Hey everybody! It's me, Ewan, Forestel. I know it's been a while since you guys have seen me, but here I am and I'm very excited to be here so that I could introduce fellow wikitri here, Marty Axe. He's going to share about his wikitri experience with you. Let me tell you just a little bit about him. Marty has been researching his family history since 1999 after having caught the bug from his mom and dad. Marty joined wikitri in 2014 and recently joined the 100,000 Contributions Club. His areas of focus on wikitri include surname studies, data doctoring, Scotland, and pre-1500 work. Past wikitri volunteer efforts have included rangering and volunteering at the wikitri roots tech booth, which is where we got to meet. He is a board member of the Downers Grove Historical Society and past board member of the Computer Assisted Genealogy Group of Northern Illinois. So we're excited to have you here and I will let you go ahead and do your thing. Thank you very much. It's a pleasure to be here, everybody, today. So let me just make sure we got the technical side of this down. Can people see my slide for an introduction to my PowerPoint slide?  I'm trying to, but in StreamYard, let me just... Oops. Let me just do that one more time. How's this? Yep, there it is. Okay, great. So want to thank everybody for attending. I think this is the end of the final stages of wikitri days and in our three to four day event. So I hope to provide a different perspective into wikitri. I've been using wikitri for about just checking nine years now. So I have...  So if you sat in on the last session with Chris and some of the other team members, they kind of went through some of that similar introduction, if you will. So I've been interested in genealogy. Most of my life, I suppose, because I am adopted and people are curious about that, I suppose. I've got it serious about it. It started about 1999 when my folks, both my mom and dad, sort of just gave me their research. They've done build out trees, largely not using the internet or just emailing people and getting stuff in the mail. So my interests include Scotland. I also am very interested in surname studies with... My birth name is Lenovo. So I'm one of those rare people, sort of like Chris, with... I've got the Lenovo dash one. I'm a dash one, or if you will. So came late, but there's just not that many Lenovo's. Porterfield, Malacote, and Axe is my adopted name. So a little background for me is I'm involved with... I'm in the Chicago area. So I was on board for about five years of that, of Cagney, which is a Chicago area genealogy group. Started off as a Stanford computerated genealogy group of Northern Illinois, but kind of spans about five or six counties in Chicago. And I'm also a board member at the Downish Grove Historical Society. I'll talk a little bit about that later. I use wiki tree for some of the things we do for our town founders and the like, and pioneers from... They came to our village. I used to be in the software industry, co-founded somebody called Solon Software in case you want to Google it. It's still around. And like any good... There's sort of levels of commitment to genealogy, and we got to the point where my wife graciously incorporated genealogy into our family vacations, because I'm one of those kind of nuts where if you go east, I can find ancestors. And the east and south a little bit, not too far south. I can find something of research. On the other side, she's actually a first generation Belgian. So not a lot for her to research. So she's been instrumental in some of my research journey, so doing some of the heavy lifting. So one of the things I do when I do various talks both here and when I was in the real and the working world, if you will, is I like to have a couple of objectives for talks. So what I want to get at, what I'd like people to come out of this talk with, and I usually do this type of talk to people that are probably less familiar with wiki tree, sometimes new. So I'm assuming this group, you know, given its wiki tree days that we probably have a little more people experience with wiki tree, but if not, hopefully we got a few that are just found it came across us. Like you got a basic understanding, get a roadmap of how to get started.  And also an overview of some of what I consider some of those compelling features. And if you sat in on some of the other sessions, even like the session, for example, that they caught kickoff this morning. And as they went around with the panelists, everybody has a different view of what, how they use wiki tree. So, so that rather than tell you all the possible things you might do in wiki tree, I'm going to, you're going to get sort of a flavor of what I found fascinating. And you may not, you may find some of those things fascinating. You might find things that I don't do like, you know, some social stuff like the discord server for wiki tree. I still am afraid with discord. Sorry about that guys that are into it. So there's parts that I don't use real heavily that are perfectly great for other folks. So what I want to start off with is just a definition of a wiki. That is the source of some confusion sometimes. Some people ask like, what's the difference between wiki tree and wikipedia, for example? And what is just a wiki in general? So wiki, the term wiki started to come about probably as a function of probably before wikipedia, but wikipedia is probably the best known wiki. And from my perspective, these are sites that basically they have lots of individual articles, but they're very interlinked. So for folks that are like my age in their 60s, you might remember everybody family habit encyclopedia on their, you know, set of encyclopedias. I had the Compton encyclopedias with that 24 of them. So you had to read about something it's like, Oh, that's interesting. I want to follow up on that. So you go to the, you go to the bookshelf, drag another book down, open that, you know, flip to that page in the book and then you flip to something else. In the case you use the index, and you might have four or five books sitting on your desk by a large table there that fit on the desk, to, if you wanted to use, if you wanted to do research that was, you know, jumping around.  And, you know, sometimes you get down a rattle and other times you can find out a lot more about that topic that you're interested in, in a very quick, quick, in very short order, if you will. So wikipedia is probably the best known wiki. And it is a broad based wiki. It's a little different than wiki tree that has articles on all sorts of things, including people that on wikipedia, you do have, there is a requirement so that it just doesn't have a billion pages, I suppose, of what's called notability. So I'll give an example, my brother used to play professional football. That's a notability. So he's, he's out on wiki, he's out on wikipedia. I'm just a geologist, started a small company, what, for the things I've done in my life, I haven't met, I haven't met their criteria for, for, for notability. So I will never be on, well, let's hope.  The, so one of the things I, with wiki, so I would, so it's a big, so some people say, why don't we just do this all on wikipedia? And the reality is that you couldn't, most of what we put in wiki tree couldn't, wouldn't qualify as content for wikipedia. So wikis usually have a high level of linking between all the content I mentioned. Some examples of wikis are a lot of, yeah, I guess I picked some that I find interesting, kind of some, some Star Trek, Mission Impossible, you know, those are, those are things I find interesting. I occasionally use those, not that much. A lot of TV shows and movies will have them, and they'll break down all the characters and things like that. So, shows like Mash and the like. And the one, the final thing I might say about wikis is there is one that's often a source of confusion is family search has a really cool wiki, but it's really a resource, it's really for resources, it doesn't have people in it. Family search has their area with people in it, but it's not wiki based. The, I find the research wiki to be really useful, mainly for, from geographic point of view. So if I go to a county, I want to know what all the resources are. They have a really nice, well organized structure for finding sources for certain geographies. But it's not, they're, they're on a, it's a wonderful wiki, but it's, they're solving a different problem than we are with the, with wiki tree. So what is wiki tree? I'll give you the, the standard, the standard tagline we've got right now. It's the mission, mission to grow a accurate single family tree that connects us all and it's freely available to everyone. The free is a big aspect of this, as you might have heard in previous sessions. Free is, it's good. It's not the end all for me. I would, you know, I would probably pay for some of the content, but it's nice that I don't have to. You can, there's different ways to engage with wiki tree. You don't have to join. You can, you can just go in and find relatives and look at them. So we like those people because they actually help pay the bills. If you're not registered, you will see, you will see some ads. So every time one of those ads pops up, little, little tip goes in the wiki tree tip jar to help pay some of the salaries of the team and keep the, keep the lights on a wiki tree. But you can also join and, and I think to join, there's no cost and you can add to the tree and collaborate with others. And we talk, historically, when I first started doing talks about wiki tree, I didn't talk mainly about the tree. I've kind of pivoted now that it's a lot of it about collaboration just on your, on not just on relatives, but also collaborating on different geographies. So if you're interested in a certain area in Scotland, there's some, which I am, there's some phenomenal resources out there that people live in Scotland. They've, I was talking, and I have one case where I, somebody was had sources I'd never seen and I reached out to the, to the person. He goes, yeah, I've got a 10,000 book library years. of Scottish history. I'm like, well, that's why I would see these things because everything's not online. One thing I like is wiki tree is privacy is a big concern in the world. So modern, so modern history is kept private. And there's a sort of a great, there's a scale of about different levels of privacy. It's not simply a binary type of approach. The other things start happening in the last few years, there's this concept called apps within wiki tree that allow people to build on top of the core technology. And that has added a huge amount of value to wiki tree. And I'll talk a little about that later. So the gist of this is it's, you know, when I started on this, it's, it's cool. I've got an, I can, you know, I can collaborate with people on third and fourth and fifth cousins and great, great, great grandparents. That was what I really saw the value in wiki tree. But as I've started to use it more and more over the years, it's, the tree is great. And it's, it's quarter and fundamental to what we do here. But it is a, it's just the starting point. So I took this picture, this picture, so I think from a little bit, a little bit older. It includes many of the people you might have seen on yesterday's session with Chris in the middle. I think that was from wiki, that was from roots tech about four or five years ago. I got a little more engaged with wiki tree back then I showed up. I ended up not doing a lot of roots, ended up hanging around the wiki tree booth and they gave me a shirt and so became a big fan and helped help people out at the booth for the last couple of days there. But