Okay, I will just make a brief, so this is Karsten. Karsten is part of the part-time scientists who want to send a rover to a place where it's very hard to do 3D printing, so enjoy this talk labeled 3D printing on the moon, the future of space exploration. Stetsjus. Hi.  Just, OK. Is it what? OK, it's OK. You don't have to know. I was just checking. OK, so we're a team called the part-time scientists, and we were funded like 2008, so that's quite a while ago, with six people. And as of today, we are about 35 people that are working on their mission to the moon. And of those 35 people, we have now 11 employees, which makes the name part-time scientists a lie. So on the corner of the slide, you see our new logo. It's a PT scientist. And yeah, well, we don't know what the PT stands for yet, but we will figure it out eventually. So for those of you that have seen our presentation last year, we did win the milestone prices, so we won 750,000 US dollars for qualifying our rover, which is quite nice. And we also got a new partner, which is a bit significant. It's Audi. And we are cooperating with the DLR, with NASA Ames, and various other partners to get this mission done. And the Google Lunar X Prize is a competition where you can get $30 million for sending a rover to the moon. So this is our vision. We want to send a rover to the moon, and it should somehow look like this. This is actually what we are currently working on. So that was me yesterday. The line's main, everything is fine, which is why I had no time to prepare the presentation, so I hope it's OK still. Yeah, we're working very tirelessly on getting that done. The cool thing is that our new rover is actually a little bit bigger again. We started with a very small one, and we figured out that it's too small. And we increased it a bit, and it's too small again. And the last size increase came in the form of the wheels, because we found out that with more surface, we can climb up higher slopes and also decreasing the weight was very helpful. And the cool thing about the new rover is that the wheels that you see on the left hand side is a new wheel, and it's 200 grams lighter, despite being bigger. And we were able to do that because the left one is fully 3D printed. And this is pretty darn cool.  Not just because we are always tight on time. So it's also very helpful that you can get 3D printed stuff quickly. We could be more organized, but we have 3D printers, which is much cooler. So 3D printing is hard. You probably know, especially those that made the ones on your own, it's very tough to get it right, because the material that you get out of the 3D printer is not what you actually expect and what can be used. But we want to do it on the moon anyway. So yeah, this is just a nice picture that came up from NASA. No, was it NASA? It came up, and it was looking very nice. So we want to take the picture of that. And we want to land near Apollo 17. So that's the tower's literal value, which is near the equator. And we want to land like five kilometers near it. And there is in a one kilometer landing ellipse. So that's hopefully the landing area, not the impact area. We are working on that. One of the dates I adjusted for sending it over to the moon was to start on the 7th of December in 2017, because that's like 45 years after Apollo 17 happened. And also we would land on Christmas. And so if someone asked what we would do on Christmas, it would be like I could say, well, I made a new crater on the moon. So hopefully we don't do the crater thing. So the reason why we chose Apollo 17 in this past is mostly because it has a very interesting geological property. It was the one mission where NASA say, oh, we don't do it just for show. We actually want to do science. And so they took a geologist with them. And so there is some known data about the geology of Apollo 17. And so that's one of the reasons we want to go there. The other reason is the lunar rover vehicle that you can see here, we want to do significant science when we go there. And we don't just want to win the Google X prize. We want to do real science there. And we want to one of the science objectives as it was said by NASA is that they want to see how the stuff on the surface after 43 years of exposure is still there, whether it was shot into little pieces or maybe they find some other reason why we didn't find anything there. But yeah, the lunar rover vehicle is made of all kinds of things like leather and piano wire fiberglass. And it's interesting to see how that worked. So this is Apollo 17. So but now for the interesting part about 3D printing on moon. So the surface material of the moon is made up of lunar regulus, which is made of silicon, aluminum, titanium, iron, oxygen, and kind of other stuff. And it's a very, very fine powder. So when you think about the moon, it doesn't have any atmosphere. So there is nothing that could transport the lunar dust around. So it's sitting there for years and years and millions of years. And there are always all those tiny micro meteorites, which are bombarding the surface and smashing the surface into very, very, very fine powder. And this powder has some very interesting properties. So the question is, how could you actually use this material for doing 3D printing on the moon? And there are like three options. One we like very much. This is the microwave-based manufacturing. So the idea behind that is that you're using an ordinary microwave, or the magnetron of it, and you melt up the material because it contains some iron. And then you can get a solid surface of that. The problem with that is the regular simulants, which are used for various testing of testing rovers, or space suits, or anything alike, they are. Well, you can microwave them, but nothing happens, which is kind of bad for testing because this makes it very difficult. But there is one interesting property that is at least known for some of the Apollo 11 and Apollo 17 samples. And this is that it contains some iron. You can see those little iron. This is elemental iron that is enclosed in the glass. And this absorbs the microwave energy very efficiently. And so with very little energy, you can actually get a liquid phase between the particles, which then heats up even more. And there is a runaway simulant reaction going on that so that you get a solid material after you bombarded it with microwave. And the question is, what can you do with that? I mean, the microwave is not as focused as, for example, as a laser where you, with the laser, if you, OK, let me start a little earlier. So if you want to do laser zintering on the Earth, you are actually anywhere. But if you want to do, you take aluminum powder, and you take a laser, and you melt it. And then you put on another layer of this aluminum powder, and then you melt it again. And with that process, you can actually 3D print aluminum. And if you want to do that on the moon, you can create very fine structures. But with the microwave, you are not so focused. And the question is, can you still do anything interesting with that? And the answer to that is yes. If you have a microwave, you can actually make a surface coating of the regulars. The problem that you have when, for example, the Apollo astronauts were coming back into their capsule, they had the problem that the regulars are so fine that it actually went through their solar space suits and they got black fingers. And so the idea is when you're creating a surface coating by microwaving the surface, then you have a solid thing where you can drive on, where you don't generate as much dust when you're landing or when you're driving on it. And if you want to build a lunar base and you have to go out often, then not dealing with as much regulars is a very nice property to have. Also, there are some interesting ideas that you can actually make a radio dish when you're with that. So you take a regular crater and you surface coat and you have an almost perfect antenna eventually after a few decades of work. Yeah, so one of the ideas that was proposed is this boring lawnmower. But we think of something cool like this one. So the idea is that you have the magnetrons on the bottom side. And while you're driving, you're actually irradiating the surface. And this irradiation brings the surface, the material, to about 1,200 degrees Celsius in a very quick time. And this starts a melting process so that you get a very nice coating. And because we are using microwave, this is a very power efficient way of doing that. This is also why we are aiming to send a little experiment to the surface of the moon with the microwaving thing. Also, it's very interesting to do that because we are very power constrained in our payload opportunities that we have. And we are also, we want to do something simple. And if you want to build a laser regular printer, then stuff gets very messy. But I will show you some pictures later on. So if you want to go into additive manufacturing, there is significantly more to building a 3D printer than just having the ability to mold the material. The problem with the regulars is that not all material is well suited. So you need to collect the material. You need to refine it in some way. And then you can use, for example, a laser to melt it. The other thing that, for example, ESA is thinking about, who of you knows actually the moon village idea of ESA? Yeah, ESA is very popular. I find that people know more about NASA than they do about ESA, interestingly. So what they want to do is they want to do, they want to print a 3D base. No, they want to 3D print a base. And they want to do it with a clue that they are taking with them. And so they want to use a binding material for the printing process. And we think that's maybe not the best idea. If you can do it just with energy, which you have plenty