her away to some people in the country. Then I left England. The people never wrote. I didn't know until three years later that my child still couldn't walk. She crawled, dragging one little foot. They were having her treated by a local bone-setter, an unlicensed physician. That's a terrible thing, Sturdy, a terrible thing. I think I knew I was a father then for the first time. But before I could reach her, the child's hip had been so twisted and torn that nothing could be done. Nothing ever will be done because of my neglect. Sturdy, I think we hardly realize she is a cripple. She has such chance, Billy. Yes, her music. She has her music. Father? Have you quite forgotten me? Oh, good morning, Mr. Sturdy. May I please? Or are you saying dreadful things I mustn't hear? Come in, dear. Thank you, no. I can manage a short walk. How are you, Dr. Ladd? Come and sit down, Larry. No, I can't really. I only came to pick up Father. He promised he wouldn't be late because I've got a big rehearsal this morning. And I love songs. You know the lyrics? That's a low-end, aren't they? Yes. We've been collaborating. He writes beautiful things. They go well to your music. You conduct yourself? No, I can't, Dr. Ladd. You see, the thing takes nearly half an hour and I... I can't stand that long without my stick. But I think this new conductor they have can give me what I want. I've heard he's quite good. But he isn't me. I don't think how you'd feel if you had to watch another surgeon performing your pet operation. Come along, darling. Goodbye, everyone. Goodbye, Mr. Lally. You see? You see the way she has to drag herself? I will not meet this man who he needs presumptuous ignorance made due to another man's daughter. What has been done to mine? Good morning, gentlemen. Good morning, sir. Well? Well, Ladd. Sturt is the finest chief of staff this hospital ever had. It's our duty to stand. Reception Room B, the nurse said? Yes. I'm nervous, Dr. Ragazzi.  You walk this morning, you walk again now. Ah, this is it. Good morning. Oh, come in, Mr. Ragazzi. I'm Dr. Ladd. Dr. Ladd, how do you do? This is Dr. Tally, Dr. Israel, Dr. Mann, Good morning, sir. Good morning, and this is my patient, Madam Clost. But where is the great Dr. Sturdy? I came here to catch the big fish, not the small fry. Dr. Sturdy has just left. He will not meet me, eh? Why not? Mr. Ragazzi, I think we'd better tell you in confidence. He's had a very painful tragedy in his family. His only daughter is a cripple. He cannot cure her? No. He is a doctor. He has a daughter he cannot cure.  An intensely painful one. He does not like it, eh? He would like it still less if I were to cure her. I've heard you claim to cure almost anything. Not claim, Dr. I have proved it. Madam Clost, as you know, was one of your patients here. She was incurable. You admitted it, all of you. Now watch. Madam Clost, will you walk across the room, please? Yes, sir. Yes. Come, come, come, come. No hesitation. Walk. Is this all right? There. You see, doctor? Hardly any limb. What little there is I shall fix on my rack. Dr. Lads, yes, orderly. You don't touch it. Let's go, let's go. How are you, sir? I took the liberty of having my racks sent over. For your approval, of course, gentlemen. There. Now examine it, please. Notice how light it is and yet how strong. The workmanship is beautiful. That's because I made it with my own hands. The wheel that turns the pulleys is worked by electricity. You, you cannot see the turning. Because it pulls only the one thousandth part of an inch an hour. That, that is gentle, eh? Yes, it's ingenious. I'd like Dr. Sturdy to have seen this. He would not have looked at it. Because the rack has succeeded where he has failed. Well, that's not the point, Mr. Rogatse. Dr. Sturdy has no objection to your machine. It is more, I think, a matter of your qualifications to use it. What does that mean? You have no degree. Oh, oh, I see. You want me to have letters after my name, eh? That satisfies you and satisfies the public. All right, then give them to me. Are you suggesting that we should recommend the Royal College of Surgeons to confer an honorary degree on you? And why not? Have you ever served an internship or studied anatomy, except from a book? Yes. Where may I ask? Where may you ask? In the dark yards at Chicago. The slaughterhouse. Then now we to understand that you began as a butcher. A butcher? No, no. I began as apprentice to my uncle. He made apparatus for doctors. They came to us and asked us to make instruments that were mechanical impossibilities. So I said to my uncle, release me for one year. I'll go and cut up carcasses to find out how the joints fit in the sockets. What holds them and what makes them bend. And then we will make the finest instruments in all the world. Well, it's unheard of. You're shocked, eh? Mr. Raghatsis, we appreciate your energy, your enterprise and your courage. And we realize that you cannot be and