09:20:14 Okay, great. Awesome. Thank you, Ben.
09:20:17 So I'm going to talk about how to deploy in the Milky Way is Sam from the gym. I personally find this topic super challenging actually. First of all, why blending is an issue.
09:20:30 And the answer to this question is actually very simple and straightforward. This is because we live inside the Milky Way, and it's a blessing and a curse.
09:20:40 And since this is a tutorial I thought I'm going to cover some of the fundamental and basic terminologies for audience that are not familiar to this field.
09:20:49 And now I will include some recent work by myself and by others for the efforts in the audience as well.
09:20:56 First of all, I want you to make two analogies to illustrate why we live inside the Milky Way is a problem for us to understand the Milky Way CGM.
09:21:06 First of all, imagine this is your house. And then your house are surrounded by a whole bunch of trees, so you live in a forest.
09:21:13 In this case, it could be difficult for you to spot any animals like Alliance, which could be dangerous, because they are hidden behind trees.
09:21:21 In this case we say your line of sight velocity is blocked by the foreground in position space, in this case in the foreground, are the trees.
09:21:31 On the other hand, imagine you had a really good stickers and you were playing some music. It turns out the whole universe conspired together and that your neighbors have exactly the same kind of stickers and playing music roughly and the same frequency.
09:21:45 So you end up just not hearing, a great music from yourself and you end up hearing a lot of noise.
09:21:52 Unless somebody else starts to play piano and a piano is at a different frequency, then all of a sudden you are able to hear that piano sounds.
09:22:01 In this case we can say, the line of sight is blocked by the foreground in frequency or wasteland, or velocity space, and in this case in the foreground is the sound.
09:22:12 So for a milky way CGM observations we suffered both problems, our line of sight, both blocked in position space, and in velocity space because of the foreground IFM that blocks, our line of sight and also blocks, the members around the same velocity.
09:22:30 Mary has beautiful beautifully tell us about the high velocity clouds and on the gift of structures in the Milky Way. I kind of want to show you a very simple cultural illustration and show you why we have all these terminologies using spectrum.
09:22:45 So imagine, this is a milky way we have this thing this is in a bunch. And then on top of it, we have the h1 this which has a beautiful extended work.
09:22:55 And then we have the intermediate velocity clouds.
09:22:58 If you project this clouds across the sky you see some large patches like this. They are called here but this is kind of our own reference and at that time they don't have data in this region from that survey.
09:23:10 So I believe this is something people might mention tomorrow as well.
09:23:14 On top of it we might have high velocity clouds and this is something Mary mentioned yesterday. Already you also see beautiful patches and all different combos complexes across the sky.
09:23:25 And if you compare this to mess together you could see that they are not always post spatial and running given lines of sight, if you take one section, and this is something you might get.
09:23:39 This is actually a spectra I cherry pick from a trunk full pie data set, and to illustrate why we have different velocity range. So you see, three initial lines at zero.
09:23:55 Number per second, you see the initial line from both wi I FM, the collective playing and also the low velocity clouds.
09:23:58 And usually we define this range using VOSR with a 20 to 30 calendar for seconds. And here, RSR means local center of rest, or, you know, this is the observers reference from our vantage point 8.5% from the galactic center.
09:24:17 And going forward we have the intermediate velocity clouds which is traditionally defined with velocity between 30 and 90 200% of the Asr, and then high velocity clouds are those with velocity higher than 90 kilometers a second plus minus.
09:24:35 So, I said that I cherry pick this spectrum. This is because most of the time you don't really see I VC VC happens at the same time, for example, this is another spectrum, you see the super strong collective emission line, but you see a teeny tiny emission
09:24:50 line from the HBC in a different direction towards the sky You see, I VC in the collective initial I happening together but you don't really see each VC.
09:25:01 And so, generally speaking, given a random line of sight, everything HVCH on features to not always appear together, and it's in time.