of because you're on the moon and there is no atmosphere, then that's significantly better than using a binding material. And yeah, so ESA is supporting the idea of using a binding material. But I think that the laser printing one is the one that we are using now, which is probably the most mature. And so that's probably pretty good. But how do you actually separate the materials that you want to use for printing? So not all of the material is printable or this is very far sintering. And so you want to collect material that is small, that is at best fine powder, which you have plenty, but the size of the particles is very oddly shaped. So it's a little bit difficult to collect the material and to process it so that it can be used for laser 3D printing. And this is where this sucker comes in. It's a lunar soil magnetic collector, or lunar soil sucker, as it was called. And it's basically a rail gun in reverse. So you take magnetic fields and you use the property that the regular material or the part that you're interested in is actually magnetic. And so you're transporting the material in this sucker and it's floating in some reservoir and then you can do your whole 3D printing with the laser melting and putting a layer on top of layer. Yeah, that should work. When you're doing a mission to the moon for the first time in a few decades and you're doing it as a private entity and you started as part-time scientists, that's not the thing you want to do on the first try. So we're keeping the best for the next missions. So baby steps first, not make an impact crater, and then microwave the lunar soil. Actually, someone did use the lunar regular simulants that are available and actually built such a 3D printer, which is easy if you're on Earth and you have the regular printer and you're actually sitting by the printer and you can do a Russian repair by knocking it when it's failing. And the results are like this. I don't know if that is good or not, but it's something and it was 3D printed. Well, I mean, you know, so the good thing is that in theory the laser-based melting should actually work. The problem with laser-based melting is that a lot of the energy that you are... So if you're building a laser, a lot of energy that you put into it is not converted into optical energy, which goes out of the laser thingy. And then you point it at a material that is not black. It is, in this case, it's more likely gray, so you have some reflectance. And so a lot of energy is wasted in this way when you are using a laser. But as such, the advantage is that you can make very fine structures or as fine as this one. I actually don't know if it's inch or centimeters. It's small, it's something. I would give it a C for effort. Yeah, I mean, if you know 3D printers, you know, especially the aluminum-sintering things, it's very difficult to get right. With the problem with 3D printing is always the material feed, right? It's, you have the material, you have the PLA, for example, and you put it through the nozzle. And in theory, it should work in practice, well, not often or not always. And this is the idea as presented by ESA. And well, as a company, we have to think about business cases and the best we could come up with was, well, we are helping them do this. And this is the ESA vision of having a 3D printed multi-dome structure or moon village, as they call it. And they are working on it. I don't know what the current state is, but they are planning to do it. And as said, they have those clue-based printers. And I think printing a 3D printing a base is a very good idea because you want to use as much of the resources that are locally available as possible because bringing one, so to give you some perspective, so we want to bring something on the moon, which is our rover, which is about 30 kilograms. Actually, we want to bring a bit more, but back to that later. So we start with 30 tons of rocket on Earth. And until we are getting into the orbit, we are down to one and a half tons. And the one and a half tons, they fly to the moon, and then they do the soft landing part thingy. And then we unload the rover, we collect the money from Google to make a party, and we get about, yeah, tops about 100 kilograms of payload mass to the surface, starting from 30 tons on Earth. So the ratio is very bad. And so the, you want to use as much resources as possible, which is called in situ resource utilization, which is now a very active topic among planetary researchers because of the rocket equation and the ratio that I told you about. Another very fancy idea about how you could actually print something is to make a thermite reaction. So you take the material, split it into the right parts, and then you ignite it, and you should have a thermite reaction, which you can use for casting then. Well, apparently it was tested with some simulants, and it should work, whether it really does, well, I don't know. But, yeah, thermite is the, what is it, iron and aluminum? Iron and oxide and aluminum, ah, yeah. So you take iron and oxide and aluminum, and you ignite it, and then they start off with a runaway reaction, and this is used, for example, for cluing together the railways. So it's a very nice reaction. It goes, the temperature goes up very high, which makes it a little bit hard to handle. So, not on the first try. Yeah, so I told you about those ideas. We are looking for people that do help us, for example. And the sort of question is, what are we up next? And among the things that we are working on right now is our rover. We are very happy about it, if it works as we planned. And this next thing we start with next year is to build, actually, the lender. And so, if you're interested in building a cold gas flying things like this, something like this. You're very invited to join us and to shoot us an email. And one of the things that I forgot to mention, we also have payload opportunities. So we want to, we are selling, actually, some of the payload that we can take to the moon. And if you're interested in helping us to shoot microwaves at some real lunar regulars, we're looking forward to hearing from you. And unfortunately, because I didn't have much time to prepare some presentation than actually already done. But I hope you have tons of questions and I hope I can answer them to you. Sorry, thanks. And that was, am I on? Yes, that was a quick and I found it very interesting talk. So if you need to leave now, please do so quietly. And if you have any questions, please line up at the microphones on the right or on the left side. And please keep the voices down so we can hear the questions from the microphones. So if you want to talk, then also leave. That would be very nice. So please be quiet. Okay, very good. So first question on the right side, the front microphone. Hello. So you mentioned a rocket of about 30 tons. Are you currently engaging with anyone through building these rockets or selling them? Yeah, we are in negotiations with the Indians. Regarding the PSLV XL. So we plan to use that one. We are also in discussions with other alternatives. Yes, so we are in discussions about that. Okay, are there internet questions? There are at the moment no internet questions. So next question from again the right microphone. Hello, can't you simply melt the regulate by focusing sunlight? Oh yeah, that was a certain alternative that we were also thinking about. The problem with that is that you need to have, so the target temperature that you're aiming for is about 1,200 degrees Celsius. If you want to use sunlight, you would need to collect enough to create about 40 watts of heat in a very small area. So you would need to have a rather large optical thing. And if you know optical things, those are fragile. And launching in a rocket is the exact opposite of having a chip by DHL. Well, I don't know if that's... I don't know who I was insulting with that, DHL or the rockets, but anyway, so you can take the... In theory, it would possibly be possible, yes, and it has been tested. The problem is that you need to have a mechanical construction for focusing and for getting into the moon. And after you have done that, you also want to do something useful with that. So you need to not just focus it on a point, but you need to move around the focus point as well. So from a mechanical construction point of view, that gets very difficult, which is why we especially like the idea about the microwaving where you just create... It's not really 3D printing, but you're showing some interesting prospects about the regular surface and that is not possible with the simulant. So this is why we're preferring that. Okay, next question on the left side, the front microphone, that's you. So I think there is currently also a challenge from NASA to do 3D printing of habitual modules on Mars. Do you have something to say about that, like what the differences to moon and what methods might work? I know about the challenge. I think it's a very good idea. I didn't investigate it too closely, I have to say, but I think that in some ways, the Lunar Regulus is easier to handle because you have those elemental iron that is sitting in the class beats, but maybe I'm wrong. So it's both very difficult to 3D print on the moon and to 3D print on the Mars, but I cannot exactly tell you which one is more challenging. It's a, yeah, sorry, I don't know. But I could imagine that when you're thinking about 3D printing on the Mars, you're most probably not thinking about, or maybe you do. I was thinking about robotic missions. So if you're, when I think about Mars, there are always people there already.  