should not be content to be merely a mechanic working under surgeons. Then why not do the theoretical work also? Quality work. What? Spend four years like a little boy studying books and writing answers to examination papers? You think I'd leave my work all that time? Leave crippled people waiting to be cured? Children? So I can learn Greek and Latin names for English bonds or not? Then understand. If you won't qualify, you must undertake no case without a surgeon. You forbid me to take cases without you. That is our rule. To prevent unemployment among surgeons, eh? To protect the public from unqualified practitioners. There's no backdoor to the Royal College of Surgeons or to wish to enter and must climb by the front doorstep. All remain outside. I will not stay outside. However much you bar me out, I will come in. I'll break down bars and bolts. I'll blow a hole in the back wall to make a door for me. Wall to make a door for me.  Keep me out when they have let you in. Oh, no. No, gentlemen. No. Bring the rack in here. Yes, sir. Let it stay at home where it belongs, where it will do some good. Not in the hands of fools. There's a charge on that. Here. Now get out. Right? I'm sorry. Things went the way they did. You. You are sorry. Did you support me? Did you defend me? When I was attacked? Did you sit there, momma's or mouse? I walked for them. Yes, yes. You walked for them. You did what Sturdy's own daughter could not. You. Yes. What is it? You walked for them. Now you must walk again today for her. For Miss Sturdy. But I don't know her. I want her to see you. But I don't know her. What does that matter? You go to her house. You hear? Tell her your history. But if she won't see me. You must make her see you. You still have treatments to be given. For which you cannot pay. You mean you take away to wreck? Yes. Unless you make her promise to see me. Tell her the doctors will not let her see me because they are afraid. Ha! Afraid that I will cure her. Tell her the truth. That I am an outsider. A nobody. But I do cure people. And that's what he said, Mr. D. If you don't see him. I'll be crippled again. Please, Mr. D. Here. Here is the paper he gave me. You can see for yourself. To Madam Anna Kloss. I, Anton Regazzi, guarantee to give you further necessary treatments on my special apparatus, the extension racks. If you'll persuade Miss LaLage Sturdy. Why, this is horrible. Basil, help me up, please. Of course, dear. But hadn't you better say where you are? I've never heard of such a thing in my life. Is this man human? He will sign it if you will let him come here. Only to see him, he asks nothing more. Please, Mr. D., do this for me. You don't know what it is to be a cripple? I... I don't. No, you are rich. You need never go when you're tired. You lie in bed unconscious. You are carried by your servants. What does it matter? What does it hurt you to be lame? But me... Please don't cry. I know how it must be for you. I'll see him. Oh, thank you. May I tell him now? Yes, tell him.  Of course, LaLage. Yes, sit down. He doesn't seem to be the sort of person you ought to see alone. The arrogant, the insolent arrogant. He's only got to see me and I'll be persuaded to let him treat me. But, LaLage... If he could cure you.  I've read about him. You'd be a woman, LaLage. Not a spirit in a prison. Basil, don't. Don't make me hope. Father says I mustn't. Sorry? You've been wonderful, Basil, all these years. You don't know what it's meant to have someone outside my family who didn't treat me as a cripple. You've never done that. I've never thought of you as one. Haven't you, Basil? But, if he could do something. Anything. Are you going to tell him your father says there's no hope? I'm not going to tell him anything. Or even let him see me walk. I'll just listen quietly to what he has to say and then tell him that he's had his pound of flesh but that he shan't touch one single bone. That's all. That's all, Basil. In just a moment, Frederick March and Florence Eldridge continue in the outside world. Meanwhile, we go to a suite in a popular hotel here on Hollywood Boulevard. A young married couple is there, hurrying to change for the evening. Oh, Jim, I can't hurry. My dress isn't back from pressing. And now I have a run in my stocking. Why such cheap stockings? Cheap? I'd hate to tell you, but I paid for these. All right, so they're not cheap. But I don't see why you have to get a run in them every time you turn around. Come in. It's the ladies' dress, Mr. Page. Oh, swell, Mary. Come on in. Say, maybe you can answer this. You've been a maid around here a long time. Do all women always get runs in their stockings? Well, I don't think they get run so often when they wash their stockings in luck. You mean those flakes? Yes, ma'am. That's the way I always do. It's just like it says in those lucks as you've seen. Rubbing stockings with cake soap is hard on the threads. And some soaps have alkali in them, and