First Results from the High-Cadence Monitoring of M31 with Pan-STARRS 1

PAndromeda: first results from the high-cadence monitoring of M31 with Pan-STARRS 1

C.-H. Lee – ASIAA seminar 29 Feb. 2012 PIs: S. Seitz, R. Bender A. Rifeser, J. Koppenhoefer, U. Hopp, C. Goessl, R. P. Saglia, J. Snigula (Max Planck Institute for Extraterrestrial Physics, Germany) W. E. Sweeney (Institute for Astronomy, University of Hawaii, USA) and the PS1 Science Consortium Outline

1. Introduction to microlensing 2. Pan-STARRS and PAndromeda 3. First results from PAndromeda 4. Prospects - Breaking the microlensing degeneracy - Beyond microlensing Introduction

Image1

Image2

Observer Lens Source

Credit: NASA, ESA, and Johan Richard (Caltech, USA)

Microlensing Basics

Angular Einstein ring radius

Image Credit: Gould (2000)‏ Position of the image

Amplification of the image

Image Credit: Scott Gaudi

Searching for Dark Matter

Paczynski(1986) proposed to use microlensing to search for massive compact halo object (MACHO) as dark matter candidates

Triggered numerous experiments towards Galactic Bulge and Magellanic Clouds

Thousands of events have been detected since 1993. OGLE and MOA report ~1000 events/yr nowadays

Results from LMC/SMC

M < 0.1 solar mass: - f < 10% (MACHO, EROS, OGLE)

M between 0.1-1 solar mass: - f ~ 20% (MACHO 2000, Bennett 2005) - self-lensing (EROS 2007, OGLE II-III, 2009-2011)

Caveats of LMC/SMC lensing experiments: - Single line-of-sight - Unknown self-lensing (star lensed by star) rate

=> M31 provides a solution to both 1 and 2 M31 microlensing

1. Why M31? - Various lines of sight - Asymmetric halo-lensing signal

2. Previous studies on M31 - POINT-AGAPE (2005): evidence for a MACHO signal - MEGA (2006): self-lensing and upper limit for f - WeCAPP (2008): PA-S3/GL1, a bright candidate attributed to MACHO lensing

Too few events to constrain f => requires large area survey Outline

1. Introduction to microlensing 2. Pan-STARRS and PAndromeda 3. First results from PAndromeda 4. Prospects - Breaking the microlensing degeneracy - Beyond microlensing

Pan-STARRS Science

- Wide-field imager with 7 square degree - 3Pi survey: 30,000 square degree in g’, r’, i’, z’, y in 3.5 years, about 1 mag deeper than SDSS - Plus selected deep fields for SNe, planets, M31 Key Science Projects

1. Populations of objects in the Inner Solar System 2. Populations of objects in the Outer Solar System 3. Low-Mass Stars, Brown Dwarfs, and Young Stellar Objects 4. Search for Exo-Planets by dedicated Stellar Transit Surveys 5. Structure of the Milky Way and the Local Group 6. A Dedicated Deep Survey of M31 7. Massive Stars and Supernova Progenitors 8. Cosmological Investigations with Variables and Explosive Transients 9. Galaxy Properties 10. Active Galactic Nuclei and High Redshift Quasars 11. Cosmological Lensing 12. Large Scale Structure PAndromeda Goals Nature of DM in the halos of M31 and MW Fraction of Massive Compact Halo Objects (MACHOs): Planets, brown dwarfs, white dwarfs, stellar remnants: neutron stars, black holes Compact dark masses detectable with gravitational lens efect - rare: 1 event in 1 million stars - short: ≤ 5 days One needs long term, continuous monitoring on large ﬁelds Statistical microlensing analysis: Rifeser et al (2006)‏

M31-stellar population inventory M31 bulge mass function at the low mass end, CMDs of PMS stars, variables M31 = NGC224 2.8 x 3.6 deg PAndromeda 37 x 47 kpc

M110 = NGC205

WeCAPP

M32 = NGC221 distance = 770 kpc PAndromeda in a nutshell

Strategy - 20 min every night over 5 month = 2% of Pan-STARRS - microlensing with short time scales of approx. 1 day - 2 pointings per night separated by ~5 h - AM always below 1.4 - r': 12 x 60 sec i': 8 x 60 sec (=51 GB)‏

Data from season 2010 - 7/23/2010 till 12/27/2010 - 91 nights (58%), 30 h, 1782 frames - latency: 2-3 days - amount of raw data = 4.5 TB Outline

1. Introduction to microlensing 2. Pan-STARRS and PAndromeda 3. First results from PAndromeda 4. Prospects - Breaking the microlensing degeneracy - Beyond microlensing M31 in GPC's view

Giga Pixel Camera and its 60 detectors labeled by the blue and red grids. The red numbering indicates the same detector corresponding to the blue numbering, but rotated with 90 deg during the observation. Each detector is composed of 4782 x 4824 pixel with 0.258 “ / pixel. The masked areas (in black) visible, e.g. in the detector 14 (marked in blue) are due to ill-functioning orthogonal transfer arrays, video guide star, data and areas on the focal plane with sub-standard imaging performance within this detector.

