CFP Ciemat: Morning.
CFP Ciemat: Hello, everyone.
CFP Ciemat: So, we're… we have been very lucky to have another customer like us.
CFP Ciemat: Year and a half as a… Of course.
CFP Ciemat: as a working talented fellow, there's a number of the call right now,
CFP Ciemat: So she did her PhDs in, I think, in 2019. Actually, that year, she came to give a seminar, you know, here I realized the other day.
CFP Ciemat: So, yeah, even with that short career, she was already invited to share her results with us.
CFP Ciemat: And after that, she had an extremely,
CFP Ciemat: Productive career in, in several places, so, so, working in several, cosmo… several cosmological surveys, documentary survey in deeply in Desi.
CFP Ciemat: holding positions in, in CCAP at Ohio State University, the University of Edinburgh, talking about that we're here in the University of Buckham with, my equity fellowship, and finally with our, fellowship. So, as you see, we have
CFP Ciemat: A very extensive career, and
CFP Ciemat: Just a few years after PhD, and her speciality is in the combination, of, different… the different surveys.
CFP Ciemat: Thanks a lot for the introduction. So, yes, I'm going to talk about cosmology from the Commission of Galaxy cluster and with lensing, but also combining data from multiple surveys.
CFP Ciemat: First of all, I'm going to give some introduction about the cosmology and these probes, then I'm going to present very recent results from this combination from the Black Legacy Subway pool dataset.
CFP Ciemat: And then I'm going to talk about also recent results of this combination, but using data from multiple surveys, and this is a project from DERSI in particular.
CFP Ciemat: So, first of all, to give a bit of introduction.
CFP Ciemat: The standard cosmological model, and the CVM,
CFP Ciemat: consists of this composition, current composition of the universe, so we have that only… about only 4% is baryonic matter, and the rest is, unknown components, so we have about 27% of that matter that we know,
CFP Ciemat: is matter, but it doesn't interact with light, so we know it exists, but we don't know yet what it's made of. We denote the total matter energy density by this symbol, omega n, that will appear throughout the talk, so the total is about 51%.
CFP Ciemat: And then the best is, that guarantee that we know is responsible for the accelerating expansion of the universe, but also, we don't know… we don't completely comprehend the nature of these components, so about 95% of the universe today is unknown.
CFP Ciemat: mentioned that the energy is responsible for the accelerated expansion of the universe today, and according to the standard cosmological model, it's a cosmological constant, so it acts as a fluid with energy density that is constant with time.
CFP Ciemat: And with negative pressure, so this is denoted by this equation of the state for dark energy equal to minus 1, and it doesn't evolve with time, so in this…
CFP Ciemat: clock in which we can see the evolution of the different energy density component in the universe with time, so with density.
CFP Ciemat: With that cosmological constant, you just have that this is a horizontal line here, but current observations still allow some… some variation as you go farther away in time. So we are trying to have
CFP Ciemat: More precise measurements of the evolution of the potential speed with time, so that we can completely, well.
CFP Ciemat: Confirm whether it fits a cosmological constant, or whether it's some other component, or it has a different evolution.
CFP Ciemat: We also have that with the astronomical model, the Big Bang Model, the universe started, with a Big Bang, and then, followed an inflationary period with exponential acceleration.
CFP Ciemat: At some point, as the universe expanded, also the universe cooled down, and this allowed the photons to decouple from matter, and this gives us a picture
CFP Ciemat: of the early universe, so this is the government microwave background. It's a snapshot of the early universe when it was only
CFP Ciemat: 300… about 400,000 years old.
CFP Ciemat: And then the universe could be accelerated at some point. It cooled down enough so that some structures could be formed, and we have the first stars, the first galaxies, and we are here now with the galaxy service that
CFP Ciemat: map all the distribution of galaxies, observing the late universe.
CFP Ciemat: And so the role of all this technological analysis is to test LANCM by comparing this, there's some delay in the Wi-Fi thing.
CFP Ciemat: But, yes.
CFP Ciemat: Okay, you already know. So we are comparing… the work of these dimensions is to compare the latent observations and check if they are compatible with those from the early universe, and this gives us a powerful test of the landlassilian model through all the history of the universe.
CFP Ciemat: So, the axis surveys, the goal of this is to map this, distribution of large-scale structure that we observed today. This is an example, a recent map from the dark kinesi spectroscopic instrument, the first data released. You can see here this nice distribution of this survey. We would be here in these observations, and then
CFP Ciemat: This will correspond to Galaxy data.
CFP Ciemat: further away from us, so I'll hire that sieve.
CFP Ciemat: And so we can learn more from dark matter and dark energy by mapping this distribution of the larger scalar structure, since this gives us information about the growth of these structures through time.
CFP Ciemat: And particular, one of these probes is using the positions of galaxies, since they are tracers of this underlying matter distribution. So, we use two-point statistics to characterize the distribution of these… the positions of galaxies, and this is what we call galaxy clustering.
CFP Ciemat: One thing that we have to take into account here is that galaxies are a bias tracer of the underlying matter density field, and here you can see this visually with these two snapshots of the millennium simulations.
