Primordial Isocurvature Perturbation in Light of CMB and LSS Data

The increased accuracy in the cosmological observations, especially in the measurements of the comic microwave background, allow us to study the primordial perturbations in grater detail. In this thesis, we allow the possibility for a correlated isocurvature perturbations alongside the usual adiabatic perturbations. Thus far the simplest six parameter \Lambda CDM model has been able to accommodate all the observational data rather well. However, we find that the 3-year WMAP data and the 2006 Boomerang data favour a nonzero nonadiabatic contribution to the CMB angular power sprctrum. This is primordial isocurvature perturbation that is positively correlated with the primordial curvature perturbation. Compared with the adiabatic \Lambda CMD model we have four additional parameters describing the increased complexity if the primordial perturbations. Our best-fit model has a 4% nonadiabatic contribution to the CMB temperature variance and the fit is improved by \Delta\chi^2 = 9.7. We can attribute this preference for isocurvature to a feature in the peak structure of the angular power spectrum, namely, the widths of the second and third acoustic peak. Along the way, we have improved our analysis methods by identifying some issues with the parametrisation of the primordial perturbation spectra and suggesting ways to handle these. Due to the improvements, the convergence of our Markov chains is improved. The change of parametrisation has an effect on the MCMC analysis because of the change in priors. We have checked our results against this and find only marginal differences between our parametrisation.Kosmologisten havaintojen määrä ja tarkkuus on huomattavasti kasvanut viime vuosien aikana. Tämä on erityisen huomattavaa kosmisen mikroaaltotaustan mittauksissa. Paremman tarkkuuden ansiosta nykyään on mahdollista tutkia varhaisen maailmankaikkeuden energiatiheyden häiriöiden tilastollista jakaumaa huomattavasti tarkemmin. Yksinkertaisimmissa kosmologisissa malleissa varhaisessa maailmankaikkeudessa on vain adiabaattisia eli kaarevuushäiriöitä. Väitöskirjassa tutkimme mahdollisuutta toisen tyyppiseen häiriöön, niin kutsuttuun isokurvatuurihäiriöön. Analyysimme perusteella varhaisen maailmankaikkeuden tiheyshäiriöt ovat pääosin adiabaattisia, mutta mukana on myös pieni isokurvatuuri-komponentti. Tämän havainnon mukaan niiden fysikaalisten prosessien, jotka tuottavat nämä pienet häiriöt varhaisessa maailmankaikkeudessa, täytyy olla hiukan monipuolisempia kuin puhtaasti adiabaattiset mallit sallisivat

Correlated Primordial Perturbations in Light of CMB and LSS Data

We use cosmic microwave background (CMB) and large-scale structure data to constrain cosmological models where the primordial perturbations have both an adiabatic and a cold dark matter (CDM) isocurvature component. We allow for a possible correlation between the adiabatic and isocurvature modes, and for different spectral indices for the power in each mode and for their correlation. We do a likelihood analysis with 11 independent parameters. We discuss the effect of choosing the pivot scale for the definition of amplitude parameters. The upper limit for the isocurvature fraction is 18% around a pivot scale k = 0.01 Mpc^{-1}. For smaller pivot wavenumbers the limit stays about the same. For larger pivot wavenumbers, very large values of the isocurvature spectral index are favored, which makes the analysis problematic, but larger isocurvature fractions seem to be allowed. For large isocurvature spectral indices n_iso > 2 a positive correlation between the adiabatic and isocurvature mode is favored, and for n_iso < 2 a negative correlation is favored. The upper limit to the nonadiabatic contribution to the CMB temperature variance is 7.5%. Of the standard cosmological parameters, determination of the CDM density $\omega_c$ and the sound horizon angle $\theta$ (or the Hubble constant $H_0$) are affected most by a possible presence of a correlated isocurvature contribution. The baryon density $\omega_b$ nearly retains its ``adiabatic value''.Comment: 20 pages, 21 figures (many in color

