Thermodynamics of the Antiferromagnetic Heisenberg Model on the Checkerboard Lattice

Employing numerical linked-cluster expansions (NLCEs) along with exact diagonalizations of finite clusters with periodic boundary condition, we study the energy, specific heat, entropy, and various susceptibilities of the antiferromagnetic Heisenberg model on the checkerboard lattice. NLCEs, combined with extrapolation techniques, allow us to access temperatures much lower than those accessible to exact diagonalization and other series expansions. We find that the high-temperature peak in specific heat decreases as the frustration increases, consistent with the large amount of unquenched entropy in the region around maximum classical frustration, where the nearest-neighbor and next-nearest neighbor exchange interactions (J and J', respectively) have the same strength, and with the formation of a second peak at lower temperatures. The staggered susceptibility shows a change of character when J' increases beyond 0.75J, implying the disappearance of the long-range antiferromagnetic order at zero temperature. For J'=4J, in the limit of weakly coupled crossed chains, we find large susceptibilities for stripe and Neel order with Q=(pi/2,pi/2) at low temperatures with antiferromagnetic correlations along the chains. Other magnetic and bond orderings, such as a plaquette valence-bond solid and a crossed-dimer order suggested by previous studies, have also been investigated.Comment: 10 pages, 13 figure

Sub-Inertial Gravity Modes in the B8V Star KIC 7760680 Reveal Moderate Core Overshooting and Low Vertical Diffusive Mixing

KIC 7760680 is so far the richest slowly pulsating B star, by exhibiting 36 consecutive dipole ($\ell=1$) gravity (g-) modes. The monotonically decreasing period spacing of the series, in addition to the local dips in the pattern confirm that KIC 7760680 is a moderate rotator, with clear mode trapping in chemically inhomogeneous layers. We employ the traditional approximation of rotation to incorporate rotational effects on g-mode frequencies. Our detailed forward asteroseismic modelling of this g-mode series reveals that KIC 7760680 is a moderately rotating B star with mass $\sim3.25$ M$_\odot$. By simultaneously matching the slope of the period spacing, and the number of modes in the observed frequency range, we deduce that the equatorial rotation frequency of KIC 7760680 is 0.4805 day$^{-1}$, which is 26\% of its Roche break up frequency. The relative deviation of the model frequencies and those observed is less than one percent. We succeed to tightly constrain the exponentially-decaying convective core overshooting parameter to $f_{\rm ov}\approx0.024\pm0.001$. This means that convective core overshooting can coexist with moderate rotation. Moreover, models with exponentially-decaying overshoot from the core outperform those with the classical step-function overshoot. The best value for extra diffusive mixing in the radiatively stable envelope is confined to $\log D_{\rm ext}\approx0.75\pm0.25$ (with $D_{\rm ext}$ in cm$^2$ sec$^{-1}$), which is notably smaller than theoretical predictions.Comment: 12 Figures, 2 Tables, all data publicly available for download; accepted for publication in Astrophysical Journa

Accounting for the tongue-and-groove effect using a robust direct aperture optimization approach

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98733/1/MPH001266.pd

Optimal Privacy-Aware Dynamic Estimation

In this paper, we develop an information-theoretic framework for the optimal privacy-aware estimation of the states of a (linear or nonlinear) system. In our setup, a private process, modeled as a first-order Markov chain, derives the states of the system, and the state estimates are shared with an untrusted party who might attempt to infer the private process based on the state estimates. As the privacy metric, we use the mutual information between the private process and the state estimates. We first show that the privacy-aware estimation is a closed-loop control problem wherein the estimator controls the belief of the adversary about the private process. We also derive the Bellman optimality principle for the optimal privacy-aware estimation problem, which is used to study the structural properties of the optimal estimator. We next develop a policy gradient algorithm, for computing an optimal estimation policy, based on a novel variational formulation of the mutual information. We finally study the performance of the optimal estimator in a building automation application