CFP Ciemat: Corresponding to the same vision of the simulation. The left would correspond to the dark matter distribution, and in the right, you can see the galaxy distribution. You can see visually that they… they are following the same underlying distribution, but they are slightly different. So this is something that
CFP Ciemat: We have to take into account in analyzing.
CFP Ciemat: And another powerful pro of these galaxy surface is with gravitational lensing.
CFP Ciemat: So, due to gravitational lensing, galaxies that are far away from us, the light that is coming from those galaxies is slightly distorted as it has to travel through all the distribution of other galaxies and matter in the universe, no?
CFP Ciemat: all these, here are gravitational potential wells from other galaxies that are, closer to us than those galaxies, which are also clustered. So, due to all this distribution of lattice curve structure, there is, some… with gravitational lensing effect that, the consequence
CFP Ciemat: the images from these sources or background galaxies are exactly sheer, so they are exactly disturbed. And this effect is correlated with all the distribution of large-scale structure between those galaxies and us, so we can extract information, so we can map this distribution
CFP Ciemat: or at a scale structure if we correlate all these shears of the solar galaxies. And this is what we do in this galaxy surveys.
CFP Ciemat: And… so we cover…
CFP Ciemat: As mentioned, we have galaxy clustering, so we correlate the positions of the galaxies to extract information from the underlying matter distribution, and this will correspond to this
CFP Ciemat: These red dots, like you can see here, these galaxies at the same time act as lenses for galaxies that are farther away, so they are the cause of this weak gravitational lensing effect.
CFP Ciemat: From these other yellow galaxies, from which we measure cosmic shear, also to extract information from all this distribution.
CFP Ciemat: And since both of them are tracing the same distribution of large-scale structure, they are correlated, and we can measure galaxy-alty lensing, which would be correlating the positions of these lens galaxies with the shapes of the source galaxies.
CFP Ciemat: So this is, these are the main props that we're using in this combined weaklensing and acid clustering analysis.
CFP Ciemat: And when using two-point correlation functions, as I mentioned for galaxy clustering, we usually combine these two to…
CFP Ciemat: In which we call a 2x2 point. It's just the combination of two-point functions.
CFP Ciemat: And then I will, when we usually call sequence to point the commission of everything, this is just in case it appears throughout the top.
CFP Ciemat: But the important thing here is that this, as… as I mentioned, the…
CFP Ciemat: Today is the underlying distribution of large-scale structures, so from this, we can extract information on the matter energy density, and indirectly on the dark energy density today. And then also sigma-I, which tells us about the amplitude of these growth fluctuations in the latter-scale structure.
CFP Ciemat: So, this type of, plus will appear slow at the top. Here, these are, the posterior distribution, so these are the preferred values of these parameters.
CFP Ciemat: Given the data, and, the inner contour will be the 68%, so 1 sigma, and the outer contour is, the two sigma contour, so 95%. And as you can see, they…
CFP Ciemat: Each combination of probes have different… slightly different directions, so what we do is to combine everything in this sequence two-point analysis to break the generosity between parameters and have more closely in power.
CFP Ciemat: There are also different types of grassy service, so we have,
CFP Ciemat: Mainly two times photometic and spectroscopy, maybe… Right.
CFP Ciemat: We've, run out here.
CFP Ciemat: So, photometric surveys, we use… we have a camera with broadband filters, which allows us to have pictures of millions of galaxies, and we need these statistics for… with gravitational lensing, because it's a very small effect, this shear distortion.
CFP Ciemat: And so this allows us to measure the gravitational lensing of galaxies, and this type of surveys are also needed to find the targets for spectroscopic surveys, which I'll cover next, but they have wash precision for direction of galaxies, because we have this proton field, so we cannot,
CFP Ciemat: It's more difficult to estimate exactly the red zone of these galaxies, so how far away they are.
CFP Ciemat: Then we have spectroscopic galaxies, such as BESI. With this, we can obtain the spectra for each individual galaxy, so we have very accurate measurement of their distance. And from Adam, this allows us to measure galaxy clustering with high precision and to make this beautiful map that you can see here.
CFP Ciemat: So, you might have heard about this service. This is how they are distributed. So, in photometric service, we have the RPH survey, in which our group has been in work since the beginning.
CFP Ciemat: And I'm going to talk more about this later today. Then we also have the kiloby survey, which I have, social support.
CFP Ciemat: Piper Supreme Count, and then, in the new generation of service, we have LSST and Euclid.
CFP Ciemat: Ubiquities also has a spectroscopic instrument, so it's in both categories, and then, currently, we also have DESI. So from this, in our group, we are involved in all these surveys, except HOC, and I am, actively involved in DES,
CFP Ciemat: Ukraine and Des. But I'm going to talk today mainly about Des and Desi.
CFP Ciemat: So, moving to the KG surveys, so I'm going to talk about recent results from just this January, from this combination of the acetastrian weekly, using, the full data set from this.
CFP Ciemat: So that's,
CFP Ciemat: had a 5170 megapixel camera mounted at the Blanco 4-meter telescope in Chile. That full survey consists of 6 years of observations that finished in 2019, but we're just now finishing met cosmological analysis of these observations. These analysis take really long.