But yeah. Okay, a question from the internet. Yeah, the first question is, is it possible to focus a microwave sharp enough to get laser quality precision in the 3D prints? That's a very good question. In the series with some antenna designs, it should be possible, but that might be difficult. What do you say? So the expert answer is it depends on the wavelengths. Yeah, no, I would say that it's definitely more challenging than having a laser where you have the concurrent light anyway. So it would be probably a bit more difficult to focus it. But the interesting thing about, we know from with a laser that it works with a simulance and so we can test it on Earth. But with a microwave, it doesn't work on Earth. And so I think it's more interesting to test that one out first. Also, it's more energy efficient. Okay, again, from the microphone on the left side. Yeah, first of all, thanks for your very nice presentation. I think I kind of imagined something completely different from, you know, as for 3D printing. But this microwave vehicle that you showed that basically creates streets, right? Yeah. Paths. If you want to make a structure out of it, how do you raise it up? Like how do you build something with it? So let me go back with that. So the basic idea from that Iza is proposing is say, that you actually have some clue thingies. So they are applying clue at certain parts or binding material to be more precise. And then they're using, build those kinds of things to put on the next layer. And with microwave, you could actually do the same. So you can build one layer, then you put on the next material on top and then you go over it again. The problems with that is that we don't have enough samples to know anything about the material that is deep within the regulars. So we know that the microwave-based thing has been tested with Apollo 17 dust, about 80 grams of it that was collected from the surface. The problem is we don't know whether the same properties are applying at material at a bigger depth. So there is a lot of research that could be done on the moon to know about that.  This is not for printing a gearbox or something, this is for building structures like these. Okay, next question, the right microphone in the front. Yeah, I think my question is more for you, especially in front, but how do you like intend to make those microwaves on the moon? You use magnetrons or like, I mean, it's not something that is light or like, and you need a lot of power, so. Actually, this is the funny thing about the magnetron, it's the energy that you need for getting the material up to 1,200 degrees, it's actually just 200 watts, and you just need it for, I think it was 30 seconds, because you have the, because you have the thermal runaway reaction going on with the microwave, so that's, so you don't need that much energy, so that's one of the significant advantages of laser, and about the weight and the size of the magnetron as well, yeah, that's a touch. And the heating, pardon? Like you have like excess heating. For the, what? For the magnetron, yeah. Because you're gonna have like dissipate, there is no atmosphere, so. Yeah, I mean, yeah. You need like radiator or something. Yeah, getting rid of heat is always very difficult because you don't have an atmosphere, so you need to dissipate it by infrared radiation. But this is, for example, something that we are doing in our rover as well, if we need to get rid of the heat, the basic way you are doing that is that, for example, with a solar panel, we are building a shadowed area, and we have the one side of the tunnel where the electronics are sitting in the rover, it's pointing at the black stars, the black space. And so, you have, here you have then a lot of cooling that is going on, and radiative cooling can be very efficient, especially when you're, when you're using special coatings. So I didn't know that, but it's really cool. There's a color that you can put on something, and it only has a 10% solar acceptance, so you just get 10% from the solar heat in what, but you can still radiate 90% of the energy that it's emitting, so that's pretty cool. Okay, the next two questions from the internet. Yeah, they're completely unrelated. Start with the first one. The, since the regular simulants are not really adequate, do you know of any robot missions that are planned to bring some of the stuff back? If I remember correctly, the Chinese mission, the last one was actually, there was a flyby, and they were testing the whole bring material back mechanism, and it was the next mission, which would be Shangri-Sriv, or four. They actually want to bring material back, so that would be the first time in a few decades that new material from the moon is coming back. And the completely unrelated question, what are the requirements to join the PT scientists? So, well, actually the requirement is that that you're interested in doing something crazy, and that you're passionate about what you're doing, that you want to contribute. You can contribute in part-time, so you don't have to quit your job and start with us. If you want to be working for us full-time, it gets a bit more challenging. But we're always accepting new applications, and so if you're interested in helping us or doing anything with us, just send me an email with what you're interested in doing, and we'll find something. There should be a form on the website, which usually does not work, where you can apply officially. Okay, we still have a few questions. The left-hand side, rear microphone please. Hi. What layer size are we looking at with the microwaving? Maybe with the rover, or how thick can you microwave? Microns, millimeters? No, actually it's quite thick, so it's about centimeters. If I remember correctly, there was, in the paper they were talking about, three to five centimeters, but I would have to look it up. There was a very nice paper ball from someone called Taylor, who's really into geological things, and it's very worth reading about it. It's also cited in the slides. Let me find that one. Yeah, here. So it's the microwave sintering of lunar soil by Taylor. If you Google Taylor and Luna, I think there are multiple Taylors, but they're all doing 3D printing on the moon, which I find very interesting. I think that the devs was rather surprisingly big. And are you going to do it with your rover, or is it just? No, so we are not going to do it with a rover, we're most likely not. The idea would be, I know our rovers, we have something that's called drop container, which are triangular structures that are sitting below the solar panel, and they can actually fall on the surface of the moon. And then they deploy, and then you have some solar power on the sides, and you have some experiments in the middle. And the idea is to use one of those drop containers for putting the microwave experiment in there. So it would drop on the surface somewhere outside our landing area. Thank you. Okay, the next question from the right-hand side microphone. Hello. So you mentioned this step-wise procedure where you do something less ambitious, like your first goal is to land the rover. Have you considered applying that to the 3D printing tool and perhaps starting out with something like what was mentioned by ESA, like bringing a binding agent and trying to see if that'll produce usable 3D prints first? Well, yeah, I mean, that would be a fair idea. But on the other hand, microwaves, so.  I don't like chemicals. So yeah, I think that doing the microwave thing is easier than probably the binding material thing. And also from a scientific perspective, it adds more value because you know that with a binding material, you can create structures. And with a laser, you can build things as well. But with a microwaving thing does not work with a simulant, which I think makes it even more interesting to actually try it on the surface on the first try. Okay, another question from that microphone, please. How do you plan to look at the decomposing rover of Apollo 17? Do you just want to take a picture or will the rover have some special device? Yeah, so the thing is our rover, as you saw. Oh, okay. So the question was how we are actually going to analyze the rover material. And the thing is that as you can see in our rover, we have three cameras and two of which are color sensors, which are wide angle, so those are used for driving. And the middle one is a Taylor lens with a black and white sensor. And in front of the sensor, there is a color filter so that you can look at different wavelengths. And with that, we can do some analysis about the material and how it is behaving. The problem actually would be to drive up to the rover and bump into it or something like this because there are some guidelines on how to approach the Apollo landing sites and there are some protection areas where we are not allowed to land and there are the protective areas where we are not allowed to drive in. And fortunately, at Apollo 17, the lunar rover that they use for driving is actually standing outside of the protection area for driving by. I don't know if that is intentional or a mishap. We would not be violating it by bumping into it, but we are not trying to. OK, I'm looking at the signal, Angel. Does the internet have any questions? The internet is very happy about the questions that are being asked right here. So the rear left microphone there, please. The next question. Beside lasers and microwaves, have you... The moon have a really good vacuum, like an old-school cathode ray tube and have the possibility to use an electron beam cannon on the regolith? So, I mean, in theory, you can use any heat source that is able to get the temperature of the regolith to a certain degree of Celsius. So, maybe. I don't know if anyone tried. So, I don't know. Sorry. OK, the next question from the right-hand-side-front microphone. Have you thought of printing parts of the rover at the moon? Because then you wouldn't have to send up so much mass. And for example, you could send up a rover with