1,220 research outputs found
The impact of cosmological neutrinos on large-scale structure observables
No full textIn the last couple of decades, several cosmological experiments probing the Cosmic Microwave Background (CMB) and the large-scale structure of the Universe have confirmed the wonderful agreement between data and the standard cosmological model,
the ΛCDM paradigm. According to the latter, our Universe is filled, besides ordinary baryonic matter, with a cosmological constant which makes the expansion accelerateand cold dark matter (CDM) as the main driver for structure formation. A small amount of energy is carried by cosmological neutrinos. While the Standard Model of particle physics predicts them to be massless, the detection of flavor oscillations highlighted how they do indeed have a mass. Unfortunately, these experiments are not able to constrain the mass scale. On the other hand cosmology has the power to do so, thanks to the considerable impact that neutrinos have on the cosmological observables. Neutrinos decouple from the photon-baryon plasma in the very early Universe, when
they are still in the relativistic regime. While on large scales they essentially behave like CDM, the high thermal velocities they possess prevent them from clustering, at linear level, on scales smaller than the free-streaming length. This induces a
back-reaction on the growth of CDM density perturbations, which becomes scaledependent, and affects the matter power spectrum and all the observables that depend upon it. Future surveys like Euclid, the Large Synoptic Survey Telescope (LSST), the Dark
Energy Survey Instrument (DESI) and the Square Kilometer Array (SKA) will likely measure the sum of the three neutrino masses (Mν) for the first time. In order to have a correct estimate of Mν, considerable efforts must be made on the theoretical side to assess which observables are the most suitable for the detection, to accurately quantify the impact of neutrino mass on such observables and to carefully study of the systematics, nuisances and biases that can affect such measurements. The research I have been carrying out during my Ph.D. was developed with this goal in mind. This thesis presents the main and most relevant results of papers published on refereed journals, sorted according to the degree of non-linearity involved in the problem. The first analysis presented extends previous works on the linear point (LP) of the two-point correlation function (2PCF) to the case of massive neutrino cosmologies. So far, the LP has been shown to be an excellent standard ruler for cosmology. By using state-of-art N-body simulations, we show that also in cosmologies with massive neutrinos the LP retains its nature of standard ruler for the CDM and halo real-space 2PCF. To do so, we use a model-independent parametric fit in the range of scales of the Baryon Acoustic Oscillations (BAOs). We also propose a procedure to constrain neutrino masses by comparing the measured LP from data to the LP of a mock galaxy catalog with massless neutrinos and the same remaining cosmological parameters. We find that the sum of the neutrino masses could in principle be detected provided that several redshift bins are used, the survey volume is sufficiently large and the shot noise of the galaxy sample is sufficiently low. In the second work we investigate the possibility that the degeneracies between the effects of neutrino mass and those of baryons on the large-scale matter distribution (e.g. AGN feedback, galactic winds) could bias the measurement of Mν in future surveys probing galaxy clustering and cosmic shear. To this end, we generate synthetic data sets and fit them using the Markov Chain Monte Carlo (MCMC) technique. Baryon feedback is modelled with fitting functions that describe the suppression to the matter power spectrum through free parameters with well-established physical meaning, while neutrinos are modelled through the HALOFIT operator calibrated on N-body simulations. The covariance matrix entering in the likelihood function contains cosmic variance and shot/shape noise as sources of statistical uncertainties,
while theoretical inaccuracies are accounted for through a mode-coupling function with a given correlation length. For the weak lensing analysis we also take into account the systematic carried by the intrinsic alignment effect. Overall, for both clustering and shear, we are always able to recover the right input neutrino mass well within 1-σ. In the sheAar survey, we also report some interesting degeneracy between Mν and the parameter controlling the amplitude of the intrinsic alignment effect. Finally, the third work concerns the clustering of relic neutrinos in the Milky Way. Since neutrinos are massive, they feel the gravitational attraction of the Galaxy and should therefore be more abundant at the Earth position than the average cosmological value. This could enhance the event rate of future experiments aiming at a direct detection of the cosmic neutrino background. This work improves past analyses by performing full 3-D calculations and including in the budget close-by structures like the Virgo cluster and the Andromeda galaxy. The neutrino clustering is computed by back-tracking particles in the Milky Way gravitational field using the N-one body technique. Our results overall confirm previous findings, but highlight how the contribution of the Virgo cluster is relevant. The local neutrino density (and in turn the detection rate) is found to be enhanced by 0.53% for a neutrino mass of 10 meV, 12%
