Larson's third law and the universality of molecular cloud structure

Larson (1981) first noted a scaling relation between masses and sizes in molecular clouds that implies that these objects have approximately constant column densities. This original claim, based upon millimeter observations of carbon monoxide lines, has been challenged by many theorists, arguing that the apparent constant column density observed is merely the result of the limited dynamic range of observations, and that in reality clouds have column density variations over two orders of magnitudes. In this letter we investigate a set of nearby molecular clouds with near-infrared excess methods, which guarantee very large dynamic ranges and robust column density measurements, to test the validity of Larson's third law. We verify that different clouds have almost identical average column densities above a given extinction threshold; this holds regardless of the extinction threshold, but the actual average surface mass density is a function of the specific threshold used. We show that a second version of Larson's third law, involving the mass-radius relation for single clouds and cores, does not hold in our sample, indicating that individual clouds are not objects that can be described by constant column density. Our results instead indicate that molecular clouds are characterized by a universal structure. Finally we point out that this universal structure can be linked to the log-normal nature of cloud column density distributions.Comment: 5 pages, 4 figures, A&A in press (letter

Spitzer Warm Mission Workshop Introduction

The Spitzer Warm Mission Workshop was held June 4–5, 2007, to explore the science drivers for the warm Spitzer mission and help the Spitzer Science Center develop a new science operations philosophy. We must continue to maximize the science return with the reduced resources available, both using (a) the shortest two IRAC channels, and (b) archival research with the rich Spitzer archive. This paper summarizes the overview slides presented to the workshop participant

Fitting density models to observational data - The local Schmidt law in molecular clouds

We consider the general problem of fitting a parametric density model to discrete observations, taken to follow a non-homogeneous Poisson point process. This class of models is very common, and can be used to describe many astrophysical processes, including the distribution of protostars in molecular clouds. We give the expression for the likelihood of a given spatial density distribution of protostars and apply it to infer the most probable dependence of the protostellar surface density on the gas surface density. Finally, we apply this general technique to model the distribution of protostars in the Orion molecular cloud and robustly derive the local star formation scaling (Schmidt) law for a molecular cloud. We find that in this cloud the protostellar surface density, $\Sigma_\mathrm{YSO}$, is directly proportional to the square gas column density, here expressed as infrared extinction in the $K$-band, $A_K$: more precisely, $\Sigma_\mathrm{YSO} = (1.65 \pm 0.19) A_K^{(2.03 \pm 0.15)}$ stars pc$^{-2}$.Comment: 6 pages, A&A in press. References fixe

On the fidelity of the core mass functions derived from dust column density data

Aims: We examine the recoverability and completeness limits of the dense core mass functions (CMFs) derived for a molecular cloud using extinction data and a core identification scheme based on two-dimensional thresholding. Methods: We performed simulations where a population of artificial cores was embedded into the variable background extinction field of the Pipe nebula. We extracted the cores from the simulated extinction maps, constructed the CMFs, and compared them to the input CMFs. The simulations were repeated using a variety of extraction parameters and several core populations with differing input mass functions and differing degrees of crowding. Results: The fidelity of the observed CMF depends on the parameters selected for the core extraction algorithm for our background. More importantly, it depends on how crowded the core population is. We find that the observed CMF recovers the true CMF reliably when the mean separation of cores is larger than their mean diameter (f>1). If this condition holds, the derived CMF is accurate and complete above M > 0.8-1.5 Msun, depending on the parameters used for the core extraction. In the simulations, the best fidelity was achieved with the detection threshold of 1 or 2 times the rms-noise of the extinction data, and with the contour level spacings of 3 times the rms-noise. Choosing larger threshold and wider level spacings increases the limiting mass. The simulations show that when f>1.5, the masses of individual cores are recovered with a typical uncertainty of 25-30 %. When f=1 the uncertainty is ~60 %. In very crowded cases where f<1 the core identification algorithm is unable to recover the masses of the cores adequately. For the cores of the Pipe nebula f~2.0 and therefore the use of the method in that region is justified.Comment: 9 pages, 6 figures, accepted for publication in A&

Hipparcos distances of Ophiuchus and Lupus cloud complexes

We combine extinction maps from the Two Micron All Sky Survey (2MASS) with Hipparcos and Tycho parallaxes to obtain reliable and high-precision estimates of the distance to the Ophiuchus and Lupus dark complexes. Our analysis, based on a rigorous maximum-likelihood approach, shows that the rho-Ophiuchi cloud is located at (119 +/- 6) pc and the Lupus complex is located at (155 +/- 8) pc; in addition, we are able to put constraints on the thickness of the clouds and on their orientation on the sky (both these effects are not included in the error estimate quoted above). For Ophiuchus, we find some evidence that the streamers are closer to us than the core. The method applied in this paper is currently limited to nearby molecular clouds, but it will find many natural applications in the GAIA-era, when it will be possible to pin down the distance and three-dimensional structure of virtually every molecular cloud in the Galaxy.Comment: A&A in press - Corrected typo (Lupus distance) in the electronic abstrac