little gears, so you can drive to a better place for printing bigger gears. I know what you mean. Yeah, have you actually used a 3D printer? Yes, I have. So, the problem is, you know, in theory. So, I was at a presentation and that was very funny. There was some guy who said, OK, my next startup is about making, solving a problem with the 3D printing industry and that is that the data files that you are transmitting to the printer are not encrypted. And so, I will ensure that the Airbus can send the 3D printing files to a 3D printer on an airport and so they can replace a part on an airplane just in time. If you use a 3D printer, you know that is very far from how everything goes. You know, even with, I mean, if you look at the aluminum wheel that you can see here, you still have those rings and they are coming from the fact that the material is contracting while you are printing it. And while this is a very known problem when you're using, how do you call Gießen? When you're using casting techniques and the software can compensate for that. But in 3D printing, this is still unknown. And so, you know, it would be nice to print something useful. But I think we are far from that. So, baby steps first, land on the moon softly, collect the money and print something. OK, very good. We have a question on the left hand side, front microphone. I'm sorry. I'm still kind of stuck with the building structure thing. And I probably know that you can't answer all these questions and there are still answers to find. But if you have the rover that runs over the surface and then beams, microwaves at the ground and then later have the bulldozer to put new soil dust, whatever, onto the microwave platform and then again have the rover go onto it again. If you go up like, I don't know, two meters high or so, at some point your rover will have problems climbing that wall, wouldn't it? And wait, I'm sorry. And so, my question is, how far away from the soil do you have to be to microwave it? Like, can't you build a satellite that, I don't know? Yeah. Excuse me, John. So the energy is lost by the radius square. So if you want to deposit 50 watts into the lunar surface and you are 3,000 kilometers away, which is like a good orbit for a lunar satellite, just to the mass, that's a lot. You would need a really big satellite. And then I would probably use a laser, because lasers are cool. And the basic idea about the first question is actually, well, you define the slopes to be in such a way that you can actually drive them up. And you also see that they are using those, how do you call them, the caterpillar things. Well, that's a bad idea. So this is an artist's rendering. It's a good idea, but the practical problems still lay ahead a lot. There will be a lot of PhD thesis about this stuff. OK, we actually still have time for Q&A. So there are questions from the internet. Second question. Yeah, there's one more question from the internet, and there's still not quite over that regular simulant thing. So the question is, why are the regular simulants so bad? So let me find that slide. So the thing that, usually when you have iron on Earth bound things, it's usually an oxide. And those oxides don't react as well to the microwave as an elemental unoxidized iron. And the interesting thing about the lunar surface is that with the bombardment of the micrometorites, there are those glass beads which are actually forming. And with the radiation, some iron oxides actually degenerate into this elemental iron. And usually, regular simulants are done by the ingredients. So you look at the regular list that you collected on the moon and you then take in all the materials so that when you're doing a spectrum, then when you're analyzing the ingredients, you get the same bill of materials to say. And then you look at the crane size and you make it fit like this. And that's about the state of current lunar regular simulants. They are not exposed to the radiation from the sun that you have. They are not in vacuum. They usually don't have those glass beads forming. They are not shot at with micrometorites. So in this way, you have the most regularists don't actually have those nanophosphate, the nanoface iron in them. That's the whole point of it. OK, so there's another question on the left-hand side. Real microphone, please. Yeah, that's you. Have you ever investigated and researched the idea of making something like bricks by just compacting the lunar dust or something like that? Yes, there have been tests with some of the material, but it was found that it's because of the shape of the material, it's very coarse. It has very rough edges. And because of that, it's not very well compressible to say it like this. I don't know if that actually makes it a good building material for something like this or not. Yeah, so the answer is, I don't know, because I know we didn't try. But I would say that the density, you can't compress it enough. You will always have some air or some vacuum trapped in it, and it might be difficult. OK. OK, same microphone, please. Have you looked at the solar-sinter project? The what? The solar-sinter project. That was the guy with the big-ass thing about vanspermeter, I think. Yeah, exactly. Yeah, so that's really cool. But as I said earlier, and the question is that the problem was with Pringing, the big-ass lens to the moon is Pringing it there. And also, the weight, this weighs a lot. And then you still need to have the mechanicals to move it and to do something with it. So it's a really cool project. I like that, but it's very difficult to do on the moon. OK. OK, so on the right-hand side. Front microphone, please. It's just a follow-up to that brick's idea. Maybe we could put some lunar dust together, then microwave it into the brick, and then use the robot to put the bricks together, and then microwave them together. Yeah. That would be cool. Yeah, baby steps first. OK, a question from the internet, please. Yeah, there's one more question from the internet. Why don't you just dig caves to build houses, or build a cube with microwaved regolith and dig a hole in it, or mill it? Sorry, what was the first part? The first part was, why don't you just dig a cave and build houses? Oh, yeah. So you don't actually have to dig a cave. There are already caves that you can use and that are ready to move in. So this is one of the ideas that is actually actively talked about. So the cool thing about the lunar surface is that you actually have something that's called lava tubes. And some of those lava tubes have openings where you can actually drive into. And I think this is a very interesting idea to build a settlement by becoming lunar cavemen again. But this is not us. So also, Iza wants to do a 3D printing. And whoever pays us, we will deliver. And the second part of the question was build a cube with microwaved regolith and dig a hole in it, or mill in it? Yeah. Sure. There are many ideas that are ranging from something we should do in our first mission and something that maybe someone should do. I would put it here. OK. I see the microphones are empty right now. The internet is apparently satisfied also. That's a great thing. That was a great talk and a great Q&A session, especially. So thank you.


Imagine, a nuclear incident anywhere in the world. Imagine, rather than leading to global disorder, the decision support system for nuclear emergencies affecting food and agriculture, better known as DSS for NAFA, springs to life. It sets up sampling plan, it navigates sampling in the field, collects data from field and laboratory, processes data and visualizes decision support options. And this is how it does it. Immediately, it downloads and analyzes data on known radiation contamination rates and within minutes gives decision makers a range of precautionary options for protecting food and agriculture. At the same time, it computes what additional data will be needed to inform decisions that will keep the population safe. It combines land use maps and crop calendars with sampling protocols for each type of crop and vegetation in potentially affected areas. And by using pre-established sampling grids, instantly creates detail assignments to guide sample collection teams in the areas. The geolocation of its mobile app even registers sample positions and adjusts the grid if they are taken off position. And at the same time, sample collectors provide additional information directly from the field via their mobile. The samples are then analyzed in pre-selected laboratories that are also linked to DSS FNAFRA. And the results of each sample are recorded directly into the system. DSS FNAFRA now contains all the information it needs to generate visuals, easily comprehensible maps of the data superimposed over geographic and land use maps. Using innovative computer algorithms and geo-visualization platforms, the information is shown without overcrowding the map, even ranking according to significance. Decision makers can even generate interactive queries, for example, about the rate of contamination in space and time. The continuously evolving situation is visible at a glance on tablets or screens and at scales from field level to national and international level. And with all of this, it requires minimal training to use it effectively. And while decision makers use this information to formulate up-to-the-minute guidance with regard to agricultural production or food consumption restrictions based on national regulations, political specificities and actual data, DSS FNAFRA is already providing support on subsequent sampling assignments and continues the data acquisition process so that authorities are always presented with the latest and most up-to-date decision support. It's vital to be well-prepared and DSS FNAFRA will be a crucial component in this endeavor.