I'm not in that picture. So a little bit about the numbers on wiki tree is founded by Chris Whitten. I think Chris is monitoring the feed here. So thank you very much, Chris, if you're still around. He started it in 2008. Just a few numbers here. They've had really exponential growth and the site after 15 years is still growing. So back and I did some snapshots a while back. As of 2019, there were there were 21 million profiles and I'll just jump to four years later. So we're up to 35.7 million profiles in over a million members. Now I'll all of those million members, they're not in every day like some of us working on our trees, but they've at least made some minor, they've usually made some contributions. So the ones that are really doing the majority of the work is really more of about a quarter million of people that have signed the honor code and have made have made more significant contributions. So getting started in wiki tree, it's like a lot of websites, but there's a there's one step that you go through. You put a little bit of information about yourself. We're trying to keep the bots out and and people like that. You wait for an email may take a few hours. I haven't done this for a while. So I don't know what the experience is today. But there's real people behind the scenes and they'll ask you. And these are people called rangers. They'll ask you or greeters ask you why you're interested and just try to get a human response. And then you're encouraged to sign the honor code. And when I first started, when I try to avoid when doing presentations, having lots of text on the screen, but this this is the one place where I kind of violate that, you know, that guideline because the honor code is really number one, it's core to our beliefs and number one, it's core to what the site does and it gives you a lot of insights into that. So and if you look at the code and say that's if some of the stuff you have issues with, then you're probably on the me, honestly, you're probably on the wrong website. But in terms of the code, and some of these, there's nine components of the code and some of them sort of overlapping what they're trying to accomplish. But a number one, it's a collaboration site. You do not I've had people that, you know, they put a they connect with a third or fourth grandparent and they want their own version of the grandparent. And if you like to be private, you and you don't really want to contribute at that level, then you know, there's you can use your genealogy program to use ancestry. It's, you know, I think you miss a lot of value by not collaborating with others. But it's, but that's core to our core to what we do. Accuracy is really important. So sourcing, we over time, we become more adamant about sourcing. On the other hand, there's a lot of different ways to source. So there's not as much as, you know, some of the goals might be to have a certain formatting style, you know, there's no brow beating over, you know, you didn't exactly put a comma here or a period there. The goal with sourcing is, can I can I look at that source information? And if I didn't enter that information, can I go is it is, is there enough information there that I can go determine what what that source is? We also there's a very kind, warm, fuzzy feeling about this site compared to others. You, you do have to, we do assume that mistakes are unintentional. There's and they encourage people to be bold. There is ability to be any change that you make on profiles, you can roll it back if you made a mistake. So so three and four sort of related is just be nice to people. And as you follow the forums, there's a forum called G to G.  And, you know, if people have issues with folks, there's a process to, there's a remediation process, and we ask you to keep it out of the forums.  So we tend to have very, I won't say it happened, but it's very rare that people get kicked off the site. You have to, you know, it's people do monitor. We do monitor for that and encourage, and we have a process we go through that to encourage be courteous, but it is a very respectful site. So it has been my experience. Privacy is a big deal. I've got a slide on privacy. I'll talk about that later. So copyrights are an issue. So don't take your, you know, but don't take everything on a fine grade page or a modern book and just cut and paste it. Information is not copyrighted, but the way it's presented is copyrighted in broad terms. Give credit where credit to also. So there's, there's a place where we do that called acknowledgements on where people have made major, major contributions on profiles. And we also have a lot of social aspects where you can give awards to people that have been extremely helpful. And those appear on in some of the newsletters that go out, the emails that go out, and that appear on the genealogy genealogist genealogist forum. So we refer to as GDG. So again, free, keeping it free is one of the core aspects. So so anyway, that's a little about the honor code. I think that's really core to what we do here. So so I'm just going back to turn to remember when I started wiki tree. So I you what you do is you create a profile, you enter some parents and grandparents. I am you can import family via GEDCOM. There are some restrictions in that. So you can't go back too far, I think, before 1700, with the idea that you're going to probably create lots of duplicates. But I will. So so I give some GEDCOM and and I like I like well written profiles. And the GEDCOMs, no matter what you do, they don't really show up as well written. So so I tend to I've used to the GEDCOM once and I just manually entered in now. But if you want to use GEDCOMs, there is a there's a better process for doing them when I joined. So and focus on what you know. And then you start climbing the tree and you can climb the tree with a there's all sorts of great links in terms of giving very basic guidance to people. So you can start climbing your tree and adding people. And the help system I found to be very useful. There's a it's up on the upper right hand corner on the sides. And you can use that to just ask questions and or not ask questions, but you can drill through certain areas like how do I source how do I it's well organized and it's linked. So if you're not on the exact topic, you might find a link to what you're trying to get. And if you your answers aren't there, there's this G2G system where you can you can ask ask questions. And it's very it's I would say it's very kind of new people. So they might they might send you to link. But you won't be mocked or ridiculed for asking dumb questions. So there is no as they say there's no then question. So at some point, and this is where I just got so excited about Wicked Tree, I don't know. I don't know why it was, but I had I had my snoopy moment, if you will, my snoopy dance moment. And you got my snoopy dance moment was when I connected to someone that was already on the tree. I think in my case, it was on my Porterfield lines, which is my maternal grandmother. And what I found is that and there's this is a well documented line. There's a book about it, you know, they go to the 1400s with a couple. Yeah, so someone had written a book about what's now 90 years ago. There was pretty well document had some errors, but but in general, it was it was extremely good. So someone had built that lineup like three or 400 years back. It was pretty cool. I went and worked on that and added documentation provided more detail in the stories, but the tree was already built for me. So that was really, really cool. So and I've had many of those. And after that, I've had many cases where other people have researched common third and fourth and fifth grandparents out there. So you get to work with them. And great things can happen for that. Just documenting things. So I give an example, somebody was working on my stepbrothers line and we started talking and it was a fourth or fifth cousin. He actually, you know, make this a short story. At the end of the day, we become friendly. I help him out with a with a gap in this Dulaney family line. And I ended up sending me an image of my stepbrothers grandmother as a child. And then he sends me nothing. Well, so what's your dress? So so he sent me the actual picture for that. So so things like that are really exciting when you can collaborate that level and share details. And I've done the same for for some other people. So so I've kind of talked so one of the things I like about wiki tree is I I always loved wiki. I like the concept of wikipedia in the early days, where it was for notable information. I just love the way it presented information. So you could click and you know, back to my example of having a whole bunch of competence and cyclopedias on my desktop. I just kind of like that idea, not having as much I like the smell of encyclopedias. I like the idea of being able to just click click click through things. So so I think this is one of the areas where wiki tree really excels. So so what I presented here is just I chose one of the profiles. It wasn't too big. But one that I thought was that I'd created for my great grandfather. And I had some weird facts to that I'd come across for him. So so I had a little more of a bio to to you know, you don't for those for some people, you just don't have a lot to say besides who because you don't know about them. This is someone I didn't know. I didn't know the man because he died at a relative unfortunately at a relatively early age. But you know, his his death in an oil field got well documented through through different sources. So I've got information on him. But one of things. So I'm going to talk about the profiles in in two different sections. So the top of the profile, the section right here is very much like your your genealogy databases. When you enter, I'm not going to get into how you create these profiles in terms of the editing mode, but you have an editing mode where you can enter husbands and brothers and sons and things like that and describe the types of relationships. You also have and then you have a biography section that you can you can do some advanced things such as you do footnoting with footnotes, or you can just write you can just start typing away. And so and you don't have to do fancy formatting. There's simple ways to put links in the profile. So you just put a couple brackets around things, for example. So it's a little bit of a I was comfortable that because I have a technical background and I and I've done some editing on Wikipedia. It can be a little bit technical. But what you do is you just go into other people's profiles, say, oh, I wish mine looked like that. And then see how they did it. And it's not done. You know, once you do it five or 10 times, it becomes kind of second nature. So I'm going to talk a little bit more about DNA later. You can put pictures that show up on the profile. I don't have a lot of great pictures from him. This was a one taken from a group family picture. So so then the rest of the profile. So you can do things like this. You can also have different headings. I didn't have that much to say about him. So I didn't have a lot of subheadings. I do have one subheading here for he's kind of unfortunately had a kind of a tragic story. His life ended up short and lived in a lot of pain. But anyway, I'm moving on. Maybe I should choose a different example. So this is the family of he had he had three children. So I organized it that way because I like to see it in the biography with these links. And then also I'm kind of a big fan of sourcing. So I've got all the sourcing here. Some of I linked up particular parts of the article. This is considered the