Science Case for ALPACA
Arlin Crotts (Columbia University)
for the LAMA Collaboration

Project Review
ALPACA Science Case
2005-07-15 Page 1
Proto-ALPACA imaging focal plane
0.86 deg diameter field
6 CCDs, 7 arcmin square, 2048x2048 E2V
1 CCD for u,b,i,z; 2 r CCDs
NASA NEOs: add two rows (6 CCDs
total) for near-Earth asteroids (plus
weak lensing, bulge microlensing, LSS,
variable stars, etc.)
full ALPACA imaging focal plane
3 deg diameter field
240 CCDs, 8 arcmin square,
2048x2048 Fairchild
deep strip, 8 columns with 6 rows of
u, 4 b, and 2 each r, i, z
wide strip, 8 more columns with 4 u,
and 2 each b, r, i, z
NEO “ears”: 4 more columns of 2
each of r, i
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ALPACA Science Case
2005-07-15 Page 2
ALPACA Survey Products (P. 1)
Well-sampled, 5-band SN light curves (to r ~ 25 each night) to discover and
identify ~50000 SNe Ia and ~12000 SN Iab/II per year. SNe Ia mostly
over 0.2 < z < 0.8 range, which is ideal for detailing the evolution and
dynamics of dark energy
Weak Lensing: 700 square degrees with multiband data good for
photometric z’s
Galaxy photometric redshift sample to r ~ 28; roughly 1 billion galaxies
For galaxy clusters, should achieve same richness as SDSS cluster catalog
(to z = 0.3) but to z = 1. Sample of ~30000 clusters
Includes strong QSO lensing e.g., J12514-2914.
Map of Sculptor supercluster (z = 0.11). Novae, bright variables.
Should find several orphan GRB afterglows per year.
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ALPACA Survey Products (cont.)
Monitor 100,000s of AGNe to r ~ 26 for multiband variability.
Large scale structure over 4 Gpc3 (comoving) to z = 1 and 9 Gpc3 to z = 1.5.
Includes M83 (7 Mpc away, starburst); two Seyferts: NGC 2997 (17 Mpc),
NGC 1097 (17 Mpc). Follow cepheids, miras, novae, eclipsing variables.
Passes through Galactic Nucleus; will find >5000 Bulge microlensing events
per year; superlative extrasolar planet search resource.
Many 1000s of variable stars: Galactic structure.
Huge variety of stellar surveys.
Discover ~50 Kuiper Belt objects per night.
Trace near-Earth asteroids of 1 km diameter to Jupiter’s orbit, reconstruct
orbits well within 1 AU and detect 50 m objects at 1 AU.
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ALPACA and Near-Earth Objects
Proto-ALPACA (with NEO extension) will
be able to detect (and recover) NEOs
down to 100m diameter at 1AU and 1km
at 5AU, for albedo a=0.05. (ALPACA will
reach 50m and 500m, respectively.)
NASA’s goal is to find 90% of all NEOs
with diameter > 1km by year 2008 (for
which they will be late), but observations
concentrate on low ecliptic latitude .
(Proto-)ALPACA covers –6 <  < -53 deg.
Proto-ALPACA will have figure-of-merit
A (efficiency x area x solid angle)
larger than any competitor soon
(including first-generation PanSTARRS),
and ALPACA will have larger A than
any planned survey (including LSTT).
(Proto-)ALPACA filter bands are tuned
to separate comets from common
asteroid types.
(Proto-)ALPACA will find unprecedented
number of Kuiper-belt objects, as well.
Project Review
Density on sky (in ecliptic coordinates) of asteroids weighted by Earth impact
hazard (contours increase proportional to density), from Kaiser et al. 2001.
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ALPACA for Bulge Microlensing
OGLE III has 1.3m telescope with
a 0.34 deg2 FOV, covers 90 deg2
total, spending ~60s/night per
pointing, finds about 500
microlensing events per year.
Proto-ALPACA will spend ~160s
per star, but has collecting area
35 times greater -> will go 10x
deeper -> 30x(density of stars).
Will cover 5 deg2 -> 1000 events
per year (3000/year w/ NEO).
ALPACA will spend >500s/night
per pointing -> 3 mag deeper ->
50x(stellar density); ~30 deg2
field -> >5000 events per year.
Microlensing follow-up groups (PLANET, FUN, MOA) want to pick the ~100 best
of these lightcurves in terms of early planet-like deviations in microlensing fit.