Forecasting economic growth in the euro area during the Great Moderation and the Great Recession

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). We estimate backcasts, nowcasts and forecasts for GDP, components of GDP, and GDP of all individual euro area members, and examine forecasts for periods of low and high economic volatility (more specifically, we consider 2002-2007, which falls into the ‘Great Moderation’, and the ‘Great Recession’ 2008-2009). We find that all models consistently beat naive AR benchmarks, and overall, the dynamic factor model tends to outperform the PMI model (at times by a wide margin). However, accuracy of the dynamic factor model can be uneven (forecasts for some countries have large errors), with the PMI model dominating clearly for some countries or over some horizons. This is particularly pronounced over the Great Recession, where the dynamic factor model dominates the PMI model for backcasts, but has considerable difficulties beating the PMI model for nowcasts. This suggests that survey-based measures can have considerable advantages in responding to changes during very volatile periods, whereas factor models tend to be more sluggish to adjust. JEL Classification: C50, C53, E37, E47dynamic factor model, forecasting, PMI model

(Un)naturally low? Sequential Monte Carlo tracking of the US natural interest rate

Following the 2000 stockmarket crash, have US interest rates been held "too low" in relation to their natural level? Most likely, yes. Using a structural neo-Keynesian model, this paper attempts a real-time evaluation of the US monetary policy stance while ensuring consistency between the specification of price adjustments and the evolution of the econ- omy under flexible prices. To do this, the model's likelihood function is evaluated using a Sequential Monte Carlo algorithm providing inference about the time-varying distribution of structural parameters and unobservable, nonstationary state variables. Tracking down the evolution of underlying stochastic processes in real time is found crucial (i) to explain postwar Fed's policy and (ii) to replicate salient features of the data. JEL Classification: E43, C11, C15Bayesian Analysis, DSGE Models, Natural Interest Rate, Particle Filters

Experimental study of main rotor tip geometry and tail rotor interactions in hover. Volume 1. Text and figures

A model scale hover test was conducted in the Sikorsky Aircraft Model rotor hover Facility to identify and quantify the impact of the tail rotor on the demonstrated advantages of advanced geometry tip configurations. The test was conducted using the Basic Model Test Rig and two scaled main rotor systems, one representing a 1/5.727 scale UH-60A BLACK HAWK and the others a 1/4.71 scale S-76. Eight alternate rotor tip configurations were tested, 3 on the BLACK HAWK rotor and 6 on the S-76 rotor. Four of these tips were then selected for testing in close proximity to an operating tail rotor (operating in both tractor and pusher modes) to determine if the performance advantages that could be obtained from the use of advanced geometry tips in a main rotor only environment would still exist in the more complex flow field involving a tail rotor. The test showed that overall the tail rotor effects on the advanced tip configurations tested are not substantially different from the effects on conventional tips

‘Lean’ versus ‘Rich’ Data Sets: Forecasting during the Great Moderation and the Great Recession

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). We estimate backcasts, nowcasts and forecasts for GDP, components of GDP, and GDP of all individual euro area members, and examine forecasts for the ‘Great Moderation’ (2000-2007) and the ‘Great Recession’ (2008-2009) separately. All models consistently beat naïve AR benchmarks. More data does not necessarily improve forecasting accuracy: For the factor model, adding monthly indicators from national economies can lead to more uneven forecasting accuracy, notably when forecasting components of euro area GDP during the Great Recession. This suggests that the merits of national data may reside in better estimation of heterogeneity across GDP components, rather than in improving headline GDP forecasts for individual euro area countries. Comparing factor models to the much simpler PMI model, we find that the dynamic factor model dominates the latter during the Great Moderation. However, during the Great Recession, the PMI model has the advantage that survey-based measures respond faster to changes in the outlook, whereas factor models are more sluggish in adjusting. Consequently, the dynamic factor model has relatively more difficulties beating the PMI model, with relatively large errors in forecasting some countries or components of euro area GDP.Econometric and statistical methods; International topics

External shocks and international inflation linkages: a global VAR analysis

Amid the recent commodity price gyrations, policy makers have become increasingly concerned in assessing to what extent oil and food price shocks transmit to the inflationary outlook and the real economy. In this paper, we try to tackle this issue by means of a Global Vector Autoregressive (GVAR) model. We first examine the short-run inflationary effects of oil and food price shocks on a given set of countries. Secondly, we assess the importance of inflation linkages among countries, by dis-entangling the geographical sources of inflationary pressures for each region. Generalized impulse response functions reveal that the direct inflationary effects of oil price shocks affect mostly developed countries while less sizeable effects are observed for emerging economies. Food price increases also have significative inflationary direct effects, but especially for emerging economies. Moreover, significant second-round effects are observed in some countries. Generalized forecast error variance decompositions indicate that considerable linkages through which inflationary pressures spill over exist among regions. In addition, a considerable part of the observed headline inflation rises is attributable to foreign sources for the vast majority of the regions. JEL Classification: C32, E31commodity prices, Global VAR, inflation, oil shock, second-round effects