Outer crust of a cold non-accreting magnetar

The outer crust structure and composition of a cold, non-accreting magnetar is studied. We model the outer crust to be made of fully equilibrated matter where ionized nuclei form a Coulomb crystal embedded in an electron gas. The main effects of the strong magnetic field are those of quantizing the electron motion in Landau levels and of modifying the nuclear single particle levels producing, on average, an increased binding of nucleons in nuclei present in the Coulomb lattice. The effect of an homogeneous and constant magnetic field on nuclear masses has been predicted by using a covariant density functional, in which induced currents and axial deformation due to the presence of a magnetic field that breaks time-reversal symmetry have been included self-consistently in the nucleon and meson equations of motion. Although not yet observed, for $B\gtrsim 10^{16}$G both effects contribute to produce different compositions and to enlarge the range of pressures typically present in common neutron stars. Specifically, in such a regime, the magnetic field effects on nuclei favor the appearance of heavier nuclei at low pressures. As $B$ increases, such heavier nuclei are also preferred up to larger pressures. In the most extreme case, the whole outer crust is almost made of ${}_{40}^{92}$Zr$_{52}$.Comment: Published versio

Power-enhanced multiple decision functions controlling family-wise error and false discovery rates

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the \v{S}id\'ak procedure for FWER control and the Benjamini--Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual $p$-values, as is the case, for example, with the \v{S}id\'ak, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing $p$-value based procedures whose theoretical validity is contingent on each of these $p$-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional "large $M$, small $n$" data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.Comment: Published in at http://dx.doi.org/10.1214/10-AOS844 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A formula for charmonium suppression

In this work a formula for charmonium suppression obtained by Matsui in 1989 is analytically generalized for the case of complex c-cbar potential described by a 3-dimensional and isotropic time-dependent harmonic oscillator (THO). It is suggested that under certain conditions the formula can be applied to describe J/\psi suppression in heavy-ion collisions at CERN-SPS, RHIC, and LHC with the advantage of analytical tractability.Comment: 4 pages, no figures, to appear in Phys. At. Nucl., vol. 7

Description of nuclear systems with a self-consistent configuration-mixing approach. I: Theory, algorithm, and application to the 12^{12}C test nucleus

Although self-consistent multi-configuration methods have been used for decades to address the description of atomic and molecular many-body systems, only a few trials have been made in the context of nuclear structure. This work aims at the development of such an approach to describe in a unified way various types of correlations in nuclei, in a self-consistent manner where the mean-field is improved as correlations are introduced. The goal is to reconcile the usually set apart Shell-Model and Self-Consistent Mean-Field methods. This approach is referred as "variational multiparticle-multihole configuration mixing method". It is based on a double variational principle which yields a set of two coupled equations that determine at the same time the expansion coefficients of the many-body wave function and the single particle states. The formalism is derived and discussed in a general context, starting from a three-body Hamiltonian. Links to existing many-body techniques such as the formalism of Green's functions are established. First applications are done using the two-body D1S Gogny effective force. The numerical procedure is tested on the $^{12}$C nucleus in order to study the convergence features of the algorithm in different contexts. Ground state properties as well as single-particle quantities are analyzed, and the description of the first $2^+$ state is examined. This study allows to validate our numerical algorithm and leads to encouraging results. In order to test the method further, we will realize in the second article of this series, a systematic description of more nuclei and observables obtained by applying the newly-developed numerical procedure with the same Gogny force. As raised in the present work, applications of the variational multiparticle-multihole configuration mixing method will however ultimately require the use of an extended and more constrained Gogny force.Comment: 22 pages, 18 figures, accepted for publication in Phys. Rev. C. v2: minor corrections and references adde

Analysis of Fantasy Fiction Series of Sarah J. Maas: A Court of Thorns and Roses

This thesis offers a feminist interpretation of A Court of Thorns and Roses, a series by Sarah J. Maas. The fantasy fiction series began publication in 2015 and released its companion book in 2018. Protagonist Feyre navigates values about femininity and masculinity, breaking standards, as she develops throughout the series to change the fae and human worlds. Feyre stands up to inequality and helps others, both human and fae, to make peace instead of war. This analysis uncovers the gender roles, literary elements, and fairy tale influences on the series A Court of Thorns and Roses. Prominent symbolism involves masks, hands, and wounds. Feyre’s new powers as High Fae have parallels with gender issues, such as how the ability to shapeshift is like her ability to shift between and to combine the masculine and feminine spheres. Through Feyre’s experiences and transformation from human to fae, Maas shows a heightened version of social issues that many young adults face, thus providing readers with assurance that their responses to trauma are valid. Filling a gap in literary scholarship about contemporary young adult literature, this thesis demonstrates the value of analyzing popular literature such as the works of Sarah J. Maas

High-performance functional renormalization group calculations for interacting fermions

We derive a novel computational scheme for functional Renormalization Group (fRG) calculations for interacting fermions on 2D lattices. The scheme is based on the exchange parametrization fRG for the two-fermion interaction, with additional insertions of truncated partitions of unity. These insertions decouple the fermionic propagators from the exchange propagators and lead to a separation of the underlying equations. We demonstrate that this separation is numerically advantageous and may pave the way for refined, large-scale computational investigations even in the case of complex multiband systems. Furthermore, on the basis of speedup data gained from our implementation, it is shown that this new variant facilitates efficient calculations on a large number of multi-core CPUs. We apply the scheme to the $t$,$t'$ Hubbard model on a square lattice to analyze the convergence of the results with the bond length of the truncation of the partition of unity. In most parameter areas, a fast convergence can be observed. Finally, we compare to previous results in order to relate our approach to other fRG studies.Comment: 26 pages, 9 figure

Outlier Detection Using Nonconvex Penalized Regression

This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the $n$ data points. We then apply a regularization favoring a sparse vector of mean shift parameters. The usual $L_1$ penalty yields a convex criterion, but we find that it fails to deliver a robust estimator. The $L_1$ penalty corresponds to soft thresholding. We introduce a thresholding (denoted by $\Theta$) based iterative procedure for outlier detection ($\Theta$-IPOD). A version based on hard thresholding correctly identifies outliers on some hard test problems. We find that $\Theta$-IPOD is much faster than iteratively reweighted least squares for large data because each iteration costs at most $O(np)$ (and sometimes much less) avoiding an $O(np^2)$ least squares estimate. We describe the connection between $\Theta$-IPOD and $M$-estimators. Our proposed method has one tuning parameter with which to both identify outliers and estimate regression coefficients. A data-dependent choice can be made based on BIC. The tuned $\Theta$-IPOD shows outstanding performance in identifying outliers in various situations in comparison to other existing approaches. This methodology extends to high-dimensional modeling with $p\gg n$, if both the coefficient vector and the outlier pattern are sparse