Correlated adiabatic and isocurvature CMB fluctuations in the wake of the WMAP

In general correlated models, in addition to the usual adiabatic component with a spectral index n_ad1 there is another adiabatic component with a spectral index n_ad2 generated by entropy perturbation during inflation. We extend the analysis of a correlated mixture of adiabatic and isocurvature CMB fluctuations of the WMAP group, who set the two adiabatic spectral indices equal. Allowing n_ad1 and n_ad2 to vary independently we find that the WMAP data favor models where the two adiabatic components have opposite spectral tilts. Using the WMAP data only, the 2-sigma upper bound for the isocurvature fraction f_iso of the initial power spectrum at k_0=0.05 Mpc^{-1} increases somewhat, e.g., from 0.76 of n_ad2 = n_ad1 models to 0.84 with a prior n_iso < 1.84 for the isocurvature spectral index. We also comment on a possible degeneration between the correlation component and the optical depth tau. Moreover, the measured low quadrupole in the TT angular power could be achieved by a strong negative correlation, but then one needs a large tau to fit the TE spectrum.Comment: 5 pages, 7 figures. V2: Added 2 figures and revised a bit the results section. This is a slightly longer version than the published one in PR

Hints of Isocurvature Perturbations in the Cosmic Microwave Background?

The improved data on the cosmic microwave background (CMB) anisotropy allow a better determination of the adiabaticity of the primordial perturbation. Interestingly, we find that recent CMB data seem to favor a contribution of a primordial isocurvature mode where the entropy perturbation is positively correlated with the primordial curvature perturbation and has a large spectral index (niso ~ 3). With 4 additional parameters we obtain a better fit to the CMB data by Delta chi^2 = 9.7 compared to an adiabatic model. For this best-fit model the nonadiabatic contribution to the CMB temperature variance is 4%. According to a Markov Chain Monte Carlo analysis the nonadiabatic contribution is positive at more than 95% C.L. The exact C.L. depends somewhat on the choice of priors, and we discuss the effect of different priors as well as additional cosmological data.Comment: v1&2: 4 pages, 2 figures. v4: 16 pages, 7 figures, iopart style. Revised the 'Other cosmological data' section, added a detailed discussion on the effect of priors, and added many figures. Published versio