that's bad, too, but not in luck's legs. You seem to know a lot about it, Mary. But does it really work? Oh, yes, ma'am, from my experience it does. My stockings keep nice and springy. And most of the ladies that come to the hotel here think that's so, too. At least they always tell me to be sure I wash their stockings in luck. Well, maybe you're right. I'd certainly be glad to find a way to run on stocking run. OK, that settles the whole business. Here, Mary, get Mrs. Page a box of lucks and keep the change. And make it a large box, too. Come on, now, dear, please snap into that dress. We hear now from our producer, Mr. DeMille. The outsider continues, starring Frederick March and Florence Eldridge with Douglas Montgomery, Donald Crisp and Marcel Caudet. One hour later, the large sturdy lies on her couch in the sitting room waiting for a gatzie. The driver's about nervously arranging the pillows. Suddenly the door is flung open and Anton Ragazzi, unannounced, stands smiling in the doorway. How do you do? I am Anton Ragazzi. Do you usually enter a room without knocking? Only when I am in a hurry. You're pardoned, please. I am the large sturdy. Miss sturdy. This is Mr. Basil Owen. How do you do it? How do you do it? I understand that you will sign this paper if I agree to give you an interview. Certainly. But then you shall have one. Now, please sign. Of course. You must not look at me like that. I am not such a villain. But you would have tortured that poor woman. You think I'd take away the rack from her and spoil my best advertisement? But I had to make her think I would. Do you call that honest? Perhaps not. But that should reassure you. To know that you're not honest? Certainly. If I were not genius, I should have to be. Oh, I say. All is forgiven to celebrities. Basil, this man is impossible. Don't get up there. Yes, yes, yes. Let her walk. I want to watch. Ah. Ah, yes. What are you doing? You're looking at me like a doctor. I won't have it. Oh, no, no, no. It's all right. I have seen you walk. And when you are not thinking, that is good, eh? Don't mind. I do mind. Mr. Rowan, take her to the sofa. I will not look. Yeah, L.A. Are you comfortable? Yes, thank you. You are recovered from the shock? Mr. Agassi. Not quite, eh?  Put out your tongue and say 99. Ah, yes. Yes, you have the crook. Oh, why do I laugh? Because I make you. I make you let me in. I make you walk. I make you laugh. And can you make her well? Basil. Does she want to be well? Of course she does. She does not say so? No. No, I will not cure her. She shall stay a crippled. That will please her father, eh? That's a lie. Mr. Agassi, I didn't mean to see you. I know you did not. But as we've got so far. Ah, we have got so far, have we? You'd better see the X-ray photos of me. Then you'll know. And then you'll leave. Will I? Shall I ring for them, Lally? Yes, please. Oh, no, no. Ask Miss Cross to give them to you. I'll be back right away. Very handsome young man, eh? Yes. You love him, eh? You want to marry him? No. Oh, yes. But you would not curse him with a crippled wife, eh? Some other woman gets him, eh? That's not nice for you. And even if you were married to him, he would go to golf and dance with other women, eh? That's all the young ones think of nowadays, you know? Dance, dance, dance. And they hold each other pretty close, too. Makes them think of marriage, eh? You beast. Yes. A man, a man is a beast. He's a dog. A dancing dog.  It's no good. Must be a fine torture lying here knowing what a good time you would have if you were not a cripple, eh? Men would go mad for you. Throw themselves at your feet. You don't want that now, eh? But if I cure you... Get away from me. What are you? A temptation of the devil? Or an answer to my prayer? Half and half. I am not all bad. Well, they are. The x-rays. Aha, let me see. Quick, quick, the x-ray. Aha. Well? Tell me. Miss Sturdy, now I know I can cure you. You... You're sure? I'm positive. Lally. Basil, don't look at me like that as though you saw me with new eyes. You mustn't... Oh, Lally, see yourself as he can make you. Will it hurt? Will it be much pain? Yes. How long? For one year. Lying down? Strapped on my rack so that you cannot move. Twelve months. And then I shall say, rise up and walk. No more limping, no more lurching, no more crutches, no more boots like clumping hoofs. But you shall dance in Cinderella slippers with your prince. With me, Lally. Oh, Basil, don't I... I can't believe it, or... Oh, I can't. Your father says it's true. He will say it is not true. What? He will believe it is not. But which will you believe? Me or him? I... I don't know. I don't know. This can't be true. Did you believe this man yesterday when he said he could cure you? I... I like to hear it, father. It was so new that it was beautiful. The lies, nothing can be done. Father, he's coming here this morning. I've asked Basil to bring him. I won't see him. He can't touch you