09:25:10 Why do I show you this. This is because we started to think about IDC HPC based on h 121 centimeter data sets. And then later on the UV community borrow this definition, a start to look at me up obstruction life.
09:25:27 So here I'm showing you a halo star skyline from Genesis, 2819 work, where she identified this is the is m of soft July as the economic per second. And then an IPC absorption line with 100, kilometres, minus hundred seconds in a different scenario, if
09:25:45 you look at a quicker absorption lines. So this is silicon to where they identified the ionized he VCs with 100 to 200 200% in this range in that range and everything in distributed RC very close to us from the Milky Way's if Sam, in the title interface.
09:26:05 So, if I put this two figures together. There is something I have not said deliberately, but you might have figured out already, which is there seems to be a hierarchical structure where higher velocity means further distance, which is illustrated here
09:26:22 when we think about I VCs, which is at a distance about 2.3 kilo per sec ah VCs are typically at a distance about 10 to go perfect.
09:26:32 So, a few years ago when I started working in this field.
09:26:37 Mary joshing I decide to put a question mark on this or is it really true. And can we try to do something else to demonstrate it, or to prove that it's actually wrong.
09:26:49 So, we decided to start with the up absorption lines, and the questions. I would like you to think about is are they are low velocity guess, in a sense, a CGM in the Milky Way that actually hidden behind a nearby FM.
09:27:04 In other words, are the signals industries that is actually coming from the Milky Way CGM so we just don't know where they are. So this is really why I am doing this tutorial today is I maybe there are signal pointed in a local lots of reaching.
09:27:20 In that case hockey with deployment.
09:27:24 For a lot of people in the audience maybe a more genetic questions to ask is, what is the guest velocity distribution in the extent is, if we're not thinking about office educational constraints.
09:27:37 So for the past few years I have been working on this, and I have been trying to solve this problems using two different approach. One is, think of the observations using simulated Milky Way analog, and the other is direct, indirect observation that approach.
09:27:53 So I'm going to tell you, both of them.
09:27:57 First of all, I think that the observations. So, for synthetic observations. The first thing we want to do is we want to identify a milky way analog. And here I'm showing you assimilation by Ryan Jews were you were seeing the h1 projection in Agile direction,
09:28:12 a face on directions.
09:28:15 What we can do is we can pick up mock observer in the set in a galaxy. That's a typical course away from the center because this is what we are in the actual Milky Way.
09:28:26 And then from there we can ask, what does the Oscar projection look like from that position, and in this case I have taken out the disk. So from a synthetic observation approach.
09:28:39 It is registered for to deploy that is Sam and a CGM because you basically just take out the data from the center and then look at the rest of the simulation.
09:28:48 And in this case, when you do all sky protection you can see that this is a long data structure, a stretch across the sky, and this is something we have been able to see in the real data as well you see elongated structures, a large patches, even though
09:29:03 the simulation observations do not have one to one correspondence from a simulation perspective, one question we can ask this question directly and get the answer, like what is the guest velocity distributions.
09:29:16 So I wanted to tackle we have from the face diagram perspective. In this case you are looking at the hydrogen density in the temperature of the CGM gas at different radio.
09:29:29 And then this is the constant pressure line and then this is the direction the pressure will decrease. So, I'm going to show you is the vertical blue lines are those most intermediate velocity guests, and this on a guest that I'm not typically observable
09:29:45 using real data, and the horizontal lines are high velocity gets a this and again, we always talk about a we are able to observe without too much problems.
09:30:10 So, first of all at 20 to 30 calendar per second, you see that in the local it gets a high velocity guess, roughly occupies the same face diagram, except for this really hot region, and then going to a further distance of 50 kilos.
09:30:14 Now you can see that the pressure to please. And this is something Mark has talked a lot about at his model. And we see it on the low end have lots of guests your occupiers submitter face diagram.
09:30:24 And it going out to Hunter, and then 200 kilo parsecs.
09:30:29 This exercise, tell me that first guest moves at a wide range of velocity in the Milky Way CGM there are local of the guests, and they are high velocity gifts.