best way of sourcing, but not you don't have to do it that way. And then there's other ways. If you're just going to throw in a bibliography and information, you can put information in there. So this is an example where someone's relatively close to me. We do want real source information. But but if you've got first or second hand information about that people that people knew them, it's legitimate to just put that in. If you put in something as a source, say for, you know, some Scottish king and say it's, you know, handed down through unsourced trees, that's not really considered much of a source. So you have to be somewhat close to the, to the event or the people to, to actually just put in information like that I just because sort of. You've also got links. You got a lot of areas over here for collaboration. So there's, there, what Wikitry is trying to do is make it as easy as possible on a single page is to build out your profiles. So, so I don't use this a whole lot, but it's what I do. It's, I do find it useful. So, so those two pages kind of break down your main profile. So this is sort of the heart of Wikitry. And this is where you're going to, at least I spend the majority of my time putting things in. So, so that's a little bit about what a profile page looks like. There is, I talked a little bit about privacy. There is a respect for privacy that I like what they do with privacy, because a lot of like GEDCOM exports and imports, it's very binary in terms of is the person dead or alive and maybe didn't really tag him properly, whether they're alive or dead. But what, what Wikitry allows you to do is have, is, is if you're the profile manager, and the profile manager is, we use the term manager versus owners, you don't have, you're not lured and got over that profile, but you're sort of more of a coordinator manager, you're managing that profile. But if you let's say you've got someone that's passed away, and there's recently or in some timeframe that there's still sensitive stories that would impact living members, we let you, we still let you, there's still the ability for those profiles to be hidden and protected. So, but at some point in the, where the marker is right now, if someone was born more than 150 years ago, or they died more than 100 years ago, they must be open. So you can't just protect large swaths of the tree. So it's a, it's an interesting, you know, sort of shades of gray in terms of how you do privacy. So we came a little more private in 2018. There's this law that was passed in the European Union called GDPR, which, which put significant fines on exposing information, particularly on living people didn't affect anybody that's passed away. But one of the major change was living members that weren't members have to be completely unlisted or completely private, basically. You might have seen some sections on DNA. This DNA is always kind of hard to explain in terms of, I find a little hard to explain sometimes when the wiki tree is, because people want to first say, oh, well, you must store. And so how do you store? How do I import the DNA into, into wiki tree? Well, the answer is you don't. So I'll start at the bottom of the slide. We don't store match the DNA results. What we do is we store the record of the tests you've made. And then as you go through the profiles, I'll show this on the next screen, you can see which cousins you might, who's, who have tested, but not necessarily did you match to. So if you went to Ancestor in my heritage or my living or family tree DNA, those basically show you people that you matched to. They don't show people you didn't match to. So, so for those third and fourth cousins, you can find people that you won't find on any other of the, any of the other DNA websites. But if you talk to those people, you might be able to find matches that, you know, that they've got on their tree that you don't have on yours, but you would have never known about them. Because wiki tree uses the fact that they're in the tree and they've taken a test on a common ancestor. So it's, it can be really useful. They, with wiki tree, we use the normal autosommel stuff and then you've got the Y and the X and the mitochondrial DNA for the, for the female side of the tree. So for example, on my Porterfield side, they go back really far. So there's, there's only one Porterfield so far when you get some more. But as you go back, the Y will, if you go back to the original Porterfields, that person will show us a possible connection. On the autosommel, it goes back, I should know the number six or seven generations, I think, to the point where autosommel really starts finding, it becomes so deluded that it's not, they're, you're not going to find real matches at that level. So then here's an example of the DNA connection. So over on the blue side here, my Malacote line, I, there's one Malacote that took a Y DNA test. So those are always interesting. I don't have Y DNA for Malacotes. So it's not a great interest to me. And then I show up here with some other Malacotes. So these are basic opportunities to collect. Interesting. I wonder why Ed Malacote doesn't have, oh, he probably didn't do Y DNA test. So these are people that are, you can collaborate on, on surname work. So, and on, on that part of your tree. So I'm interested in certain, I have four or five surnames that I've, that I focus on very heavily. And Malacote's one of them since it is my maternal great grandmother's line. So, so I, so we talked a little bit about profiles. And, you know, that's court of wiki tree. But there's also other ways in which to collaborate beyond just finding cousins. So what I've done on this slide is, and this is, I would probably say this is still incomplete. It's very incomplete about just, but it'll give you an idea of some of the ways you can collaborate. So geographic collaboration, and the way, and some of the ways you collaborate on, let me think, on almost all of these, these have projects behind them. So projects are things on wiki tree rejoining. It's basically have a group of common interests. Some of the, excuse me, some of the profiles more active, like Scotland, for example, they'll send me an email every year. Do I still want to be contributing to this project? So I'm fascinating on one, I'm fascinated on Scotland. For one of my, I just, I sort of identify more with my Scottish roots, although I'm thinking I probably have more English roots than, than Scottish. If I looked at percentages of, of DNA, but so I, I, I'd focus on a couple counties in Scotland. I've been over there and done some genealogy, you know, visited the museum or the archives and stuff like that. So you can go join different geographic projects. Population and era based groups, if you will, there's a lot of really passionate groups on both Magna Carta, Mayflower. I've got to, I've got two Mayflowers. I'm not involved in the project because you can, you know, because there's only 24 hours of the day on the planet Earth. So it just, you just run out of time at some point. The Huguenots, I'm kind of interested in. I've got one Huguenot relative. And then I started working on pre 1500, because my port of fields go pre 1500 a little bit. And I started getting into, I don't know why I even got into this, but you just sort of go down this rattle. I got involved in the, I'm going to probably mispronounce it, but the Dalriada DALRI, ATA that were group people that moved back and forth between Scotland and Ireland. So I worked on, on that part of the tree a long, long time ago. Also for people that are more generous and kind and patient, I'm not sure if I've fallen into that category all the time. There's different programs to help other people here. So there's a mentor program. There's the greeters program for new people. There's help page development, training videos, a lot of people, a lot of people do. The training videos also get into an area we'll be talking about later today than I'm on a recorded video for is the, there's an ambassador program. So if you want to reach outside of wiki tree, the, I was a mentor for, I'm trying to think which group it was a mentor. Yeah, I think it was a mentors. So there's a group, if you people that 24 by seven watch the tree for, for evil doers, if you will, there are people that come in and just do damage to the tree because they apparently have nothing better to do in life. So there's folks. We signed up for an hour or two slots a week and we'll watch it for certain behavior on the tree, excessive deletions. I found that to be interesting. So I did it for a few years and then moved on to other things. I'm also kind of a data wonk. So where I've sort of got interested in wiki tree is on what's called the data doctoring program, which is trying to clean up profiles. wiki tree has this project through the wiki, what's something called wiki tree plus, which one of the team members built up over time that does a phenomenal job of analyzing the data on wiki tree for, for inconsistencies and things that are incorrect. So think about these, there's, there's a jet come analyzers out there, think of jet come analyzers and multiple times 10 in terms of the things that, that they find that are inconsistent. So it's really useful tool to, to help improve the accuracy of wiki tree over time. Profile improvement. I enjoy, this is an area where we, they encourage people to take basic profiles that have just sort of been imported in or it just has one or two lines and, and, and tell the story about that person.  So there's always something you can put in, in better sentence form, I think, then, then, then making it look like it's just something from a genealogy database. Connectors I enjoy working with trying to connect as many people together as possible. And there's an arborist program, which is kind of cleverly named. These are the people that merge, merge parts of the trees together. So, so I do some merging on the within wiki tree. So I was talking about projects. There are, so there's, there are also the other type of project are surname projects. So surname projects are, you know, basically, there's also a group in the UK called that does one name studies that we sort of work closely with. So surname projects are ones where I'm focused on Porterfield name. I tend to do most the editing for this project, but over time I wouldn't make people adding adding more content here. So I put information that we put information in my case about sources I've broken out the different groups with this goal of trying to get all the Porterfield stuff, you know, get them all connected at it's probably a pipe dream, but hopefully we get, we get more, we can get deeper on some of the Porterfield lines that we can't track back to Scotland right now. So there's also, if you like, there's also, this is my stinking badges page, if you will, to quote an old movie. There's also people ways that wiki tree and other wiki treeers can recognize you. So there's, there's basic ones like the new sign up, you got a wiki tree genealogist. There's also things that I'll talk about in a moment, maybe connect, connectathon and previous session Chris and some other folks had talked about the various connectathons. I use wiki tree for cemetery work also and excuse me, pre-1500 certified. So there's different thing and I'm DNA tested. So you can tag your profile. So when people look at you they know what you're interested in and maybe what you've done. So it's a, it's a little bit of a brag page, I guess too. So so one of the, one of the things with wiki tree is we're always constantly striving to make the tree more accurate.  