without my permission. He can, father, if he has mine. Lally, you don't mean this? I do. Then let me tell you this. For the sake of my patient who trusts me, my reputation, if you choose to put yourself in the hands of an unqualified practitioner, you will have to leave this house and me. I've got my mother's money, and my own. I'll leave today. Lally, did this man hypnotize you? Perhaps. He stirred up all my senses and played on them because he knew. What, Lally? Oh, father, don't you know Basil? I want him. And why not? But he isn't worthy of you if he doesn't know that you've got qualities of mind and soul and... Souls don't count with men in marriage. If you were a lame woman, you'd soon find that out. You don't know what you're saying. All the things that all my life I haven't said. Could you have ever fallen in love with mother if she had been lame? Could you? Don't ask me that. I won't. Because I know. I've known it ever since I read a sentence in a book. Men are more physically particular than women. And it struck me like a blow that that was true. Father Basil can't love me like this, even though he wants to. And I can't blame him. Because I know that if I were a man, I wouldn't want to marry me. I should want a woman beautifully perfect. The sort of woman Basil wants. Oh, father, I could make him marry me for pity if I played on his chivalry. But I can't stoop to conquer. Lally, Lally, why are you so proud? Because my life has been one long unending humiliation. It's crucified my soul. And this man comes and tells me he can take the nails out, lift me from the cross. He can do nothing for you, Lally. He doesn't understand enough of surgery to know he can't. There's nothing known to... But there's the unknown, always. Well, Lally, he's here. Bring him in, Basil. Thank you. Good morning, Mr. D. You know my father? I have had that pleasure. I want you to tell my father what you told me. It won't be necessary. I know what he told you. And I know what you told her.  Yes. And does she believe you? Does she? I can see she does not. She believes me. Lally, tell this man to leave. Do you hear? I can't, father. Then do you believe him? And I believe in God. A God who does things. A God who gives people the power to do them. I'm going to believe. I'm going to. Lally. Father, darling, you're absolutely right. I couldn't stay here. You're going to leave me? Suppose he makes you worse. Then I shall know I never can be better. Never marry. You can be better. Can be well. Listen. I have a house where I've had another patient. Rooms that are vacant now with a balcony that overlooks Regents Park. For you shall be all day, all night long in the open air. And I'll come to see you, Lally, always. Every day. Oh, Basil. That means you'll go? Of course she will. Lally. Father, please understand. I must.  And I can give it to her. Right leg is fastened. Yes, sir. Now the left. There. So. You are comfortable, Mr. Eddie? Yes, thank you. There will be pain. You must try to accustom yourself to it. Turn on the switch. Now.  You, you feel it? Yes. Yes. Yes. Yes. Increase on the right. You understand, Madam Clost? Yes, sir. The rack is doing well, Mr. Eddie. I have been gradually strengthening the pull. I could tell. The night seems so much longer now. Five months. You must count by the months. It will not seem so long. Three months. Four months. Five months. But every day has 24 hours. Madam Clost. Yes, sir. Morphing. Oh, Mr. Agassi. Why did you telephone for me? Is she in much pain? She says no. But she's so restless. She must not be. She must lie absolutely still. I told her that. She's been very sad all day. Why? Why is she sad? What is that Mr. Basiloin around here for? Well, he hasn't been here for a few days. Almost a week. Why not? He called. He's been very busy. Busy?  Doesn't he know everything depends on him? Why is she suffering like this if not for him, eh? Call his house.  Yes, sir. I've wheeled Mr. D under the balcony. He wants us to watch for him. I'll see her there. Yes, sir. Is that you, Anton? Anton himself. I thought I heard you inside. You recognize my voice, eh? I recognized your language. Who is the fool? Uh, some, uh, some friend of Madame Closte. A man called Richardson. He, he lives in Putney. Why did you come tonight? Well, because I passed here on my way back from the palace. I was dining with the king. It is agreed no lies, eh? No. I came because, uh, Madame Closte phoned me. She said you were restless. So when I met your Mr. Basil Owen downstairs, I told him he must not come up to excite you. Then he did come? Of course he did. He told you that he would. No, he only said he might. And so you wondered if he would, hm? And when a woman wonders if a man will come, she wonders if he loves her. Now you know, eh? Yes. He sends you all his love and a thousand kisses. All his love? All. And says good night, sleep well, and dream of him. You mustn't think he's been neglecting me. He's come every time he could. It's been dreadful for him all these months. Dreadful? To watch your spirit conquer your pain? To see me suffer. He can't stand suffering. A woman should always be beautiful. Should she? You think that, that is the only thing that matters to a man? You're talking like my father. And when I asked him if he could have fallen in love with a cripple. Yes. He wouldn't answer me. And let me answer for him.  