deep-south: test runs, early results and request for time...

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DEEP - South: Test runs, early results and request for time allocation Hong-Kyu Moon and DEEP-South collaboration Korea Astronomy and Space Science Institute © Young-Beom Jeon

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DEEP-South: Test runs, early results

and request for time allocation

Hong-Kyu Moon and DEEP-South collaborationKorea Astronomy and Space Science Institute

© Young-Beom Jeon

CollaboratorsM-J Kim, H-S Yim, Y-J Choi, Y. Bae, D-G Roh,

J. Park and B. Moon

J-L Yu, J. Hahm, J-W Park, H-Y Cho, S-M Lee,

S-H Kim, K-M Jeong and S-C Shin

J. D. Lee, S. Lee, Y. Ryu, Y. G. Park, J. H. Kim,

H. J. Jin, M. S. Jeong and J. Song

M-J Kim et al. DEEP-South: Preliminary Photometric Results from KMTNet-CTIO

H-S Yim et al.DEEP-South: Scheduling and Data Reduction Software Subsystem

Group posters

Demand for survey & physical

characterization of NEOs

NEO Discovery data (MPC, June 1 2015)

Database of Physical and Dynamical Properties of NEOs,

(DLR, June 1 2015)

Period: off-season for exoplanet search

Filters: mostly, Johnson-Cousins BVRI

Targeted photometry: 45 full nights/telescope/yr for 5 yrs (2015-2019)

Survey: in search for Atens and IEOs during dawn and dusk; ecliptic plane patrol

Data mining: KMTNet bulge- and SNe- archives: SUPERTRAMP (SoUthern hemisPhERe TRAckelt Mining Project)

DEEP-South at a glance

We investigate bulk properties of small bodies and

the pop as a whole with visual broadband photometry

Goals

CTIO, Chile

SAAO, South Africa

SSO, Australia

DEEP-South:Deep Ecliptic Patrol of

the Southern Sky

We defined 10,536 TFs in equatorial coordinates and named wrt. ecliptic coordinates

The size of each TF (4 sq. deg.) is the same as the FOV of 18k x 18k CCD

The advantages:

1) Systematic debias of MBA for pop studies

2) Conveniences in operations and data reduction

3) Monitoring of long-term variability of comp. *s

Target fields

Observation modes

OC: Opposition CensusNW: NEOWISE follow-upSP: SPHEREx follow-up

S1: Sweet spot surveyS2: Ecliptic survey

TO: Target of Opportunity

S2: Survey 2

S1: Survey 1

TO

* Ecliptic coordinates; survey/census areas not drawn to scale

OC/NW/SP

Strategy

• LC: little is known for obj with P≥ 8-10 h;

* benefit from non-aliased data on longer timescales

* orb/rot periods, spin states; shapes & satellites

OC : densely-sampled LC

S1 : sparsely-sampled long-duration LC

• Color variations: inhomogeneity on surface or any evidence for collisions in the recent past

• Albedo & colors:

NW: NEOWISE photometric follow-up

S2: population studies of MBAs

• Challenges of incorporating people:

- They make different decisions at different times

- Different people make different decisions given

the same inputs

- People need to eat, sleep, socialize & get paid

• Don’t require people to do things that machines

can do better (vice versa)

• An ideal system fuses intelligence & adaptability,

with the computational power of machines

Roles of machine

DSS management and analysis GUI

Network File

System NFS

LusterParallel

FileSystem

OpenStack cloud management platform

Virtual machine VM provisioning: Nova VM image mgnt.: Glance

Security group control Virtual network mgnt.: Neutron

DEEP-South Scheduling System DSSData Reduction Control & Management

DRCMRaw data

VM VM VM VM VM VM VM VM VM

Moving Object Detection Program MODPAsteroid Spin Analysis Package ASAP

VM VM VM VM VM VM VM VM VM

HTCondor pool

DEEP-Southvirtual cluster:

6 + 256 + 16 cores

Workflow managementDAGMan

DRCM-DAGMan RESTful Web InterfacesWorkflow submit, suspend, resume, monitor, cancel and other jobs

observation data

MODP/ASAP Analysis request and result

MODP/ASAP Tools optimizationMODP/ASAP Tools parallelizationMODP/ASAP Workflow template

ScienceCloud

Scheduler & pipeline: Yim+

Test runs: autumn season 2015 (Feb 12-May 28)

@KMTNet-CTIO; resumed on July 21 @ three

KMTNet sites* MPC provides us with monthly ephemerides of 13k NEOs

Results:

we obtained preliminary lightcurves of…~10/40 PHAs (due to unfixed WCS problems) including 3 NHATS* objects,observed 3 Cometsand surveyed 7 S2 fields

*NHATS: Near-Earth Object Human Space Flight Accessible Target Study

DEEP-South test runs

Test runs: target PHAs

Observed Not observed

2001KY66 1990UQ 1978CA 2000PN9 1951RA

1999SL5 1999GK4 1998SS49 2001BO61 1989QF

2000OH 2008OB9 1999XA143 2001CV26 2003RB

2007CA19 2006SV19 2001SN289 2004QD14 2003YK118

2004BB103 1998ML14 1990MU 2005JF21 2003YT1

1999JM8 2005JE46 2005NZ6 2006SU131 2008JV19

2004GA1 2004QY2 1959LM 2011QD48 2013NK4

1979VA 2007RQ17 2011UW158 2015DE198

1994AW1 2002CE 1989JA 2011SV71

1994CC 2002TD60 1996SK 2012CL19

CTIO

SSO

SAAO

0-1 h

1-3 h

3-50 h

ObservedNot observed

During the 2nd test run period (July 21 – September 9)

Test runs: statistics

Preliminary LCs: Kim+

1 2

43

H=17.9 H=17.2

H=17.4, binary H=19.5, NHATS

IAUS 318

Time allocation: once every 2 nights; to alternate with SNe search

Semi-automated runs: obs. scripts (Observation Command File, OCF) & TAT w/local times

Other issues:

1) WCS

2) MEF with “chips”

3) Standard * observations @ 3 KMTNet sites

4) SDSS filters

Requests

V, t -> G(x, y), P (LC)V, t -> λ, β, 3D shapecolor, t -> surface inhomo-

geneity

P, λ, β, t -> YORPLC, t -> surface activity,

satellites & multiplicityorbit & PA/NPA rotation

x, y, t -> orbitorbit, t -> Yarkovsky

effect, orbital resonance, capture & tidal stripping

Observables to aBig picture

Observables Physicalparameters

Timevariations

Evolution

V-> H-> color

x, yt

V -> production ratesH -> D, pv

color -> taxonomy

D, pv, taxonomy (pIR) -> m, ρ

orbit, color -> family & population

orbit, D (m, color,taxonomy), t -> evolution &

migration

* Multi-band photometry data