customer sanitation in Python so the audience is for people who are very relatively new to data science in Python. I'll do a step-by-step walkthrough so if you are already an expert you're welcome to stay as well. You can check out my GitHub account here and directly look at the slides and the data and the sample data and code if you want to walk through as I'm talking. Customer sanitation is very important for every single business. Imagine if you can segregating your user base into different groups then you can provide them with customized products and services and customization normally makes people happy that probably means higher profit for your company is great for the business. Take the 2012 Obama re-election campaign for example Obama is a data science team they use very tailored messages to target the voters based on the behavioral data, demographic data, financial data so that definitely have helped Obama win a lot of undecided voters and the election as well. So for the rest of the talk I'm going to pretend I'm a new data scientist in this company called Ypedia. It's one of the world's leading hotel booking companies I'm really excited to join it and obviously has some competitors out there with similar names so the mission of the company is to revolutionize how people travel through data and technology so on my very first day of work the CEO gave me a huge assignment. He has a board meeting coming up he needs to answer a few questions such as providing a report of underperforming and overperforming segments and how to tailor different new marketing campaigns for different cities coming up in the next few weeks and the most important question how to improve user booking rate which is a bottom line of the business so as a newbie in a company I want to impress the CEO I say yes I'm going to help you with that so what should I do? I go to our data engineering team and they give me this CSV file. They give me this CSV file with a lot of numbers and I have new need to come out of the work plan very quickly to answer the very difficult question for a board meeting so I'm going to first explore data then understand what kind of user information I have in the first place then I'm going to try to use some of the basic data tactics to answer the three questions so I know in Panda I can I know in Python I can use NumPy and Pandas that can help me easily explore the data so first of all I load the data I load the CSV file into Pandas using a read CSV function in Pandas okay is it better? okay great so and this this is this sample data is from the WIPDF homepage and the data engineering team has logged the basic information about what kind of information people are searching for and whether they have made a booking or not so after we after we load the data into a data frame which is some something similar to Excel table in pandas and we can use function such as head to take a look at the first 20 rows of the data so this is the kind of information we have in a database so we have date we have date time which is we should have time stamp when people make a booking we have location data where where the user made a booking so it's worth noting that the data here is anonymized into integers so into seeing the actual location location name the city name we're seeing an integer here corresponding to a different value and we have information like whether the booking is made on mobile or not whether it's a marketing package related to it and what marketing channel is a booking from checking date check out date great so these are really useful information so in pandas we can we can operate we can use a few different operations on on data frame we can do view that's what we did just now we can also select we can also select data let's say if I want to just look at the different site names we have what I can do here is yeah you would there you would in this way I'm only selecting one column instead of the whole data frame I can we can also merge different data frame together into one table into one data frame and then we can also group by data frame to understand the aggregator numbers on based on the based on the group values that's something I'm going to demonstrate later on so in pandas and many different functions that's very easy to that's very easy to use they can directly give you exploratory data analysis results for example min and max and unix to give you a unique number of entries in the in the column and the describe function info function d types function these are also very very easy to use exploratory data analysis functions you will see a lot of information of the data frame by just typing one word so after we understand what data we have the next step is to understand whether we can validate some of the business logic so one of the biggest lessons and learn so far is really never trust a raw data given to you because whatever data that's given to you is very easy it's very common to have programming bugs when people are logging the data for human mistakes if this data entered by human beings so in this case there are a few business logics I want to check the first one is it's a checking date actually later in a booking date so you're booking a date for some you're booking a trip for some time in the future not for some time that's has already passed and whether the checkout date should be greater than the checking date so you are actually you're staying for a positive number of days instead of a negative number of days and the number of guests should be more than zero so you are booking it not for a ghost but for actual human beings yeah so these are the and that definitely a lot more checks you can think of and I encourage everyone who is out there doing data analysis to perform as many business logic checks as you can think of so for demonstration purposes I'm just going to check whether the checking date are there any data entries where the checking date is actually after whether check is before the booking date so I'm performing a select operation on data frame here here I'm going to select where the checking date is less than the booking date yeah yeah we do have a many entries on where that doesn't follow this business logic and it's interesting to take note that when for data frame operations you can directly do add, subtract and multiply same as how we manipulate numbers here which is one of the beauty of data frame operation for example when I create new variables sample duration and a duration or days in advance I'm directly using subtraction here between different columns when we have when we create new columns that with more complicated business logics for example I want to exclude those data entries we found invalid just now using a date check and I wanted to assign a null value to these data entries that means I need to have write some if or else if function here when the data logic is more complicated we normally use a row operation instead of directly do a subtraction between two columns we can define a row operation so the operation then can be aligned row by row to the data columns for example I define a row I define a function here on duration that's to be applied to every single row in the data frame then later on I can directly apply this function to the to the whole data frame that's how I get my new column so that's another common operation in data frame okay with this understanding without data so we can go ahead and answer first question what are some of our performing and underperforming segments so here I'm going to introduce a different function that's called group by so what group by does it will split the data points in based on certain object based on certain columns into different based on into different group values then you can apply a aggregate function on each of the group values then the last step is combine the results together to form a new data frame let's see how it's been done here we can try to get the booking rate for every single channel what I'm doing here is our group by the data frame based on the channel values then I will apply aggregate function mean and count to this column is booking is booking here is a binary column is at a 0 1 so the mean of this column will give me a booking rate and the count of this booking and the count of this column will give me the number of booking attempts let's see what we get yeah so now we can see we get the number of bookings and the booking rate for every single channel here and it's worth noting that after you apply a group by aggregate function the channel which is a group name will become an index so instead of a common data frame column you'll be index what we normally do is we will reset index so this group name will become a column name again after that you can sort the values by booking rate or sort the value by channel name up to your preference yeah so let's take a look at channel 0 here it has about 12,000 number of bookings and booking rate is 7.2% this compared to the overall booking rate let's take a look at what it is which is 7.9% so can I say this channel has a lower booking rate than the rest of other channels so for other economic sense statistician out there you might say that might not be true because I'm simply comparing average so what's the statistical significance behind it so that leads us to the next question how do we test the statistical significance of the outperformance so I'm introducing a concept of T sample two sample t-test here two sample t-test is a hypothesis test for the equality between two binomial samples and in this case I'm looking in a booking rate for each sample and this is the binomial sample because we are looking at data points where the value is either 0 or 1 that's why we call it binomial and in order to look at whether there's a real difference in a probability distribution of the two samples we need to understand the concept of random error some random sampling error so if we see the difference between the two samples is it because of random sampling error but because there is a real underlying difference between the two samples so introducing a concept of Z score and p-value here which some of you are probably familiar with so the p-value is a value that measures how likely how likely the difference we see is actually due to random sampling error and the underlying distribution is actually the same so if the p-value is very small that means the two distribution we are looking at are indeed different so let's look how we implement this in Python. I created a function here called that's comparison so I'm using looking at a formula here I need to get n which is a number of bookings and p which is a booking rate for both for both samples and I calculate n and p for the first sample then I can calculate n and p for rest of the bookings then I use the step package from sci-pi to calculate the z score and the p-value and add a new column here significant if