I tell you... What? Nothing. You make yourself well for Mr. Basil. You make yourself beautiful and strong. It will be safe. But he wants me. He does want me. Oh, not as much as I want him, perhaps. Because I'm selfish, Anton. But I'm so weak and so tired. I couldn't hold on if I didn't know. If I weren't sure. You will hold on. He will help you. And I, I will help you. I will not leave you now until you go to sleep. You go to sleep, Lale. And dream. Until your dreams come true. You go to sleep. Because they will come true. He will sit beside you. Because he, he loves you. And as the months pass, he will be there, always. And then the time will come, not long. The crocuses begin to push out of the earth like flames. And you too shall rise. How he will love you then. If you will go to sleep now. Because he loves you. He loves you. He loves you. What? Mr. Owen is here. In the living room. Stay with her. If she wakes in pain, give her morphine again. He must sleep for now. Good evening, Mr. Owen. What's the matter? Why'd you call me? The matter is, I shall throw up the case. What? Yes, throw it up. What? Because I will not fail. But I thought you couldn't fail now. You've succeeded.  I have done, but nature has not. You must lie here in the imperfect stillness, six months more, till all that I have broken sets binds together, six months. What have you been all week? I've been busy. And I've needed some relaxation. I've called her. You think that's enough?   Lally and I understand each other. She knows. She is so weak, she cannot know. She only feels. Feels that you have another woman whirling in your arms.  Yes, I've wanted to sew fine a thread that if one tear falls on it, it is broken. I would assume that she should, should bleed as cry. I didn't know. I mean, I didn't think. Has it really done any harm? Well, I have not let it. I have told her lovely lies. Got her off to sleep by making love to her. For you. She's asleep? Good. Good. Good. That another man should play the lover to her? What have you in your veins? Red ink and lukewarm water? We can do without that. I stuck it out for six months. You think it was easy?  I never knew it would be like this. I never dreamed that... and I can't stand suffering. I never could. The water in your blood isn't even lukewarm. Can't stand suffering. And yet you say you love her. You, you do say that. Of course I do. Yes. Then you will come tomorrow morning at 10 o'clock and tell her so. You hear? Yes. But you will say it with conviction. Strongly. Or if you do not. If you fail me, if you make me fail, I will smash every bone within your body into splinters. So you shall be a cripple that no one can cure. Not even Ragazzi. Now, now you can go and relax. Mr. Ragazzi. How is she? She woke up twice. I had to give her the morphine, but it doesn't seem to put her off. She's half unnerved, half awake. She keeps calling for Mr. Owen. I'll see her. You wait outside. Yes, sir. Basil. Basil. Basil, where are you? Basil. Is that you? Is it you, Basil? Yes. I knew you'd come. I tried to stay awake. You. You must sleep now. Stay near me, Basil. I'm afraid. Afraid? Of what? Afraid if you go. I won't get well. Always a cripple. Always. No, no. You will get well. You will be well and strong soon. And I... I will always love you. It makes no difference, Lally Darling. You must believe that. It makes no difference. No matter what happens, I love you. Basil. Basil. You must sleep now. Good night. Aren't you going to kiss me? Good night, Lally. Good night, darling. Station identification. This is the Columbia Broadcasting System. Frederick March and Florence Eldridge resume the events of our play shortly. Tonight, our inside glimpse of Hollywood centers on film cutting. Film editors are to motion pictures what city editors are to newspapers. As the DeMille film editor, Miss Ann Borkins, has helped me make pictures for 25 years. And hers are the only hands apart from my own to which I've entrusted a film cutter's shares. Having gone through more than a million feet of film, Ann is now well equipped to answer the question that is probably first in your minds. What does a film editor do? Well, C.B., I'd say we cut out of a finished picture everything that is not essential to the most effective telling of the story. It's a great deal like putting a jigsaw puzzle together because the last scenes of a picture may be filmed first for production economy and the first scenes filmed last. You get an idea of how much cutting is required when you stop