Baofei Li: Good morning everyone. Today our speaker is branches cooked and he'll give us talk on elevating patients in the CMT using LC LC LC let's welcome him.
Brajesh Gupt: Hi. Oh, so today I'm going to talk about a word that appeared on archive. Two weeks ago, it was done with a pay a sticker dong region and we're not showing up with a chemistry, not
Brajesh Gupt: So the title of the talk is elevating tensions in the sea and be using to quantum cosmology. So as we know that the standard cosmology, which is, which consists of six parameter lambda Cydia model.
Brajesh Gupt: You know succeeds extremely well in explaining, most of the features that we see in the CME. However, there are certain, you know, small anomalies low significance anomalies that have been observed over the past you know 1020 years and
Brajesh Gupt: And interestingly, as I will explain in the talk that they show up at a scale which which is actually which can be affected.
Brajesh Gupt: By the new quantum quantum cosmology dynamics in the very early very early universe. So in a nutshell, what, what I would like to talk to you about today is that are the loop quantum gravity effects imprinted on the
lsmolin: Excuse me, you know, advancing the slides with sure
Brajesh Gupt: Yeah, and I will let one slip, just in a second. Yeah.
Brajesh Gupt: Okay, yeah. So in this talk. Every I'll be
Brajesh Gupt: In a nutshell, explaining how Luke quantum gravity effects that you know originate in the high plank regime can still survive. And, you know, connect with observations and you know give useful insights
Brajesh Gupt: In CMT. Okay. So on slide to now. So the universe. According to plunk that is basically the six parameter lambda CDN model consists of first
Brajesh Gupt: A primordial power spectrum which is basically the two point function in for a space of the scale or perturbations that arise in the variable universe.
Brajesh Gupt: And these power spectrum this promoter spectrum can come from, you know, mechanisms like inflation or any other variable universe we can we can assume that might have. But in this talk will will
Brajesh Gupt: Will consider inflation as as a source of these, you know, primitive power spectrum. So in the standard Lando city and model, the standard answer for this power spectrum is taken to be a nearly scale brilliant innovative hospital as shown in here.
Brajesh Gupt: Which is characterized by two parameters as that is the amplitude of the power spectrum and NS that correspond to the slope of the spectrum, or it's also called the spectral index. So as an NS these two parameters correspond to the primordial physics characterizing the spectrum.
Brajesh Gupt: Then at the onset of, you know, radiation after the onset of radiation era.
Brajesh Gupt: The astrophysics.
Brajesh Gupt: Of various you know ingredients of the Universe come come into picture and later at
Brajesh Gupt: At a later stage CMT is formed. So between radiation at the onset of radiation era, the matter density and the cool modern cold dark matter density start becoming important
Brajesh Gupt: And they drive how these scale or perturbations, which was named in the in the primordial era, they lead to the formation of CMT
Brajesh Gupt: After the formation of CNE these two parameters that Tita MC so Tita basically is a characteristic scale.
Brajesh Gupt: angler scale of the barbarian acoustic isolation seen in the CMT and Tao is the regeneration optical depth. So in this way, the six parameter models they easily can be classified into a primordial
Brajesh Gupt: Parameters SNS you know after primordial before C NB a parameters medicine density in and cold dark matter and the late policy MV physics. I know. Also, you know, go and buy T DMC and Tao.
Brajesh Gupt: So, so this is a theoretical lambda CPM model. So, so to say, given some values of these parameters, one can, you know, Lando city model predicts certain observers, for example given six parameter model and using these bowling balls many equations to evolve and
Brajesh Gupt: Evolve the parameter power spectrum wanted today using most most widely used, you know, software called can one sees
Brajesh Gupt: For different observers, a way the the model predicts for different observers is all these show up in terms of, you know, see TT CE. CE C D and sci fi so
Brajesh Gupt: So T corresponds to temperature. He for the emote polarization and five for the Lansing. So basically these observers are, you know,
Brajesh Gupt: The power spectrum of temperature fluctuations and emotional range fluctuations and the lensing aptitude in the CMT and they are expanded in in the aerospace in alignment multiple space.
Brajesh Gupt: So after you know
Brajesh Gupt: Getting them some prediction from the lambda Cydia model what one can do is
Brajesh Gupt: Compare the these observable reality by lambda Cydia model with what have what is observed by, you know, experiments like plank and so on so forth.
Brajesh Gupt: And then one finds a best fit value of these parameters as NS omega omega city Toronto and that is the lambda CPM model selected by the observations. So this is
Brajesh Gupt: How you know the parameter estimation is done and the lambda city model is fixed by using observations.
Brajesh Gupt: And as is well known that all major features of the absorb power spectra are quite well explained by the lambda Cydia model. As you can see in these two plots on the left, I show the CL TT plot the temperature spectrum.
Brajesh Gupt: That the best fit lambda save your model sits very much on top of the you know the observed data points for the by the by, like mission, the latest plan 20 2018. However, there are some small differences at less than 30 but we'll come to that.
Brajesh Gupt: Similarly, for the event correlation spectrum, we can see there is a great agreement between the six parameter lambda city a model and plunk observation.
Brajesh Gupt: This model further predicts you know lensing attitude that has to do with the week lensing for CMT and the beam or polarization spectrum which
Brajesh Gupt: Is expected, which can be independently tested using using feature observations. I mean, the observations, until now, they're not precise enough to
Brajesh Gupt: Measure be more relation spectrum and hopefully in coming, if I'm not wrong five to 10 years we should have good enough measurements of, you know, be more spectrum to gain some further insight into lambda CT model.
Brajesh Gupt: So while there is a great agreement for, for the most part.
Western: And then he has a small comments and
Western: Just in the Indian one is a logarithmic scale. What is Lena scale. So it's just a rhetorical or there is a point here because you're expanding the region in one the interest in region one and not the other.
Brajesh Gupt: Yeah, actually. So yeah, in principle, I should have also, you know, so on the left for the temperature, the level of scale is only between
Brajesh Gupt: Two to 40 and after that is linear. So that is to i that is usually done to show these differences between, you know, the experiment and theory at at low multiple
Western: At the same will be having you would get some
Yeah.
Brajesh Gupt: Yeah, I mean, you would get what is just that, then one would also have to do a lot with new skill on y axis, which I could have done. But the point I wanted to make from these thoughts is
Brajesh Gupt: Not what the differences. But, you know, the agreement for the larger range of hell. Okay. But, but you're right that can be done and you if you did that, you would see that there's a small differences in immolation in the similar skills as well.
Brajesh Gupt: Okay, I think you can do we can do to the anomaly. Okay, thank you.
Brajesh Gupt: So as I was saying, while there is a, you know, great agreement between theory and observation, for the most part, there are certain features or low significant significant anomalies that have been observed in past 10 to 20 years. So these anomalies surroundings are basically
Brajesh Gupt: Slight disagreement between theory and data.
Brajesh Gupt: They are independent independent from each other. They are low significant, but when one considers them together, they become significant for example.