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ALPACA Science Case
2005-07-15 Page 6
Luminosity Distance versus Dark Energy Density
The distance modulus (m – M) is
cosmology dependent; distance at
given z depends on expansion
(de)acceleration and spatial
curvature. SN Ia standard candle
relation puts constraint on
~(demwhereas CMB
anisotropy first acoustic peak
constrains tot, which together
currently constrain dem the
level of a few percent. Similar
constraints are found by
comparing cosmic microwave
background constraints with m
from cluster masses. Gives
reasonable cosmic ages.
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SN Ia Peak Luminosity/Duration/Color Relations
L-relations : m15 (Phillips 1993)*,
MLCS (Reiss et al. 1996, 98), stretch
(Perlmutter et al. 1997, 99), CMAGIC
(Wang et al. 2003), C12 (Wang et al.
2005) relate duration (and color,
shape) over light curve to brightness
at maximum e.g., m15(B)  drop in
brightness 15d post-maximum (0.51.5 mag).
Duration appears to be predicted
primarily by mass of 56Ni. Are there
other parameters?
of SNe Ia is from Riess et al. 1995, ApJ, 438, L17.
* MB  m15(B)  1.1] (Altavista 2003, PhD thesis)
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ALPACA Science Case
2005-07-15 Page 8
Parameters affecting SN Ia Luminosities
Event width (m15) can predict SN Ia luminosity to ~15% r.m.s., including color measures
(CMAGIC, C12) reduce this to 7-10% r.m.s. Are the residual errors due to measurement
error? Intrinsic processes? Extrinsic? Fundamentally stochastic? Possible factors include
(some treated in publications, with disagreement on nature, size – even sign – of effects):
56Ni
mass
Single or double-degenerate progenitor
Metallicity
Progenitor compositional structure e.g., C/O varying with radius
Rotational velocity (rotational support influencing density structure)
Magnetic fields
Density structure depending on mass of progenitor before accretion
Convection structure in deflagration front
Viewing angle
Ejection asymmetries
Circumstellar interactions
Varying extinction laws
Weak lensing magnification variation
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ALPACA Science Case
2005-07-15 Page 9
SN Observations with Proto-ALPACA
Nightly photometry in 5 bands:
u(310-410nm), b(415-550nm),
r(565-745nm), i(750-1050nm),
z(950-1050nm). ubri are spaced
in log(), minimizing Kcorrection errors. i band for
high redshift.
Simulated Proto-ALPACA SN Ia lightcurves including realistic
effects of weather & instrument (checked against Gemini ETC).
Combined nightly sensitivity
AB(r) ~ 25, provides S/N > 10
SN Ia detections in 3-5 bands
for > 5 epochs each, to z = 0.8.
Expect ~4000 SNe Ia & ~2500
SNe Iab, II at this S/N level.
Our PUC collaborators (Minniti,
Clocchiatti) have generous access
to 8m-class scopes (devote ~10
nights/year, or ~300 SN, host
galaxy redshifts)
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Photometric ID of SN Type
On the basis of color alone (7 d
after max) one can separate SNe
Ia from all other types
Reddening
Slight ambiguity of z = 0.3 Ia with
z = 0.1 Ibc is cleared up by
different evolution of SNe
through color-color plot over
event.
Star = SNe Ia
Circle = I bc
Triangle = II P
Square = II b
Diamond = II N
Number labels = int (10*z)
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SN Color Evolution
Red = SNe Ia
Green = I bc
Blue = II P
Number label = days after max.
Evolution of color over SN peak easily breaks the degeneracy between
z=1 SNe Ia and z=0.3 SNe I bc (and further separates SNe Ia from others)
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SN Ia Host Galaxies
SNe Ia tend to be closely associated with
prominent host galaxy. (SNe II sometimes
associated with disconnected star
formation knots.)
Sullivan et al. 2003
Project Review
Tonry et al. 2003
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Accuracy and Reliability of Photo z’s
Accuracy of photometric redshifts
Systematic uncertainty ∆z / (1 + z) < 6.5%
Photometric uncertainty
Reliability of photometric redshifts
No “outliers” out of ≈ 150 redshifts
“Contamination” < 1% (Lanzetta et al. 1998)
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Plan for Proto-ALPACA SN Ia Studies
Project Review
ALPACA Science Case
2005-07-15 Page 15
Are Spectroscopic Redshifts Practical?