And one of the knocks is they tend, they can be inaccurate. And if I, and I certainly can't tell you that ours is 100% accurate, I would tell you that there is that, that we have an army, a small army of people focused on making, making sure whatever's in the tree is correct. And if it's not correct, we have ways of modifying the profile. For example, by having a research notes section on a particular person, if you really, really don't know what the father is or, or there's some doubtful, you know, sometimes there's shades of gray on in terms of whether this is really a child or not. So we can actually put that in, in words, and describe the research we've done, versus just putting a tag on it that says doubtful, but we can do it, we can put a tag on it says it's doubtful, but you can actually explain what the level of research we have right now with the idea being that more researchers can come in and add to that. So and provide, and I've been able to do that. And I've had people where once I put research notes on, they come in and say, oh, well, I've got this source, or I, you know, if it's, if it's recent enough, I know actually, I actually knew these people, so I can, you know, so I can add more information. So again, a great place for collaborating there in terms of collaboration is a great way to make the tree more accurate. So, so there's a lot of different tools taught this, this, and this is the innovative database selection, I should probably just call it wiki tree plus is what it's known as. That's a whole another conversation in itself. The merging is done to create a merging project, the arbiters, arborists take care of that. Pre-1700, pre-1500 was an area where there's a lot of what's in a kind, a lot of imagination in terms of profiles that weren't properly documented. So one of the things over time is pre-1700 and pre-1500 is a little bit more locked, particularly pre-1500. It's a little more locked down because it's pretty well built out and, and there's certain areas that could be built out a little bit better, but, but yeah, you need very specialized skills to do that. So when the Jed come in, I taught a little bit, we only, we don't let you import the world anymore. So they have to be people born after 1700. And there's a process for reviewing the duplicates. And back to accuracy, we cite sources, we collaborate, and all these topics basically are focused on making the tree more accurate, which is a really major part of the effort around here. So socialization on wiki tree. I have talked about when I joined wiki tree, it was all about the tree. There is a huge social side to wiki tree that, there's probably, there's people that participated more than I do, but you can do team building things like when you do the, we have these events, the thongs, if you will, where we have a three day weekend where we do sourcing, we have three day, three day weekends where we, excuse me, where we try to clean up the profile errors, we have three day weekends where we across the year of the year where we try to do connecting. So you, we have, gosh, how many teams do we have? I don't know, maybe 30, 40, 50 teams. I'm on a really small team of pre 1500. We just, because there's just not a lot of those people out there, they're certified, but there's people that are organized by geography.  So they, they, they turn it into like a three day party. And then during these thongs, some of the people at Wigatree, well, every four hours, they'll have a little get together and see how things are going, give out some, some, some awards and, and, and giveaways. So it's, it's a very, it's a, it kind of sucks you into more to doing something more than just adding your, adding your great, great, great, great grandparents in. There's also something called ambassadors. We'll be talking about how they actually get, did a recorded session for that, that shows, that happens in an hour after this session. And we'll be, we'll be answering questions there, but ambassadors is a broad category of people that do outreach, whether we do, there's people that do talks like this. There's people that, there's people that do blogging about Wigatree. There's people that do social media. There's people that do videos. So all of those things, if it's, if it's outbound, trying to tout the, the wonders of Wigatree, those are all, that all falls under our ambassadors umbrella. There's a lot of thanking and being thanked. That's kind of cool when you first start getting used to it or getting into Wigatree. Picture of the week, profile of the week, member of the week. There's people sitting around, you know, searching out, searching out these things to, to acknowledge an award and various members. So it's, it's, it's kind of nice. I think it was profile week, long, long time ago. They, they just, people just find you when you're out here working. So on the site. And I talked about badges before. And then the GDG, for new people, I would strongly suggest you spend some time in the, in the GDG area. And then the Discord server, it's a wonderful thing. I was on it this morning. I just think I just need training for it. So, but I, you know, not just saying bad about Discord, it just, there's so many things, so many aspects to Wigatree. You can't do them all. So sorry for picking on Discord a little bit today. So a couple final slides here is, so as part of the various community channels, I think there's going to be an announcement later today of what we're doing in 2024. But we started in 2021, they started these different challenges. So AJ Jacobs, who I think was, was, had a presentation earlier this week as part of the, the first two days of Wigatree days. We had some big names. I mean, CC Moore, Wigatree, Henry Lois Gates, from PBS fame. So we, and I sat on a couple of these, I sat on, who's I sit on? Oh, CCs. It was interesting. So we do research for a week or two for this one. And then we present the research. And it was interesting talking to CC. She's like, I do this for a living. So I just haven't spent much time on my tree. And she brought her son in, I think, on the meeting. So, so there's a, there's a startup, there's a kickoff and then a, I present the results aspect of this. So that was kind of cool. And then they recast it in, in 2022 and focused on famous people. I didn't participate a lot in this one. So I don't know if they actually did brought people in, probably not Robbie Coltrane, but, but the, but they brought people in for, for the presentation. And, or to do the research. And this year, they focused on different community challenges. So they went after different groups and said, can you give us, I think it was eight or 10 profiles. And then we'll have a small army of Wigatree volunteers like doing this, we'll research those profiles and see what we can find. So, so I'm looking forward to what the 2024 Wigatree challenge will be. And so my Wigatree interest, you probably kind of figured this out from what I've focused on that I thought was, was interesting, but finding more ancient ancestors is a big thing for me. I like, I like the writing biographies, wiki, wiki style. I think wiki tree is one of the best places for writing biographies, because you can actually, rather than just jump out the working, actually make them look like an attractive story. You can add images on your stories, you can have formatting, you can, you can make them look like a, like a mini book almost. CERN name studies is a big thing for me, data doctoring, collaborating with other members. I do a fair amount of that. And the famous people are kind of interesting. I just, it's sort of a, if I'm bored, I might go check some of my connections. I'm going to be Gary Chapin fan, by the way. Don't spend a lot of time on that local history. Actually, in the last few years, I've been in a lot more with getting our tree town founders on, on wiki tree. And they're not related to me at all, because I didn't, I didn't grow up in this town, but I also went team captain for some of the wiki thongs. I'll kind of share that and kind of sitting doing a second seat on that these days. And finally, the project that was opened up a few years ago, I can update this slide. The, yeah, two years ago, I don't know when I was, but there's this connectors project that they now have gone through the database and done this seat, what's called a CC7 project. So it's the connected, it's a connection count of seven degrees from your profile. So I went from 1300 to 16 and I actually just kicked over 2000. So I've got to update that in the last, recently. So, so that that's kind of an interesting project. So, so what are the challenges? I, this slide used to say wiki tree challenges, but that actually has a meaning in our community. So, so what, what, why a wiki tree may not be for you or what might she get frustrated in?  It's not always easy to collaborate. So the, for people that are, that are my age group used to get a report card, you know, written on paper and it used to say, does he play well with others or did he play well with others? If you didn't get that checkbox, you're probably going to struggle the wiki tree.  There is always, there often is confusion about or disagreement perhaps over things, but it's, you know, you basically go to the sources if you don't agree on something. Biographies can be hard work. I, I find writing, I struggle with writing. I think a lot of, a lot of wiki treeers, I think a lot of genealogists do. It can be a little challenging, understand the wiki tree markup language. Start small, copy from other people. You don't have to write these big elegant profiles when you start. I've heard people, other people that are not fans of wiki tree saying, well, you know, I went in there and found an old profile that was in bad shape. And I said, well, yeah, that's just an opportunity. But I think over time we've got a very, the older profiles and the poorly, poorly sourced profiles are getting cleaned up. We're getting less of them every day. So we still have work to do in that area. Another challenge with wiki tree, it's just, it's just one other genealogy tool knocking on your door. So I'm not saying people should wiki tree should be the end all for everybody. But it's something I would encourage you to have in your tool kit if you will. So so a little bit just to summarize, I hope you got a basic understanding of wiki tree. It is a hard topic for me, I find to just, it's not something you can put a box around and explain the entire thing in one sitting. I hope you got a little basic understanding of one way to get started. And I hope that you gathered from, there's certain things that I enjoy doing wiki tree that if you talk to six other wiki treeers, like for example, if you sat in on the previous session with Chris and, and, and some of the other team, they all have different things they get out of wiki tree. And I'm kind of in the same boat, there's certain things I like about wiki tree, or certain areas I focus on wiki tree, there's others that, hey, it's a really useful thing for other people, but it's not me. So, so hopefully, at least entice you to, to, if you're not a wiki tree user to put in your toolkit. And if you are using wiki tree or haven't used it a whole lot, I hope I've, I hope that I've given you a couple ideas of terms of different things you could do with wiki tree. So anyway, that is my session for today. Thanks everybody for attending. And I'm going to jump over to the chat to see if there's anything, I think, Azure or someone who's going to be monitoring the chat, is there any, is there anything we need to talk about into any questions that came up that, that I can answer? Yeah, yeah, there were a few, there were a few questions. And then I just wanted to share, Kay Knight, she's excited with your presentation, she's going to share it with the genealogical society that she's with, so that they can review it in advance of her presentation that she's going to do in spring, in the spring. So that was really cool. And then we have Stephanie Hill, she says her year anniversaries tomorrow, she joined after watching last year's wiki tree day videos. So that's exciting. And we have Eric Lavra watching the wiki tree app session now, but he just wanted to say thanks to you, as it was this presentation last year, that convinced him to start using wiki tree.  