Brajesh Gupt: I'll be focusing on two particular anomalies here. The first I'll be talking about is the last scale power anomaly and this is this can be slightly seen in
Brajesh Gupt: The on the slide in the previous on the previous slide on the temperature spectrum that for less than 30 there are not so good agreement between, you know, observation and theory.
Brajesh Gupt: But a better measurement or better better measure of this anomaly is in terms of the Anglo coalition functions which can be obtained from the CSM essentially. So here
Brajesh Gupt: When the black dot points are the observational data points and the red one is the, you know, standard Lando city and model. So at the large angliss game for example from four angles bigger than 60
Brajesh Gupt: black dots are almost hugging the zero line, while the red curve is away from the away from zero. So, this is what is called the lack of power or, you know, large scale power anomaly.
Brajesh Gupt: In the CMT and so to further quantify that what one can do is integrate the power at at large angles by computing this quantity here as half
Brajesh Gupt: So this is just integrated between minus one, minus one and one half of the absolute value of sci fi task were so when sees that the value of us have directed by lambda CPM model, the best fit land or CPM model is quite different from what plank measures.
Brajesh Gupt: The second normally I'll be talking about today is the lensing aptitude. So the Lansing aptitude Al is is a scaling parameter that is using the land as a model and in the standard land as a model in the theory.
Brajesh Gupt: L is taken to be one. So, so any best fit lambda city a model should agree more or less with with Al equal to one.
Brajesh Gupt: But as you can see in this contour plot between
Brajesh Gupt: Al and Tao, the inner one sigma contour, which is the target here is outside air equal to one or either way as equal to one line this horizontal line.
Brajesh Gupt: Is not within one sigma of the best fit Lando city a model. So this is again an anomaly. I mean it is within two sigma, but not in one sigma. So, this is again as low significant low significance anomaly.
Brajesh Gupt: First, so this. Yeah.
lsmolin: Yeah. What are the sigma. The first anomaly. The low power Atlanta jangled
Brajesh Gupt: That's approximately 2.8 so around three sigma
lsmolin: So nobody will blame us to know this.
Brajesh Gupt: But I can hear. Can you say again.
lsmolin: Nobody would blame a cosmologists for annoying or one sigma sigma
Brajesh Gupt: Yeah. But the thing is, that's the point I was trying to make that independently just standing alone one sigma anomaly or physical anomaly.
Brajesh Gupt: They may not be important. But when taken together, let's say you had a model that could explain more than one anomalies, then that would be something that will be taken seriously. So independently. They are not so significant. But when taken together, they become significant and
Baofei Li: Let me add that, that the power suppression at larger scale fisheries, you said almost every sickness.
Baofei Li: And and people consider that really seriously, even the plank collaboration themselves, right, that quite quite seriously. So for the lens. You know, normally, as you said this. The significance is less, but for the hour suppression people do take that seriously.
Thank you.
Yeah.
Brajesh Gupt: So,
Penn State: Can also comment on one thing. Yeah, so the basically is a point that you in fact one is St. Mary's his papers that
Penn State: what one does is given a theoretical model one looks at realizations and if in fact 1000 realization
Penn State: If you find jobs have observed values in 1000 realizations. People don't worry. So this is what is between two and three sigma basic
Penn State: But if, in fact, our to such anomalies than one is looking at that I already knew wasn't really realized only in one in a million or so realizations and then people start worrying and just amplifying on what
Penn State: You're saying, and also wanted to just make a small comment on what Carlos saying about the previous transparency.
Penn State: Point of the Aero bars, and this is something that we explained to us. And then I also confirm with the people that the aero bars in the law else
Penn State: They are of course they are, you know, cosmic variances everywhere. And also there was one upon square root of 12 plus one.
Penn State: But there's a numerator and the numerator is really the mean amplitude and because I mean amplitude is so small, for the electric polarization. As you can see that you're going from
Penn State: Sort of, it's almost I don't know one or two or something, one less than one, whereas for the temperature, temperature is around 1000 right
Penn State: And therefore those Airbus also sort of reduced just because of the numerator. So I just wanted to make mention that because that might be important later I get
Penn State: A question about this is such a
Penn State: High
Penn State: The measurement of CF data and a of Al, are they completely independent in our statistical science.
Penn State: Or do you expect for instance a Lansing to depend on the observed large scale.
You know, power, no power distribution it
Penn State: So I just wanted to make sure the two are completely human
Brajesh Gupt: Power suppression.
Brajesh Gupt: Feature of an anomaly is independent from
Brajesh Gupt: From the features we are seeing it.
Brajesh Gupt: So yeah, they are independent. Yeah.
Penn State: So the temperature, temperature, I mean dungarees here so you can correct this temperature. Temperature is one one measurement and the lensing is another measurement and so that no one needs all those majors.
Penn State: Down we explained that latency predominantly changes to the small scale part spectrum, so to say, large values and not not small.
Brajesh Gupt: Okay. Should I go ahead
Brajesh Gupt: Okay, I'll, I'll continue. So, so the fact that al equal to one doesn't lie in one sigma contour in this able to plot led to a recent recent submission by the Valentino men chair. Oh, and silk.
Brajesh Gupt: To say that there is a possible crisis and cosmology. So the possible crises that they
Brajesh Gupt: Said was goes as follows. So they considered a close modern universe like universe with space or spatial curvature and they found they found that introducing spatial curvature alleviates the problem of, you know, you know, Al equal to one, lying outside the one signal control, however.
Brajesh Gupt: To do that, what they had to introduce large spatial curvature, which then, you know, led to disagreement between theory and observation at at at small angliss kids. So, so this is what they say the possible crisis that on one hand, we are trying to fix a problem which
Brajesh Gupt: fixes the problem, but then creates another problem, but
Brajesh Gupt: But they would, they were trying to do this by introducing spatial curvature and as I will explain later in this in the talk that the introduction of spatial coverage. It is not really needed and this crisis is actually not there.
Brajesh Gupt: So,
Brajesh Gupt: We have to the next slide. So I mean, needless to say that these anomalies are interesting, but let's just review why they are interesting. So, as explained that statistical significance of these individually and all these are low.
Brajesh Gupt: However, when they consider together, they can become quite significant and imply that we live in a very specific and highly likely not highly likely highly unlikely realization of the university provide the model.
Brajesh Gupt: So here I will just taking a snapshot of the recent one of the paragraphs in the recent plonk paper, the
Brajesh Gupt: The highlighted part says that if any of the anomalies have a primordial origin, then they are large scale nature would suggest an explanation rooted in the fundamental physics.
Brajesh Gupt: This. Thus, it is worth exploring any model that might explain anomaly, or even, you know, even better multiple anomalies naturally or with very few parameters so. So this talk is essentially
Brajesh Gupt: Giving a concrete realization of this highlighted area and this this paragraph.
Brajesh Gupt: And furthermore, they say that given a theoretical prediction new probes of independent modes on similar scales would increase the significance of these anomalies. So as you'll see that in addition to, you know, resolving these two anomalies. We can make certain predictions.
