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高速観測への備え― 木曽トモエゴゼンの例 ―東京大学大学院理学系研究科附属天文学教育研究センター
酒向 重行

第9回光赤外線天文学大学間連携ワークショップ, 2018/12/25, 埼玉大学

2Outline
1. Kiso / Tomo-e Gozen
2. High-speed observation system of Tomo-e Gozen
3. Advantages of high-speed observations
4. New CMOS camera module

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Kiso / Tomo-e Gozen

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Q1

•

Project P.I. Shigeyuki Sako

Q2
Q4

• Sako et al. 2018, SPIE

the first wide-field CMOS camera

Q3

The Tomo-e Gozen

Camera body of the Tomo-e Gozen Q1• 105-cm Kiso Schmidt telescope• FoV of 20 deg2 in φ 9 deg• 84 chips of CMOS, 1k x 2k pixels• Consecutive frames in 2 fps (max)• Movie big-data of 30 TB/night (max)• Absolute time accuracy of 0.2 msec
• Room temperature, Non-vacuum

21 chips of CMOS sensors of Q1

Q1 and Q3 cameras on Schmidt telescope

Survey power for transient events

Intensive Science Programs

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1. Northern sky survey- Elv > 40 deg (7,000 deg2 ) every 2 hours
CMOS

Field of View (deg2)

100

Tomo-e Gozen

10ZTF

192522

unexplored universe

LSST
PanSTARRS

23iPTF
Decam
HSC25 22TAOS II

0.1- SNs, Novae, variables, NEOs

20

18

1

- Record all events < 20 mag (dark clear night)

191716- 3 visits per night

CCD

110SDSS

100

Temporal resolution (sec)
The numbers in the circles show limiting magnitudes.

2. Follow-up / Simultaneous- GWs, neutrinos

Simulation of northern sky survey- FRBs, NSs, BBHS, meteors, NEO,-

Each circle: FoV with Φ9 deg
Yellow: Milky way

3. Fixed FoV + high-speed- 2-fps@ 20 deg2 -- 200-fps@ 52” x 38”- Occultation of TNOs, YSOs, flares, FRBs, NSs, BBHs, meteors

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Volatile data management system
On-site (10 Gbps network)

Volatile
Tomo-e Gozen
Data

Information

Knowledge

AIAI

Photometry

Buffer server

30 TB/night~300 TB

Kiso, Nagano

Transientdetection

Every events(every 1min)for Science teams

Coordinate
gridImage
Coadd

Off-site

GW
Supernova~1% of RAW

External
sever~1% of RAW~1% of RAW

Imagetrimming~1% of RAW

Moving obj.
detection~1% of RAW

Compressi
on~1% of RAW

Reduction servers~84 CPUs

Longtermstorage
data

High-energy
transient

WWWserver& DB

Young stellar
objects
Solar system&Space debris

DB servers~300 TB

Transported
every 1-month

Mitaka, Tokyo
1 Gbps, commercial line

Astronomical
data centerin NAOJ
Data archive &web server

Cyber space of Tomo-e Gozen

Knowledge

Information

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Collaboration with various fields via movie big-data and AI

Gravitational
wave physics

Tomo-eGozen

Space debris
andsatellites

Neutrino
physics

Simultaneousobs. with
X-ray andradio

Spaceguard• Time-domain observations with HOURS to MSEC resolutions• QUICK optical follow-ups with a few 10 DEG28

9High-speed observation systemof Tomo-e Gozen

Performance necessary for high-speed optical observations• High-speed frame read without dead time
1. Image sensor• Low read noise• Low power dissipation or cooler• Consecutive data acquisition

2. Data acquisition• High absolute time accuracy• High time stability

3. Optics• Wide field

4. Computing•

5. Operation

Large storage, high-speed processing & network, data visualization• Quick telescope system• Quick communication system for observers

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1. Image sensor•

High-speed frame read without dead time•

Low read noise•

Low power dissipation or cooler

11Large pixel CMOS sensor- 19 µm pix-1-

Micro lens array + cover glass
Rolling shutter
Photosensitive / package = 0.35
Analogue 16-ch outputs- Photon sensitive: 370 – 730 nm- Well: 6,000 e-, 53,000 e- @ G=x16, x1.7
- Read noise: 2.0 e-, 9.2 e- @ G=x16, x1.7

- Dark current: 6 e- sec-1 @305K- Power consumption: 230 mW chip-1 @2-fps

 Less than sky background in dark night, 50 e- sec-1, at room temperature

Photoelectric conversion efficiency
0.68 at a peak of 500 nmefficiency- Canon 35MMFHDXM- 2,000 x 1,128 pixels, front side illuminatedKojima et al. 2018, SPIE

