On Convergence Properties of Shannon Entropy

Convergence properties of Shannon Entropy are studied. In the differential setting, it is shown that weak convergence of probability measures, or convergence in distribution, is not enough for convergence of the associated differential entropies. A general result for the desired differential entropy convergence is provided, taking into account both compactly and uncompactly supported densities. Convergence of differential entropy is also characterized in terms of the Kullback-Liebler discriminant for densities with fairly general supports, and it is shown that convergence in variation of probability measures guarantees such convergence under an appropriate boundedness condition on the densities involved. Results for the discrete setting are also provided, allowing for infinitely supported probability measures, by taking advantage of the equivalence between weak convergence and convergence in variation in this setting.Comment: Submitted to IEEE Transactions on Information Theor

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

We consider the problem of finding a near-optimal policy in continuous space, discounted Markovian Decision Problems given the trajectory of some behaviour policy. We study the policy iteration algorithm where in successive iterations the action-value functions of the intermediate policies are obtained by picking a function from some fixed function set (chosen by the user) that minimizes an unbiased finite-sample approximation to a novel loss function that upper-bounds the unmodified Bellman-residual criterion. The main result is a finite-sample, high-probability bound on the performance of the resulting policy that depends on the mixing rate of the trajectory, the capacity of the function set as measured by a novel capacity concept that we call the VC-crossing dimension, the approximation power of the function set and the discounted-average concentrability of the future-state distribution. To the best of our knowledge this is the first theoretical reinforcement learning result for off-policy control learning over continuous state-spaces using a single trajectory

Photon Production from a Quark--Gluon Plasma

In-medium interactions of a particle in a hot plasma are considered in the framework of thermal field theory. The formalism to calculate gauge invariant rates for photon and dilepton production from the medium is given. In the application to a QED plasma, astrophysical consequences are pointed out. The photon production rate from strongly interacting quarks in the quark--gluon plasma, which might be formed in ultrarelativistic heavy ion collisions, is calculated in the previously unaccessible regime of photon energies of the order of the plasma temperature. For temperatures below the chiral phase transition, an effective field theory incorporating dynamical chiral symmetry breaking is employed, and perturbative QCD at higher temperatures. A smooth transition between both regions is obtained. The relevance to the soft photon problem and to high energy heavy ion experiments is discussed.Comment: Paper in ReVTeX. Figures and complete paper available via anonymous ftp, ftp://tpri6c.gsi.de/pub/phenning/hq95ga

Data production models for the CDF experiment

The data production for the CDF experiment is conducted on a large Linux PC farm designed to meet the needs of data collection at a maximum rate of 40 MByte/sec. We present two data production models that exploits advances in computing and communication technology. The first production farm is a centralized system that has achieved a stable data processing rate of approximately 2 TByte per day. The recently upgraded farm is migrated to the SAM (Sequential Access to data via Metadata) data handling system. The software and hardware of the CDF production farms has been successful in providing large computing and data throughput capacity to the experiment.Comment: 8 pages, 9 figures; presented at HPC Asia2005, Beijing, China, Nov 30 - Dec 3, 200

Data processing model for the CDF experiment

The data processing model for the CDF experiment is described. Data processing reconstructs events from parallel data streams taken with different combinations of physics event triggers and further splits the events into datasets of specialized physics datasets. The design of the processing control system faces strict requirements on bookkeeping records, which trace the status of data files and event contents during processing and storage. The computing architecture was updated to meet the mass data flow of the Run II data collection, recently upgraded to a maximum rate of 40 MByte/sec. The data processing facility consists of a large cluster of Linux computers with data movement managed by the CDF data handling system to a multi-petaByte Enstore tape library. The latest processing cycle has achieved a stable speed of 35 MByte/sec (3 TByte/day). It can be readily scaled by increasing CPU and data-handling capacity as required.Comment: 12 pages, 10 figures, submitted to IEEE-TN

Factors influencing awareness of community-based shorebird conservation projects in Australia

We examine the awareness of potential volunteers (n = 360) living near nine community-based shorebird conservation projects. About half of the people sampled (54%) were unaware of the nearest project. Awareness of interviewees varied substantially among projects (28-78%). Apart from gaining awareness of projects through membership of natural history groups (43%), many respondents heard of projects through friends and relatives (20%), rather than through media such as newspapers (14%) and television (2.3%). We demonstrate that community-based projects can be quantitatively and critically assessed for awareness. The use of rapid, cost-effective assessments of awareness levels has application in many conservation projects. <br /

Measurement of the Strong Coupling Constant from Inclusive Jet Production at the Tevatron pˉp\bar pp Collider

We report a measurement of the strong coupling constant, $\alpha_s(M_Z)$, extracted from inclusive jet production in $p\bar{p}$ collisions at $\sqrt{s}=$1800 GeV. The QCD prediction for the evolution of $\alpha_s$ with jet transverse energy $E_T$ is tested over the range 40<$E_T$<450 GeV using $E_T$ for the renormalization scale. The data show good agreement with QCD in the region below 250 GeV. In the text we discuss the data-theory comparison in the region from 250 to 450 GeV. The value of $\alpha_s$ at the mass of the $Z^0$ boson averaged over the range 40<$E_T$<250 GeV is found to be $\alpha_s(M_{Z})= 0.1178 \pm 0.0001{(\rm stat)}^{+0.0081}_{-0.0095}{\rm (exp. syst)}$. The associated theoretical uncertainties are mainly due to the choice of renormalization scale (^{+6%}_{-4%}) and input parton distribution functions (5%).Comment: 7 pages, 3 figures, using RevTeX. Submitted to Physical Review Letter

Site-specific protein modification using immobilized sortase in batch and continuous-flow systems

Transpeptidation catalyzed by ​sortase A allows the preparation of proteins that are site-specifically and homogeneously modified with a wide variety of functional groups, such as fluorophores, PEG moieties, lipids, glycans, bio-orthogonal reactive groups and affinity handles. This protocol describes immobilization of ​sortase A on a solid support (Sepharose beads). Immobilization of ​sortase A simplifies downstream purification of a protein of interest after labeling of its N or C terminus. Smaller batch and larger-scale continuous-flow reactions require only a limited amount of enzyme. The immobilized enzyme can be reused for multiple cycles of protein modification reactions. The described protocol also works with a Ca²⁺-independent variant of ​sortase A with increased catalytic activity. This heptamutant variant of ​sortase A (7M) was generated by combining previously published mutations, and this immobilized enzyme can be used for the modification of calcium-senstive substrates or in instances in which low temperatures are needed. Preparation of immobilized ​sortase A takes 1–2 d. Batch reactions take 3–12 h and flow reactions proceed at 0.5 ml h⁻¹, depending on the geometry of the reactor used.United States. National Institutes of Health (RO1 AI087879