Brajesh Gupt: For cosmological parameters that can be you know
Brajesh Gupt: Tested by future observations. So in this way, these anomalies provide an opportunity for quantum gravity to connect with observations and particularly in El que si will see that
Brajesh Gupt: The standard answers for the parameter passport given by these parameters as an S This is modified in such a way
Brajesh Gupt: That there is actually power suppression for low values of k that is corresponding to large Angular scales, which is where these anomalies exist and this will result in alleviating on you that you anomalies.
Okay, so
Brajesh Gupt: So in this talk. Basically, I'll be using a flat FL RW model with an inflationary potential 940 years and establish the potential is what will show the plots plots for but the results also go through quite well for for the quadratic potential, potential
Brajesh Gupt: So the main ingredients will be the pre inflationary dynamics of El que si background dynamics, which were the singularity is resolved and there is a bounce.
Brajesh Gupt: On which now we have quantum perturbations evolving, which give rise to the parameter for spectrum.
Brajesh Gupt: And will choose suitable initial conditions for both the wagons geometry and perturbations, which will then at the end will find
Brajesh Gupt: That the accuracy predictions provide better fit to the observational data as compared to the standard you know answers for the power spectrum. And there are testable predictions for the future observations. So
Brajesh Gupt: That's so before I go on any questions.
Brajesh Gupt: Okay, good. So I'm not, I will not go too much into detail of a new quantum cosmology, as this audience is quite familiar, but I'll just give a you know a lightning review.
Brajesh Gupt: So, so in Lucknow cosmology of
Brajesh Gupt: The Big Bang singularity is the salt and you know the it is replaced by non singular quantum bounds and given an inflationary potential, one can actually evolve the universe, starting from cosmic microwave background all the way until pounds and this program.
Brajesh Gupt: Of, you know,
Brajesh Gupt: Know, completing the evolution all will have to bounce has been, you know, carried out in a lot of detail for the past 1015 years
Brajesh Gupt: And then using the dressed metric approach that was also developed, one can study how quantum perturbations.
Brajesh Gupt: Contrast with quantum fields can evolve on this background quantum geometry and give rise to, you know, accuracy power spectrum.
Brajesh Gupt: And as usual, we will work with sharply peaked you know states for the background geometry for which as discuss recently by the paper by Kaminski Karnofsky unleavened ASCII the dogmatic approach is free of on the infrared complications.
Okay.
Brajesh Gupt: So let's complete initial conditions. So,
Brajesh Gupt: If it there is tremendous freedom in the choice of initial conditions, both for the, you know, background geometry and perturbations.
Brajesh Gupt: So we proposed.
Brajesh Gupt: In a paper.
Brajesh Gupt: With a bay and we proposed, you know, a prescription to fix these freedom and choose appropriate initial condition for the background geometry and perturbations.
Brajesh Gupt: So for the background geometry we fix the initial conditions using elements from observations and quantum geometry and for details of these I
Brajesh Gupt: Refer to you an LPG talk that I gave on August 30 2016 or just look at this paper. So essentially the idea is that
Brajesh Gupt: After fixing the background geometry, one gets approximately hundred and 41 he folds from bounds, all the way up to today.
Brajesh Gupt: And the good thing about this initial condition is that this is it is independent of any choice of the potential in between. So, and
Brajesh Gupt: So if one chooses a popular potential it very nicely works out the internet dynamic so that the you know the number of he falls from the bounds until today. You mean you do the same.
Brajesh Gupt: For the permissions. On the other hand, we, we fix Heisenberg state for quantum perturbations using Planck scale dynamic of a QC and a variation of quantum ventilation of vendors as well. Coverage about this, which is
Brajesh Gupt: Which is like a maximum allowed quantum homogenize it and I thought to be conditions for the corner perturbations.
Brajesh Gupt: So let me take a pause here and say it depends Pendleton's while corrosion hypotheses says that in the very early universe singularity is quite simple in the sense that wild Ritchie, Ritchie, Ritchie scale blows up the wild condition is zero.
Brajesh Gupt: And the big pack.
Brajesh Gupt: But in a quantum in a quantum theory, the wild card which cannot banish because the electric electric and magnetic part of the wild tensor, they are connected to each other.
Brajesh Gupt: So the simplest generalization of that idea that we came up with was to consider.
Brajesh Gupt: You know, consider states for which the expectation values of electric and magnetic part of the wild tensor zero and the uncertainties in electric and magnetic parts.
Brajesh Gupt: Of the world cancer are minimized an equal to each other and by so we call it you know principle of quantum homogeneity. And I start up. So, this
Brajesh Gupt: Fixes unique state for the perturbations, which in turn will give you know it is to, you know, greater power spectrum and so on so forth.
Western: Was already the 2017 paper.
Brajesh Gupt: Yes, so this is also just summarizing the 2017 paper. Yes.
Brajesh Gupt: Okay, so if you use if you fix the background geometry.
Brajesh Gupt: So this is again review these two plots were also discuss in the 2017 paper.
Brajesh Gupt: So on the left here I show the evolution of number of, you know, he forced from bounds given by envy.
Brajesh Gupt: And the inset shows how the, you know, number of he falls, you know,
Brajesh Gupt: Basically very impressed upon so nobody forced essentially is, you know, log of the scale factor. Yeah.
Brajesh Gupt: So as we can see, like,
Brajesh Gupt: This plot corresponds to, you know, Stravinsky potential from the bounce until T star. So, to start is the time when the characteristic mode, you know, accessorize are basically the onset of inflation. So there are approximately 16 if holdings.
Brajesh Gupt: And during this evolution. As you can see the rule, the energy density of the background scale of field remains finite at the bounces maximum and then decreases and
Brajesh Gupt: Only between zero like a until the in 10 seconds the energy density falls below 10 minus three. So language him, you know, last only for approximately 10 seconds and that is enough to, you know, leave observable imprint which can, you know, show up in the CMT
Brajesh Gupt: So just a little bit of review. Why, how
Brajesh Gupt: These UV you know corrections to quantum geometry lead to, you know,
Brajesh Gupt: imprints on the large scale.
Brajesh Gupt: Alaska spectrum. So in general relativity. If we compare the scenario between generativity in Locarno cosmology in GR the Richie Rich and blows up at the at the Big Bang. So
Brajesh Gupt: The if we have all the radius of curvature, which is which goes as square root of one hour, which is killer. It goes to zero at at Singularity okay and
Brajesh Gupt: And if we just drag the evolution of, you know, most of perturbations. They always are smaller than the radius of curvature. So, so the radius of curvature or, you know, the, the, the curvature never excites them is because they are the most remain ultraviolet, all the way up to singularity.
