Bielefeld University

About: Bielefeld University is a education organization based out in Bielefeld, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Quantum chromodynamics. The organization has 10123 authors who have published 26576 publications receiving 728250 citations. The organization is also known as: University of Bielefeld & UNIVERSITAET BIELEFELD.

Fluctuations and Correlations of net baryon number, electric charge, and strangeness: A comparison of lattice QCD results with the hadron resonance gas model

Abstract: We calculate the quadratic fluctuations of net baryon number, electric charge and strangeness as well as correlations among these conserved charges in ($2+1$)-flavor lattice QCD at zero chemical potential. Results are obtained using calculations with tree-level improved gauge and the highly improved staggered quark actions with almost physical light and strange quark masses at three different values of the lattice cutoff. Our choice of parameters corresponds to a value of 160 MeV for the lightest pseudoscalar Goldstone mass and a physical value of the kaon mass. The three diagonal charge susceptibilities and the correlations among conserved charges have been extrapolated to the continuum limit in the temperature interval $150\text{ }\text{ }\mathrm{MeV}\ensuremath{\le}T\ensuremath{\le}250\text{ }\text{ }\mathrm{MeV}$. We compare our results with the hadron resonance gas (HRG) model calculations and find agreement with HRG model results only for temperatures $T\ensuremath{\lesssim}150\text{ }\text{ }\mathrm{MeV}$. We observe significant deviations in the temperature range $160\text{ }\text{ }\mathrm{MeV}\ensuremath{\lesssim}T\ensuremath{\lesssim}170\text{ }\text{ }\mathrm{MeV}$ and qualitative differences in the behavior of the three conserved charge sectors. At $T\ensuremath{\simeq}160\text{ }\text{ }\mathrm{MeV}$ quadratic net baryon number fluctuations in QCD agree with HRG model calculations, while the net electric charge fluctuations in QCD are about 10% smaller and net strangeness fluctuations are about 20% larger. These findings are relevant to the discussion of freeze-out conditions in relativistic heavy ion collisions.

Global distribution of particle phase state in atmospheric secondary organic aerosols

Abstract: Secondary organic aerosols (SOA) are a large source of uncertainty in our current understanding of climate change and air pollution. The phase state of SOA is important for quantifying their effects on climate and air quality, but its global distribution is poorly characterized. We developed a method to estimate glass transition temperatures based on the molar mass and molecular O:C ratio of SOA components, and we used the global chemistry climate model EMAC with the organic aerosol module ORACLE to predict the phase state of atmospheric SOA. For the planetary boundary layer, global simulations indicate that SOA are mostly liquid in tropical and polar air with high relative humidity, semi-solid in the mid-latitudes and solid over dry lands. We find that in the middle and upper troposphere SOA should be mostly in a glassy solid phase state. Thus, slow diffusion of water, oxidants and organic molecules could kinetically limit gas-particle interactions of SOA in the free and upper troposphere, promote ice nucleation and facilitate long-range transport of reactive and toxic organic pollutants embedded in SOA.

Identification via channels

Abstract: The authors' main finding is that any object among doubly exponentially many objects can be identified in blocklength n with arbitrarily small error probability via a discrete memoryless channel (DMC), if randomization can be used for the encoding procedure. A novel doubly exponential coding theorem is presented which determines the optimal R, that is, the identification capacity of the DMC as a function of its transmission probability matrix. This identification capacity is a well-known quantity, namely, Shannon's transmission capacity for the DMC. >

Estimating Aggregate Consumer Preferences from Online Product Reviews

Abstract: Today, consumer reviews are available on the Internet for a large number of product categories. The pros and cons expressed in this way uncover individually perceived strengths and weaknesses of the respective products, whereas the usually assigned product ratings represent their overall valuation. The key question at this point is how to turn the available plentitude of individual consumer opinions into aggregate consumer preferences, which can be used, for example, in product development or improvement processes.To solve this problem, an econometric framework is presented that can be applied to the mentioned type of data after having prepared it using natural language processing techniques. The suggested methodology enables the estimation of parameters, which allow inferences on the relative effect of product attributes and brand names on the overall evaluation of the products. Specifically, we discuss options for taking opinion heterogeneity into account. Both the practicability and the benefits of the suggested approach are demonstrated using product review data from the mobile phone market. This paper demonstrates that the review-based results compare very favorably with consumer preferences obtained through conjoint analysis techniques.