CFP Ciemat: The white field of this survey covers 5,000 square degrees, which corresponds to this area that you can see here in the south, and it overlaps with other cosmological surveys, such as Eclipse, Castillia, and Barry with kids.
CFP Ciemat: And it has 5 optical bars, JRIs, Z, and Y, and compared to the previous analysis, you have 3 that cover 3 years of observations, this dataset is higher relative.
CFP Ciemat: with 50% higher source density, which is used for weak lensing, so we have more signal for this with gravitational lensing probe.
CFP Ciemat: There are different cosmological tools that have been used within this. So, to start the history of expansion, we have, we can use Taiwanese supernovae.
CFP Ciemat: variant acoustic oscillations, which is a nuclear scale imprinted in the matter distribution that comes from via the universe.
CFP Ciemat: Then, people have been doing follow-up of gravitational waves, and this allows us to get a measurement of the growth of expansion of the universe.
CFP Ciemat: And some people have also been working on a strong lensing.
CFP Ciemat: And then we have several probes that allows us to know the history of growth of the largest scale structure, and as I mentioned, we have large scale structure of galaxy clustering, with gravitational density, and galaxy cluster counts.
CFP Ciemat: And from this, the main probes are, supernovae EVAO, gases clustering, and cluster counts.
CFP Ciemat: And we are about to finish the full analysis of these main problems. So, the final supernova analysis already finished in 2024.
CFP Ciemat: The final VAO measurement also finished in 2024 and was combined with supernova last year. This is an analysis that was led by Tiamat, and Santi presented it last year in a seminar.
CFP Ciemat: Yup,
CFP Ciemat: Now, I'm going to talk about this combination, gases, and we're glancing from that full dataset that just, was released in January. This will be the focus.
CFP Ciemat: And we're just waiting for the final analysis of… from guys. The Cluster Council is expected this year. So, this year, we expect to have the… the combination of all these groups, which was the main probes for which this was designed at the beginning, so it will be very attractive, and…
CFP Ciemat: And as mentioned, this three times super nice is finished in January, there was
CFP Ciemat: a webinar in which the results were presented, and here you can check all the papers that were released. So there are more than 20 interconnected papers overall, but I'm going to talk about the main one, showing the Finance 2.0 resorts.
CFP Ciemat: And so, in this, I already mentioned a bit that we have some galaxies for which we measure galaxy class 3, and act as lenses for the source galaxies for which we measure cosmic shear.
CFP Ciemat: We split this galaxy sample in several redshift bins, so we do a tomographic analysis. So here we… we split in these red-shap shells, and we… here you can see the distribution of the number of galaxies in these tomographic bins as a function of redshift.
CFP Ciemat: So we have, for the source sample, for which we measured reclensing.
CFP Ciemat: We have about 140 million Galaxy 6, which,
CFP Ciemat: A huge number and an increase with respect to our previous analysis, and we are split into four tomorrow afternoon.
CFP Ciemat: And then for the lenses for which we measure galaxy clustering, we have this magnlin sample that has about 11 million galaxy positions, so this is a smaller number because we need a higher red circle in this case.
CFP Ciemat: And this is split in six domestic teams, and, this election, was optimized in a previous work myself in Dima.
CFP Ciemat: And just to get an idea about these measurements, so we extract two-point statistics from this galaxy position, so this is an example from Galaxy Cluster.
CFP Ciemat: So that you can see the dependency with cosmology. So, in our analysis, we remove the smallest case of this correlation, for which we have more modeling uncertainties.
CFP Ciemat: And then, these are the… the two main parameters that we can obtain information from. So we have the matter energy density, for which… for… here you can see how it affects our signal of galaxy clustering, depending on whether you have a higher matter energy density or a smaller one.
CFP Ciemat: And S8 is the clustering amplitude, so it's, as you can see here, it's basically related to the amplitude of our signal. So the higher S8 means the structure is more clustered, so we have more signal in the galaxy clustering measurements. And these two effects are
CFP Ciemat: slightly, tangential, so they are… that's why, yeah, they have… this is like a field, and this is basically the amplitude of the signal. So these are the main, parameters that we can constrain that I'm going to show you in the next plots.
CFP Ciemat: But this… the analysis overall is very complex, so we have to go from pictures observed in the telescope to these contours, as you can see here, and this is a summary of all the papers that were released in January. I'm not going to go through all these boxes.
CFP Ciemat: But you can see that this is why it takes several years to finish this analysis.
CFP Ciemat: And this is how the measurements look like. So these are the two-point… these two-point statistics for cosmic shear, so this is correlating the… the shapes of the… the sources.
CFP Ciemat: This is correlating the positions of these lens galaxies, and this is the cross correlation. And we removed one of the beams for the lens sample, because we have a systematic effect that we can detect, but we still don't know if that's…
CFP Ciemat: we have a bad feed to the data in previous VIN, and this is why we decided to discard it. But overall, we have a…
CFP Ciemat: An increase of the signal through noise with respect to the previous analysis, and so this is very promising.
CFP Ciemat: And as mentioned, so here the goal is to compare with the early universe observations so that we can test LAMA CBM. In the contours, essentially.