Brajesh Gupt: While they look on the cosmology, since he can, which has an upper maximum the Radius. Radius of curvature has minimum at the bounce. So because of that,
Brajesh Gupt: There are some modes which interact with the radius of curvature and these modes are actually the Long Island modes. So in this way, you know, the Planck scale dynamics of LTC affects the long wavelength modes and it, it leaves the short will end modes, just as they are so
Brajesh Gupt: When, when these modes arrive at the onset of inflation. The short wavelength modes which correspond to, you know, large
Brajesh Gupt: You know,
Brajesh Gupt: Not wave number or large volume of multiples they remain in punch TV state, but the more in five months or longer life moves. They are excited they are not in one inch TV state. And that's how
Brajesh Gupt: So this cartoon essentially explains how you know the the LPs evolution keeps the memory of quantum gravity era.
Brajesh Gupt: In the spectrum of the quarter perturbations.
Brajesh Gupt: Okay, so before I go to discussion of the predictions observations. If there are any questions, I'm happy to answer them.
Brajesh Gupt: Okay. All right. So, so after fixing the initial conditions and considering the LTC dynamics. Now we can compute what the LTC power spectrum looks like at the end of inflation.
Brajesh Gupt: We see what you find that as opposed to the standard answers, which is just going to type by the amplitude all the past from as and NS
Brajesh Gupt: The accuracy spectrum is modified
Brajesh Gupt: As a shown in this figure here.
Brajesh Gupt: So the blue line shows the hospital for style Minsky potential that one shows for quadratic potential. And as you can see for large key.
Brajesh Gupt: Which are the modes which remain, you know, smaller than the radius curvature, all the way up to pounds. The LTC connections are negligible. But for small k wavelengths
Brajesh Gupt: Small K modes, the NPC corrections become important. And so this can be characterized by this function f k here. So this one can select LTC correction function here. So for landscapes one small
Brajesh Gupt: It's smaller than one
Penn State: Is that a question. Yeah. I was wondering why there is a turnover for very small values of k. That means very largest
Penn State: Can you say yeah
Penn State: Yeah, the physical effect.
Brajesh Gupt: Yeah, I mean, so I mean if you if you consider even
Brajesh Gupt: You know, longer, we will have modes for smaller than 10 minus five, there are still oscillations and the you know the power increases. So, I mean, this is something we are still considering we are looking at. But at the moment, I
Brajesh Gupt: I don't know if there is a physical explanation why there is
Brajesh Gupt: No such a feature. It's okay. Let me say one thing. So, this this plot determine shown, this is after beginning, you know, the power spectrum for individual case. So the actual power spectrum for all the case looks very much oscillators.
Brajesh Gupt: So this is after this is the average power spectrum. Okay.
Penn State: Yep, having just a side by side you Mike. There is a as you can see that there's a vertical line that vertical line is the one which is
Penn State: The maximum, they will enter the minimum key that can be observed. Just because finiteness of the the horizon and the puzzle.
Penn State: So what these effects that you're referring to, which is what we are trying to understand are really
Penn State: Really big ones that are not observed that part of the background in some ways outside. They're not directly observed that will be, but they can have
Penn State: Effect on because of non kosher on it is because these most could interact with the observable mode. And this is something that we're doing. And the point is that there are several factors which affect the dynamics and what we don't understand is
Penn State: One by step by step which factor is more dominant which back this last song. That's what we're thinking about
Brajesh Gupt: Thank you.
Brajesh Gupt: Yeah so. So the message from this slide is that there is a power suppression in LTC at small k and there was some recent recent work by ungerman Copeland and local with suggest and
Brajesh Gupt: They looked at power spectrum with an article approximation and then results show is is that these results will hold true for a larger class of immigration potentials, so, so, so the power suppression.
Brajesh Gupt: Is thinking a Robust. Robust phenomena and the change of potential
Western: Mission and you gave a very good, good. So the physical idea of why FK has this fall, but I can you just say give me a hint of how you actually computed from the previous assumptions and mobile
Brajesh Gupt: Yeah. So basically when when when takes this initial condition for perturbations.
Brajesh Gupt: Like a using the pen was advised by, you know, using the maximum home it and so for P condition and then evolve the spectrum, you know,
Brajesh Gupt: Numerically from bounds, all the way up to the end of inflation and
Brajesh Gupt: So,
Brajesh Gupt: Yeah, so you just do numerical evolution from this
Western: Is a function of k and
Yes.
Brajesh Gupt: You do it.
Brajesh Gupt: You do keep it.
Brajesh Gupt: So,
Brajesh Gupt: When for your space and for each key you compute an avoider. Thank you. I mean, this is not a continuous spectrum. I'm just showed it to just to guide the I
Yeah. OK. OK.
Brajesh Gupt: OK, so
Brajesh Gupt: If one considers this suppress power spectrum of NPC and then further evolves how what uses Boltzmann codes and this will build software to compute what the physical absorbers look like so.
Brajesh Gupt: This is a plot that shows what the comparison between accuracy standard answers and the observed data. So the blue line, as you can see in the low energy
Brajesh Gupt: It's suppressed as compared to the standard answers. And when you do a more quantitative analysis. You see, one finds that the QC Apollo spectrum indeed fits better with the data as compared to other standard answers and that is at the cost of no additional parameter
Brajesh Gupt: And the good thing is also that you know at large else which come from these large game modes be stoned. Don't get affected by blank screen dynamics, the power spectrum agrees quite well with the standard answers and also with the plant data.
Okay.
Brajesh Gupt: So already, here we can see, you know,
Brajesh Gupt: An employee. This suggests that
Brajesh Gupt: This large scale power anomaly can actually be solved using el que si spectrum. So the next slide.
Brajesh Gupt: As CT de which is the angular correlation of templates in every part representative perspective, this can be obtained from CL, actually. But see, if it provides better measure know visual and also quantitative measurement of how would the power normally possibly anomaly looks like.
Brajesh Gupt: So here again we see three plots for the blue one is accuracy prediction for see theta, the dashed red is for central and sides and these are bad thoughts are the
Brajesh Gupt: Blank observational data. And you can see that the LTC plot a curve is closer to the observations as compared to the standard answers.
Brajesh Gupt: Furthermore, when when consider compute the quite
Brajesh Gupt: As half which is a more quantitative measure of the power supply chain. Normally in the incentive standard answers, the value is possibly 40 42,000
Brajesh Gupt: And inaccuracy we find that as have has reduced to one third of that says 14,000 so in this and this value is much closer to what the plan 2018 data predicts so it's it's a significant significant improvement as compared to the standard
Brajesh Gupt: Answers and the
Brajesh Gupt: The anomaly been goes away from it will will not goes away, but
Brajesh Gupt: One can account for most part of the anomaly using this suppressed power spectrum.
Brajesh Gupt: About the second anomaly which has to do with the you know lensing aptitude.
Brajesh Gupt: Just to review again in lambda CD model, the standard six parameter Lando city a model.
