1,662 research outputs found
The sizes of BLRs and BH masses of double-peaked broad low-ionization emission line objects
In this paper, the sizes of the BLRs and BH masses of DouBle-Peaked broad
low-ionization emission line emitters (dbp emitters) are compared using
different methods: virial BH masses vs BH masses from stellar velocity
dispersions, the size of BLRs from the continuum luminosity vs the size of BLRs
from the accretion disk model. First, the virial BH masses of dbp emitters
estimated by the continumm luminosity and line width of broad H are
about six times (a much larger value, if including another dbp emitters, of
which the stellar velocity dispersions are traced by the line widths of narrow
emission lines) larger than the BH masses estimated from the relation which is a more accurate relation to estimate BH masses. Second, the
sizes of the BLRs of dbp emitters estimated by the empirical relation of
are about three times (a much larger value, if
including another dbp emitters, of which the stellar velocity dispersions are
traced by the line widths of narrow emission lines) larger than the mean
flux-weighted sizes of BLRs of dbp emitters estimated by the accretion disk
model. The higher electron density of BLRs of dbp emitters would be the main
reason which leads to smaller size of BLRs than the predicted value from the
continuum luminosity.Comment: 7 pages, two figures and one table. Accepted by MNRA
Less is Better: Recovering Intended-Feature Subspace to Robustify NLU Models
Datasets with significant proportions of bias present threats for training a
trustworthy model on NLU tasks. Despite yielding great progress, current
debiasing methods impose excessive reliance on the knowledge of bias
attributes. Definition of the attributes, however, is elusive and varies across
different datasets. Furthermore, leveraging these attributes at input level to
bias mitigation may leave a gap between intrinsic properties and the underlying
decision rule. To narrow down this gap and liberate the supervision on bias, we
suggest extending bias mitigation into feature space. Therefore, a novel model,
Recovering Intended-Feature Subspace with Knowledge-Free (RISK) is developed.
Assuming that shortcut features caused by various biases are unintended for
prediction, RISK views them as redundant features. When delving into a lower
manifold to remove redundancies, RISK reveals that an extremely low-dimensional
subspace with intended features can robustly represent the highly biased
dataset. Empirical results demonstrate our model can consistently improve model
generalization to out-of-distribution set, and achieves a new state-of-the-art
performance.Comment: Acceptted by COLING 202
The Correlation Between Spectral Index And Accretion Rate For AGN
In this paper, we present a correlation between the spectral index
distribution (SED) and the dimensionless accretion rate defined as
for AGN. This quantity is used as a substitute of
the physical accretion rate. We select 193 AGN with both broad H and
broad H, and with absorption lines near MgI from SDSS
DR4. We determine the spectral index and dimensionless accretion rate after
correcting for both host galaxy contribution and internal reddening effects. A
correlation is found between the optical spectral index and the dimensionless
accretion rate for AGN, including low luminosity AGN ( sometimes called "dwarf AGN" (Ho et al. 1997)). The existence
of this correlation provides an independent method to estimate the central BH
masses for all types of AGN. We also find that there is a different correlation
between the spectral index and the BH masses for normal AGN and low luminosity
AGN, which is perhaps due to the different accretion modes in these two types
of nuclei. This in turn may lead to the different correlations between BH
masses and optical continuum luminosity reported previously (Zhang et al.
2007a), which invalidates the application of the empirical relationship found
by Kaspi et al. (2000, 2005) to low luminosity AGN in order to determine their
BLR sizes.Comment: 10 pages, 7 figures, accepted for publication in MNRA
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