So that's great. I may turn the man love to him, he's pretty, he's kind of going on wiki tree. So.  She's excited to be here and learn things. We do have a question from Wayne about creating a profile for each family member. And this is added to an overall tree. This is different than other genealogy sites that have charts. Well, you certainly have, there's, there are charts available for the information to enter in. The thing that's different here is, like if you have a, like I use family, I still use family tree makers as a genealogy program.  So like an, like an ancestry type system or other ones, you just copy people and rather information. And it's, you have this phenomenal challenge of propagating errors. So if we have errors in wiki tree, just as one example, is you get it corrected in one place and you can have a lively discussion as to, you know, whether this person was really a child or, or not. So, but yeah, so it's, it's the single occurrence of one person versus private occurrences of all these different ancestors in, in each person's database. So it can be a challenge sometimes. I've, you know, you can get in little, yeah, it can be a challenge sometimes if you don't agree on facts. I, I haven't really run into those. I know other people have so. Okay. And the next question is from Ann and she's asking, what are degrees? I'm thinking, I'm going to take a guess as this is the talking about the connection count of seven. They're like seven degrees. Like there's the old joke about this. I don't know how it started, but one of the people we have is we, there's the running joke about the Kevin Bacon's been in a movie with almost everybody in Hollywood. So there's this thing called the seven degrees of Kevin Bacon. And it's sort of paired. It sort of is similar to that. And we actually have Kevin Bacon's genealogy. So you can find out how related you are to Kevin. And I'm actually related in distant, distant fashion. But the, the degrees of the, so like for anybody like my wife, my, my children, I'm one degree away. My son's wife, I'm two degrees away. My son's children, I'm two degrees away. The, and then you end up going sort of like, sort of back and forth on your, on your tree in some ways. So for some people, so it's not, so I'm, you end up with this, if you're trying to, to do the count, if you're trying to bump up your counts, there's this weird aspect of your, your rooting for multiple marriages and divorces to bump up your count. I shouldn't say it that way, but, and then your, your hope, your root, and if you're from the US, you're hoping you got a lot of those folks that are farmers in the 1800s that had 18, you know, I've got, I've got one family with 26 kids and another with, okay, two, two wives and another with 24 kids. I think that was with two wives. So those, those are great for your connection counting, but, but somebody has 20,000 to 30,000 now. I have no idea how that is physically possible. So yeah. So degree is just the distance from you. So it could be a step sibling or, you know, it's just how far away that person is from you on the tree, basically. And then Anne has another question. Can she do a tribute to my late BDF? Yeah. So you can set up pages, particularly if she's unfortunately, you know, I understand she's passed. So once people have passed away, you can certainly set up tribute pages. If it's something recent, I would probably, and you're going to share very personal information, I would coordinate with family members, but, you know, so just be aware it's out on the internet, but, but I've certainly done that with people with my ancestors.  I should really have great pages out there for them. They were really great people, but so on a list. The never ending list. So Sandy is asking, how do I find famous people I'm related to? So I can drop that into the chat with a link for the connections. If you want to talk about that, I'll take care of that. Yeah. And if you look at my profile, number one, you'll, I did some of that. So I, at one point, I did all the presidents and the Magna Carta. So I put some of that in my profile. So yeah. So, and if you go to like Chris actually answered the question for us, I guess, so if you click connections under the my wiki tree pull down menu, it takes you to that page and you can then go to featured connections. And that'll show you what the featured connections are, but you can also just search for, if there's somebody you have in mind, you can search for that person on wiki wiki tree and then check your connection to them. All right. Well, I think that was, that's the last question. Thank you, Marty, for one another wonderful presentation this year. Thanks for the invite. All right. Thank you everybody for tuning in. We have next up on the schedule for today. Coming up next on this main stage will be the wiki word search. And that's going to be a live game at 1015 Eastern Standard Time. Also at 10am next up is the making a great German profile that's from the Germany project. And out on the apps and extension stream, we have starting out with the wiki tree browser extension with Greg Clark and Marie Maloney. So that's all great content today. And I've pinned to the top of the live chat the welcome landing page that has links and event information for it for today. So again, thank you everybody for tuning in and we'll see you around. Bye.


but I think two fundamental reasons. One of them is that, so this is what we're going to be talking about today. This is a set of bonds that goes by the name of thermodynamic uncertainty relations. So yeah, the first reason that it's close to my heart is that I think besides David's work that's presented in the previous lecture, this is about seriously ongoing research. So we are going to be talking about maybe two or three of them, you're going to be driving one of them from the fluctuation theorems. But if I tell you that there are at least 50 of them out there, believe me, because it's true. So why do they come with so many different flavors and just like so many different expressions? It's because they are bonds that actually are written in terms of that captured the conditions that you impose on the system and the system's dynamical evolution. We're going to see it, we're going to discuss it. So this is the first reason. But the second reason is that, so during this course, we've been always talking about that resources, right? So there's a resource, what is like the minimal something something, minimal cost of actually carrying some process. When you're given a minimal resource, how do you carry out a task efficiently and so on and so forth? So these guys, they talk about it.  So what we had in equilibrium statistical physics was that, okay, you have this isolated system and they sort of like the fundamental thing that you get on. This is that all the microstates are equally likely. And when you write down the Boltzmann, Gibbs Boltzmann distribution, basically you have a universal principle that is guiding you to derive the thermodynamic properties of the system such as temperature or pressure and so on and so forth, right? So and also there is a kind of an expression which we call the second law that kind of looks like a resource constraint because it dictates what kind of a physical process is allowed or not. Only those that actually increase the entropy are allowed, right? So when it comes to non-equilibrium states, so we are considering mesoscopic systems, right? Small fluctuating systems. They're incredibly, incredibly exposed to fluctuations. And this means that, yes, okay, they're often also far from equilibrium. So can we find the universal principle that actually identifies the behavior of the systems as we did in equilibrium statistical physics? The answer seems like no, because they come in such, again, in different flavors and different types. But what we can do is, for example, we know how to identify non-equilibrium state states, right? How do we identify non-equilibrium state states? We know it, right? It's a question, seriously, like, okay, sorry. Okay. How do we identify non-equilibrium state states? No, no, no, just don't. Okay, this is a detailed balance. But how, this is a detailed balance, what you're mentioning is that. But basically the way that we identify non-equilibrium state states is that you have non-vendation currents, you have entropy production, okay? You have non-zero entropy production, you have dissipation, you have an entropy cost of actually maintaining a process, a time of dynamic process, it's non-equilibrium state state. By the way, this is like the one of the take on messages, okay, we need to be, we should definitely know this with our hearts, it must be encoded there. So one of the things that we can do when we have a non-equilibrium state state is that also, depending on this definition of like this dissipation and the vanishing fluxes, we know that if you have a time-independent driving protocol, and okay, I'm going to abbreviate it as NESS, okay? I don't wanna keep saying non-equilibrium state state because it's too long, I get tired. So when you have something like that and time-independent driving protocol, what you have is basically a constant average entropy production rate. And when you have something like an average entropy production rate being constant, we can write down beautiful, lovely, and really, I don't know, friendly fluctuation theorems, okay? Like for example, like this one. These are the fluctuation, I mean, this is a form of a fluctuation relation, detailed fluctuation relation. I think we saw also the integral fluctuation relations yesterday, okay? So this is basically suggesting that this is a universal formula, okay? Maybe it's not stating some universal principle, like as an equilibrium statistical physics, but we cannot have these universal principles because now what we have for the entropy production is that entropy production becomes a random variable, okay? It's exposed to fluctuations. We need to speak in terms of probability distributions. We need to concentrate on the statistics that define these thermodynamic quantities such as entropy production. So this is as universal as we can get. This is basically saying that it is exponentially more probable that you observe an increase in the stochastic entropy or entropy when you actually compare it to the probability of observing a decrease, a corresponding decrease in entropy, okay? So this is one form of a detailed fluctuation relation, but one other set of relations and more like an expanded version, actually not only include entropy production, but some currents, okay? You're going to be defining them formally, okay? Currents are basically, some think of it as like some set of physical quantities that actually contribute to this change in the entropy as your system evolves, okay? So today by using that kind of a joint fluctuation theorem we're gonna derive a set of complimentary relations called the thermodynamic uncertainty relations, one of them, okay? And what these guys do is basically providing an understanding of the minimal energetic cost to maintain some physical process if you want to satisfy some amount of