Brajesh Gupt: The lensing aptitude is taken to be one and when, when he looks at you know best fit Lando city a model of from plank data illegal to one is outside the one equal to outside the one sigma contour is in here. The only go to one line is outside this red control for the standard handsets
Brajesh Gupt: And
Brajesh Gupt: And as you can see that when we do we compute L in using LTC power spectrum. The, the one single contour of accuracy has shifted down and now illegal to one is within one sigma of
Brajesh Gupt: The is within the one sigma contour. So in this way, the anomaly of, you know, lensing aptitude is dissolved in and QC by restoring a really good one. Within one sigma country so
Brajesh Gupt: There is no crisis and the crisis again was
Brajesh Gupt: Pointed out by by in a paper by Valentino material and silk. So this people got a lot of attention because it was published in Nature and
Brajesh Gupt: Where they try to argue that
Brajesh Gupt: There is
Brajesh Gupt: This anomaly of lensing amplitude not being consistent when standard lambda CPM model.
Brajesh Gupt: Center with the Flatland OCD model and one had to introduce special curvature. But when you speak introduce special characters to solve this problem.
Brajesh Gupt: There is a huge disagreement between you know theory and observation at at other scales and this the name it as possible crisis and cosmology. So by resolving this anomaly, we see that actually there is no crisis because now equal to one isn't is within one single contract so
Brajesh Gupt: That this crisis is nothing to worry about.
Can
Brajesh Gupt: Now, in addition to resolving these two anomalies. What we can do is also make predictions that can be tested by future observations. So let's compare what standard answers and, you know,
Brajesh Gupt: The values of six parameter models.
simone: Let's see here. So,
Brajesh Gupt: To
simone: End to figure out the microphone. But the crisis, they were referring to wasn't in the discrepancy in the measure of each. Not really.
Brajesh Gupt: Oh, and that's
simone: Like that, in order to like better feed the large scale CME spectrum using spatial topology, then the discrepancy increased making it less
simone: Easy to hide it behind claims or maybe systematics or something like that. But I think their main message was. Was that right. They may be when people say that the supernova and CMT measurements of hobble are consistent, maybe, maybe we're missing something.
Brajesh Gupt: So, so the tension that you're talking about is completely separate. So this is in addition to what the astronaut anomaly is. And in this talk. I'm not
Brajesh Gupt: We're not saying anything about the Hubble date anomaly.
Brajesh Gupt: Because this
lsmolin: Just stop you there. Do you know of anything, any result from the quantum cosmology that addresses. We have both.
Brajesh Gupt: Not that I'm aware of, no.
Penn State: So in this particular calculation, the edge actually does increase but increases by point once it is not. I mean, the thing is that all this calculation just refers to see him be right.
Penn State: So it really is referring to these very large scales, whereas this cosmological ladder, which gave you a larger value. If it's not
Penn State: Is completely different method. And so we're not usually just taking the same data that plan gave. And so, so this does not really change very much at all just changes by point one or something. In case by point one, but it's not. It really is no no difference at all. Okay.
lsmolin: Thank you.
Western: But I do should CC have been interrupted. I have a question on the slide, the number 15 on the first anomaly. I wonder if so, because look quantum cosmology.
Western: make the situation better but doesn't solve it. So I wonder if you have control of the parameters and, for instance, if you were using a different polite potential. So, or if you were acting on other parameters. If the situation get even better.
Brajesh Gupt: So with the two potentials that we consider Steve inskeep initial inquiry potential, the results are the same in Chile, because the power spectrum doesn't change much. Okay, and
Brajesh Gupt: So,
Penn State: Sorry, go ahead. Sorry.
Brajesh Gupt: Yeah, I mean, and there is no other freedom in the parameters that we can that we can play with to
Brajesh Gupt: To further look for reduction of in as half
Penn State: So, um, can you tell us now the discrepancy. I mean, now that this S has reduced want the discrepancy is there is still some discrepancy, would you say it is one sigma. It was 2.8 sigma, you said before, but is at once.
Brajesh Gupt: And fi. Yeah. So for that, we will need to do for like more analysis to look at, you know, like realization and then compute what the thing ceiling giving us of those
Brajesh Gupt: Are the anomaly would be now so so that that's a good solution. I mean, I haven't looked at what
Brajesh Gupt: How many sigma they normally would be. Now after taking a QC spectrum.
Penn State: I have a related question, but I just wanted to say. And again, maybe a long weekend same, but as more about this, but it's not easy to calculate these things.
Penn State: You know the one sigma sigma. Yeah. The reason is because will wear a CSR almost uncorrelated. I said almost because
Penn State: Because of masking. There is some correlation introduce actually but but but see the data is very much correlated. So really, how to how to use huge covariance matrix understand it and it's not an easy simple calculation.
Penn State: Yeah, so, so, yeah. So one one answer to that. One is to really. But that's not the kind of thing that we're done so far just taking different realizations is what one would like to do, but that's a lot of work.
Penn State: Question is about
Penn State: What freedom you have in MQ see whether it has the same number of parameters as before. And therefore, one can in principle, compute the base factor.
Penn State: Comparing which of the two is preferred by the data. If there is an additional parameter. I can't tell from what you have presented, there isn't. It looks like a then of course, you won't be penalized by Occam's Razor for that is good.
Penn State: Right, but computing based factor would be very interesting. In this case, I think the one more question by beyond key, but you can
Penn State: Yeah, so I just the last couple of weeks I was in Paris and Milan, and that is, those are the planting and they of course are more frequent is than than Beijing. I mean that they also do basement.
Penn State: And other way around. It just opposite side that much more basin. And so, in fact, the discussions are completely different. And in fact, in Hanover, they're talking about calculating a sector that was exactly what
Penn State: I think it's good to look at it from all angles.
In whatever way you want, but anyway.
Penn State: Hey,
Penn State: This is a journey.
Penn State: And I, I have a question. Yeah, he goes in the same direction of adding a parameter ambition factors, can you go to pitch to Tina.
Penn State: Yes. Yeah, so look quantum gravity is giving you this function f. Okay, yeah, it is alleviating the tension. So the question is, suppose that I wanted to model this phenomenon.
Penn State: Independently of quantum gravity by postulating a function f. Okay 40 Sansa we one of the ones that the plank 2018 paper. As for the cutoff below some some key.
Penn State: So in that way. I would introduce one or two parameters. Yes. Now I could fit.
Penn State: My data or try to resolve a completely the anomaly by fitting those two parameters. Do you know what one gets as the scale for
Penn State: K cut off and for the power below the cutoff.
Brajesh Gupt: Actually that would that would depend a lot on what are you, what you are using to model this FK. For example, if you are just doing, you can do a polynomial fit. So that would again, I suppose, I mean, I haven't done that, then the tendency. But I suppose that
Brajesh Gupt: The scale.
Brajesh Gupt: That one would get by doing that fitting would be very much similar to the scale that we el que si is giving you
Penn State: Okay, thank you.
Penn State: This question and the answer was the value to all depend on what exactly what parameters we use and how much polynomial fitting
Penn State: But it turns out that there is a recent paper that has also done that IP, which is actually in fact they were excited by the shape of this curve because they were finding that the data suggests something like this.
Penn State: And so I think what we're to do is to understand the the paper, much better.
Penn State: But the scale at which the production happens that prefer one is saying is the same and that what they're doing is what it was just hungry. So yes, that maybe just take a step function.