Wavelength (nm)

12Limiting magnitude
Duration time of flash (sec)5-σ limiting magnitude
26 1002210.1

0.01

10100

t

24

20
18

10countflash

22
CMOS

16

20

CCD

18
16

14

14

12

12

100.01

0.1

110Exposure time (sec)
CMOS :CCD :efficiency=0.65, Nread=2 eefficiency=0.90, Nread=5 e-assuming same filter-bandwidth and pixel size

100

100.010.1

11000

Apparent moving speed (arcsec/sec)
Tomo-e Gozen :PanSTARRS, ZTF :LSST :

0.5 sec/frame, Nread=2 e30 sec/frame, Nread=5 e60 sec/frame, Nread=10 e-Kojima et al. 2018, SPIE2. Data acquisition•Consecutive data acquisition•

High absolute time accuracy•High time stability

DAQ and GPS system

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GPS antenna

Telescope rack
Server roomin the dome

Camera units

optical fibers of 50-m length

to main building
10-Gbps LANAnalogue DAQ

LVDS-optical convertor, PCIe bus extension I/OSensor control signals

GPS trigger @1st pixel readGPS receiveru-box EVK-M8N

ZZ0-046A- 1,344 ch of 16-bit ADC, 400 ksps
- 9.9 Mbyte/sec/chip at 2-fps- Synchronized with each other camera- 24 boards, 32 bits, 10 MHz, bus-master DMA- Consecutive data acquisition- High-stability synchronization clock, ~10-5- UTC time

- Absolute accuracy: ±0.2 msec

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Measurement of absolute time accuracy of GPS system
LED circuit triggered by 1PPS signals
GPS antenna

u-blox EVK-M8T
1PPS signals are generated.

Scan direction

Correcting lens ofSchmidt telescope Turning-on time

Obtained
FITS frameAbsolute time accuracy of ±0.2 msec isconfirmed.

3. Optics•15

Wide field• Photometry with many reference sources• Quick follow-ups for rapid variables

Movie obtained in 2-fps,
consecutive 6 frames every pointing

Raw data

Diff data

1 fps

1 chip, FoV of 39.7’ x 22.4’•5-σ limiting mag: 18.7 mag•

Photometric accuracy: ~10 millimag @ time scale < 5 sec

20

102

relative
photometry

010t (min)20

Relative counts•

Relative counts

20

10

2

010t (min)20

4. Computing•

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Large storage, high-speed processing & network, data visualization

Computing and data communication system implemented at Kiso observatory
Telescope rackCameraunits

digital I/O +Weather monitoring system

Servers

LVDS – opt convertor

GPSantenna- Abs. accuracy:

optical fibers of 50-m

±0.2 msec- Freq. stability:~10-5

Status visualization system

Telescope dome
2F control room•

Telescope controller

1F server room

• Camera controllers

CPU
72 cores
Memory 640 GB
HDD
40 TB

• Buffer servers

CPU24 cores
Memory 256 GBHDD
384 TB• Analysis servers

CPUMemoryHDD• Storage serversCPU
12 cores
Memory 128 GB
HDD
384 TB

Remote operation system
via VPN + VNC

90 cores1024 GB
96 TB

Main building
10 Gbps, fiber connection

1 Gbps,FLETs, NTT

Tomo-e Gozen Sky Map

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5. Operation•

Quick telescope system•

Quick communication system for observers• Quick information sharing•

LINE-like app optimized for business•

Many species of apps and bots.

•

Easy and quick communication with multimedia.

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https://slack.com

Free plan is available, but standard plan:¥960/user/month  Academic discount of 85% off!!
-Apps (unlimited)
Searchable messages (unlimited)Group video call
Screen sharing• Project management•

Status monitoring•

Free plan is available.

I recommend OISTER to use slack and asana-like services.

https://app.asana.com

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Advantagesof high-speed observation

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Advantages of movie data
1. Science objects•

Rapid variable objects•

Fast-moving objects•

Flash phenomena• Machine learning (random forest, SVM, neural network)
2. Big-data approach• Sparse modeling• Data mining

3. Image processing

4. Statistic andfrequency evaluation• Cosmic ray and spike noise removal• High dynamic range (HDR) processing

5. Atmospheric variation• Noise spectrum• Daily variation• Periodic signal processing• Seeing variation

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1. Science objects•

Rapid-variable objects: Binary black hole MAXI J1820+070
Simultaneous observations with Optical and X-ray
Optical (Nayoro/MSI)