CFP Ciemat: 1 and 2 sigma contours, and this is actually already the result of these three times super analysis, compared with CMV observation. So here, in red, this is the…
CFP Ciemat: that prediction from the CMV observations from… from three combined CMV observations, so from
CFP Ciemat: three surveys, the Produce EMB plan, Act, and SPT. This is the…
CFP Ciemat: this resort for S8, assuming La Nasibia, the standard cosmological model, and this is our result from, from this year 6, combining elastic last 3 and with Larson. As you can see, they are compatible.
CFP Ciemat: Yeah, at the… yeah, at the two point something similar, I'm going to go a bit more into the details.
CFP Ciemat: And this is, again, now the same plot, but with more quantum, so now here, in blue, this is the CMV, so the early universe result.
CFP Ciemat: And in pink, this is our result from this year 6, compared with previous results from the previous analysis from this. So, you can see, overall, we are consistent with our own results, and the consistency with the CMV has been
CFP Ciemat: Moving around, over the years. So, in…
CFP Ciemat: In the previous analysis, we were at 1.5 sigma compared to… to plan.
CFP Ciemat: in our current analysis, if we compare with Planck, we have less tension, so we are more in agreement with the CMV… with Planck in this analysis, but when you combine all the data from different CMV surveys, also the contours are tighter.
CFP Ciemat: And that makes this, this difference to be larger. But we're still at the 1.8 sigma level, so it's consistent.
CFP Ciemat: with, CMV?
CFP Ciemat: Now, if we compare with other, Galaxy surveys, current Galaxy surveys, like Probe, weak lensing, and Galaxy Clustering, this is what we have. So, here again, blue and pink are the same results.
CFP Ciemat: In the… we have here also the result of the ZR6 cosmic share only. Of course, it's larger, because here we're not including galaxy clustering.
CFP Ciemat: And in the other two contours, this is comparing with other weightlensing results from other surveys, from Kids and HSC that I mentioned before. As you can see, we are also consistent with them, but with much lighter core screen, so this is just state-of-the-art for these probes.
CFP Ciemat: Now, we can also compare with other probes that I mentioned before. So here, this… here, this is a vertical vision that is… these are not results from this only when combining supernova and bionacoustic oscillations, which allows us to… to constrain the matter energy density.
CFP Ciemat: And… and when we combine this with also plaster comes from this, we obtain this orange contour that is much tighter, and… and again, it's about… is…
CFP Ciemat: In this case, the… the discrepancy with CMV is a bit higher, because this country is tighter, but it's at the level of 2.86. So, depending on… on…
CFP Ciemat: Depending on the people, yeah, some people find it already more intentional, less, but it's still consistent, and it's level.
CFP Ciemat: And now we can also explore all this work with LandoCDM. We can also, in this paper, we also look at the equation of states for dark energy, which is this W parameter. So here, this… a horizontal line would mean the cosmological constant.
CFP Ciemat: We allow for variations of this parameter to see if we are in agreement with the cosmological constant or not, and this is what we obtain if we combine everything, so all the approach from this.
CFP Ciemat: As you can see, we are, still consistent with the cosmological constant. So this is, bezel probes, without including clusters in this orange contour.
CFP Ciemat: It's consistent with this,
CFP Ciemat: dashed line, and also the CMB is also consistent. So, when considering this, just this one free parameter for dark energy, we don't see any preference, for extensions to Lamasia, but I have to say that there's still some, work in this to consider,
CFP Ciemat: said, well, other dark energy models, and the result will come out very soon, so considering,
CFP Ciemat: higher order terms of this, dark energy equation of state evolution, which show some more tension with the lambda CBM model, so it will be exciting.
CFP Ciemat: And this is now similar plot, but combining with external data. So now, here, the orange contour, which is much more tighter, is combining with all external data, so also with CMB data, also with vinylastic oscillations from DESI,
CFP Ciemat: And including, of course, all the supernova. From there, another cluster comes from external surveys. So this is the most constraining combination that we can find, and so we constrain with this the KS equation of state at the 2% level.
CFP Ciemat: And it's still consistent with a cosmological construct, in this case.
CFP Ciemat: So, as I mentioned, stay tuned for more complex organism models that will be released in a few months. They are wrapping up with some ideas.
CFP Ciemat: Now, I wanted to talk a bit more about the other project, from DESI. So, using combination of classic combining data from multiple servers as well.
CFP Ciemat: So, as I mentioned, there are two different types
CFP Ciemat: photometric and spectroscopic. Photometric ones are needed to measure with gravitational density, and spectroscopic ones allows us to measure the acid stream with the highest position, so the ideal thing to do would be to combine these two.
CFP Ciemat: So use the spectroscopic satellites for galaxy clustering, and then combine with big lensing data from other satellites.
CFP Ciemat: So, this is the… what we have done in DESI. So, DESI, the dark energy spectroscopic Instrument, is a stage four, five-year stethoscopic survey, but math has been extended to 8 years, using the Maya 4 meter telescope at Keith Peak National Observatory.