the value is one sorry if the p-value is less than 0.1 then I can confidently say the two samples are indeed different so assign value one negative one and zero if it's significantly larger smaller whether it's not significant at all so let's perform this function in in a channel we are looking at just now so that's the result we have can you know all these intermediate values I use here to calculate the z-square and p-value let's look at channel 0 again yes it's booking rate 7.2 percent and for other bookings other than this sub-segment the average booking rate is 8.1 percent and we can we can see this this channel is performing worse in average with statistical confidence and some of the channel here where where the booking rate is actually when the number of bookings is very small we can see that we cannot is that sample size is not big enough for the fast test statistical significance so with that we can confidently answer the first question here is a little outperforming segment here's a little underperforming segments and there are some segments here we simply don't have enough data to say it is outperforming underperforming so with that we can move on to our next question how do we tailor different marketing campaigns for different cities so before we understand how to tailor different marketing campaigns we need to understand what are different clusters of cities are there what are the characteristics after understanding that we can think about how do we tailor our marketing campaigns so I'm going to introduce that your classroom here which is what we call unsupervised learning in machine learning terms so unsupervised learning it means that there is no label assigned to each city you can consider each city has one data point to get looking at here there's no label assigned to it and the classroom help us find the underlying structure among these data points so in Python we can use SK learn package yes all the common machine learning algorithm estimators we can use and for these unsupervised estimators such as k-means or SVM the common function we use is model predict the predict function will help us predict model in a classroom algorithm so the way you run machine learning algorithm in Python does it very standard you create the object of the algorithm estimator then you use predict to predict label in the classroom algorithm there are a few steps I normally follow when I create classroom in pandas first one we need to first step is we need to understand what are the features we can use so in this case our goal is to distinguish different cities so we need to understand what are the characteristics what are the features that distinguish one city from the other then this can come from your business sense this also come from the exploratory analysis you did just now I selected eight different features with which I think are going to be relevant here then what I'm doing here is I'm going to the group by function I explained just now I use group by to create the city level data for these metrics and the second step is to understand whether we should standardize the data by standardizing the data I mean getting a number of standard deviations from the average so this step is very important especially for classroom mechanism like key means because when we calculate the distance between different variables if the magnitude of one variable is a lot larger than other variable so we are putting a lot more weight into one variable instead of the other for example if one variable is in a magnitude of a thousandth and harass another variable is in a magnitude of a single digit so the distance between the first variable we have much larger weight in terms of overall distance compared to the second one so by standardizing the data we can avoid this problem so the next step we need to choose classroom method I'm using key means here and also a number of clusters number of clusters I'm choosing an ad hoc three number three here you can imagine the marketing campaign budget only allows three different marketing campaigns for three different types of cities so that's definitely subject to a business context and what how many classes you want to get and there are also a lot of different methods out there for you to determine what is the optimum optimal number of k right one of the common methodology you can use is what we call apple method so you help you select the optimal number of k even you increase the number of k at the point the is not going to help you fit a model better yeah it's as I mentioned just now the way to create a classroom algorithm on using csk learn is very easy you create the object you specify the parameter in here and class equals three then you can immediately feed the data so we two lines are called you created a classroom algorithm great let's run this great so now we created these three clusters in an eight feature space eight dimensional space how do we visualize the data we know we can visualize 2d data 3d data probably not 8d data so one way to visualize the data is to use the technique called principle component analysis so you help you reduce the eight dimensional space into two dimensional space you can imagine component our principal component analysis is something like if we reduce the dimensional space but the steel tries to maintain the data variability within the raw data so in that way you can get a two-dimensional graph that maintains a lot of the variation in the data I'm using a package decomposition and a function pca here and again with one line of code you can easily reduce the dimension from 8 to 2 with that I can plot I can make a scatter plot based on the two dimension we have then let's see what this graph shows so this is three clusters we created just now one color indicates one cluster and this is a good this is a good illustration of the basic principles behind k-means points that are very close to each other are in the same cluster so how would this be useful right so we have these three different city clusters how do we apply it in this marketing campaign context so we need to understand what are the exact differences in the business metrics for these three different clusters here I need to merge a data merge a data first merge is another common operation for data frame in pandas this is a standardized data I use just now I selected user location city and cluster from this standardized data frame then merge it with the original data that's before standardization and using a common column which is a user user location city here then I group by the user look I group by on cluster then I get them the mean of all the business metrics for each cluster yeah so we have cluster zero one two here let's see how they are being different right so let's look at cluster one you can see that people in cluster one stay for a lot longer and they also book a lot more in advance and they travel a lot more they travel a lot further and for cluster zero here for cluster zero here they tend to be a larger group with a high number of adults high number of children and they book more rooms so these are probably the family types who always travel with a larger group so by understanding these characteristics of different clusters so your marketing campaigns can tailor to the specific purpose for why people travel and that means your marketing campaigns are going to be more effective because you know how to target them exactly great so um and other remarketing there are a few other common users of clustering for example insurance by grouping different policy holders into different groups you can understand what are the policy holders who have a higher average claim costs so that might help you set the premium price for different for different insurance policies and for city planning if you have a large number of households and you want to be community centers it's important to understand what are different clusters based on the house type value geographical locations yeah so with that we can go ahead answer our next question which is basically um how do we improve how do we improve the chance of booking for individuals before understand what triggers people to um how do we do that that we need to understand what triggers people to have a high chance of booking what are the factors that lead to people who are more likely to make a booking so i'm introducing a concept of supervised learning here because when we look at individual user data we have a label associated with each data point the label here is whether the person has made a booking or not so what decision tree does it will split the data into different subsets and they will try to make sure a subset is either all zero either all one so and the data is splitting in a way that you will choose the attribute that explains that does the best job explaining the data first for example example i show here is duration lesson lesson we go on 2.5 so people who only stay for one or two days are very different from people who stay more than that so that's how the data is being split up again we can use package from a scale learn the tree decomposition cost validation and so on the steps are very similar to clustering but one major difference here is because this is we are we are using a data points we're using a data sample with labels so we can split the data first into test and train we can build a model based on the training data and later we can test the accuracy of using a test data so using test train test split this single function i can split the data into test and train with the test size being 20 percent of the data um i then create a object using under the decision tree classifier class then again similarly i feed the data with the feature that i have and the outcome variable which is the label here so let's see what that gives me yeah so in this case i'm using the class zero from the sample okay then after we create a decision tree we can visualize the data to see what it looks like to visualize the decision tree i'm using pie dot data here so i convert the decision tree into a pie dot data and i use a function export graph width to plot the graph of what the of the decision tree after converting it to a pdf okay this is expected because the sample i'm using is only 200 so that's also one of the limitations of decision tree if your sample size is very small and and you set very stringent conditions such as i want to have six different leaf loads and the minimum sample is at least 200 right so that's the incompatibility of your sample size and the parameters you are using so in this case i'm using a cluster zero let's see what the different what are the other clusters here so i'll sample group by i'll group by the cluster and to see what is the count for different cluster so we see um cluster two has a much larger sample so let's use cluster two here to see what we get okay great so with the largest sample we get a much