Analysis and Optimization of Deep Counterfactual Value Networks

Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future states predicted by deep neural networks. This paper analyzes new ways of encoding the inputs and outputs of DeepStack's deep counterfactual value networks based on traditional abstraction techniques, as well as an unabstracted encoding, which was able to increase the network's accuracy.Comment: Long version of publication appearing at KI 2018: The 41st German Conference on Artificial Intelligence (http://dx.doi.org/10.1007/978-3-030-00111-7_26). Corrected typo in titl

The transition from COVID-19 infections to deaths: Do governance quality and corruption affect it?

We investigate the impact of governance quality and corruption on the propensity of COVID-19 infections to result in deaths, while controlling for a wide range of socio-economic country characteristics, for 139 countries. Governance quality is negatively associated with mortality from COVID-19, for a given number of infections. This result holds for the aggregate governance index and for most of its components, in particular government effectiveness, rule of law, and control of corruption. Corruption among business executives, judges and magistrates, the legislature, and among government officials exerts the largest impact on COVID-induced deaths. We propose directions for future policy initiatives

Status of experimental knowledge on the unbound nucleus 13Be

The structure of the unbound nucleus 13Be is important for understanding the Borromean, two-neutron halo nucleus 14Be. The experimental studies conducted over the last four decades are reviewed in the context of the beryllium chain of isotopes and some significant theoretical studies. The focus of this paper is the comparison of new data from a 12Be(d,p) reaction in inverse kinematics, which was analyzed using Geant4 simulations and a Bayesian fitting procedure, with previous measurements. Two possible scenarios to explain the strength below 1 MeV above the neutron separation energy were proposed in that study: a single p-wave resonance or a mixture of an s-wave virtual state with a weaker p- or d-wave resonance. Comparisons of recent invariant mass and the (d,p) experiments show good agreement between the transfer measurement and the two most recent high-energy nucleon removal measurements

Inelastic scattering of protons from 6,8^{6,8}He and 7,11^{7,11}Li in a folding model approach

The proton-inelastic scattering from $^{6,8}$He and $^{7,11}$Li nuclei are studied in a folding model approach. A finite-range, momentum, density and isospin dependent nucleon-nucleon interaction (SBM) is folded with realistic density distributions of the above nuclei. The renormalization factors N$_R$ and N$_I$ on the real and volume imaginary part of the folded potentials are obtained by analyzing the respective elastic scattering data and kept unaltered for the inelastic analysis at the same energy. The form factors are generated by taking derivatives of the folded potentials and therefore required renormalizations. The $\beta$ values are extracted by fitting the p + $^{6,8}$He,$^{7,11}$Li inelastic angular distributions. The present analysis of p + $^8$He inelastic scattering to the 3.57 MeV excited state, including unpublished forward angle data (RIKEN) confirms L = 2 transition. Similar analysis of the p + $^6$He inelastic scattering angular distribution leading to the 1.8 MeV (L = 2) excited state fails to satisfactorily reproduce the data.Comment: one LaTeX file, five PostScript figure

Probing Nonlocal Spatial Correlations in Quantum Gases with Ultra-long-range Rydberg Molecules

We present photo-excitation of ultra-long-range Rydberg molecules as a probe of spatial correlations in quantum gases. Rydberg molecules can be created with well-defined internuclear spacing, set by the radius of the outer lobe of the Rydberg electron wavefunction $R_n$. By varying the principal quantum number $n$ of the target Rydberg state, the molecular excitation rate can be used to map the pair-correlation function of the trapped gas $g^{(2)}(R_n)$. We demonstrate this with ultracold Sr gases and probe pair-separation length scales ranging from $R_n = 1400 - 3200$ $a_0$, which are on the order of the thermal de Broglie wavelength for temperatures around 1 $\mu$K. We observe bunching for a single-component Bose gas of $^{84}$Sr and anti-bunching due to Pauli exclusion at short distances for a polarized Fermi gas of $^{87}$Sr, revealing the effects of quantum statistics.Comment: 6 pages, 5 figure

A new insight into the observation of spectroscopic strength reduction in atomic nuclei: implication for the physical meaning of spectroscopic factors

Experimental studies of one nucleon knockout from magic nuclei suggest that their nucleon orbits are not fully occupied. This conflicts a commonly accepted view of the shell closure associated with such nuclei. The conflict can be reconciled if the overlap between initial and final nuclear states in a knockout reaction are calculated by a non-standard method. The method employs an inhomogeneous equation based on correlation-dependent effective nucleon-nucleon (NN) interactions and allows the simplest wave functions, in which all nucleons occupy only the lowest nuclear orbits, to be used. The method also reproduces the recently established relation between reduction of spectroscopic strength, observed in knockout reactions on other nuclei, and nucleon binding energies. The implication of the inhomogeneous equation method for the physical meaning of spectroscopic factors is discussed.Comment: 4 pages, accepted by Phys. Rev. Let

Solving kk-means on High-dimensional Big Data

In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement. For the $k$-means problem, this has led to the development of several $(1+\varepsilon)$-approximations (under the assumption that $k$ is a constant), but also to the design of algorithms that are extremely fast in practice and compute solutions of high accuracy. However, when not only the length of the stream is high but also the dimensionality of the input points, then current methods reach their limits. We propose two algorithms, piecy and piecy-mr that are based on the recently developed data stream algorithm BICO that can process high dimensional data in one pass and output a solution of high quality. While piecy is suited for high dimensional data with a medium number of points, piecy-mr is meant for high dimensional data that comes in a very long stream. We provide an extensive experimental study to evaluate piecy and piecy-mr that shows the strength of the new algorithms.Comment: 23 pages, 9 figures, published at the 14th International Symposium on Experimental Algorithms - SEA 201