CFP Ciemat: So the basic survey started in May 2021, and it's finishing the first 5 years of observations, but as I mentioned, it has been now extended to 8 years.
CFP Ciemat: So the instrument has
CFP Ciemat: 5,000 robotically controlled optical fibers that allows us to paint the spectra of individual galaxies for 5,000 of them at the same time, which is amazing.
CFP Ciemat: So, in total, it's expected to catalog retics from over 60 million of galaxies in 8 years, covering a large area of the sky.
CFP Ciemat: So the focus of this project is, I mentioned to use,
CFP Ciemat: the optimal combination between DESI and other service. So, here you can see the overlap of DESI for the data release one, which are these… this gray dots. So here, darkest gray means more coverage, so it's reaching,
CFP Ciemat: Basically, all these telescopes scan the footprint several times, so darker day means that it's more complete in that part of the observation. And here, this observation areas not observed yet by this, because it's only the first year of observations.
CFP Ciemat: On these…
CFP Ciemat: gray areas are that they are observed, but not with full coverage. So, it's still the first year, so this will improve.
CFP Ciemat: with next data releases, I saw some overlap with this, weak glancing service that I mentioned before. So here, you can see in red, this is Kids 1000. So this is the previous,
CFP Ciemat: These are from Kids, not the latest one. Then we have here the best footprint that I showed before, so it only overlaps with this in the northern part of this, and then it has also some overlap with HSC, which is in the north.
CFP Ciemat: So, here, in this project, we are using now the VESI galaxies as lenses, so to measure galaxy clustering, and they act as lenses for the weak lensing galaxies from the other stars. So…
CFP Ciemat: You can see here, and we do this combined analysis for all the combinations of testing with the other side.
CFP Ciemat: And for this project, we are using the first data release from DESI, which is the first year of observations. This is a similar map to what I showed before, but now showing the different places, or all the galaxies observed by DESI are split in different galaxy samples.
CFP Ciemat: So here, this is a bright galaxy sample, then we have luminous red galaxies, emission lamp galaxies, and quizzes. This is, just,
CFP Ciemat: Well, each one of them has a different red sequence, so again, we are here, and this is going to higher red zone, also farther away from us, and basically you have these different galaxy samples that we can use to measure galaxy clustering. So in this data release that was, was released one year ago.
CFP Ciemat: Our 13 million casts were already released, and we are currently analyzing the first 3 years of observations.
CFP Ciemat: So in this project, we… for combination specific lensing, we are using these two galaxy samples, so this is… I go into a lower galaxy lens, let's say, from what… from all the information.
CFP Ciemat: And this is, that is the main result of one of the papers. This one was led by me, doing a three times-to-point analysis, so…
CFP Ciemat: This is similar to what I showed before, but in this case, we are using this year 3, so it's using the first 3 years of observations, because the full data set is not public yet.
CFP Ciemat: And it's a basic project. So here you can see, this is, in yellow, these are the analysis of this year's pre-cosmic shear, used for this analysis.
CFP Ciemat: And then, in blue, this is the combination of Desi DR1 galaxy clustering with Galaxy RC lensing, so dark correspondation with Desi R3.
CFP Ciemat: And then we combine everything in this real contour to obtain the tightest constraints, again, on these main parameters, which are the matter and energy density, and SA, which is the clustering output. So it's always these two main parameters.
CFP Ciemat: We have done this for all the survey combinations, so also with kids and HSC, and you can see here, these main results of the whole combination of galaxy blasting and with benzene, compared with every time CMD observations from plant.
CFP Ciemat: And, Lando Sevilla.
CFP Ciemat: And again, this is, consistent with the CMB, with a lower Placidian amplitude, but still consistent at the 1.522 sigma level.
CFP Ciemat: So this is consistent with,
CFP Ciemat: These are the analyses of,
CFP Ciemat: of data from other external datasets combined for the first time with the EDR1 data, and all of this… it's very interesting to see that all these surveys are consistent with each other, and also consistent with the CMB.
CFP Ciemat: And this was part of, let me say, epipheral, so besides this paper that I just showed that is using… is a type of observables most similar to what is used in this, so we use, I mentioned before that we split Tara as a sample into monochib pins.
CFP Ciemat: And in photometic service, we have to project,
CFP Ciemat: Through this thermomatic beam, so we lose the…
CFP Ciemat: we lose one of the dimensions, so it's an angular quantity, but it depends on the position of the sky. So it's a 2D,
CFP Ciemat: statistic, let's say. But there is another analysis that uses the full-feed information for the galaxy clustering part, taking advantage of the zero spectroscopic survey, and you can have
CFP Ciemat: more precision, so we can… so this gives us, higher constraints of amateur and residency, and then there is another paper
CFP Ciemat: that uses simulation method analysis, that doesn't include cosmic shares. This is also using projected statistics, but it doesn't include the cosmic shear observable.
CFP Ciemat: I'm just mentioning it because they appear here in these plots. The text is a bit small, but here in orange, this is the result from my analysis that I showed before.
CFP Ciemat: In colored is, the result from seminar therapy, but it uses the 3D information from DESI, and that's why it has hyper constraints on these parameters.