to think that if all the film photograph for souls at sea, for example, were shown, it would take 36 hours to run the picture. The average picture, when cut, runs about 90 minutes. I suppose you editors wonder why we directors don't save you a lot of trouble by shooting only what's good. No, we know that each scene has to be shot from many different angles. Otherwise, the set might have to be rebuilt at great expense if certain close-ups and angles were overlooked. Frequently, some of the best scenes and touches in the picture are the result of gambling a few extra feet of film. There are some things, however, that we can always depend upon to photograph the same, like scenery, properties, or costumes. I can remember the trouble we had years ago when costumes lost their sparkle or faded a little as the months of shooting went by. Complete new wardrobes often had to be made. We've eliminated that great ways today, or I should say the people behind this program have largely eliminated it with Lux Flakes. Lux is the official wardrobe-cared paramount because it keeps costumes looking glamourously fresh for the camera. It's a very rare case when I have to cut a strip of film because of costumes. The contributions of the film editors are not only visual. They also work miracles with sound. And one of our tricks is what we call pinching. That consists of taking the soundtrack of a speech that is delivered too slowly and speeding it up by removing the silent portions between the words. We've also developed another science called dubbing. In Mr. DeMille's picture, the Crusades, two armies of knights and armor rode madly across the field and crashed together while riding in full tilt. We made separate soundtracks of thundering hoofs, clashing armor, shouting men and the rain of blows on shields. Then we fused them all together. The result was that we had a realistic battle seeing filled with many different sounds and yet each sound remained distinct like the instruments of a symphony. That roughly is what the film editor does to make a picture more exciting. And you don't mind, Chief, I'll cut right here. Thanks, Annie. Once again, Frederick March and Florence Eldridge in The Outsider. Six months have dragged wearily by. Months of torture and endless waiting. But at last the rack has completed its work. It's the day of the final test when the large sturdy is to walk for the hospital staff. Ragazzi, excited at the prospect of his triumph, lifts her carefully from the table and carries her to a chair. There, there.  No, no, no. Don't try to stand. Just sit. I could stand. I know it. But not yet. You must wait for our friend, you know, for the physicians and surgeons who forbade me to practice because I knew no medicine. They shall see. Madam Clust. Yes? Where is that Mr. Basil Owen? Has he called? Not yet. And you call him. Tell him he should be here. Perhaps he's ill. Tell him to come if he's dying. If not, I'll go and bring him dead. Yes, sir. You mustn't go, Anton. You must be here when the doctors come. I won't have your triumph spoiled. I have no triumph if you have not yours. What do you mean? When first you walk, you want to go to Basil Owen, hm? I want him to be here. I also. Why? Because for you and for him, I have made something straight again. Yeah. I've never even thanked you, Anton. Oh, I want no thanks. I shall have glory. Is that all you care about? Yes. It's strange. You've done everything for me. And yet I must have felt it wasn't for me. Because I'll remember what he did when I've forgotten you. He? Basil. Oh. I was afraid for a while in the beginning. I thought he was weakening. And then one night he came to me. After you put me to sleep. And I knew then that he was mine. All mine. He told me it made no difference. That was love, Anton. Real love. For the first time. Yes. Yes, it was. And so because of that love, when you take your first step. I shall go to him. Half past eleven. Why in heaven's name don't they come? Basil, sit down.  I can't help it. I'm nervous. I'm not. Look. See my hand? I don't see how you can be so calm. Because I have faith, Basil. In myself. In Anton. In you. You're so sure. Yes. It's hard to explain, but I am sure. Perhaps it's because I have so little to lose. Because even if I should fail. I could still be happy. Happy? Lily, how can you say that? You said it for me. Remember? It makes no difference, darling. I love you. No matter what happens. I love you. Lily, I don't know what you mean. Well that. That night you came to me. When I was alone. I don't know what you mean, Lily. Basil, you are nervous. You haven't forgotten. Forgotten what? Lily, darling, you. You must have been dreaming. Oh. Oh, I see. If you're afraid, Basil. No, of course not. But. Well. I never said that, Lily. I didn't. You don't have to be so apologetic. I never meant to hold you to it. It was only that. It gave me strength all those months. Just to think you did love me enough. Not to care about it. Lily, please, please. And that's why you're nervous. You're afraid I'll say you.  