precision, which is like given in terms of inverse uncertainty. But to make it more precise because when I say it like that it's just like worse in the air, first I'm gonna put a verbal statement, okay? So the first TUR, it was derived in 2015. You can go and check this one. And in the context of, is anyone interested in biology? There was an end going like no, there was. Okay, that's perfect. It was derived in the context of biochemical reactions because the question they asked was the following, okay, stochastic thermodynamics is good and cool and you can universally bound some fluctuations, but let's say often enzymatic reaction. So this is the between, this is the end. Between this guy, okay, we are going to, we want to say something about the uncertainty or the precision of some physical quantity that we want to relate to the thermodynamic cost, okay? I'm going to say process, but take it as like a, I don't know, biochemical reaction. Okay, the reaction process. Okay, is the main message clear? Because if that is not clear then we're not going to be able to get beyond and about this. But give me feedback. If you don't give me feedback, I feel really, I feel sad, like seriously sad. Okay, thank you. Okay, so we talked about, okay, we are asking this question basically and it can be I think summarized as, we want to do that because it's useful because we think biological systems actually do it and we think, to design really more efficient computers you need to be able to do that too. Okay, you need to be, you need to have as like little amount of an uncertainty as possible. Okay, so let's start with actually a minimal system. Bound, yes, exactly. Bound's precision by dissipation. You want to provide a bond on the precision by dissipation. By the, I mean, you can think of also as like the uncertainty. Bound by dissipation. I will come to that, but if you don't get the intuition of it, the formula won't mean anything, I think. Okay, I will come to that. I'm doing it. So let's start with a minimal model. Okay, this is the system. So non-equilibrium steady state. I am coupling it to one heat batch. Is it enough to have non-equilibrium steady state? Or am I coupling it to multiple heat batch? Okay, multiple heat batch. Okay, I'm gonna tell why then. But let's say one, that too. If you don't have, if you don't want to have an non-equilibrium steady state, you can just couple it to one heat batch and you're good to go. But so just, let's remember this one. There is an implicit time dependence. Let me write it just like that. Okay, this is the master equation that's describing the system dynamics, right? So we got that, we know that. Okay, that's perfect. So one of the things that we wanna do is also, I want to sort of emphasize it if we don't know the difference between sort of like, if you, what happens whether you couple it to like one heat batch or multiple heat batch. There is an implicit sum here. When you couple this system to multiple heat batch, this actually is this term. Which is basically encoding the probability of making a transition per unit time. It's just the sum of the contributions of each heat batch. That's the, because when you couple a system to multiple heat batch, you know that system is gonna make a jump, right? You know that this time dynamics of different heat batch, they're actually imposing some dynamics of the system, okay? But you don't know which jump will it make and for, I mean, due to how, due to which coupling it will jump. So there is actually an implicit sum when you have multiple heat batch. This is actually in Esposito and Wandombrok, like page three or something like that. You need to see that, okay? And indeed, if you need to have one equilibrium steady state, you're having multiple rats. So that's good. So we can define a trajectory, right? We are evolving the system. We have, okay, continuous time and space, but discrete set of like the states or the configurations of the system that the system can visit, okay? So let's use little like this, maybe omega and define it as, let's say that this is the initial state that your system is in. It's time t zero, okay? And then you're going to jump to another system, I'm sorry, another state, bup, bup, bup. So I'm going to keep writing this up until two xn, tn, vn, where basically tn is your final time of the dynamical evolution. So system evolves between time zero and t, okay? So what this trajectory encodes is the successive set of states that the system is visiting, okay? I'm jumping, I'm here initially at t zero, I'm in the state x zero, and I'm jumping to x one at t one by the effect of the heat path v one, okay? And then you can basically encode all of these history of the states in this kind of trajectory, okay? This one, what do I, can you help me? I'm really afraid of, yeah, okay. Now I need to make some changes because it's going slower than I thought, but okay. Okay, I can still talk about this. Okay, so but let me tell you one thing. Esposito van den Broek, did we read it or not? Be honest, you didn't, right? Okay, I know there are too many classes and there are like, okay, too many things to do, but it's really, I mean, to understand something like that at the level of something, this is, as I said, I mean, this is ongoing research and this is serious research, so we need to be able to sort of, for example, just reply like directly what it takes to have an equilibrium steady state or how to write down like a trajectory because we are now going to define something called current. It's a function, an isometric increment function. So in these, I mean, it's gonna be mathematically precise. You're gonna understand it, but we need to be able to physically understand it, okay? Okay, perfect. So given a trajectory, we can actually define a new quantity that would allow us to count this net transition rate. Transition rate is basically encoding the jumps that you're making from one state to another, okay? So this is jumping, this is the transition rate from the state x prime to x, okay? I'm gonna use this one. Say this one. So we are counting and don't forget the word of counting because actually, I mean, maybe it's gonna change, but one of the questions in the homework is actually dependent on full counting statistics and we're gonna see why it's called counting statistics, but. Okay, so let me actually label this by, for example, i or j, yeah, okay, j. So j equals zero is encoding this x zero, t zero, okay? j equals n is encoding this one and our trajectory is encoded starting from j equals one to j equals n, okay? So I'm defining this in terms of this j's. So I'm going to write it like this one starting from j equals one to n. How do you count jumps from one state to another? This is something that you can encode in terms of direct delta functions, right? If you're making a jump from x prime to x, you need to basically write down the direct delta function that specifies that at that point in time, if you're making a jump from x prime to x, then you're gonna get a counting, a count, one count, only if you're making that transition. So this is why we're using direct delta function and this whole term itself is gonna come in terms, yes. Exactly. By the influence of, by the influence of v. Exactly, okay, okay. Exactly, yes, yes, exactly. So when I use this script v over here, it means that, yes, exactly, it's under the influence of heat bath v, okay? You can have, I don't know, we want to be in kind of like heat baths and they're all fixed at some inverse temperature, basically. We want them to be also another point. We want them to be at different temperatures. You're gonna keep them at the non-equilibrium state. And the idea is that basically, I mean, everything interesting in the world happens because there is conflict. You're coupled to two heat baths. They have their own temperature. They want to dictate their own temperature. They're stretching you like that. So what are you gonna do? You're gonna go out of equilibrium, right? So this is like the intuitive explanation. I'm gonna put this one. Do I need to put something different? Yeah, okay, the heat bath. Okay. This is basic, uh-huh. What are the two screens of the delta function? I think it's the chronicle delta function. Chronicle delta, yeah. So the second delta should not be there, probably.  If you look at what you wrote, probably the second delta should not be there. The second, no, no, but this is, I mean, the second delta encodes the fact that you're jumping from some X prime to X. Yeah, yeah, but the way you wrote, there is delta, the delta should be a comma. The second delta should be a comma. The here or? No, no, no, previous one. Okay, this one, okay, okay, okay. This one you're talking about. Yeah, yeah, yeah. Yeah. Are you thinking about it? No, no, but it's okay. I mean, it's just a notation issue. Okay, let's think, yeah, okay. Anyways, yeah. So basically, I will argue that it's actually true, but because you need to keep, do you see it? This is delta saying that X prime, J minus one should be equal to X, right? So this delta should not be there. I apologize, I apologize. I'm sorry, I was thinking that maybe you weren't like, yeah, maybe I was getting something here wrong, but I'm thinking no, no, you need to keep track of this. Okay, I apologize. Yeah, okay, I'm gonna do my best. Okay, do you see, okay, let me erase this. Okay, I'm gonna take this one over here and then write it again, okay? You see this though? Okay, I'm gonna do some over this. Okay, is it okay or should I go bigger? Okay, perfect, perfect. Okay, this is something that you use to count the transitions between states. So we understand what this means physically, right? I'm happy, okay, I see has nothing, I get really happy. Okay, now, here comes the definition of current, something that we didn't actually define before, I think, in this context. So of course, there is an implicit dependence on the trajectory of these things, right? So let me not lose notation. So now we are summing over v's if you realize, okay? Because we are going to call it something, I'm going to define what it's called. Okay, this is something important. Okay, this is what we call a generalized accumulated current as you go through a trajectory. We have a trajectory dependence, okay? So what is this? Did we define this? We didn't define this. So this is actually the only one in position on how do you define a current function, okay? The current function is incredibly general, okay? But there's only one in position that you need to satisfy and it is this one, on this one. You're taking this and impose this. This is a minus. So what does this mean? So this component over here, it allows us to actually count the state. If there's a question, I can definitely take it. Question? Can you repeat what are xj and xj prime? Okay, the thing that, okay. So this is how we write the master equation. Okay, maybe I should have used y. I apologize for that. Yeah, this is how I got used to it. But these are two different states, okay? This is basically something that tells you that you're jumping from x prime to x, okay? So I say that let's use j to actually keep track of these numbers. So this is basically how you're labeling j. j equals zero gives you this part of the trajectory. j equals one gives you this part of the trajectory and the trajectory that you encode is basically going from time t equals zero to time t equals some big t, finite t, okay? So the final value of j is equal to, it equals n, okay? So when you write this kind of a thing by Kurnakar Dalta, what you're keeping track of is that you want to count the net number of transitions between states, right? A longer trajectory. Okay, that's why you're