Optical (Kiso/Tomo-e) absolute time
accuracy of
0.2msec

X-ray (Swift/XRT) 100msec bin

6.149 msec/frame(150Hz, Kiso/Tomo-e)

MAXI J1820+070
ref star

Sako et al. 2018,
Astronomical telegram 11426

Fast –moving objects: Near earth object (NEO) 2012 TC4Movie data of 2012 TC4- Kiso/Tomoe, 1 sensor, 39.7’ x 22.4’- 2 sec/frame, reproduction speed x200

Urakawa et al. 2018, JpGU2018

Light curve and Model fitted curve

Relative magnitude•

小久保ら 2018
天文学会春季年会

Geometrical model

1718

model
Tomo-e observations

190

6
12
Elapsed time (min)-Primary period is 12.3 min, with a
Secondary period ~8.5 min.

222. Big-data approach•#12

Machine learning• Random forest classifier• 3380 sets of training data including artificial data as NEOsDetection#1Frame data including
simulated NEO~3,000 records

Feature extraction
and labeling• False positive rate ~ 1%
• True positive rate ~ 99%
Test• Un-cataloged fast-moving-objects of~500 events/night are being detected.

#12 – #1 (6 sec apart)subtracted image

Kojima et al 2018, 天文学会秋季年会

othersNx

Sparse modeling
NyTime- Expressed movie frames as a matrix.

Morii et al 2017, AJ

Original matrix
Image pixel- Decomposed to Low-rank and Sparse
matrixes with GoDec method.

NEO candidates

ClassifierTime

Original (galaxy + flash)repeatplayback

Pixel ID (Nx x Ny)•Training

Low-rank

SparseSearch for transient eventsin Sparse matrix.

Compressed to ~10% sizeTime

Low-rank (galaxy)Sparse (flash)23

4. Statistic and frequency evaluation

6.45-msec resolution observations of Crab pulsar

一木ら 2018, 天文学会春季年会•••

Kiso/Tomo, partial readout, 299” x 29”
6.45 msec/frame, ~50,000 frames
UTC time synthesized by GPS（±0.2msec accuracy）

1 frame image (6.45msec exposure)

50,000 frame average image (total 322 sec exposure)

NIR image

Crabpulsar

Ref star

Photometry value (counts)

Periodic pulsations of 33.7 msec
50,000 frames
Light curve at the pulsar position

TimeσFolding analysis
P=33.73792msec

Holding analysis with P=33.73792msec
Differential image (perk - out of peak)
M1 Crab nebula ( Supernova remnant)Pulsation clearly
detectedframes

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5. Atmospheric variation• Daily variation• Seeing variation Lucky imaging

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New CMOS camera module

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Camera module with the Tomo-e CMOS sensor••••

Front side illuminated CMOS with micro-lens array
2k x 1k pixels
Read noise ~2 eRolling shutter•••••max 100 fps (full-frame)
Consecutive frame read
16-bit cube FITS
GPS time stamp on image file
CoaXPress interface••Frame grabber board: Matrox Radient eV-CXP
Development tool: MIL library

CoaXPress (BNC)

Commercially available
in the near future

Matrox Radient eV-CXP(dual port)

Now developing control software (Linux) with MIL library by IoA/UT team (Doi and Sako et al.).

This CMOS system will be available for astronomy community
including OISTER in the near future.

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Optical triple-beam CMOS camera for Kyoto 3.8-m telescope

supported by KAKENHI Kiban-S, Supernova (P.I. Doi)

Near infrared camera (Nagata et al.)NasmythinterfaceofKyoto 3.8-m

Optical camera (Ohta and Maeda et al.)OPTOPT+NIR

NIRf/61284mmNasmyth platform

Chimera-like design

image: Wikipedia

Summary•

1-m Kiso / Tomo-e Gozen•

Performance necessary for high-speed optical observations•

Advantages of high-speed observation•Camera module with the Tomo-e CMOS sensor---

CMOS x 84 chips, 20 deg2, 2 fps
Movie big-data of 30 TB/night (max)Absolute time accuracy of 0.2 msec
Collaboration with various research fields via Tomo-e cyber space

High-speed frame read without dead time
Low noise, low power
Consecutive data acquisition
High time accuracy
Wide field
Large storage, high-speed processing & network, data visualization
Quick telescope and communication systems

Science objects: rapid variable objects, fast-moving objects, flash phenomena
Big-data approach
Image processing
Statistic and frequency evaluation
Daily weather variation- Control software is being developed- Optical triple-beam CMOS camera for Kyoto 3.8-m telescope2829APPENDIX

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