for 50 meV, 50% for 100 meV or 500% for 300 meV
On the degeneracy between baryon feedback and massive neutrinos as probed by matter clustering and weak lensing
No full textMassive neutrinos, due to their free streaming, produce a suppression in the matter power spectrum at intermediate and small scales which could be probed by galaxy clustering and/or weak lensing observables. This effect happens at scales that are also influenced by baryon feedback, i.e. galactic winds or Active Galactic Nuclei (AGN) feedback, which in realistic hydrodynamic simulations has also been shown to produce a suppression of power. Leaving aside, for the moment, the complex issue of galaxy bias, we focus here on matter clustering and tomographic weak lensing, we investigate the possible degeneracy between baryon feedback and neutrinos showing that it is not likely to degrade significantly the measurement of neutrino mass in future surveys. To do so, we generate mock data sets and fit them using the Markov Chain Monte Carlo (MCMC) technique and explore degeneracies between feedback parameters and neutrino mass. We model baryon feedback through fitting functions, while massive neutrinos are accounted for, also in the non-linear regime, using Halofit calibrated against accurate N-body neutrino simulations. In the error budget, we include the uncertainty in the modelling of non-linearities. For both matter clustering and weak lensing, we always recover the input neutrino mass within ∼0.25σ confidence level. Finally, we also take into account the intrinsic alignment effect in the weak lensing mock data. Even in this case, we are able to recover the right parameters: in particular, we find a significant degeneracy pattern between Mν and the intrinsic alignment parameter AIA
About twin primes and distribution of primes
No full textThis paper give us a demonstration of twin primes conjecture using approximation of function �(iupsilon) that we introduce in section 6. Section 1-5 give us introduction to terminology and a clarification on (iupsilon) terms. In particular section
5 is really important because of its Lemma. Section 7 reassume foregoing explanations and it give us two theorems and one corollary;the theorem 7.2 give us exact approximation of twin primes counting function
Established and Outsiders at the Same Time - Self-Images and We-Images of Palestinians in the West Bank and in Israel
No full textPalestinians frequently present a harmonizing and homogenizing we-image of their own national we-group, as a way of counteracting Israeli attempts to sow divisions among them, whether through Israeli politics or through the dominant public discourse in Israel. However, a closer look reveals the fragility of this homogenizing we-image which masks a variety of internal tensions and conflicts. By applying methods and concepts from biographical research and figurational sociology, the articles in this volume offer an analysis of the Middle East conflict that goes beyond the polar opposition between “Israelis” and “Palestinians”. On the basis of case studies from five urban regions in Palestine and Israel (Bethlehem, Ramallah, East Jerusalem, Haifa and Jaffa), the authors explore the importance of belonging, collective self-images and different forms of social differentiation within Palestinian communities. For each region this is bound up with an analysis of the relevant social and socio-political contexts, and family and life histories. The analysis of (locally) different figurations means focusing on the perspective of Palestinians as members of different religious, socio-economic, political or generational groupings and local group constellations – for instance between Christians and Muslims or between long-time residents and refugees. The following scholars have contributed to this volume: Ahmed Albaba, Johannes Becker, Hendrik Hinrichsen, Gabriele Rosenthal, Nicole Witte, Arne Worm and Rixta Wundrak. Gabriele Rosenthal is a sociologist and professor of Qualitative Methodology at the Center of Methods in Social Sciences, University of Göttingen. Her major research focus is the intergenerational impact of collective and familial history on biographical structures and actional patterns of individuals and family systems. Her current research deals with ethnicity, ethno-political conflicts and the social construction of borders. She is the author and editor of numerous books, including The Holocaust in Three Generations (2009), Interpretative Sozialforschung (2011) and, together with Artur Bogner, Ethnicity, Belonging and Biography (2009)