Penn State: So that they are trying, or sometimes I'll just two parameters. One is when when it stops and added the depth of the scale, scale.
Penn State: But I think this I'm dead were to understand better, but the paper is is Patrick Peter and somebody else the paper just appeared. And so we're to understand
Penn State: The spirit of what Satya before was mentioning that is, yeah, you don't have those parameters. So from our point of view.
Penn State: Yeah, I think we can do the understanding to the Beijing one, then I think calculations that would be very good, because the base factor will just tell us how much better. This is compared to the standard
Brajesh Gupt: Yeah.
Brajesh Gupt: Yeah, I mean, these comments are really very helpful for us to, you know, new feature work on this.
Brajesh Gupt: Okay, so going ahead.
Brajesh Gupt: So we were looking at the relevance of the various parameters, directed by planks will with the standard and salads and blacks plank with the
Brajesh Gupt: AC power spectrum. So we see, we see that most of the parameters are almost like fire. These parameters change by less than point 4% but the optical depth that has to do with
Brajesh Gupt: The elite time renovation.
Brajesh Gupt: Changes by 10% in and QC and it increases. So that's a, that's an interesting and interesting creature. And as I explained in previous slides that as half that basically captures the power suppression anomaly is reduced by a factor of three. So,
Brajesh Gupt: So while these differences in other parameters cannot be, you know, measured but future observations are expected to provide you know independent measurements of optical depth. So when those
Brajesh Gupt: Measurements are available, one can actually compare with observation and see how well these predictions, you know,
Brajesh Gupt: hold true with those new data. So in addition to, you know, solving the existing problems, you know, we are able to make testable predictions for the future observations. That's the lesson from this slide.
Brajesh Gupt: Okay, so, so, so far what we had been doing was we we have been doing is
Brajesh Gupt: We have Luke quantum quantum cosmic cosmology equations we have fixed initial conditions and computed the skater. You know, the pyramidal power spectrum at the end of inflation and compared with observations.
Brajesh Gupt: So in this analysis. What we had 10 as the we have fixed the area gap flow quantum gravity to be the one. There was obtained by black hole entropy competitions long back. So the we have fixed in delta to be valued at 5.17 FRANKLIN SQUARE
Brajesh Gupt: Now, what we can do is turn this around that we Let's, for the moment, suppose that delta is not a it's not fixed. We treated treated as a free parameter and let's instead of fixing at using Blackboard and probably can computation. Let's fix it using long data so
Brajesh Gupt: For, for convenience I have defined this quantity RB, which is a square root of six times cell towers for by to convert it into then scale essentially
Brajesh Gupt: And interestingly, we be find this kind of posterior probability for RB. Okay, so this value RB not is is the value corresponding to delta not which is
Brajesh Gupt: 5.17 opt in from black entropy competition. So in this flawed, we see that there's a peek in in this distribution, that is to say that there is a preferred value of RB and
Brajesh Gupt: What is interesting is that the value of RB obtained from black hole and probably competition.
Brajesh Gupt: Is within one sigma of the peak. So this suggest the face of like a
You know,
Brajesh Gupt: A good synergy between the theory and observation.
Brajesh Gupt: Were no independent competitions from different ideas coming into you know agreement. So we are we not is well within the 68% confidence level.
Brajesh Gupt: Moreover, what it shows is that if one increases area gap too much, like for example 10 times then
Brajesh Gupt: This would this plot would suggest that that will be rolled out even at 95% confidence level. So there's not much room to increase, you know, or to consider lot valleys of a gap.
Brajesh Gupt: On the other hand, if one decreases the value of a gap. It is ruled out at a 68% but it is still allowed at 95% so that one can understand in the following way that
Brajesh Gupt: Information increases area gap too much can
Brajesh Gupt: You know the bones will the scale of the bounds will decrease and the bounce will start happening at at at quite low energy scales and then one would
Brajesh Gupt: One would see if you see corrections, even at, you know, you know, small angliss games which is definitely not you know preferred by the data.
Brajesh Gupt: On the other hand, if one decreases area gap. Then if one, in some sense, Allah is allowed to take delta going to zero limit. One is approaching basically the big bank like the
Brajesh Gupt: The thing that we just had the bounce becomes larger and larger and larger and then the power spectrum of El que se becomes more and more, you know, close to the one rated by the, the standard answers perspective. So that's why I mean there is this
Brajesh Gupt: There's a long tail at when
Brajesh Gupt: You know, for smaller values of RB so that's that's a way to understand it.
Baofei Li: Yes, I have a question here. Um, so I understand that this is true, is you fix the number of before. Right.
Baofei Li: Because I can always play a little with just allowing the number of you forced to change and in principle, I will expect this
Baofei Li: Distribution is probably distribution is going to change. I'm around
Brajesh Gupt: So this is an. So remember the we fix initial condition for the background geometry. So, for each value of delta the background geometry would be fixed. So, for a given value of delta, there is no freedom in choosing the number of Esports
Brajesh Gupt: Is that the
Baofei Li: British maybe I can rephrase have yours question. So the background dramatically under initial conditions for the perturbations for fixed using
Baofei Li: inspirations from the vile curvature hypothesis. But suppose we go back to the initial conditions which are used in the dress metric
Baofei Li: Dress metric approach like which one obey and William Nelson, we're doing then there is a lot of freedom in the choice of five pounds and then one can Van Den this window will probably increase. Do you agree.
Brajesh Gupt: Yes, because I just let me, let me think about it.
Brajesh Gupt: Yes. So if you let if you let five pounds, be a free parameter in addition to the into being a fee parameter. Then I agree with you. But in this work. I mean, the value of five pounds is fixed.
Brajesh Gupt: I agree, yes.
Baofei Li: Yes. Why that is right. So when you mean that the data gap or 10 times is rolled out and 95% confidence level and so on.
Baofei Li: Is these results like are these results like in also in conjunction with the previous and normally results like or they are independent. Like are you demanding that the anomaly results be also fixed in the same way.
Brajesh Gupt: When
Baofei Li: You're playing with this area gap.
Brajesh Gupt: Yes, yes, absolutely, because this, this is obtained by comparing the predictions with the observations with the blank data. So it's the same data.
Baofei Li: Same plank data, same, same elevation alleviation of the anomaly results and then demanding the Bay Area gap changes right
Brajesh Gupt: Okay, so
Brajesh Gupt: If you, if you fix the if the data is is fixed. And if you are changing one parameter, then the degree at least the anomalies that is all cannot be the same. It will be slightly different great example. For example, if RB is too low, then the situation is same as the standard answer.
Baofei Li: Exactly, yeah.
Brajesh Gupt: So okay, so
Baofei Li: One final question on there. So since you have a very nice result on that. If you decrease the gap 10 times
Brajesh Gupt: Yeah, and
Baofei Li: It is ruled out at 68% confidence level. If you recall in one of your works, you had considered
Baofei Li: I'm going away from your basic assumptions. No, but you considered like slightly widely spread states.
