Magnetism and Mott Transition: A Slave-rotor Study

Motivated by the debate of spin-density-wave (SDW) versus local-moment (LM) picture in the iron-based superconducting (FeSC) materials, we consider a two-band orbital-symmetric Hubbard model in which there is robust Fermi surface nesting at $(\pi,0)$. We obtain the phase diagram of such system by a mean-field slave-rotor approach, in which the Fermi surface nesting and the SDW order are explicitly taken into account via a natural separation of scale between the Hund's coupling and the Coulomb interaction. We find that for a sizable range of Hund's coupling the Mott transition acquires a strong first-order character, but there also exists a small range of stronger Hund's coupling in which an enhancement of magnetization can be observed on the SDW side. We interpret the former scenario as one in which a sharp distinction can be drawn between LM and the SDW picture, and the latter scenario as one in which signs of LM physics begin to develop in the metallic phase. It is tempting to suggest that some FeSC materials are in the vicinity of the latter scenario.Comment: 7 pages, 5 figures; v2: Added discussions on anisotropy in renormalized hopping, clarifications and discussions with regard to orbital order, new inset in Fig. 3(d), expanded and revised bibliography, plus other minor revisions. Accepted to PR

Inventories and Optimal Monetary Policy

We introduce inventories into a standard New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model to study the effect on the design of optimal monetary policy. The possibility of inventory investment changes the transmission mechanism in the model by decoupling production from final consumption. This allows for a higher degree of consumption smoothing since firms can add excess production to their inventory holdings. We consider both Ramsey optimal monetary policy and a monetary policy that maximizes consumer welfare over a set of simple interest rate feedback rules. We find that in contrast to a model without inventories, Ramsey-optimal monetary policy in a model with inventories deviates from complete inflation stabilization. In the standard model, nominal price rigidity is a deadweight loss on the economy, which an optimizing policymaker attempts to remove. With inventories, a planner can reduce consumption volatility and raise welfare by accumulating inventories and letting prices change as an equilibrating mechanism. We find also find that the application of simple rules comes very close to replicating Ramsey optimal outcomes.Ramsey policy, New Keynesian model

Deep Habits in the New Keynesian Phillips Curve

We derive and estimate a New Keynesian Phillips curve (NKPC) in a model where consumers are assumed to have deep habits. Habits are deep in the sense that they apply to individual consumption goods instead of aggregate consumption. This alters the NKPC in a fundamental manner as it introduces expected and contemporaneous consumption growth as well as the expected marginal value of future demand as additional driving forces for inflation dynamics. We construct the driving process in the deep habits NKPC by using the model’s optimality conditions to impute time series for unobservable variables. The resulting series is considerably more volatile than unit labor cost. General Methods of Moments (GMM) estimation of the NKPC shows an improved fit and a much lower degree of indexation than in the standard NKPC. Our analysis also reveals that the crucial parameters for the performance of the deep habit NKPC are the habit parameter and the substitution elasticity between differentiated products. The results are broadly robust to alternative specifications.

Inventories, Inflation Dynamics and the New Keynesian Phillips Curve

We introduce inventories into an otherwise standard New Keynesian model and study the implications for in.ation dynamics. Inventory holdings are motivated as a means to generate sales for demand-constrained .rms. We derive various representa- tions of the New Keynesian Phillips curve with inventories and show that one of these speci.cations is observationally equivalent to the standard model with respect to the behavior of in.ation when the model.s cross-equation restrictions are imposed. How- ever, the driving variable in the New Keynesian Phillips curve - real marginal cost - is unobservable and has to be proxied by, for instance, unit labor costs. An alternative approach is to impute marginal cost by using the model.s optimality conditions. We show that the stock-sales ratio is linked to marginal cost. We also estimate these various speci.cations of the New Keynesian Phillips curve using GMM. We .nd that predictive power of the inventory-speci.cation at best approaches that of the standard model, but does not improve upon it. We conclude that inventories do not play a role in explaining in.ation dynamics within our New Keynesian Phillips curve framework.