nicer tree so let's look at the left side of the tree here so for people who are staying only for one or two days and only with one adult and they are booking really you know zero days in a month that means they are doing the same booking um we can see the probability of booking in this case the first value here is a number of zero this is the second value number one so the overall booking rate here is almost like 30 30 plus percent right so this is compared to average booking rate only eight percent so you see people are traveling in very small groups and they're not booking very much in advance they have a much higher chance of booking and similarly you can see other branches where we give you we give you subgroups they have a much lower chance of booking so with that in mind you can customize your product and services to nudge people to book more for example um if someone is booking 90 days in advance or 180 days in advance you know this person is probably less likely to book in that case um your marketing campaign you can target them with a marketing promo code and for your product you can nudge them you can nudge them with nicer features for example a futures like a recommendation for recommendation for the season we are going to travel so with this kind of customized product and services by understanding the chance actual chance of booking um you can improve the overall chance of booking for your website yeah so besides product marketing nanocomu use case in decision tree is weather forecasting what kind of signals we're more likely to lead to rain yeah so we have written probably less than 100 code 100 lines of code now and um we answered some of the really hard questions for the board meeting and this is some of the basic customer segmentation in python and at least some of the resources here you can explore and further learn more about it my best advice is uh really dive into our problems and uh get a data set yeah very interesting and analyze it and how you improve um how you improve your data analysis skills how you improve how you apply the data to business context is just to practice thank you any questions yeah that was packo sg 2016 how would you assess the effectiveness of your clustering of decision tree using only offline validation what that means is you got 80 percent how you assess it so maybe you can create five different models and you have the budget to invest all of you on that how would you pick which one to go with yeah yeah that's a very good question so i think before you decide which algorithm to use you need to first understand the data for example k-means um the k-means algorithm demonstrates us now it's only suitable for certain type of data because for every um machine learning algorithm there we are making huge assumptions about what kind of data we have for example machine k-means is very bad for elongated data it's assuming the clusters are wrong right so if you know your data set as something that's not run clusters that's probably something you shouldn't use and in order to validate the data there are few techniques you can use without ab testing for example you can use cross validation that means you'll keep training your data using different proportion of test and train and to only um then you'll get the you only get optimal model with the best with the highest um accuracy so that um there are these are mechanics you can use to make sure the model for the parameters are using are optimal but i would say um there's nothing that can replace ab testing to understand how if ab testing a lot about behavioral response it's about after you have the intervention how people are going to respond to it right so all my talk um i think all this methodology i demonstrated just now is only on the very first part about what kind of um what kind of data structure what kind of data insights you can get to understand what are actions that might likely to lead to a difference in behavior for example um i'm assuming banners and the higher chance and lower chance of booking you can come up with ideas for the intervention but the effective intervention is a whole different story and how people are going to respond to it thanks thank you


So, this is where we had stopped our discussion how do you stretch a pulse and so far we have discussed the simplest possible geometry using a single grating couple of plane mirrors and a concave mirror and we had said that if you want a greater stretch a greater chart then you need multiple passes more often than not as we discussed if you really want a 200 picosecond pulse the path difference would better be something like 6 centimeter. So, either your stretcher will be very big which you do not want or you have to do multiple passes by so that the effective path travel is much more okay so that leads us to little more complicated geometries this geometry is called 3C geometry I am not very sure what the correct pronunciation of 3C is but then let us just call you that so here what you have is you do not have one grating rather you have two parallel gratings and I have not animated this slide but you can see right it comes in similar kind of separation takes place and then it comes here comes in now the path has increased a little bit and again by 3C geometry you can make not only a pulse stretcher but also pulse compressor in fact in the laser that I used as opposed to this was a geometry for the compressor the earlier geometry was the one for a stretcher now more components you have in a system more parameters you have that you can control and get an accurate match but more complicated also becomes okay next let us okay we have already said this but let us say it again so if you put in an uncharved pulse uncharved input in any of these geometries then you get a chart output and you get a stretcher you put in a chart input the output is uncharved then you get a compressor provided the chart that was there in the original pulse is exactly compensated this is perhaps the 8th time I have said it in the last module and the present one but this is something that we should never forget so if you have a negative chart in stretcher generally you want to give a positive chart in compressor and vice versa so different people prefer different things some think it is better to have positive chart in the stretcher negative chart in the stretcher some feel it is the other way round so it is completely dependent on what you want to do alright next move on to another geometry which is known to be quite a good one it is quite popular it is called Martinez geometry in Martinez geometry once again you have two gratings but unlike in tree C geometry the gratings are not parallel if you produce them they would make an acute angle and another thing that is very important is Martinez introduced telescope between the two gratings it is not as if this geometry is not used actually you get a good amount of stretching using this but can you tell me what could be a possible problem in Martinez geometry using lenses right so you are making a short pulse travel through lens so that itself introduces some chart so the question is are you using good lenses or not if you use very good quality lenses in the telescope then actually Martinez geometry works fine but one needs to be careful about that it is not such a big problem because in any case you want to stretch so I am sure you do not want to use it in a compressor but in a stretcher this works and in fact Martinez had shown that the efficiency of this geometry is quite good and one difference between the earlier geometries that we have discussed and this one is that here in Martinez geometry you end up introducing a positive chart okay the gratings are facing are almost an acute angle okay next let us move on to something that is a little more complicated and this complicated arrangement is called an offener triplet okay this is one slide that I should have animated but it would have been too much of work as well so I did not so let us see if you can understand the understand what is going on here what do we have here unlike the other geometries this looks like a more complicated arrangement right because first of all you have a plane mirror then you have a grating after the grating you have a concave mirror followed by a convex mirror followed by this HRR does anybody know what HRR could mean well there is a VRR so H and V would mean horizontal and vertical respectively yeah these are called roof retro reflectors and this is what they look like and usually these are very good because already the angle between the two reflecting planes is defined so you cannot really mess up things there it is so we have something like this in the retro reflectors in our spectrometers in our case we have three sides of a cube this is sort of a hollow cube and the coating can be different it can be aluminum can be gold can be dielectric can be nothing so it depends on what you need so this is a horizontal roof reflector this is a vertical roof reflector so what is happening the input comes hits this mirror and comes to the diffraction grating this number one is the first part on the diffraction grating then where does it go it goes to the concave mirror from concave mirror to convex mirror from convex mirror back to concave mirror and from there it goes back to the diffraction grating once again to form point number two from here the beam goes to a vertical retro reflector and of course if it is a retro vertical roof retro reflector and if it is a retro reflector of course it has to send it back and good thing about retro reflectors is that the incoming and outgoing beams are parallel to each other opposite direction but parallel so it comes back and hits the diffraction grating here at point number three goes straight the concave mirror from concave mirror to convex mirror then back to the concave mirror and back here in point number four from there it goes to the high reflector horizontal retro reflector and then it goes out what is the need for such a complicated arrangement we actually provided the answer already in one of our earlier discussions we have given you the answer what is the need of such a complicated arrangement remember we have said that if you want a good amount of sharp to be introduced then the path length would better be large here path length is large without the stretcher having to be too large okay if you suppose you had only this mirror concave this plane mirror concave mirror and grating you can understand path length would have been maybe one fifth or one tenth of what it is in this arrangement right so this is basically a geometry in which a lot of passes are made so that the effective path lengths is significantly large and you can get a good amount of sharp introduced and the reason why I give you trouble with this kind of a complicated geometry is that in the laser that we use the stretcher is you can