Lee et al. 2012, AJ, in press PAndromeda cadence

Lee et al. 2012, AJ, in press

PAndromeda observation cadence. The histogram shows the number of visits (0, 1, or 2 times per night) on M31. The black line indicates the lunar phase (1 for full moon and 0 for new moon). The red line shows the distance of the M31 center from the moon as a function of observing date A pause in the observations is visible in December when we were reaching the limit of the 2% PS1 time. Seeing distribution

Lee et al. 2012, AJ, in press Point-spread function (PSF) distribution of the first season of Pandromeda in the bulge (left panel) and disk (right panel) field. The PSF distributions of the rP1 (iP1) are shown in the blue (red). PAndromeda pipeline Data analysis 1. Start from warped images (skycell)‏ 2. Apply diference imaging analysis (DIA) based on Alard & Lupton (1998) and Goessl & Rifeser (2002)‏ 3. Study a 40'x 40' sub-field in the central region of M31, a 20'x 20' sub-field in the disk

Lee et al. 2012, AJ, in press Difference Imaging Analysis (DIA)‏

Lee et al. 2012, AJ, in press

Zoom-ins to an example diference image of skycell 078 in the iP1 band. Left panel: positive (white) and negative (black) residuals are visible at the position of variable sources. Right panel: the center of M31. The white circle indicates a distance of 5’ (1.12 kpc) from the center of M31 (marked with the white cross). The vertical and horizontal masked areas are the gaps between the detectors. The size of this image is 20’ X 20’. The white box outlines the size of the zoom-in presented in the left panel. The ﬂux cut level of these two images is the same. , where si = sign {fi -f(ti)}, and Microlensing candidates

Position of the six microlensing event candidates detected in the central 40’ X 40’ region of M31 from PAndromeda. The coordinates, R.A. (J2000) in hour and Dec. (J2000) in degree, are also shown in the ﬁgure.

Lee et al. 2012, AJ, in press PAnd1 and PAnd2

Lee et al. 2012, AJ, in press PAnd3 and PAnd4

Lee et al. 2012, AJ, in press PAnd5 and PAnd6

Lee et al. 2012, AJ, in press

Outline

1. Introduction to microlensing 2. Pan-STARRS and PAndromeda 3. First results from PAndromeda 4. Prospects - Breaking the microlensing degeneracy - Beyond microlensing Einstein Timescale

The only physical information we can extract from the light-curve is the event timescale:

Image Credit: Arno Riffeser

Can we determine the lens mass and distance…? Breaking the Degeneracy

If we can measure: i) microlens parallax and ii) angular Einstein ring radius , we are able to determine the lens mass and distance (Gould 2000):

Image Credit: Gould (2004)

Measuring θE (1)

Lens-source separation (Alcock et al. 2001):

Image Credit: Alcock et al. (2001)‏

Comparison of PS1 images (left column) with the HST images (right column). The HST image of PAnd-1 is from a median of three ACS 814 nm archive data of HST Cycle 5 proposal 6300 by H. Ford. The HST image of PAnd-2, PAnd-3, and PAnd-4 are from ACS 814 nm archive data of HST Cycle 18 proposal 12058 by J. Delcanton. The HST image of PAnd-6 is from ACS 606 nm archive data of HST Cycle 13 proposal 10407 by H. Morrison.

Lee et al. 2012, AJ, in press Measuring θE (2)

Finite-source effect:

The source size is derived from color (Kervella et al. 2004):

Image Credit: Batista et al. (2009)

We have developed a fast and accurate algorithm to detect finite-source effects (Lee et al. 2009):

which can be calculated numerically using the composite Simpson’s rule with n(an even number) grids:

Measuring θE (3)

Astrometric Microlensing:

Centroid of the images

Centroidal shift relative to the source

Image Credit: Scott Gaudi

Finite Source + Finite Lens

Finite-source effect:

Finite-lens effect:

: Heaviside step function

Lee et al. 2010, MNRAS Luminous Lens + Finite Source

Luminous-lens effect:

: position of the lens

: flux ration between the lens and the source

Yellow : PSPL Blue : FSFL, Δm = -2 Gray : FSFL, Δm = 0 Green : FSFL, Δm = 2

Lee et al. 2010, MNRAS Events towards GB, SMC, and M31

Centroidal shift relative to the source

Maximum centroidal shift when

Lee et al. 2010, MNRAS Observation with VLT

PRIMA for VLTI VLT Interferometer With a reference star at 10’ and 200 m baseline, can achieve 10µ accuracy in 30 mins.

Limiting magnitude: 18(15) mag with UT(AT) in K-band given a 13(10) mag reference star. Image Credit: ESA =>M31 events are too faint! Outline

1. Introduction to microlensing 2. Pan-STARRS and PAndromeda 3. First results from PAndromeda 4. Prospects - Breaking the microlensing degeneracy - Beyond microlensing Variables in M31 Cepheid Besides the microlensing events, we also found several Cepheids, eclipsing binaries, and novae. This demonstrate the feasibility to use PAndromeda data to study variables in M31

Lee et al. 2012, AJ, in press

Nova Eclipsing Binary Summary

Microlensing 1. As a preliminary study, we have detected 6 microlensing events in the 40’ X 40’ FOV of M31 center 2. The full data from 2010 and 2011 season is currently under analysis 3. We will apply our ﬁnite-source algorithm to search for ﬁnite-source events

Variables Cepheids, eclipsing binaries, and novae in M31