09:30:39 However, nearly half of the CGM guests by mess. It's moving at the low to intermediate velocity, and this is something we cannot appear, therefore this is hidden from observation.
09:31:06 We can go one step further, to ask what is the general mess flux distributions. So I work with for the last year, and take one of the simulations. And it is also a milky way analog at a relatively low Max, and then I look at the overall message distribution
09:31:08 x assumptions off guests faces. So here you see that in the great band, this on the gas movie, low velocity with respect to the center of the galaxy, and then actually dominate the flux compared to those high velocity guests, moving hundred kilometers
09:31:27 per second or higher.
09:31:29 second or higher. So the takeaway point here is, there's a significant amount of guests mass, regardless of guests face is moving on low velocity and this is something we observers, often ignore or actually we do not have access to, in general, And then
09:31:46 now you start to see different patches. And this different patches or the velocities shifted to the observers, restaurants, so remember our solar neighborhood is not in a goddess center.
09:31:58 So we don't really get into real flux, with respect to the galaxy, everything is projected along our lineup sites.
09:32:05 So the second takeaway point here is the observed guest velocity should be corrected to the Milky Way reference.
09:32:13 We can illustrate this problem, further by counting calculating the total inflow and outflow.
09:32:32 indicate in the radio velocity. The radio directions. And this is a value that's not directly observable in observation.
09:32:38 And now I'm going to shift me observer, to the local standard of rest, not you can see the value actually changed quite a lot depending on the face, you are looking at for in the codec no codec slow rate may change by a factor of 10 from that some other
09:32:55 the galaxy that I look at from the Milky Way to reference to the local standup rest.
09:33:01 And then for up I guess with temperature rotation of four to take to the six. In general, we see that the cold to warm cash flow rate may change by a factor of two, from the nucleus reference to the MSR.
09:33:16 So, this is saying that the inflow and outflow rate estimates from the Milky Way CGM is due to our vantage points. And this is something Marissa has mentioned yesterday that if you think about the influence rate and also rate of HPC in the Milky Way.
09:33:30 You really need to think about what kind of corrections in 3d models you assumed, and that might result in some difference in the numbers.
09:33:40 So, since this is interactive observations, and I want to discuss with all of you here about like what kind of simulate them up with analog, we should use it what kind of parameters we shoot used to identify a good Nicola analogs.
09:33:56 We have talked a lot about mess and guest faces. So I don't want to dive into those. I'm going to focus on the mythology, in the cinematic fear. First of all, mythology.
09:34:08 So, this is a foggy galaxy in. I like this galaxy, because it hasn't really beautiful work. So this is something, something we have see in the Milky Way as well.
09:34:20 So, my first go to criterion is, if I'm going to take a milky way analog, I want to make sure that at least, is a trauma is similar to what we see in the Milky Way.
09:34:31 When I go further to analyze the radio density profile and also the desktop profile along the directions. So here in grey, I'm showing you the radio that's the profile from the simulations and Brad, I'm showing you what people measure from the Milky Way.
09:34:48 Way. So you don't see like 100% match the overall you see that the radio profile drops in a similar way, in a different scale and consistent between the simulation and the observations.
09:35:01 So I think this is something that's important. If you want to find them go to analog to make sure that the guests distribution are generally consistent.
09:35:12 The other point is about kinematics. So, for kinematics I'm showing you the data here from Capella adult 2008 on the x axis, you're looking at a galactic longitude, and on the y axis you are looking and and look with your breath velocity, and in bright
09:35:29 pink in the HR intensity is very high, you have to see a lot of each one here. And then, in this light green and light blue as cutter you see very faint h1 or h2 one that's more diffuse.
09:35:43 So, what is this figure means, imagine this is the Milky Way desk, and this is the center of the galaxy.
09:35:51 And the solar system is away from the center at a point five kilo per se. It is co rotating with a desk, out of velocity about 222 number two seconds.