Compilation of detection sensitivities in thermal-neutron activation

Detection sensitivities of the chemical elements following thermal-neutron activation have been compiled from the available experimental cross sections and nuclear properties and presented in a concise and usable form. The report also includes the equations and nuclear parameters used in the calculations

Acute fetal anemia diagnosed by middle cerebral artery Doppler velocimetry in stage v twin-twin transfusion syndrome.

In stage V twin-twin transfusion syndrome (TTTS), up to 50% of surviving twins die or experience permanent disabilities, likely due to acute intertwin hemorrhage resulting in sudden severe anemia of the survivor. Although fetal middle cerebral artery (MCA) Doppler studies demonstrate strong correlation with fetal hemoglobin values, acute hemorrhagic events are more difficult to diagnose, and optimal timing of delivery of the survivor poses an obstetric dilemma. We report a case of newly diagnosed stage V TTTS at 28 weeks gestation, complicated by acute severe anemia diagnosed by significantly abnormal fetal MCA Doppler studies. The anemic twin was urgently delivered and is doing well without significant sequelae

Physics case of the very high energy electron--proton collider, VHEeP

The possibility of a very high energy electron-proton (VHEeP) collider with a centre-of-mass energy of 9 TeV has been presented at previous workshops. These proceedings briefly summarise the VHEeP concept, which was recently published, and developments since then, as well as future directions. At the VHEeP collider, with a centre-of-mass energy 30 times greater than HERA, parton momentum fractions, $x$, down to about $10^{-8}$ are accessible for photon virtualities, $Q^2$, of 1 GeV$^2$. This extension in the kinematic range to low $x$ complements proposals for other electron-proton or electron-ion colliders.Comment: 6 pages, 2 figures, for proceedings of DIS 2017 worksho

Initiation of HIV therapy

In this paper, we numerically show that the dynamics of the HIV system is sensitive to both the initial condition and the system parameters. These phenomena imply that the system is chaotic and exhibits a bifurcation behavior. To control the system, we propose to initiate an HIV therapy based on both the concentration of the HIV-1 viral load and the ratio of the CD4 lymphocyte population to the CD8 lymphocyte population. If the concentration of the HIV-1 viral load is higher than a threshold, then the first type of therapy will be applied. If the concentration of the HIV-1 viral load is lower than or equal to the threshold and the ratio of the CD4 lymphocyte population to the CD8 lymphocyte population is greater than another threshold, then the second type of therapy will be applied. Otherwise, no therapy will be applied. The advantages of the proposed control strategy are that the therapy can be stopped under certain conditions, while the state variables of the overall system is asymptotically stable with fast convergent rate, the concentration of the controlled HIV-1 viral load is monotonic decreasing, as well as the positivity constraint of the system states and that of the dose concentration is guaranteed to be satisfied. Computer numerical simulation results are presented for an illustration

From EM to Data Augmentation: The Emergence of MCMC Bayesian Computation in the 1980s

It was known from Metropolis et al. [J. Chem. Phys. 21 (1953) 1087--1092] that one can sample from a distribution by performing Monte Carlo simulation from a Markov chain whose equilibrium distribution is equal to the target distribution. However, it took several decades before the statistical community embraced Markov chain Monte Carlo (MCMC) as a general computational tool in Bayesian inference. The usual reasons that are advanced to explain why statisticians were slow to catch on to the method include lack of computing power and unfamiliarity with the early dynamic Monte Carlo papers in the statistical physics literature. We argue that there was a deeper reason, namely, that the structure of problems in the statistical mechanics and those in the standard statistical literature are different. To make the methods usable in standard Bayesian problems, one had to exploit the power that comes from the introduction of judiciously chosen auxiliary variables and collective moves. This paper examines the development in the critical period 1980--1990, when the ideas of Markov chain simulation from the statistical physics literature and the latent variable formulation in maximum likelihood computation (i.e., EM algorithm) came together to spark the widespread application of MCMC methods in Bayesian computation.Comment: Published in at http://dx.doi.org/10.1214/10-STS341 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org