summing, yes, great. Okay, that's why you're summing from j equals one to n. We should have made it two hours. We should have made it two hours, I said, the t yours. Okay, okay. No, but no, no, no, it's not, I have time, no, I was just making a comment. I was getting your feedback. Is that the current is defined in terms of, is not the net number of state transitions. Rather, at each state transition, you have a originating state, the initial state and a final one. We want a function of those two things, your initial state and the final state. The only restriction is that that function's gotta be anti-symmetric. If I were to do the same transition the other way, then I get negative. The current, there's a way that that term is used in this literature, is the sum total of that function which is defined at each transition along all the transitions in a trajectory. The trajectories are themselves random variables. The number of transitions there will be as well as the transitions themselves are going to vary from one run of the experiment to the other. So everything that's going to be talked about here is the averages of these currents where you're averaging this accumulated number, this accumulated sum of this function of each transition along a given trajectory, you are averaging that over all the trajectories. So as Gilder was emphasizing, it's a very, very general beast. Current in the sense that you and I normally think of it, like a number of electrons accumulating at a one side of a plus terminal, minus the ones that left at the negative terminal, that is a current, water flow is a current, but it's really very, very weird things can be a current. For example, it's a valid current to say the change in the opinion of the people in this room about, I don't know, whether it's dark outside or not. If you have that going, they give it a plus one, if you think that it's actually now becoming dark and a minus one, if you think of it's now not becoming dark, that is a current. I think the easiest example is that you have a coin, you're flipping a coin. Every time you get heads, just add one. Every time you get tails, just get minus one. Oh, it's gotta be the same coin that's going along. Once it becomes a head. But you're, okay, yeah, okay. It's not IID, it's once you get a head, then you would go back the other way and that would give you a negative. Okay, and more going thermodynamic. I think one of the things that we can do to make sense of this kind of a thing is that this is basically what we call an anti-symmetric increment, okay? It can come in different forms and the way that it comes in different forms is how we generate different expressions for currents. Okay? So for example, let's say that E of EX prime is actually corresponding to the energy that you have in state X prime and also EX is the energy that you have in the state X. So something like this, if you put it here upon this description, what you're gonna get is actually something like a net heat full of, okay? Along that, right, but I mean, yeah, of course, I mean, it's always along that particular trajectory or we wouldn't be discussing stochasticity in currents. That's why I'm always, yeah, I try to put it here and we have this dependence on trajectory. Okay? How many hands are you getting? Is it clear to people what a current is? Okay, but so from now on... I think there is something wrong in the number of particles hoping from X to X prime this is about V because we have XJ prime, but... Yes. And you need to keep track of like at which step of the trajectory you're jumping from where to where. That's why you're using some label like J. Yeah, okay, but what's XJ prime? Because we'll define X1, X2. Okay, but I said that J, I mean, if it's not clear, you can just take it like that instead of V, you're using J. Okay. Oh, okay, okay. Okay, yeah, you can do that, but I'm still going to argue, but anyways, okay, okay, let's go like that. So now I need your help because I thought that would be like a one hour of a class because we would be, I don't know, we would probably know how to deal with non-equilibrium steady states and sort of like how to, I don't know. I think, yeah, maybe you didn't reply because of some shyness, but yeah. So I'm going to then try to go really, really slow, okay? And I'm going to do my best, but I need you to give me an incredible amount of feedback. Okay, please, please. What's the difference between an equilibrium and a non-equilibrium steady state? What is the definition? Not how is it achieved with baths, but what's the actual definition? Do people know? Okay, exactly so. So that's the crucial thing, that there's zero. So let's say you have a system with three states. I can have it be that the marginal distribution over those three states is not changing in time, but probability mass is cycling in those three states. That is a non-equilibrium steady state. If you're in an equilibrium, there is no net probability flow going between any two particular states. That's the crucial thing and the way it is actually achieved in practice is by having multiple baths, okay? So part of the intuition that's going to be driving here is that entropy production goes up when you have very strong asymmetries in that non-equilibrium stationary state of moving the probability from one flow to another one. That's how you get it, that you get a lot of current. It's the current of the probability flow in the non-equilibrium steady state and the current of these operators that Gilger was showing is a relationship between those two that's actually driving the thermodynamic and certainty relation that is coupling the energetics of the process of being at the non-equilibrium steady state to the actual just transition values of the currents. Okay. And now it's gonna go more smooth because there is one thing left. Okay. Based on this one. Yeah, I can, yeah, just write this. Okay. So one thing that we can emphasize at this point is that we know how we, okay.  Yes. For d xx prime, how it is dependent on vj, like. I didn't understand. D xx prime, the generalized accumulated current. Okay. It depends on vj, like I mean the delta. Yes, it must, right? Yeah, no. Because you need to know that you have a state transition, right? You are jumping from one state x prime to x and there's a difference in energy. But let's say that you're a couple to different heat paths. If there was only one heat path, yeah, it would be trivial. But let's say that you have, you're a couple to different heat paths and we labeled them to, we want to we and blah, blah, blah, and we labeled them by vj. And we want to know that which heat path is actually causing this transition, right? So you need to include this kind of a term here. That information is in and new, but also in this one. So that's, that's correct. Any kind of a vj, you don't have to think about it. You are summing all over, all of these vj's when you're, when you're actually defining your current. This is how we define a generalized accumulated current. Okay? You're summing up all the contributions. Okay, so, great. It's a baby j and this is a, okay, i. Okay, let's go with i. But I mean, from this point on, you're not even going to actually label these kind of things. Let's just keep it like that. This is a baby j. And yeah, this is a big, big j. I thought this was actually obvious, but okay. Okay, yeah. Sorry about that. So I will be careful with the labels, okay? So what you want to do when you're computing the current, the total current is bad. You have heat vat one and then heat vat two. System is making a jump from one state to another. You want to keep track of like this jump, you know, okay, this jump is happening, but due to which coupling, okay? And when you're computing the current over a trajectory, you need to keep track of, or they account for all the jumps that are occurring due to any of the heat vat couplings. That's why you have to sum over v's. And once you sum over v's, you're basically getting this, all of these contributions, this current mini, mini baby. You can think of like this baby currents from one heat vat and then the other heat vat, but once you write down the complete generalized accumulated current function, what you want to have is that all of these contributions, the sum of these contributions, okay? Is it clear or not? I mean, this is something that we've been doing with the master equation, right? So it shouldn't be that, is it familiar or not? Okay, it's great. We're labeled with vj the number of this buff that's causing the jump between xj and xj plus one. Yes. So that's what we're labeling with vj. I actually say this sentence. Yeah, yeah. I remember it when I defined the trajectory. Yeah, okay, okay, okay. Yeah, but thanks for reminding that. I think it makes things clear. I just wanted to be sure. Exactly, no, but that's great. I mean, this is the case. If you're making a transition because it's, you know, like this j equals t equals, let's say, I don't know, three, then basically you need to account for the contribution of the batch that makes you jump at p equals three, okay? And this is just an abbreviation for that, okay? So after that, one thing that we can do is, okay, we talked about thermodynamics and certain two relations, we talked about fluctuation theorems and we know how to write down fluctuation theorems, right?  The entropy change. And then you run the movie backward and you're having a decrease in entropy, but we all care about the entropy production as a random variable itself. And the, just the probability distribution that is characterizing entropy production, right? But in a thermodynamic uncertainty relations, there are two components. When I actually started this lecture, I tried to emphasize it. There are some, for example, joint fluctuation theorems that not only say some things about the statistics underlying entropy production behavior, this entropy behavior of the system, but also currents that contribute to this change in the entropy as you evolve through a trajectory, okay? So thermodynamic uncertainty relations include these two terms. Basically, one of them is the average entropy production that you accumulate, okay? And the other one is this one. The variance of the current divided by the mean square of the current. This is called the precision, okay? You want to keep this as low as possible. You have a comment? Okay, okay. So I'm gonna put like the prototypical bonds here, but I mean, you can also write this as, okay, again, emphasizing your system is evolving starting from zero to finite t, okay? I think this looks like that. Did I forget something? No, okay, okay. You, okay, not for today, but for the exam, okay? I'm talking for the exam right now. We know, we should know, we must know how to write down things like this. Entropy production, average entropy production, like trajectory, current, and so on and so forth. Because this is like the center, like this is the core of stochastic thermodynamics. This is the foundation. Even if you don't do stochastic thermodynamics, even if you hate stochastic thermodynamics, I think it just gives you an idea about how to model things, right? So we should be able, I mean, I'm saying this is a TA right now that we must probably know how to write this kind of things. Oopity. Okay. Everyone is okay with this? Okay, perfect. Oh, we are going to take sort of like this historical bulk, but it's like a really brief history because the first TUR was discovered in 2015. This is something that you can find and I guess right now there's a textbook on introduction to stochastic thermodynamics by Luca Pallici, I guess. And these are things that you can find in textbooks. These are things that you can find in articles, but I'm going to provide them just to give an idea. Mean square. So they come in this form. This is the most general form. This is the first one that people derived. Again, in the realm of biochemical reactions, okay? This is the precision term. This is the average entropy production that you incur as you evolve the system in a time interval from zero to T, okay? What does this say? Is, okay, do you have an intuition combining with the first verbal statements that I had in the lecture? Do you have an intuition about what this says?  