say modification of this often a triplet arrangement thankfully it is not as complicated as what it is here but we will see what it is but before going there you must have noticed that we have registered references of papers there if you are interested to study more all you have to do is go to these references and you will get leads to further detail about these things and again before moving on I am sure you can understand how much of effort would go in to design something like this it is not easily done in earlier days everybody worked with homemade lasers typically those lasers would be bulky even now for some applications you have to make your laser typically the laser would be bulky because it is difficult for us to do things that are very complicated and also you do not want to do it because maintenance is an issue but in commercial systems the design is complicated and nowadays at least up to this part generally nobody has to do anything themselves but still it is important that you know as for all you know somewhere sometime you might have to make your own apparatus where this understanding would come handy okay with that we move on to the laser we have we have a one box coherent Libra laser Libra amplifier we are going to talk more about the amplifier in one of the subsequent modules but for now let me just show you the ray diagram for a stretcher and you already see the complication look at the input the trouble starts here the input goes through 2 mirrors that are like this okay and this thing is important if you ever have to align the laser yourself or if you ever have to even see whether the stretcher is working properly or not so let us see what happens this here is the input comes through SM5, SM6 so in Libra user's manual SM means a mirror which is in the stretcher and the number would of course indicate the sequence okay so it goes through SM5 it does not hit any and impinges on the grating okay and it is a simple uncharred beam hitting the grating so on the grating it looks like a spot a circular spot we will come to this 2, 3, 4 relative positions later so this is where it comes goes to SM3 which is a circular big mirror from SM3 it goes to SM4 from SM4 it comes back to SM3 and hits the grating once again and in a correct alignment if your alignment is perfect then this beam number 2 should hit the grating lower than beam number 1 that is point number 1 point number 2 is so far it has done one hit on the grating right so since it has hit the grating once it has been dispersed so beam number 2 which is directly below beam number 1 spot number 2 let us say is no longer a circle you see a stripe a streak has somebody seen when these guys opened up you have seen right so this is actually a streak it is not a circle then okay this is 1 this is 2 goes back here back here then back to SM3 then it hits the grating above spot number 1 and it is still a streak then from here it goes to SM6 sorry think I got it a little wrong 1 2 from 2 it goes to SM5 SM6 back to spot number 3 comes to SM3 goes to SM4 comes back and then when it the last time it hits the grating that dispersion is gone because so many passes again well dispersion is still there but you do not see a streak anymore once again you see a nice circular spot and that is what goes to SM7 and from there it moves out okay so this is the stretcher we have in our laser where we have in our laser we will see in our amplifier and this is the compressor once again the compressor has only one grating earlier I have shown you a design with two gratings right but here since it is a one box laser everything has been made very compact so minimum number of optics has been used so instead of putting another grating what they have done is here it is perhaps not very clear about what it happens here but once again there are several passes and here you can see the relative positions of the beams 1 2 3 and 4 once again the first beam that goes in is circular second and third are streaks fourth one is where the spatial dispersion is taken care of but not spectral dispersion and that is beam number 4 which goes out okay this is what we have so that almost concludes our discussion of stretchers and compressors but then I might have given you the impression over the course of this discussion that if you want to stretch a beam or if you want to compress a beam all that is there at your disposal is grating or prism so you will see in literature designs using not gratings but prisms okay that is understandable but that is not the only thing in fact whatever technology we have is moving towards miniaturization so I think the latest development in this field is something called VHG solid glass volume holographic grating so you remember we talked about the Bragg mirror right Bragg mirror where reflection is from different layers here also what you have is a very small device and so far I do not know anybody else does it there is this company called Ondax which has now been taken over by coherent Ondax market says and the principle was known long ago and in fact when this was demonstrated long ago as well in 1987 optics later as paper but then now this company has developed it and marketed it as a product and it is very simple what you have is you have an optical fiber feeding the pulse into it and as what is it that we have to remember if you are going to use optical fiber in an application like this you better use a polarization maintaining fiber it is very important and in the next module we will see how we use polarization very effectively so typically what you have is you have this fiber going in if it goes in through here then there are since it is a holographic grating there are several reflecting surfaces and different reflecting surfaces reflect different frequencies it is as simple as that so red gets reflected first followed by green followed by blue so if your input was a broad pulse chart pulse provided the chart is such that the trails and blue leads then this kind of an arrangement is going to give you a compressed output otherwise the sequence of reflecting mirrors has to be opposite but the good thing here is that if you take a pair of these VHG stretcher and compressor all you have to do is put in the pulse the initial output of the oscillator uncharped pulse you put it in here let us say then what will happen you get a chart pulse and you get a chart pulse in which red leads and blue follows in the compressor side just turn it around let the beam going from here and not from here then what will happen then it will get compensated so the same piece of optic can be used either as a stretcher or as a compressor depending on which is the input which is the output and I have not seen it but from the pictures on the website and all it seems like something that is about this size so the stretcher that I used 20 years ago was about this size square the stretcher we use now is about this maybe this and the one we are talking about here is this so that is what advent of technology and miniaturization does ok so much for pulse stretching and pulse compression we are going to next discuss the actual amplification bit of chart pulse amplification method.


I started talking to James on our time dating website around the middle of August 2020. After a few brief messages, he asked me to email him via his own personal email address, which I did. The first email that he sent me informed me that he had lost his wife six years ago from cancer and had been encouraged by his son to go on the dating website as he was lonely and was looking for someone with the same qualities to look after and spend time with. He also asked for my mobile number. It wasn't long before I received my first phone call from him and I have to say that he had a divine voice that I could have listened to for hours. He asked me to call him at 6am in the morning so that he could start his day better after talking to me. He then requested that I came off the dating website, which I did. He told me that he was due to fly to Turkey in a couple of weeks for eight weeks to undertake his job before he retired. This he did so and I was not able to have a first meeting with him because of his work commitments. It wasn't long before he messaged to say that his computer had been confiscated in customs due to Covid. He then asked me to send him two Apple computers and an Apple Watch to monitor his heart. He stated that he was unable to do his work and he would pay me back with interest. I actually had no hesitation of helping this man who I believed in and really thought was honest and trustworthy. The address he gave me was of his interpreter in Cyprus. In all, the cost to me was £5,200. Once he knew I had posted them, he asked for my bank account details to enable him to place the debt into my account. He then informed me that his bank had frozen his account for 21 days. This obviously was when alarm bells started going off. Due to the fact that I had spent all my savings on helping him, I felt that I needed to keep him sweet in the chance that he would refund me the money that he owed me. A week later he asked me to take out a credit card to enable him to gain money from as he had no money for his medication or food. This I refused. He then asked me to use my overdraft and I told him that I didn't have one. A couple of weeks later he sent me a package with a cheap t-shirt, bracelet and necklace in. The t-shirt was purchased from a local shop and the parcel was posted in Newcastle upon time. Still, I never questioned any of this. After the 21 days had lapsed, I asked him to repay me the money that he owed me as I was £1,000 overdrawn in my account and had no funds to pay my monthly rent with. He informed me that he needed an iPad to sync him with his computer in order to access his bank account. It was at this time that his phone calls became less often and his daily messages too. In the next few weeks he informed me that he had been in hospital overnight on three occasions as his medication was not correct and he was dehydrated. After a week of not hearing from me, he messaged to say that he was unwell and had been in a hospice. At this point I replied enough and I told him that he had my bank account details and the iPad that I had sent him and he needed to pay me the £5,200 that he owed me. Needless to say that that was the last I heard from him. The next day I contacted the police and reported this as romance fraud. I would like to mention that this man who I now feel did not exist swept me off my feet even though I had never met him. I have not had a long-time relationship since 2003 when I divorced and had never been treated so affectionately by any man.  I have needed to take out a credit card in order to live as he took all my savings. On speaking to a professional person they have told me that I am not to blame or shame myself as these people are very skilled at what they do and he was.