09:36:03 If we will kind of got the center, l equals to zero. There is no projected velocity from the rotation co rotations of the shoulder neighborhoods. In this case, if we look at all the guests along that direction, everything will be at zero number of projects,
09:36:20 because there's no projections. So this is what we see here at equals to zero, towards the DR center you see that most of the guests are centered around zero.
09:36:32 number per second, because you're very few production effect.
09:36:35 On the other hand, if we look at something like L equals to 90, which is a the directions offset to where our rotation is. So this is kind of like you are in a car and moving on the street and you find out that you have a friend sitting in a cafe.
09:37:04 And from your perspective your friends is moving away away from you but in reality it's just your car, moving away from your friends. So we see similar things in the Milky Way, alpha equals to 90, we find that all the guests are moving at the negative
09:37:08 velocity, meaning that they are moving away from us. And in this case this is because we have the rotation velocity projected along the line of sight and then you see everything moving away from the server neighborhood.
09:37:21 So, from here you can figure out that this is the positive velocity because we are rushing towards everything. And then inside galactic center we don't see anything, a higher velocity because there's no protective velocity.
09:37:34 So this is what observations of the Milky Way tells us in a simulation you can do something similar. So this is the simulation that Ryan work on in, I took the simulations, and built a senator collected coordinate systems and figure out that this is what
09:37:51 what the h1 looks in the simulator galaxy.
09:37:55 The exact values doesn't really match with the observation but overall the rotation shape and equal to zero or equal to 90 you roughly figure out that they are the same amount of guests, and a kinematics are roughly right.
09:38:10 So, this is something I want to emphasize that if you want to use a simulated mutually analytics to understand the Milky Way guess distribution and kinematics, it is really important to make sure that you at least have the first order rotation.
09:38:25 Right on. So, this is my summary one about the effective observations, which is first.
09:38:32 There is a non negligible amount of mass in a milky way CGM, and that's about 50%, and they are moving a low velocity Rishi therefore they are hidden from traditional HPC observations.
09:38:44 And then second, another observations are really useful for evaluating all this observational biases, but we have some challenges. First, how to find the most appropriate mutually analog, and this is something I look forward to discussing with you all
09:39:06 what's in your mind, that's the most important criteria you like to use to select the Milky Way analogs. And then I think different theories might have different ideas about their own simulations and there are systemic uncertainties in it. So, forum,
09:39:15 the simulation perspective, how can we trust the results of the synthetic observations and how can we make sense of all those uncertainties.
09:39:23 I look forward to discussing all this with you all.
09:39:26 And now let me move on to the second approach, which is directly using observations and data.
09:39:32 So, as I show you from that you'll be absorption wise, I asked you the question that are there local off the gas in the SMS CGM hidden behind the AFM.
09:39:44 And the answer is yes, according to synthetic alterations of mercury analogs.
09:39:48 I want to take your question, the step further, to ask how can we test this directly with the observational data.
09:39:57 I think the most direct approach is using close pairs of Quasar a stark difference in technique. So this is a slide I stole from Hannah Bish where you find a store, and then the questions are quite, they are very close to each other.
09:40:19 the difference of the two which hopefully tell us what's the SS in a CGM. I'm not going to go into details here Hannah has put out a really lovely video Oh Halo 21 new result, and it's on the YouTube, a, I encourage you to go check it out, and has any
09:40:39 here as well so you are welcome to ask her questions and have more discussions during the free cover off. I'm going to move on to some indirect approach, which is using models to understand that all Skype distributions.
09:40:47 So I'm assuming you are cartoon illustrations about what we understand the Milky Way is an independent interface. So, you have the solar system here it is, you know, I FM, and above it, you have heard this Hedo, etc.
09:41:02 That's kind of cool rotating with the ISS at lagging velocity.
09:41:06 the ISS at a lagging velocity. So traditionally we have this lesser approximation, which is based on hydrostatic equilibrium where the density goes off exponentially. And this technique, and this model has been widely used a UV communities and also providing
09:41:29 And how does this model tell us.