Gendered Adaptations: Canadian Rewritings of Classical Texts. Author-Translator Conference 2010, University of Swansea, Wales
No full textQuantum many-body scars : realizations and applications
No full textauthor: Gabriele Calliari, BScMasterarbeit Universität Innsbruck 202
The Last Bastion of Architecture
No full textThe essay is a critical interpretation of Rem Koolhaas' theory of Bigness. In fact, of the theories that have best marked the development of architectural culture since World War II – from those of the Smithsons to Rossi, from Eisenman to Venturi and Scott Brown – Rem Koolhaas’s theory of Bigness has probably, more than any other, investigated the intrinsic possibilities of architecture at the end of the 20th century. In light of the number of pseudotheories that have largely characterized the last decade, Bigness is the last constituent fact of recent history: an extremely lucid attempt to draw to a conclusion a history that goes back to the very invention of the modern city, comparing it with architecture’s own immutable core, its physicality, even exposing the theory of Bigness itself to the risk of total failure. The essay investigates the development of the theory of Bigness from its incubation in Koolhaas’s book Delirious New York in 1978, to the "official" presentation in S,M,L,XL in december 1995. The essay presents some parts of the PhD research "L'architettura dei libri. Progetto, scrittura, editoria nella ricerca architettonica contemporanea", developed by the author at Università degli studi G. D'Annunzio, Chieti, Facoltà di Architettura di Pescara, in 2001-2004.
Log 7 Winter/Spring 2006 includes essays of Richard Anderson, Marie J. Aquilino, Amos Gitai, Pier Vittorio Aureli, Manuel Orazi, Jean-Louis Cohen, William Drenttel, Peter Eisenman, Luis Fernandez-Galiano, John Kaliski, Sabir Khan, Reinhold Martin, Gabriele Mastrigli, Deborah Richmond, Julie Rose, Paul Virilio, Eyal Weizman, Mirko Zardini.
Log 7
Winter/Spring 2006
Co-edited by Denise Bratton
Saggi di Richard Anderson, Marie J. Aquilino, Amos Gitai,
Pier Vittorio Aureli, Manuel Orazi, Jean-Louis Cohen, William Drenttel, Peter Eisenman, Luis Fernandez-Galiano, John Kaliski, Sabir Khan, Reinhold Martin, Gabriele Mastrigli, Deborah Richmond, Julie Rose, Paul Virilio, Eyal Weizman, Mirko Zardini
Quantum many-body scars : realizations and applications
No full textauthor: Gabriele Calliari, BScMasterarbeit Universität Innsbruck 202
Quantum many-body scars : realizations and applications
No full textauthor: Gabriele Calliari, BScMasterarbeit Universität Innsbruck 202
Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions
No full textAbstract Robotic technology is expected to transform rehabilitation settings, by providing precise, repetitive, and task-specific interventions, thereby potentially improving patients’ clinical outcomes. Artificial intelligence (AI) and machine learning (ML) have been widely applied in different areas to support robotic rehabilitation, from controlling robot movements to real-time patient assessment. To provide an overview of the current landscape and the impact of AI/ML use in robotics rehabilitation, we performed a systematic review focusing on the use of AI and robotics in rehabilitation from a broad perspective, encompassing different pathologies and body districts, and considering both motor and neurocognitive rehabilitation. We searched the Scopus and IEEE Xplore databases, focusing on the studies involving human participants. After article retrieval, a tagging phase was carried out to devise a comprehensive and easily-interpretable taxonomy: its categories include the aim of the AI/ML within the rehabilitation system, the type of algorithms used, and the location of robots and sensors. The 201 selected articles span multiple domains and diverse aims, such as movement classification, trajectory prediction, and patient evaluation, demonstrating the potential of ML to revolutionize personalized therapy and improve patient engagement. ML is reported as highly effective in predicting movement intentions, assessing clinical outcomes, and detecting compensatory movements, providing insights into the future of personalized rehabilitation interventions. Our analysis also reveals pitfalls in the current use of AI/ML in this area, such as potential explainability issues and poor generalization ability when these systems are applied in real-world settings
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