CFP Ciemat: And then there is the other analysis that has different, analysis choices. But the nice thing to see here is that, all of these analysis are highly consistent, even though they are using
CFP Ciemat: very different assumptions in the… both in which data to include, what paragraph was seen in the models, and other assumptions in how you… you carry out this initiative. So, this is very nice.
CFP Ciemat: Now, if we compare this with our analysis, we have here, for example, a comparison of the cosmic shield part. So, as I mentioned, one of the
CFP Ciemat: conclusions of this project is that we reanalyze the public cosmic CR data from this survey with our own pipeline, and we compare with previous results from these collaborations
CFP Ciemat: In this viewer,
CFP Ciemat: This point has a different symbol because it corresponds to another data set that is more recent, so that's why we are not… we don't expect an agreement with this data point, but for all the other cases, our work is recovering what was released before for this… by this collaboration.
CFP Ciemat: And then it's, again, a comparison of the constraints, now combining galaxy clustering with weak lensing, with other analysis in the literature. So here, there is also
CFP Ciemat: of this paper, led by Agnes and I are shown here in bold, and they are compared with previous analysis of the
CFP Ciemat: of these data sets, and they are, in general, consistent between them, which is also very nice to see. All of them are slightly lower than the CMB, that's why there is some talk about the essay tension going on in cosmology, but this is still at the level of between 1 and 3 sigma, so it's not
CFP Ciemat: And participatory on.
CFP Ciemat: Now, we are working, as I mentioned, in the analysis of the VR2 data, so the first 3 years of observations. So now here, you can see that this is darker gray, so the base observations are more complete, so it would be very nice to analyze this data. And there is a new weak lensing data set, which is decade, so this is using
CFP Ciemat: Also, that DCAM camera that this uses.
CFP Ciemat: But, including more observations from this camera, that's all…
CFP Ciemat: it's more of homogeneous than the less data, but it covers a larger area, and there has also been some cosmic share analysis of this data. So the main advantage here is that it has…
CFP Ciemat: a much bigger overlap with adversity data, which will allow us to have vital constraints, especially in this combination of Galaxy plus 10 equivalency.
CFP Ciemat: Galaxial silencing Revolution.
CFP Ciemat: So here,
CFP Ciemat: Yeah, so here you can see, again, similar to before, but with decades, we have about 5,000 square degrees, which is much higher overlap than before, and the lazy data is also more complete.
CFP Ciemat: looking ahead, so by the way, this is a project we are working on now with Ardon, so maybe at some point in the future, she will present some resources about this analysis.
CFP Ciemat: And looking ahead, we also want to combine this WD data with Euclid. So right now, I mean, here's a similar picture of the overlap. It's not great for, for…
CFP Ciemat: for the Euclid data release one, and Desi data release one, because Euclid started observing from the ports, and Desi started observing from here, so it will take some years to have more overlap, but Euclid is expected to cover almost… I mean, Euclid is a satellite
CFP Ciemat: in a space, so it will cover most of the observable area, so it will overlap with most of this. At some point, and this will be a very interesting project. So, looking ahead, we are interested in… in carrying out this combined analysis.
CFP Ciemat: And now, to conclude, I have presented legacy results from the 6 years of observations from a combination of weak glancing and galaxy clustering.
CFP Ciemat: And here we find, between 2 and 3 sigma lower values of the state, this clustering amplitude parameter, compared to, early time observations from the CMB.
CFP Ciemat: I think it's consistent with what was found in periodsis.
CFP Ciemat: This is also the first time we combined all four dark energy probes, proposed at the beginning of this. So we combined 3 times 2, BAO supernova, and clusters, and we obtained
CFP Ciemat: in this combination, a similar constraining power as CMV in our main constraint parameter, which is also really nice, because CMV has been, so far, the most constraining experiment alone for continuous parameters.
CFP Ciemat: And then in other UCBMs, when we are allowed to vary the identity equation of the state.
CFP Ciemat: This constraints, this parameter to 4%, are still consistent with the model, and if we combine with all available data, we can increase this constraint to 2%, and still we find no reference.
CFP Ciemat: But this is… there's someone doing work corresponding this to other population models.
CFP Ciemat: And second, the purpose of paying those modular constraints from the combination of multiple surveys, so kits, DES, and HSC weak lens and data, with this EVR1 galaxy clustering.
CFP Ciemat: And the main conclusions from this project is that we have reanalyzed state-of-the-art public reflencing data with a unified modeling pipeline, and we still find consistent results between surveys and within service provisional results, so it's a very robust consistent interest.
CFP Ciemat: of weaknesses. In this case, we still find lower values of the state compared to the CMB from plant, and still consistent with the analysis.
CFP Ciemat: So, thank you for your attention.
CFP Ciemat: I'm happy to pick any question.
CFP Ciemat: So, we're still for Adam.
CFP Ciemat: Okay, thank you for your nice clear thought.
CFP Ciemat: I was wondering, how robust all of this is. So you say it's very consistent everywhere, but you said there are 50 parameters, and only 6 are the parameters which are physical.
CFP Ciemat: measurements, or KLP use in this because there is another ratio.