09:41:38 Imagine you would have a halo store and I hit a star is at a distance about the away from us, which means he has a projected vertical hype about z, which is defined me.
09:41:43 And then if I use the HS the telescope to measure the column density. So, the y axis here is the projected Austin six columns as the along the vertical directions.
09:41:55 I would get a diagram like this. The further away to start, no more material you're going to collect along the line of sight. And this solid line here is what's predicted from the snap approximations.
09:42:09 So basically it's in the first order approximation is a really really good model to understand the guests distribution, in general, even this whole interface.
09:42:19 And as we go to higher and higher distance, you realize that you've reached a plateau. And this is because in a flat Flat approximation that instantly goes off, drop off exponentially so we don't really expect any material, and much further distance,
09:42:36 especially if we increase our measurements at the distance equals to infinity almost, we don't really expect more material to be collected.
09:42:46 If we zoom in, into this region's not Here I'm showing you the collective latitude of the quasars because honestly Darth our assistance super far away so it doesn't make sense to show the projected distance from quasars.
09:43:00 So, it hatch region which is boy here, no fluff model predicted a constant density distribution for all the guests because there's no variation across this guy.
09:43:11 However, if you're looking at the data itself, really, the data itself give us. We're trying which is a higher quality of latitude, you see more projected stuff at local at the latitude you don't see as much.
09:43:25 And so this is say the fluff drama to can't fully explain the ultimate six column best distinct worst Quasar satellite, even though this is a really good approximation for this better silence data already.
09:43:40 And I went ahead to analyze more data, and this is a different ions. Now we are looking at a cynical Tour, which is on a different face compared to auction six.
09:43:48 So here on the left you are looking at the center sideline, from where savage important records were in the flesh model reproduce the beta very well. And then on this region where I'm showing the equation data to analyze, you see that in general, the
09:44:05 the data doesn't really fit with the flat set, really well. And so again, when we use the data, which is to come forth right now we also find that the Fletcher all mature cannot follow it explains the sky color does it distributions scene towards Quasar
09:44:21 sites.
09:44:22 And so, this is, I believe the indirect evidence for Angus Tennessee jumped on the last lap.
09:44:29 So I decided to want to how to build a really simple model for the Milky Way CGM which is extended to jam, it is only accessible to the equator sidelines.
09:44:39 And my motto is build about, no fluff at your arbitrary and I decided to just add a super simple constants into the profile in a CGM and, and to see whether it works.
09:44:51 And it's in around the same time of Judea decided to build upon this model, a half or more sophisticated. That's what the distribution where it is depend on the radio, and also the z directions, at the same time you have a kinematic component.
09:45:07 So, I'm going to show you how those different models differs, and what consensus we have, be able to reach.
09:45:15 So, this is the silicon for common vested distribution as a function of collective latitude, as I showed you earlier, the flesh that your army shoots predicted a plateau, for everything, which you can clearly see does not match with the data very well.
09:45:30 And then my model which is a really simple continent that's the model that has extended CGM, that is able to largely cover the recovery, the common density as a function of collective latitude.
09:45:45 And on top of this, just model which has multitude dependence in it because of our radio dependence. Now you can see that a lot of different directions you expect to see different columns as deep as a function of collective latitude.
09:45:59 So the takeaway points from this comparison is it send us the jam components, if necessary to explain me using data, either is optimistic or silicon for, however, model details might differ depending on what you put into the model.
09:46:17 So, this is my summary point to, first of all, we have the quasar data, a I do not go into details about it later bye look forward to handle telling us more, you're going to have recovering sessions, if people are interested, and my work shows that a
09:46:44 CGM component is necessary to explain to you the data. However, we need to talk more about what kind of details have been put into the model to get any audience I believe so I look forward to hearing more from his perspective.
