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LaNotte, the TNG metric system after two years of data.

Emilio Molinaria,b, Nauzet Hernandeza

aFGG-INAF, Telescopio Nazionale Galileo - Rambla J.A. Fernández Pérez, 7 38712 Breña

Baja, TF - Spain; b INAF - Istituto di Astrofisica Spaziale e Fisica Cosmica, Via E. Bassini, 15 - 20133 Milano - Italy;

e-mail address: molinari@tng.iac.es

Abstract. The night accounting system laNotte, presented two years ago at SPIE Amsterdam, has now been working without interruption and a wealth of data are becoming available. We can confirm that the human interaction of the night operator is a key factor, so that a manual editor has been given to operator in order to fix all unavoidable errors and misevaluation during the night. The connections with several logging and telemetry databases complete the necessary inputs. We were thus able to monitor the effect of the introduction of a major new instrument (Harps-N@TNG), to measure with accuracy the meteo variability on the Observatory of Roque de los Muchachos, the frequency of technical problems of the various devices. laNotte complex is also an straightforward way to account for the operations toward funding bodies, providing them with a standard set of data and the quick possibility to look for historic trends. Keywords: observatory management, observatory efficiency, metrics.

1 INTRODUCTION We presented two years ago [1] the metric system adopted at Telescopio Nazionale Galileo (TNG) for the night accounting and observatory efficiency. TNG is an Italian 3.5m telescope located in la Palma, Canary Islands, and hosts three instrument available in real time: DOLORES, a visible imager and low resolution spectrograph, NICS, an infrared imager and (very) low resolution spectrograph and HARPS-N, a visible, high resolution, high stability spectrograph. The three instruments serve different science cases and have different modus operandi, more or less complex, more or less automated. laNotte system allow us to monitor the technical failures and shutter open efficiency for each night and instrument, and of course the meteo conditions of the site. All this is part of a bigger effort towards observatory efficiency, aiming to give more data to astronomers for the same financial and human efforts (see for example also [2]).

Definitions

In Table 1 we lists the definition for night status used for accounting and computations:

Table 1. Time definitions.

Night length The period between the end of nautical twilight in the evening and the beginning of the nautical twilight in the morning

Meteo downtime Whenever the telescope operator declares that the meteo condition are not suitable for observing and no observations are performed. The visiting astronomer can decide to observe in bad conditions but not in dangerous conditions (operator decision).

Techno downtime whenever a technical failure in the observatory stops observations. Typically a ticket is open directed to maintenance.

Engineering time Time not observed for observations and used to perform tests in the telescope or instruments, integration of new equipment, pointing model refinement …

Idle time (wasted) time, not used when otherwise could have been observing time (def. below) Observing time Whenever meteo and technical conditions would allow an observer to take images Shutter open time The sum of the exposure times of the frames in a period (night)

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2 FEEDING THE DATABASE The two databases which are used in this work are the lanotte database with status of the night, filled every 5 minutes, and the FITS images database, filled with every taken image after completion. While the latter has a high level of automation, relying on the communication of each instrument control software with the observatory control system, the former need the intervention of the night operator who sets and changes the night status using an internal web page.

Fig. 1 laNotte web page, used by night operator to set the current status of the night

Moreover, the dark level is set computing the beginning and end of the civil, nautical and astronomical twilights, the two last considered valid for astronomical observation. The result is a series of entries as shown below:

id | date | night | status | dark --------+---------------------+---------------------+--------+------ 267190 | 2014-05-20 20:00:01 | 2014-05-20 00:00:00 | 0 | 0 267191 | 2014-05-20 20:05:01 | 2014-05-20 00:00:00 | 0 | 1 267192 | 2014-05-20 20:10:01 | 2014-05-20 00:00:00 | 0 | 1 267193 | 2014-05-20 20:15:01 | 2014-05-20 00:00:00 | 0 | 1 267194 | 2014-05-20 20:20:01 | 2014-05-20 00:00:00 | 0 | 1 267195 | 2014-05-20 20:25:01 | 2014-05-20 00:00:00 | 0 | 1 267196 | 2014-05-20 20:30:01 | 2014-05-20 00:00:00 | 0 | 2 267197 | 2014-05-20 20:35:01 | 2014-05-20 00:00:00 | 0 | 2 267198 | 2014-05-20 20:40:01 | 2014-05-20 00:00:00 | 0 | 2 267199 | 2014-05-20 20:45:01 | 2014-05-20 00:00:00 | 0 | 2 267200 | 2014-05-20 20:50:01 | 2014-05-20 00:00:00 | 1 | 2 267201 | 2014-05-20 20:55:01 | 2014-05-20 00:00:00 | 1 | 2 267202 | 2014-05-20 21:00:01 | 2014-05-20 00:00:00 | 1 | 3 267203 | 2014-05-20 21:05:01 | 2014-05-20 00:00:00 | 1 | 3 267204 | 2014-05-20 21:10:01 | 2014-05-20 00:00:00 | 1 | 3

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From the telescope archive data about performed observations are extracted, together with exposure times and instrument. These are used to build the night snapshot which gives the observer a rapid information of the moment, and is used at the end of the night to build the final night statistics. Snapshots can be as interesting as the cases shown in Fig. 2.