Baofei Li: And there we saw that the bounce density decreases, which is also a result independently by Croce and Montoya earlier sell QC so that is effectively decreasing the area gap so I can, can I view that this can this analysis. In fact, or constrain
Baofei Li: Even widely spread states like can I can I can I put dark turn the argument around and use it to constrain the kind of states which are allowed in LTC
Brajesh Gupt: Oh yeah, that's the
Baofei Li: Next thing they do gap but choosing not different types of states.
Yes.
Brajesh Gupt: One can do that one can do that. Okay, but with what which way it will be the like the before the exact details would have to be figured out
Baofei Li: And and i think like, we also have to see like whether those infrared problems with QC or result or not. But if they are under those caveats. I think we can use this argument to also constrain the kind of steaks, one can consider
Penn State: Yeah, I think what what I'm saying. The last remark email is a key one, namely that when we are doing that very widely
Penn State: Spread straight states right and that night. We're still using this metric and as but I'm just pointing out of work not just not
Penn State: That invite issues that were pointed out by Kaminski and non ASCII. And when I asked you that they are actually pointing out that well no will have to revisit that calculation.
Penn State: So the statement was that that are brightly big stage than one has to revisit the calculation, not on the background but of the
Penn State: Of the patients or together. And I just wanted to make sure that the hobbyist question is correctly, then I mean what is not fixing the number of he falls right
Penn State: The number of people's will be tied to the choice of data. Yeah. And so as
Penn State: I mean, this is the symbol is fixed. That's certainly true, but it's not true that one is fixed. The number of evils. If you like in bottoms questioning
Penn State: Where it's not true that one is fixing this five hours or something like that. That is all going to be going by what the value of delta is as delta is very and I think
Penn State: I just has brought us to check the data was varied or a range of a million sort of spider.
Penn State: So it was really quite a lot larger range range that was considered and this is the best rate and well quality two arguments to say that there is no other minimum in the
Penn State: You know, chi square for to update the chi square feet that this will only be the, the only only minimum. I just wanted to add that one volume.
Baofei Li: Okay, we're just going to ask another question, but it has to do with the previous slide, like, since I'm asking. Yeah.
Baofei Li: So the result that there is a power suppression.
Baofei Li: And large scales we know, like, it depends.
Baofei Li: Like, let us go beyond your hypothesis of the initial conditions, but if you
Baofei Li: Look at the general initial conditions there can be initial conditions in LTC with the power suppression.
Baofei Li: doesn't occur because it is tied to the choice of initial state. I want to understand it for the for the optical depth for the optical depth your result that optical depth can go to that slide for the optical yes yeah so your result that optical depth increases by 10% yeah like
Baofei Li: Do you guys think like it has, it is it is tied to the to the inspiration from the vile curvature hypothesis.
Baofei Li: Or do you think like it is a more general result which probably will be also valid if you take for thought Radia Vedic states at the bounce or some other kind of states at the bounce.
Brajesh Gupt: So,
Brajesh Gupt: So there is a slight called frequently asked questions where I talk about it. But let me let me answer the question right now. So this kind of increasing in value of optical depth will would be there.
Brajesh Gupt: In any mechanism which, you know, produces power suppression. So this is tied to power suppression.
Brajesh Gupt: If you have powers of enhancement on the, on the other hand, then one wouldn't see this kind of increment in the value of top
Baofei Li: Okay, so then probably this anomaly will become worse and that
Brajesh Gupt: It will become worse. Okay.
Baofei Li: Okay, thank you. So let me let me add just one comment to to finance coming so
Baofei Li: I have done.
Baofei Li: I use initial under the Vatican states before they bounce, you know, in the contract phase and then you find
Baofei Li: You know, QC, and then you find power in haste, man. In fact, for most of the initial state that you try to find blindly unless you introduce
Baofei Li: An argument as a value and radiation doing you find enhancement that in that case, you also find that the notion of these are very large and that they don't go Shannon, this can affect the power spectrum and have a high chances to produce suppression.
Baofei Li: A that's exactly, that's a second order effects. I just wanted to mention that even if they bear power spectrum has enhancement is still
Baofei Li: A you use what people call the notion modulation. The effect of non oceanic this on the power spectrum, you can still produce a separation and therefore increasing the value of the of the of the optical bad
Baofei Li: Thing, the statement is that even if we consider states which cause power enhancement at large Angular scales non kosher entities can in principle, suppress that power still increased optical depth. Right. Yeah.
Brajesh Gupt: Yeah, if you can see the non aggression modulation, then yes, absolutely. Yeah. Thank you. Thank you. One. One thing that though I missed that.
Brajesh Gupt: Okay, so. So in this way, we see that there is a nice interplay between what theory can tell for observations and from what observations can, you know, teach us about fundamental theory. Okay, so in summary what we have, what I've talked about is an idea of quantum gravity in the sky and
Brajesh Gupt: I just, I would just recall this paragraph that I from blank paper that I showed in the beginning of this talk, the highlighted part is what they
Brajesh Gupt: Were they say that anomalies. If they have primordial origin and if there is a model to explain that. That would be great. And so we presented here a concrete realization of this highlighted idea.
Brajesh Gupt: And following following the highlighted, you know, part in this paragraph, we see that they they do say themselves that future observations, you know, you know, can
Brajesh Gupt: I may be able to, you know,
Brajesh Gupt: Test predictions from these models and actually would increase the significance significance of these anomalies. So along those lines. We can also make some testable predictions in particular for, you know,
Brajesh Gupt: optical depth.
Brajesh Gupt: So as as you want, explained I in personal QC framework itself. They are ongoing work mainly led by Yvonne where one can generate, you know, one can get suppression of power in the in Cl and the temperature. Temperature correlation and immobilization
Brajesh Gupt: With the legacy. And so we wouldn't need to revisit you know these this analysis again to see how well those
Brajesh Gupt: Approaches do and what our prediction for those. Okay.
Brajesh Gupt: And an important
Brajesh Gupt: Point that one question that
Brajesh Gupt: I get asked is, again, about the how many free parameters are in the model. So when you get the choice of initial conditions and the data being fixed from the back, black hole entropy calculations. There are no, there are no fee parameters in the model.
Brajesh Gupt: In cosmology literature. There are other mechanisms to, you know, invoke power separation, but they require you to know, add some features to the inflation a potential, which usually come with additional parameters. So we know parameters. And the reason we know free parameter being there.
Brajesh Gupt: Certainly these these models would fit better with the observation as compared to those models. So there's no symbolic symbolic interplay between fundamental theory and observations.
Brajesh Gupt: So come into black slide I would just use it to our frequently asked questions we have kind of already discuss them and doing the questions.
Brajesh Gupt: So the first question, like a which but I'm kind of asked was a can other mechanisms lead, lead, leading to similar power suppression lizard is all too similar consequences. The answer is yes, that in any search mechanism where there is a power suppression.
Brajesh Gupt: The optical depth world would be larger and amplitude lensing amplitude become will become smaller and therefore the tension between two CMT anomalies would be reduced.