Spectrograph operating w/ imager might
obtain 20 spectra simultaneously (every
5 min), or about 800,000/y vs. 30,000/y
of “decent” SNe Ia
~ 50% of host galaxies require < 10
exposures (for 10 detection, 1nm
wavelength resolution)
90% of host galaxies from High-z SN
Team (HZT) found at I < 25. Typically I
~ 23. (Williams et al. 2003, AJ, 126,
2608)
night
10 nights

Williams et al. 2003: magnitudes of HZT SN Ia hosts (0.43 < z < 1.06)
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Improving SN Ia Standard Candle Relation
The primary challenge is likely to be control of systematic errors. One method
of dealing with this might be to split the sample of 100,000 well-sampled light
curves into redshift bins (~0.1) small enough that residual error in cosmological
parameters are insignificant (see next slide), then perform a principle component
analysis on the subsamples of ~10,000, and compare the results from different
subsamples to gauge evolution. The quality of the data might allow us to explore
10-20 parameters. By finding the covariance of luminosity in a single bin with
this parameter set we should be able to reduce the scatter significantly by
producing a detailed luminosity model, or at least discard outriggers.
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Luminosity Distance vs. Dark Energy Equation of State
Behavior of dark energy can be
parameterized by its pressure-like versus
mass density w = p/(w=0: “normal
matter,” w= 1/3: cosmic strings,
wquintessence, w=1:
cosmological constant). Current limits
combining CMB anisotropies, LSS and SN
Ia constraints limit w at the 0.1 level
subject to limits on our uncertainty
regarding the SN Ia standard candle
assumption.
c.f. Lewis & Bridle 2002, Phys Rev D, 66, 103511
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Worked Example for 2000 SNe Ia
2000 SNe with r.m.s m = 0.2, sampled in
z via deep, ground-based imaging. Get
maximal discrimination in dark energy
density f at redshifts 0.3 < z < 0.8. This is
true of most dark energy models, in this
case quintessence (scalar field potential
with slow-roll) versus k-essence (similar but
with coupling to kinetic energy term) as
might help explain why de ~ m
Wang & Garnavich 2001, ApJ, 552 445
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Luminosity Distance vs. Dark Energy Dynamics
Statistical errors only: even
assuming that we are unable to
reduce the scatter in inferred SN
Ia luminosity below 20% r.m.s., the
number of SNe will allow us to
achieve statistical errors in ~10
redshift bins at the level of mag
= 0.002. This is the same size
proportional error one sees across
a z = 0.1 bin if one assumes a
value for m which is incorrect by
3%, roughly the uncertainty in the
near future. An error mag =
0.002 is small compared to the
deviations between predictions of
different physical models for dark
energy; a value of a few percent is
sufficient to differentiate many
currently surviving models.
Project Review
Standard candle apparent brightness at moderate
redshifts for different models of dark energy:
(baseline) de=0.7 cosmological constant – value of
0.6 or 0.8 varies by about 0.13 in mag at z=1, (thick)
pseudo Nambu-Goldstone boson, (thin) supergravity,
(long dashed) pure exponential, (thick dotted) inverse
tracker, (short dashed) periodic potential (Weller &
Albrecht 2001, PhysRevLet, 86, 1939)
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Cosmological Measures of Dark Energy
Universal equation of state w=p/ describes expansion’s dynamics and therefore H(z).
What we actually observe are measures of H(z) and redshift integrals* over H(z), the
angle distance and luminosity distance:
Supernovae as standard candles:
luminosity distances dL(zi)
Baryon acoustic oscillation as standard ruler:
cosmic expansion rate H(zi)
angular diameter distance dA(zi)
Weak lensing cosmography:
ratios of dA(zi)/dA(zj)
*Comoving
distance
is related to expansion rate H(z):
and the observed distances (in flat Universe) dL = R0 r (1+z), dA = R0 r / (1+z)
The three independent methods will provide a powerful cross-check, and allow ALPACA to
place precise constraints on dark energy (+growth of structure via cluster counts+strong
lens delay timings+large-scale structure Alcock-Paczynski+cluster integrated Sachs-Wolfe…)
0
Project Review
Spatial frequency k (h/Mpc)
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Combining ALPACA Dark Energy Constraints
The simplest dark energy investigation
method sensitivities to estimate are
SN Ia standard candles, weak lensing
shear and baryon oscillations. To
express dark energy dynamics, we use
w = w0 + wa a = w0 + wa /(1+z), where wa
describes the redshift change in w. A
few points:
E
f
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