Index: trunk/doc/release.2015/ps1.diffs/diffs.tex
===================================================================
--- trunk/doc/release.2015/ps1.diffs/diffs.tex	(revision 40577)
+++ trunk/doc/release.2015/ps1.diffs/diffs.tex	(revision 40695)
@@ -63,11 +63,30 @@
 \section{Introduction}
 
-The age of synoptic surveys has come.  As optical (and other
-wavelength) telescopes are surveying ever increasing areas to ever
-fainter flux limits with multiple repeats, there is a growing interest
-in the study of transient phenomena.  This technological progress is
-well matched with the current scientific emphases on large samples of
-supernovae (SN), microlenses, asteroids, and other transients and
-variable sources.
+The past three decades have seen the increasing importance of
+time-domain surveys in astronomy.  These include asteroid searches
+such as the Lincoln Near-Earth Asteroid Research
+\citep[LINEAR][]{2000Icar..148...21S}, the Lowell Observatory
+Near-Earth Object Search \citep[LONEOS,][]{1995DPS....27.0110B}, the
+Catalina Sky Survey \citep{2003DPS....35.3604L}, and ATLAS
+\citep{2018PASP..130f4505T}; microlensing surveys such as MACHO
+\citep{1993ASPC...43..291A} and Optical Gravitational Lens Experiment
+\citep[OGLE,][]{1992AcA....42..253U}; and searches for supernovae and
+other transient sources such as ASAS-SN \citep{2014ApJ...788...48S}, the
+Palomar Transient Factory \citep[PTF,][]{2009PASP..121.1395L}, and the Robotic Optical
+Transient Search Experiment \citep[ROTSE-I,][]{2000ApJ...542..251A}.
+
+The Pan-STARRS Observatory \citep{chambers2017} has been a leader in
+the searches for both explosive transient / supernova and potentially
+hazardous asteroids.  According to the statistics maintained by David
+Bishop\footnote{http://www.rochesterastronomy.org/snimages/archives.html},
+since 2009, 40\% of all supernova have been discovered by
+Pan-STARRS\,1.  Similarly, 24\% of all Near Earth Objects (NEOs)
+discovered to date have been found by
+Pan-STARRS\footnote{https://cneos.jpl.nasa.gov/stats/site\_all.html}.
+Since 2014, when Pan-STARRS shifted its primary mission to the search
+for NEOs, this fraction has increased to 41\%. Both of these search
+programs use nightly observations to hunt for features which have
+changed, either between multiple images in a single night or between
+the current image and an archival reference image.
 
 PSF-matched image differencing\footnote{We eschew the popular term
@@ -88,5 +107,5 @@
 of the convolution kernel as a linear combination of basis functions,
 which allows the least-squares problem to be reduced to a matrix
-equation.  \citet{2000A&AS..144..363A} showed how this can be expanded
+equation.  \citet{2000AAS..144..363A} showed how this can be expanded
 to allow spatial variation of the kernel across the images.  Of
 course, the basis functions used for the kernel may be completely
@@ -137,5 +156,5 @@
 basis functions, $g_i(x,y) k_i(u,v)$, where the inclusion of
 $g_i(x,y)$ allows for spatial variation of the kernel.  In order to
-enforce conservation of flux \citep[following][]{2000A&AS..144..363A},
+enforce conservation of flux \citep[following][]{2000AAS..144..363A},
 we specify that all of the kernel basis functions have zero sum,
 $\sum_{u,v} k_i(u,v) = 0\ \forall i$.  This may be achieved by scaling
@@ -161,10 +180,10 @@
 $\chi^2$ between wide and narrow kernels.  Setting $c_i \equiv 0$ and
 $p_i \equiv 0$ reduces the above equation to the
-\citet{2000A&AS..144..363A} formalism, but with the normalisation
+\citet{2000AAS..144..363A} formalism, but with the normalisation
 ($b_0$) included explicitly.  In practise, the above sum will only be
 over small regions (known as ``stamps''), and if we assume that the
 spatial variation is not large, then we can simply use the coordinates
 of the stamp centres for the $g_i(x,y)$; this allows a faster
-calculation \citep{2000A&AS..144..363A}.
+calculation \citep{2000AAS..144..363A}.
 
 To simplify the equation, we write
@@ -199,5 +218,5 @@
 other special polynomial for the $f_i(x,y)$ and $g_i(x,y)$ is simple
 and convenient.  The kernel basis function sets of
-\citet{1998ApJ...503..325A} and \citet{2000A&AS..144..363A} are
+\citet{1998ApJ...503..325A} and \citet{2000AAS..144..363A} are
 \begin{equation}
 g_i(x,y) k_i'(u,v) = \psi_i x^\ell y^m u^p v^q \exp((u^2+v^2)/2s_i^2)
@@ -338,11 +357,13 @@
 \subsection{Stamps}
 
-The choice of stamps is key to successful PSF-matching --- the
-convolution kernel is only as good as the stamps used to construct it.
-We use a merged list of sources from photometry of the two input
-images as the basis of our stamps list.  Sources with a flag
-indicating that it is anything other than a pristine astrophysical
-source are excluded.  At the present time, we make no effort to select
-sources of a particular color or range of colors.
+Since we restrict the analysis of the kernel required for PSF matching
+to the small ``stamps'' centered on bright stars, the choice of stamps
+is key to successful PSF-matching.  The convolution kernel is only as
+good as the stamps used to construct it.  We use a merged list of
+sources from photometry of the two input images as the basis of our
+stamps list.  Sources with a flag indicating that it is anything other
+than a pristine astrophysical source are excluded.  At the present
+time, we make no effort to select sources of a particular color or
+range of colors.
 
 We exclude sources with any masked pixels that would affect the
@@ -490,5 +511,5 @@
 progressive software packages producing \citep[e.g.,
   SWarp:][]{2002ASPC..281..228B} and using \citep[e.g.,
-  SExtractor:][]{1996A&AS..117..393B} weight maps to characterise the
+  SExtractor:][]{1996AAS..117..393B} weight maps to characterise the
 noise over the image.  Because of simplicity and lower calculation
 cost relative to weights or standard deviations, we prefer to
@@ -993,5 +1014,6 @@
 \clearpage
 \bibliographystyle{apj}
-\bibliography{apj-jour,references}
+%\bibliography{apj-jour,references}
+\input{diffs.bbl}
 
 \end{document}