Like, yeah. Okay. So do you remember the question that I posed here, right? Yeah, okay. So just thinking about the positions of this, this is inverse entropy production, right? So if you want to have large precision, what do you want to have, or vice versa? Yes, exactly. There's a trade-off between precision and dissipation, right? You're paying with dissipation. If you want to have precision. This is what, okay, if someone just asks you, interventions, even if you don't remember anything from, I don't know, these moments of your lives, you can think about it as like this, okay. What is a thermodynamic uncertainty relation? It's a relation between precision and dissipation, and if you want to be more precise, then you're going to pay thermodynamically, okay? And the payment is done in terms of entropy production, okay? This is one form of it. So I told you that you can apply different thermodynamic uncertainty relations to different settings, right? So it means that, okay, we define different settings by imposing different conditions on how the system evolves dynamically in some finite time interval, and this only works for a specific set of physical scenarios. If you are in non-equilibrium state state, you can use this time-independent driving, okay? So by the way, I'm using always this term driving, driving protocol. Do you know, I mean, how we can sort of like driving the system or is it just like, yeah, for example, great, okay. So what we think about when it comes to driving, you know, like a thermodynamic, you know, like this system in a thermodynamic process is that, and a thermodynamic process is, I think, it can be formally defined by two components. This, I was having a problem with because it was so amorphous to me that I read Chris Dresden's Key's paper on actually the first like this derivation of detailed fluctuation theorems from finite bath formalism that we are gonna discuss at some point in time. So he gives a definition of thermodynamic process as a composition of three components, okay? You have a system, heat reservoirs that are fixed at some different, you know, that are fixed at some temperatures. So beta, I, and they are fixed at some temperature. So they have their own equilibrium distributions that are characterizing themselves. This is the first one. And we are talking about a thermodynamic process. So if you don't couple the system and the reservoirs, you're not gonna have something like that, right? So establishing and breaking coupling with the thermal reservoirs. This is one part of the thermodynamic process. And the other one is, this is mostly how it symbolized a lambda. It's a control perimeter, okay? And it is basically, yeah, external force, external field, apply a magnetic field. This is what we call a driving protocol. This set of functions of t, little t time, okay? This is a, yeah. But yeah, sometimes, I don't know, some sources say that these two of them is also a driving protocol. So when I say we're driving the system, we need to think about two things. Establishing, breaking contact with thermal reservoirs and just using an external work perimeter. This third element here, basically, yeah, it basically, yeah, corresponds to what you said. You have an external agent that is manipulating the system from outside, okay? So I talked about this because, yeah, we keep saying that, oh, non-equilibrium steady-state. There's this time-independent driving. But what if you actually want to do something different? Okay, consider some different types of driving, such as periodic driving with some different conditions. One of the UIs that work for the scenarios, because this is incredibly strict. You can't believe how strict this is. Yeah, non-equilibrium steady-state is cool, but it's comprising a really baby subset of scenarios, okay? Are we out of time? Where does that appear in the equations, for example, on the left? That's behind Gilder right now. It's an argument of the W. So when people talk about doing work on the system, the way that that manifests itself in this stochastic thermodynamic formulation here is by changes of W. And so lambda of T is just a way of encapsulating that. So it's actually W of lambda of T. So something different that you can have if you make this condition a bit more flexible, but not too much flexible, is something like this. It's a weaker bond, but you're actually making this condition flexible. What you wanna do is to see what kind of physical scenarios you're allowed to apply these TURs for, okay? This is called, I don't know like this, this is the original TUR, an ESS TUR. This is called something that I plan to drive, but probably not today, because we are gonna be using joint fluctuation theorems and so on and so forth. Joint fluctuation theorems of entropy production and current. So it's a fluctuation theorem of two random variables, okay? The fluctuation theorems that we saw yesterday, they only comprise one random variable, which is entropy production. Now we need to also, we want to also account for some other random variable or variables. We are gonna start with two, like entropy production and one current, that contributes to this entropy production. When I say contributes, just think about the definition of the current and the definition of molecular rim steady space. So here is the thing. An ESS identified by non-zero, let's say, zero current or non-vanishing currents is, I think it's better, entropy production. Non-zero entropy production, okay? So these are all the same thing. So when you have non-zero entropy production, there are some non-vanishing currents contributing to that non-zero entropy production. This is the idea. We want to keep track of these currents. Okay, this is something called GTUR or FTUR. I mean, it first went with the name of generalized thermodynamic uncertainty relations, but then I think it's now called fluctuation theorem, like thermodynamic uncertainty relations, because it is basically using in its derivation this joint fluctuation theorem of currents and entropy production. Okay, so depending on the time, I am either stepping here and getting feedback from you because I think I must know where you're standing, how you're feeling, and so on and so forth, because I also started to get scared about the homework. Like how do you feel about the homework? If we had, yeah, if we have some hard time with this kind of a thing, then maybe I can do extra restation hours, we can have discussions. I can do so many things for you, just ask me, okay? And if you want, we can actually slow down with the schedule itself, so we don't maybe have to talk about some really, you know, like thermodynamics of computation, like in all by like itself, in its own profundity, okay? I think it's better to understand this kind of principles right now. So I want you to give me feedback. You can tell me how terrible of a lecture I am. It's also allowed. But yeah, please give me feedback. So how do you feel about this kind of a thing? Do you think it's, what is the pace for you? A flight example from Io channel for other things and not like in the general form, so that's what's part of what confused me. Okay, because you had a course on stochastic thermodynamics, but from, I don't know, like this, yeah, again Io on the bead and so on and so forth, like more like the continuous, like the, like an Udo Seifried approach, I guess, yeah. But you, okay, that's good. Okay, how can I make it easier for you? Do you want to give me your previous lecture notes so that I will fix the notation for the upcoming lectures? Okay, you wanna come here, actually? Yeah, I think your two previous lectures were awesome in the sense that, I mean, we already saw them, these subjects, but that's an overview. So, it was fast, but because we already saw that subject, I think, was good. The subject is new, so that is a little bit harder because we didn't knew the subject. Okay. And just low the pace. So, I think it's fine. I think I have to see again the lecture and then I can tell you if you are a good or a bad. I mean, I have to see it again because if I didn't catch it because I'm too sleepy, that doesn't mean you were bad. So, I can't tell you later. That was fair, yeah. But so, when I came to this class today, I assumed that you know how to, I mean, because we provided you the Vandenberg and Esposito, this holy book. I say that it's a holy book. I think he said something along these lines. It's okay, it's like, okay. It's richness is like a book. I must do it, yeah, I know. But yeah, so yeah, I thought when I was coming to class today, yeah, I don't know. Like most of the participants in the class today would be able to write down like this, for example, I don't know, like this master equation and tell directly without being shy, like non-equilibrium status states, like how do we characterize them and so on and so forth. So, yeah, it surprised me a bit, but I think this must be totally normal. So I'm shutting up right now, but yeah. Okay, so a couple of things. It is crucial. Everybody please go through that paper by Christian Vandenberg and Massimo Esposito. It is very easy to read. It's very clear. It does not have this kind of material in it. So that's the first thing. It'll talk about driving protocols, the stuff that I was interjecting. See, part of what's, there's an issue that, there's an assumed language that's being used and so on, which would have been based upon you having read that paper at a minimum. And if you haven't, then that kind of means that the language we're using doesn't really even make sense to you. So please do go through that article. There's also you can find online. Palletti and Pigoletti, unfortunately, you're not gonna be able to find the textbook online. Yeah, so this is the holy paper. Yeah. I actually send it to Slack channel as well. Okay, yes. Okay. So there's also a textbook online PDF by Naato Shorishi. No, it's not available yet. It's the first draft. It's not available. Oh, not the final one, but the draft is available. It's pretty close. Yeah. And so I would recommend also. No, David, David. It's not pretty gorgeous. Let's not go with that. It's a whole book. This is a paper. But if they need to, please, please, please. If they need it, let them come to me. I will do my best. I will get that. I'll get that. So if you also have questions about things that are not in that paper, take a look in the PDF as well. Now, something else I also want to emphasize. You have a resource. Guja is one of the world's experts in thermodynamic uncertainty relations. She's done some very important, good work in it. Very, very brilliant stuff. So exploiter, user, take advantage of what she knows about these topics. It really is some very profound things, but it will be most effective if you first, at a minimum, have read Van de Brocken Esposito, that paper. Okay? So I think, anyway. Thanks, everybody. Thanks. Thanks. Good job. Thank you very much. How is it for the conserving of this process? I mean, I don't know. It's not conserved, no. No, it's not, of course, conserved. So I'll just tell him. No, I mean. It's not conserved. No, no.


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