Brajesh Gupt: However, the exact quantity to features as in what the value of tower would be and how many segments within how many segments, the equal to one, become that might be different for different powers oppressions different power sufficient begin mechanisms. OK.
Brajesh Gupt: The next question would be what what sets the scale for LTC corrections. So as I went through the slide.
Brajesh Gupt: The we saw that the curvature skill which is Richie scale. It has an upper maximum at the bounce and that defines
Brajesh Gupt: A landscape or or we have number KL QC which basically sets the scale for these NPC corrections so modes which which have
Brajesh Gupt: Compatible or smaller wavelengths than, you know, wave numbers then kale QC they they are affected by quantum dynamics, while the modes which are very ultra violet.
Brajesh Gupt: That in that is a very, very large. And can you see the remaining bunch Davis state at the onset of innovation and those molds to not acquire any corrections. So with that, I would thank you. I would like to thank you very much. And if you have questions, I'm happy to take them. Thank you.
Baofei Li: Let's turn our speaker.
Baofei Li: Do you have any questions.
FAU: I have a question.
FAU: So effective is you just reviewed at the end is
FAU: That the K less than KL QC modes get excited
FAU: By an interaction with the curvature, maybe this is a very naive question. But how does that lead to suppression of power or small.
Brajesh Gupt: Okay, so you can think of it as a ligament. There's these modes get. I get excited, they can
Brajesh Gupt: This is a, this is a quantum perturbations. So this excitation come with the amplitude and a phase. So, these the quantum interference between between the
Brajesh Gupt: Two these modes can
Brajesh Gupt: Can lead to destructive interference and that can lead to power suppression. So in other way. If this excited modes can be written as Bollywood transmission over lunch. David state.
Brajesh Gupt: And these bugaboo transmission comes with alpha and beta parameter and and if you compute the ratio of the power of the power between the excited and not excited and there is a term that is that has to do with two times imagery part of alpha or beta. And that can become negative
Brajesh Gupt: And
Brajesh Gupt: That would lead to, you know, power, the ratio one less than one. Thank you.
Baofei Li: Another question.
Baofei Li: Yep. So this is just
Baofei Li: A follow up of the last thing that you mentioned about free parameters and and i mean he's not only a question for you is also for our body or for any anybody in the audience.
Baofei Li: And he said, waste and that is it myself. I asked myself and and has to do with this, the number of free parameters, because, you know, one can take two viewpoints here.
Baofei Li: You know you introduce free parameters like the, the amount of expansion after the bounds or the initial state of perturbations, etc. Or one introduces principles to fix those freedoms.
Baofei Li: But in the first case, then they count as free parameters and in the second they don't. So, you know, what is your viewpoint.
Baofei Li: About, you know, consider the freedoms as as real freedoms or, you know, introducing principles and therefore removing them because you know I could introduce a different principle and you and
Baofei Li: What did you report on that or a bias or, or, you know,
Brajesh Gupt: Oh, so let me say what I think is that
Brajesh Gupt: So these principles if they
Brajesh Gupt: Like what plank says in there. This this cutting
Brajesh Gupt: In the paper is that if take for anomalies. If there's a fundamental theory or fundamental explanation that helps reduce the significance of these anomalies.
Brajesh Gupt: I mean, that would be interesting. So in on it on a similar line, I would say that if the principles one introduces has no origin in
Brajesh Gupt: In quantum dynamics or the fundamental quantum geometry, then
Brajesh Gupt: That is well motivated and
Brajesh Gupt: And that can be taken to be like
Brajesh Gupt: You know,
Brajesh Gupt: And then one can take this idea of fixing the freedom using prints for more seriously. And here what we have done is like this is just the first step towards know trying to
Brajesh Gupt: Understand how are you know various elements of quantum geometry can help us, you know, fix these freedoms and then analyze the you know the outcome. So some of this isn't my my viewpoint and there is
Brajesh Gupt: No.
Brajesh Gupt: Other people, people say,
Brajesh Gupt: Well, what do you think
Penn State: Yeah, so
Penn State: Thank you for asking this because I want you to raise this question my son.
Penn State: So the yeah I mean, you're right.
Penn State: The
Penn State: Okay, so let's that initial conditions. One is for the background. And that was a little bit of confusion. I think in the discussion before the
Penn State: Initial condition for the background has nothing to do the Wildcat which hypothesis. And then there's an initial condition the perturbations.
Penn State: And my kind of point of view is that, well, you always needed initial conditions of probation, so you don't just say, because by Stevie's vacuum somewhere in the middle of the evolution right to bear the
Penn State: Dynamics is approximately
Penn State: Approximately
Penn State: Exponential
Penn State: Expansive with approximately explanation approximately a decision. And so I think replacing that with some initial condition I i think that you know just completely clueless.
Penn State: Because otherwise, want to count how many, how much freedom that was in including the babies vacuum condition. Right. So, to me, the, the condition operations is really just like the punch Davis and therefore there's no new from
Penn State: Now, and the conditions for the background geometry. On the other hand, which is not coming from anything like Welker which hypothesis.
Penn State: Or more precisely what we call quantum homogeneity and and sort of your hypothesis.
Penn State: It is really an additional thing and it really has to do with quantum geometry. To me, it is again. I mean, you're completely right, one could just say that there is an additional parameter number of he falls, but
Penn State: I do feel that this is sort of, you know, since things are working out well is a pointer that there is something right about that initial condition.
Penn State: And I'm not happy with that initial condition. I think it has to be much better, much more sharp much more precise much more satisfactory than what what is currently available.
Penn State: But I think if there was sort of a sharp initial condition, then I wouldn't call it as a parameter. I mean, at the moment, the way that the initial condition is formulated for the background as to do is a little bit
Penn State: Not completely satisfactory for reasons I can explain but maybe not not not to take too much time.
Penn State: But if I were to find a place it by something which is really compelling. Then I really feel that is not a parameter. I mean, it's just, it's just like, you know, initial conditions is something that you need. And that's what they say. So that's my point of view.
Baofei Li: Thank you and me. I, I basically agree with you but I only you know as myself, that was compelling means depends on you know on the voice asking the question so so I never know if what is compelling for me is not compelling for somebody else. So, so
Penn State: Yeah, I agree. But I mean, in some sense, as we saw before, you know, basie and then frequent test and
Penn State: All this subjective judgment that come in, come in. Anyway, all a lot about
Penn State: What is the correct way of looking at some
Penn State: Likelihood, you know, so the I agree that it is
Baofei Li: Very would think anything we we were
Penn State: Sufficiently successful right in many, many ways then you sort of feel that will doesn't is that's what happened at the bottom is vacuum right
Penn State: I mean it's not compelling by any means, but everybody thinks it is ok it's not a compelling because just put in the middle of evolution somewhere.
Penn State: And if you look at what happens to those more in the, in the past, it's not as obvious that it was more should be in the basement of his vacuum when they exit the Hubble horizon, but we saw thing it's compelling because it works well.
Baofei Li: Any more questions.
Baofei Li: Our speaker again.