CFP Ciemat: So, Gaia, I mean, Gaia catalogs are used to remove the stars from the galaxy sample, but they have not been used as a cosmological proof. There are other cosmological analyses that use quasars from Gaia.
CFP Ciemat: combined with other probes to obtain some constraints, but we have not explored this in this, or in this analyzed. And regarding the parameters.
CFP Ciemat: It's just that…
CFP Ciemat: I mean, having more astro systematic parameters, I would say that makes it more robust in a way, because you are considering all these sources of system… systematics. It makes the analysis more complex to run.
CFP Ciemat: But we have… this is why we removed this VIN, VIN tool that I mentioned before, because we had…
CFP Ciemat: So, for example, here, I don't go through this because it's more technical, but in the paper, we show,
CFP Ciemat: how the results vary when you consider different astrophysical systematics, different calibration systematics, and other data splits. And as you can see here, our main results are all consistent when you do all these different variations. So this is
CFP Ciemat: Considering, for example, more parameters for intrinsic alignment, which is one of the statistical systematics, this is related to directive calibration, which is one of the main systematics.
CFP Ciemat: And when you consider different ways to do this calibration, you still find something that is consistent.
CFP Ciemat: And one of the…
CFP Ciemat: The issues we had with this VIN that we removed from the analysis is that in one of the parameters, this is what we obtained, so this is the… the prior that we were assuming, given our calibration, but what the posterior distribution of this parameter was hitting the atoper prior.
CFP Ciemat: And was unresolved, and here's something that didn't change. If you consider different relative calibrations, we still had issues with this VIN.
CFP Ciemat: So we don't have our future data, and this disease was a red flag for us, so we decided
CFP Ciemat: in the end, to remove it. And this is something that we…
CFP Ciemat: We can have an idea why this VIN in particular is more problematic, which is, you know, second one, because it's related,
CFP Ciemat: So, this is why it's difficult to estimate red ships in photometic surveys. So, for example, these are the broadband filters used in this.
CFP Ciemat: And for some galaxies, the spectral distinction is very… is degenerative when you consider with these veins. Now, we would have to go to the infrared to be able to distinguish, to… to pinpoint the relationship of this galaxy.
CFP Ciemat: There's also, in this in particular, a bit of a gap between these two filters. As a consequence, we've…
CFP Ciemat: we saw that when using, when estimating the photometic reduction, there is a tail that matches with VIN2. So, we know that this VIN
CFP Ciemat: can have more particular… it's more difficult, in some sense, and we think that given the… just the increasing statistical precision that we have with the full data set, now this
CFP Ciemat: this, yeah, we need more accuracy also from the data set, so this is something that, we already saw some hints in the previous analysis, but it was not statistically significant, and now maybe more difficult to fit the data point. But in any case.
CFP Ciemat: Our main results don't change whether you include this VIN or not, so it's just…
CFP Ciemat: So, design is more… a lot… very robust, yeah.
CFP Ciemat: There was also a person. Yeah, Jose, no, Jose first, no.
CFP Ciemat: I mean, this is a nice question, but you showed the S8 parameter, which is connected, I think, to the 8 megaparsec scale. Are there any reasons to look at that particular scale, and what if that scale is more sensitive to modeling or sematics, and that's why you see a discrepancy?
CFP Ciemat: Yeah, I mean, there was also, was a pain point, because one…
CFP Ciemat: of the problems of assuming that the scale is… that is not only… it's in me a parsecs over age, so all the distances we consider in cosmology depend on this age parameter, which is related to the… the growth of expansion of the universe.
CFP Ciemat: So, depending on the audio rates, this skill can also change. So, some people, others.
CFP Ciemat: There was a proposal to use sigma-12 instead, so using both metal parts that don't depend on age, and there are some analysis that use those parameters. In particular, I didn't include the figures here, but in the
CFP Ciemat: in the other analysis from the DESI analysis.
CFP Ciemat: In this analysis, the constraints around this sigma 12 is the top sigma 8, and still, you can reconvert this to a state and you have this inconsistency. Basically, we have not…
CFP Ciemat: obtain constraints with this parameter in this, but still, you can see some discrepancies with the CMB, even if you remove this dependency, or you consider a different skates.
CFP Ciemat: And sometimes, it's also interesting that in the Bism, there's also shown DESE VR2,
CFP Ciemat: there's… I didn't include it here, because it's part of the different analysis, but the recent BAO measurements from DCDR2 start to be inconsistent with the CMV for omega and for the matter energy density.
CFP Ciemat: So…
CFP Ciemat: they are… the experiments are increasing so much in precision that we're starting to see, like, that they are blowing apart in some of the results, so it will be very interesting to see what we find in the future.
CFP Ciemat: Jennifer?
CFP Ciemat: Well, on the… when you compare the results with the blank results, are you using the same plant results? Because it looks to me that, at least the region… plant region changed, changed along the… all the processes. Yeah, so here, the…
CFP Ciemat: This is a broader control, because it's a… the analysis of plan data using the same priors used in the other… in the… in this analysis. In particular, in the planned release, they fixed the… some of the neutrino masses.