When you needn't worry. You won't be. Lily, listen. You're going to be all right. I just know you are. But. But. Oh, God. Lily, don't make me say it. No, don't. Because I couldn't bear to listen. If only you'd waited, Basil. If only you'd given me the chance. If I did fail to let you go. But the fear within your eyes when you walked in this room. Lily, if I've hurt you. You have. Oh, not because I've lost you. I should have known it was too beautiful. But because just this once. I hoped. He leaves. But someone loved me. Just as I was. Lily. Lily. Darling. Here. Here, gentlemen. Here. Our laboratory. Where we will perform the great experiment. Lily, you're all right. Lily. Yes. Now. Now, gentlemen. You have seen the x-ray plates. You have seen how the bones have been stretched. Now. Now you shall see the final proof. Mr. Dirty has still not taken her first step. We have been waiting for you. Mr. Rowan, will you stand over there, please? No, no, no. In front of her chair. About 10 steps away. There. Now. Now, Mr. Dirty. Take my hand. Stand up slowly. So. Now. Wait evenly on both legs. So. Now. Now let go of my hand. So. Walk over to Mr. Rowan. I. I've forgotten how to. Not since. Not since. No. Right foot. Left foot. Think. Think. What's the matter? Here. Walk.  Call her. Hold out your arms to her. Call her to you. Lily. Lily. Come to me. I. I can't. I can't. I can't. Stand back. All of you, stand back. Lily. Lily. All of them. Yes. All of them. How do you feel? I feel nothing. Why don't you cry?  That wouldn't help. It isn't your fault. You tried. And I failed you. Twelve months of torture. Twelve months.  No, I'm done. Come in. Dr. Sturdy is here. Father. Lily. Oh, Father. Lily, my darling, don't cry. Don't cry, darling. You. You know. They just told me. That Ragazzi has failed. Yes. I have sent it to the papers myself. Mr. Ragazzi. It was not necessary. You think I cannot take my medicine? That I am finished? Oh, no. No, you can tell your doctor friends with notebooks that I'll begin again tonight. I found out the doctors know something that I do not. So I shall become a doctor myself. Yes. To find the way to cure Lily. What if you have found it? Father. What did you say? Mr. Ragazzi. You have taught me how to cure my daughter. How to cure her? I have seen your x-rays. I know now what we can do. Father, don't say it. Just to make me feel. It's true, Lily. You'll walk again. You will. Oh, God. Lily. Then. Then it has not all been wasted. It's just beginning. She'll owe it all to you, Mr. Ragazzi. Thank you. Thank you, doctor. I would like to feel I. I did something. I'm going to take her home now. I'll have the car brought around. Anton. I leave you alone. No, please. I hate to leave here. Somehow. It will be better. You will be happy again. He will return to you. Father. Yes. He will come back when he knows. Do you think I want him? As he is. As he is. As he was always. I never loved him, Nin. I loved someone else. Who? Who, Lily? A man who spoke to me in a dream. A man who came to me that night. Who held me in his arms. Held me to him. Soul and body. That man never would have left me. But there is no man like that. There is. Oh, darling. I love you. It makes no difference. No matter what happens. I love you. Wait. Oh, wait. That night. Was it a dream? No. It was the truth. Goodbye, Lily. Don't go. Don't go, Anton. You were there. It was you that night. Yes. Oh, Anton. Don't stand up. Anton, hold out your arms for me. Call me to you. Call me, Anton. Are you. Are you really walking? Yes. To you. Walking to you, Anton. Our play ends, but not our stars' performances. A little later, we'll hear again from Frederick March and Florence Eldridge. Each week, we try to bring you as guests someone of particular interest. Tonight, we've been unusually successful. Standing beside me now is a man whose life work parallels that of Anton Ragazzi to a startling degree. The friended 38 years ago by a cripple, he resolved to devote himself to the help of other such unfortunates. Never having been to school, he was not equipped to enter a medical college, and so developed his own methods. Though not a physician, he is founder and head of the Milton H. Berry Institute for Paralysis Correctment, located near Hollywood. Its directors include the famous author Rupert Hughes and Fred Stone, the noted actor. Through our play, we learned of a man who dared to aid the hopeless when all usual efforts failed. Such a man as our guest, Milton H. Berry. Thank you, Mr. DeMille, and permit me to state that I am not a doctor. I'm a teacher. My institute is a school, not a hospital. Those who come to me are not looked upon as patients. They are pupils. From my friend Rupert Hughes, I've learned some amazing things concerning your work.  Of men and women whose spines have been broken in automobile accidents, brought back to health for normal activity.  