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

Abstract

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.

9 pages, 6 figures, accepted for publication in A&A

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Cited by in corpus (1)

• The Perils of Clumpfind: The Mass Spectrum of Sub-structures in Molecular Clouds