CFP Ciemat: So if you allow this parameter to vary, then the control looks like this. So it… when it's… when it looks like just a narrow where it leaves, it's because the sum of the masses is fixed, which is the pure… So they have got the same barriers, you don't need to go by… Exactly, to compare on the same terms.
CFP Ciemat: And then the other things that, I mean,
CFP Ciemat: you were talking about the system analytics. For example, the hero, the other approach, when talking about SSAM, so what's the leading, system analytics that you can get? And you were saying, more or less.
CFP Ciemat: this before, but mentioning several of these syntax, but what's the latency setup? Yeah, so…
CFP Ciemat: As you can see, I'll go back to…
CFP Ciemat: So… Depending on how you look at it, so one of the…
CFP Ciemat: main systematics in terms, if you don't get this right, you get bias constraints, are the… the photomatic redshifts, and the… the bias when you stimulate the cosmic shear. But this… this is why this analysis takes so long, because we spend a lot of time trying to… to calibrate this very well.
CFP Ciemat: And the result is that if you assume different assumptions in this calibration, we still find the same results. So our…
CFP Ciemat: In that sense, what is limiting us the most is that we are removing a lot of data points that I mentioned before. We remove all the smaller scales because they are more difficult to model, and we have more uncertainties in the modeling part there. So if we…
CFP Ciemat: could include those cases, this… these constraints would be much narrower. So in that sense, the limiting systematic are… the modeling in this much case, which, for cosmic shear, is impacted significantly by the bionic feedback effects.
CFP Ciemat: that make a suppression of the multiple spectrum, and we still don't know. There are different models of poetic feedback from different hydrodynamical simulations, and we still don't know which is the right one. So it's one of the…
CFP Ciemat: More postcards?
CFP Ciemat: Thank you.
CFP Ciemat: Yes, I have one that may be sort of a concluding kind of question. So, when you go to the different conferences and the meetings.
CFP Ciemat: what is the overall sentiment, or even your own opinion, about the Sigma A tension? Is that something that people feel is going away, or is that something that's
CFP Ciemat: I mean, future analysis is going to look into it, but, is there still excitement or questions about it?
CFP Ciemat: So… Because it is consistently always below, so it's not like it's around… Yes.
CFP Ciemat: I wanted to show the comparison with other frequency data here. So here.
CFP Ciemat: last year, there was a release of this result, this last cosmic CR measurement from Kids, Kids Legacy, and surprisingly, they… I mean, their previous results were around here, and surprisingly, they moved towards the CMB quite a lot, so now they are fully consistent.
CFP Ciemat: with a CMV, one sigma or less. So after that analysis, everyone was saying that I say tension is dead, and everything will agree more. And now that…
CFP Ciemat: But as you can see, our results are still consistent with what we had before, so it is still at 2 sigma or so. So I think now, after these results.
CFP Ciemat: Like, that feeling in the community is going back to… we are in the same position as before.
CFP Ciemat: At least, but depending on the person, on who you ask, they will say that it's consistent because it's two sigma, or they will say there is an extension. But at some point, you say 3 sigma, what is this three sigma? It's when you combine with all the best probes, from here.
CFP Ciemat: Okay. So we combine with supernova… the supernova SVAO and gusters.
CFP Ciemat: Is someone at home who wants to make a question, can't you talk?
CFP Ciemat: I don't… the PAL Supernova Trusted, is one of them driving… is one of them much lower than the others, per se? Or,
CFP Ciemat: Not parti… it's not that… no, it's just that I think it's a tighter constraint, as you can see here. I mean, all of them are consistent, but if you stay at the same spot with tighter constraints, it just increases, usually.
CFP Ciemat: No course counts?
CFP Ciemat: So, sorry, just to comment on this, how it was on the other analysis, with the C, what was the type of tension? So in the DBAO, it was with only…
CFP Ciemat: It was 1.5 and 2, but it's only…
CFP Ciemat: 3 times 2 points, so it's consistent.
CFP Ciemat: So here, we obtained…
CFP Ciemat: And that one is comparing with plan, so if we compare with the same CMV data, it's 1 sigma with SDR6 3 times 2, and 1.5 with the SDR3 across the ZDR1.
CFP Ciemat: Lastly, it's… consistent.
CFP Ciemat: I want both to make another comments, questions, okay? As it can be measured somehow totally different, or not? Because clustering in galaxies…
CFP Ciemat: Is there a way to market this way of plastering about his path, or there is no other way?
CFP Ciemat: You can see… well, you can see here that with other probes, I mean, with super non-BAO, you only measure omega-M, but there are also… you can obtain with cluster counts.
CFP Ciemat: Here, they are combined with CDAMS2, but they also, by their own, they also give results on a site, and you can obtain the prediction for a state from CMB,
CFP Ciemat: So these are… so basically, yeah, this is information about the growth of a structure, so you need to have some proposo.
CFP Ciemat: That gives us some information about the distribution of large-scale structure, to have information on NSA.
CFP Ciemat: Questions?
CFP Ciemat: Okay, Nick, thanks again.
CFP Ciemat: We'll see you next week, in the next session.
Jorge Carretero (PIC): Thank you. Bye-bye.
CFP Ciemat: I, by the…