Neste Rallin asiakasryhmien käyttäytyminen tapahtuman aikana

Opinnäytetyön toimeksiantajana oli Sports Business School Finland. Opinnäytetyön tavoit-teena oli selvittää asiakkaiden tapoja kuluttaa rallitapahtuman tarjoamia elämyksiä sekä niitä perusteita, joilla noita elämyksiä valitaan. Johtopäätökset haluttiin tehdä siitä, kulut-tavatko eri asiakasryhmät tapahtuman tarjoamia elämyksiä eri tavoilla, ja jos kuluttavat, selvitetään mitkä ovat suurimmat erot asiakasryhmien välillä. Tässä tutkimuksessa valitut muuttujat pohjautuivat aiemmin vuonna 2015 Sports Business Schoolin tekemään tutkimukseen, jossa vastaajat vastasivat spontaanisti eri tekijöitä, jotka vaikuttavat heidän haluun osallistua rallitapahtuman eri osatapahtumiin. Kyselyssä sovel-lettiin jo olemassa olevaa Sports Business Schoolin kyselylomakepohjaa. Tutkimus suoritet-tiin kvantitatiivisena tutkimuksena Webropol surveys -palvelun avulla. Jyväskylän ammattikorkeakoulun opiskelijat suorittivat aineistonkeruun haastattelemalla yhteensä 337 katso-jaa Paviljongin kilpailukeskuksella sekä Harjun erikoiskokeella. Tuloksista kävi ilmi, että Neste Ralli Finlandilla on lojaalit asiakkaat, jotka osallistuvat vuo-sittain tapahtumaan itse lajin takia. Tuloksista selvisi, että tärkeimmät tekijät erikoiskoetta valittaessa ovat asiakasryhmästä riippumatta samankaltaisia. Näkyvyys katselualueelta eri-koiskokeelle ja turvallisuus erikoiskokeella nousi sukupuolesta, tapahtumaseurueesta ja käyntikerroista riippumatta todella tärkeiksi tekijöiksi katsojille. Paviljongin kilpailukeskus osoittautui tärkeäksi vierailukohteeksi kaikille vastaajille. Erikoiskokeiden täytyy olla entistä houkuttelevampia, jotta yhä useampi ihminen päätyy tien varteen katsomaan lajia. Yleisöerikoiskokeita voidaan aina kehittää parempaan suun-taan ja tulevaisuudessa järjestäjien kannattaakin keskittyä siihen, mitä itse asiakkaat odot-tavat saavansa tapahtumasta irti.The theses was assigned Sports Business School Finland. The goal of the thesis was to find out how customers consume the experiences of the rally event and the reasons for choos-ing those experiences. This resulted in drawing conclusions if different customer groups consume events that offer different experiences in different ways, and if they consume, find out what the biggest differences are between the customer groups. The variables selected in this study were based on the Sports Business School survey ear-lier in 2015, in which the respondents responded spontaneously to various factors influ-encing their desire to participate in various events in a racing event. The questionnaire ap-plies to the existing Sports Business School questionnaire. The survey was conducted using a quantitative approach and the Webropol software. The students of Jyväskylä University of Applied Sciences completed the collection of data by interviewing a total of 337 specta-tors at the Paviljonki Competition Center and the Harju Special stage. The results showed that Neste Rally Finland has loyal customers who participate every year because of the race itself. The results showed that the key factors in selecting a special stage are similar regardless of the customer group. Visibility from the viewing area to spe-cial stages and security in a special stage were very important factors regardless of the cus-tomer group. The Pavilionki Competition Center turned out to be very important place to visit for every spectator. In the future, the organizers should put more effort to special stage development and try to offer more for the existing customers

pH-RL: A Personalization Architecture to Bring Reinforcement Learning to Health Practice

While reinforcement learning (RL) has proven to be the approach of choice for tackling many complex problems, it remains challenging to develop and deploy RL agents in real-life scenarios successfully. This paper presents pH-RL (personalization in e-Health with RL) a general RL architecture for personalization to bring RL to health practice. pH-RL allows for various levels of personalization in health applications and allows for online and batch learning. Furthermore, we provide a general-purpose implementation framework that can be integrated with various healthcare applications. We describe a step-by-step guideline for the successful deployment of RL policies in a mobile application. We implemented our open-source RL architecture and integrated it with the MoodBuster mobile application for mental health to provide messages to increase daily adherence to the online therapeutic modules. We then performed a comprehensive study with human participants over a sustained period. Our experimental results show that the developed policies learn to select appropriate actions consistently using only a few days' worth of data. Furthermore, we empirically demonstrate the stability of the learned policies during the study

Using generative adversarial networks to develop a realistic human behavior simulator

Simulation environments have proven to be very useful as testbeds for reinforcement learning (RL) algorithms. For settings where an actual human user is involved, these simulation environments allow one to test out the suitability of new RL approaches without having to include real users at first. It obviously does require the simulator to have a certain degree of realism, however, realistic simulators for the behavior of humans in the health domain are rarely seen. To generate realistic behavior, the simulator could be driven by data from real users, but this might lead to privacy issues. In this paper, we propose to use Generative Adversarial Networks (GANs) for generating realistic simulation environments. In this first step, we use an existing simulator that simulates daily activities of users and the GANs are used to generate realistic sensory data that accompanies such activities. After training, the original (potentially privacy sensitive) data can be thrown away and the simulator can simply be driven by the GAN models. Results show that a model trained on real data shows similar performance on the data artificially generated by the GAN