09:46:50 We have a lot of challenges in this reaching as well for example in the Milky Way CGM alone, collect a lot of you is largely inaccessible. So we have to figure out a way to understand that part of the CGM, and only I'm gonna hand with, even though we
09:47:04 find that the extent of CGM is necessary. However, from our Quick Start they don't we don't actually see that much CGM SS if you compare it nearby Quasar pair sightlines, so perhaps we need more sophisticated sophisticated model with non physical guests
09:47:23 distribution in a CGM. So, this is something that haunts me all the time. And I love to hear your thoughts like, what, what kind of models, you have in mind, and what we need to do to figure out the general milky way she can get entities distribution.
09:47:39 With that, I'm going to end here and take questions, or we can all go to breakout rooms, and have a discussion, like yeah
09:47:53 you Jaan, that was, that's great.
09:47:57 What we'll do now is, you know, take a couple more minute question two or three more minutes, maybe one question here and just has her hand raised and then migrate over to the breakout room,
09:48:14 beautiful young I really, I love the way that you explain our perspective and so I always get turned around when I think about a local standard of rest versus galactic standard of rest.
09:48:30 I think you know we've talked, explain this to me before but I just want to ask a very straightforward I feel like I know how to pose the question now.
09:48:42 Yeah. Is it How is it called Bella. 2008 So, each one, each one velocity distribution where like you're looking toward galactic center, and you know the line of sight velocity is zero but you know you're always, you're always up at some galactic latitude
09:48:56 or whatever so it's a projected velocity. When you put into the Galactic standard of rest, rest frame Are you basically subtracting out that kind of velocity shape, or is this rotation have nothing to do with galactic standard for us.
09:49:10 Yeah, this is a good question. So my understanding is got to spend a breath correct that rotation projector rotation whichever direction you are looking at.
09:49:22 However, there is a difference between you correct the value or you correct, the velocity vector, because the galactic center of rest. Still, the velocity vector is still points at the local MSR, even though you have corrected the velocity, even though
09:49:38 you're not able to point the velocity vectors to the Milky Way center. So I think the galactic center of rest def not really reflect what's going on, if you're able to migrate to the Milky Way center and see it there because he only corrects the first
09:49:57 projected rotation.
09:50:00 Yeah yeah yeah okay okay so if I'm trying to understand, for example like velocities, but I have line of sight velocities that I have toward you know Halo stars and quasars or whatever context in the Milky Way.
09:50:14 And I want to know like kinematic Lee what's happening. Is it easier, in your opinion, to just look at the local standard arrest, and then just kind of have that rotation in mind and do.
09:50:26 I don't know, do that more visually in terms of that comparison.
09:50:34 Um, this is a good question. I think different opinions, different people might have different opinions on this. To me, I think, local standard rest is easier because I know this is with respect to our heart, and my observing restaurant, and the galactic
09:50:49 center of breath. The name itself is a little misleading, therefore it's not straightforward because it collects it correct the projected rotation biceps are correct, the velocity vector, so sometimes I opened up confused because I thought it's going
09:51:04 to send over so much points are worse than Milky Way center. It's not that case. So I think Josh has a really good model in his regular paper with Mary like America in 2012, where they see field of 3d model to correct for that area, correct me if I'm
09:51:20 wrong. My impression is they did a 3d model to try to account for that effect mean for the, the inventory. Yes, yes. Yeah, just just set that up in terms of it having different motion components and then what you would actually get for the inflow rate.
09:51:38 There's also the deviation velocity can always be used if people want where you basically deviation velocity is how much the velocity deviates from a simple model of galactic rotation.
09:51:51 So that kind of gives you, you have a simple model galactic rotation in mind and then you immediately see where all the guests is relative to that so that can be a more intuitive type of velocity to us and that's why I think Bart Walker set that up at
09:52:04 some stage originally in his oldest review, and it's been useful. You do have to be careful in terms of what you use for that model of rotation for galaxy, but it can be a useful reference point.
09:52:17 Oh, great. Yeah, I like that idea. Thank you.