How, Mr. Berry, are these things brought about? One must thoroughly understand the action of muscles of live bodies. The laws that govern the mechanics of local motion and be able to apply them to the individual case. Before you can train the mind to concentrate with sufficient force to re-educate impaired muscles, the physical energies of the body must be developed. At some time in your career, Mr. Berry, something must have happened. Some case must have arisen that made you feel you had discovered a successful method for re-educating damaged muscles. What was that case? Yes, it did happen. Many years ago in Des Moines, Iowa, it concerned a young woman completely paralyzed from the waist down. A dozen doctors gave me their diagnosis of her case and told me I was crazy to think she would ever walk again. I did not blame them in the least.  Since then, I have helped over 2,000 infantile paralysis cases and 400 victims of other types of paralysis. It's not that I doubt what you've told us, Dr. Mr. Berry, but assuming that it is true, why aren't your methods practiced everywhere? Remember, Mr. Demille, I had been but one lone man practicing this method until I taught it to my son, Milton Jr. and Mr. Marion French. Our foundation, which is strictly nonprofit, was formed for the purpose of establishing a larger school to teach this method to qualify young men and women who, in turn, can go to centers of population and do just as we've been doing at the Berry Institute. Until the plans of the foundation are complete, I am limited to 100 cases at one time. On behalf of those 100 children and young adults, now under my care, let me thank you and the Lux Radio Theater for the splendid entertainment you bring them every Monday night. We've been happy to have you here, Mr. Berry. To Mr. and Mrs. Frederick March, I owe a debt of gratitude to Miss Eldridge for helping me interest her husband in the role of Jean Lafitte and to Fred for the superb characterization he's giving Lafitte in the Buccanea. For such great material, CB, it's pretty hard to miss. Like most people, I only knew Lafitte as a pirate, as an American hero. You know, it was a revelation to me to find out that unless he'd plunged in with men and ammunition to help Andrew Jackson and his cat-at-army at the Battle of New Orleans, all of America west of the Mississippi might now be part of Canada. One of Lafitte's most exciting exploits and amusing occurred when Governor Claiborne offered a reward of $500 for him, dead or alive. Lafitte was so indignant that the small amount he rode around New Orleans posting offers of $10,000 and that Buccanea was the only pirate in history who saved a nation. There never has been a more mysterious figure no one really knows where he came from or where he went after his career in America was over. He was resourceful and brilliant and a romantic man with all the color of a fiction hero. The Buccanea is the answer to an actor's prayer.  Speaking of the theater, what about this play the marches are going to do? It's called The Christian Hero, Mr. DeMille. Based on the life of Sir Richard and Lady Steele. You mean the Sir Richard Who with Joseph Addison wrote the spectator and the tatler? That's right. John Cromwell is going to direct and we hope to open on Broadway around Christmas time. Playing here tonight has certainly given us the itch to get back to the stage. I hope it'll be as much fun. We'll miss you both in Hollywood. But my wish is that the play will have a record-breaking rung. To both of you, a great success. Thank you, CB. Good night. When Edna Fairbaugh wrote Cimarron, she enriched modern literature and the screen with one of the most compelling stories ever dedicated to the Romantic West. Our adaptation of that story awaits you next Monday night. Had we personally asked each one of you, whom above all others, would you choose for the spirited role of Yancy Cravat, I feel certain your decision would be identical with our own. So we bring you Clark Gable. Starring with Mr. Gable, Virginia Bruce, and a special guest, Miss Edna Fairbaugh. Our sponsors, the makers of Lux Flakes, join me in inviting you to be with us in the next episode of Cimarron. Mr. Lux Flakes joined me in inviting you to be with us again next Monday night. When the Lux Radio Theatre presents Clark Gable and Virginia Bruce in Cimarron. This is Cecil B. DeMille saying good night to you from Hollywood. Reach to follow your attention this week to the Silk Parade, a brilliant feature in your local stores. It offers a colorful pageant of rich displays and timely hints on the latest fall fashions. Good silks are amazingly durable and most of them are safe in water alone, but you can trust them to gentle Lux Flakes. So you are being thrifty as well as fashionable when you wear silks in this season of elegance. Your announcer has been Melville Rui. This is the Columbia Broadcasting System.