Fig. 2 Snapshot after the end of night of 26 February 2014. Of the 10:45 hours dedicated to operations 3:25 are accounted for engineering time with new instrument (G)iano, then observing with (H)arps-N and (D)olores. At the end of the night telescope was closed due to bad weather for 45 minutes.

The end of the night also marks the feeding of the leNotti database with aggregated infos about the night: id | date | night_length | night_observ |dwmete | dwtech | idle | ! ------+---------------------+-----------------+-----------------+-------+----------+-----------+- 2651 | 2014-05-11 00:43:29 | 8.6666666666667 | 1.25 | 0 | 7.41667 | 0 | !2653 | 2014-05-12 02:03:45 | 8.9166666666667 | 2.25 | 0 | 0 | 3.33333 |

! 2655 | 2014-05-13 05:18:08 | 9.4166666666667 | 9.1666666666667 | 0 | 0.166667 | 0.0833333 |! 2657 | 2014-05-14 05:08:45 | 8.5 | 6.5 | 1.75 | 0 | 0.25 |

2659 | 2014-05-15 04:53:13 | 8.75 | 8.25 | 0 | 0 | 0.5 |! 2661 | 2014-05-16 05:45:11 | 9.3333333333333 | 7.4166666666667 | 0 | 1.91667 | 0 |! 2663 | 2014-05-17 05:57:09 | 9.3333333333333 | 9.3333333333333 | 0 | 0 | 0 |! 2665 | 2014-05-18 05:39:03 | 9.0833333333333 | 9.0833333333333 | 0 | 0 | 0 |

2667 | 2014-05-19 05:28:10 | 8.6666666666667 | 8.6666666666667 | 0 | 0 | 0 |! 2669 | 2014-05-20 05:06:29 | 8.3333333333333 | 6.3333333333333 | 0 | 0.333333 | 0.166667 |! 2671 | 2014-05-21 05:27:16 | 8.6666666666667 | 8.6666666666667 | 0 | 0 | 0 |!

id | shopen |eng | | night_instr | night_astr | night_oper | night_supp !

------+----------+-----+-+-------------+-------------+------------+-----------! 2651 | 0.91667 | 0 | | 12 | M. Bo*** | 23 | 0

2653 | 0.94889 |3.33 | | 1 | | 23 | 11! 2655 | 2.6733 | 0 | | 2 | V. Lo*** | 24 | 11! 2657 | 1.8511 | 0 | | 2 | V. Lo*** | 24 | 11! 2659 | 4.65 | 0 | | 12 | | 24 | 6! 2661 | 5.3347 | 0 | | 12 | S. Ho*** | 24 | 6! 2663 | 5.3729 | 0 | | 2 | | 24 | 15! 2665 | 4.2339 | 0 | | 12 | A. Ni*** | 24 | 15! 2667 | 6.875 | 0 | | 12 | Z. Zh*** | 27 | 19! 2669 | 2.5059 | 1.5 | | 1 | | 27 | 19! 2671 | 7.3333 | 0 | | 12 | A. Bo*** | 27 | 19

and from these data we can build reports and statistics.

2 QUASI-AUTOMATIC REPORTS Every day the observatory staff receives a report prepared by the night operator on the night. This report contains data automatically retrieved from the laNotte database and includes the last snapshot of the night. All technical downtime and engineering time in there must be also manually commented and justified. All the observed programs during the night are accounted as per shutter open, and data about particular programs may be sent to the PI after request. Also, the Observatory Department Heads receive once a week a report which emphasizes the percentage of each night which was lost due to technical or meteo problems.

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An example is shown in Fig. 3, where it is immediately clear when a particular night underwent special conditions, so that specific countermeasures can be taken. Finally, a yearly report is due to the TNG Financing Body (INAF) and laNotte system provides it easy to deliver. A search on the last 12 months can be performed and the important data of the given year are produced. For 2013, latest report issued we reckoned that the basic statistics was as shown in Table 2, also comparing with previous year. Along with these bare numbers a complete view of the year is produced, as presented in Fig. 4. The data are here aggregated on a weekly basis and the color codes give at a glance the yearly behavior. Of particular interest to the Board is to have an idea of the site conditions (evidenced with the fraction of time lost due to bad weather) and the technical failures of the telescope and instrumentation (also reported in a separated graph).

Fig. 3 Weekly report sent to Observatory Departments. Light green high scores are the aim, and other color codes help finding the cause of the lack of efficiency. Efficiencies in the right tabular numbers are computed as ORM (Observatory of Roque de los Muchachos) being the fraction of good weather, TEL as the fraction of operation without technical failures, and OBS as shutter-open time over available good time. During thw shown week, a couple of night are worth being checked for technical problems and another couple were affected by really bad weather. Also, a 46% of shutter-open on Sat 01/03 should be investigated.

Table 2. Basic statistics of one complete year, produced for the Telescope Board Report.

2013 2012

Average down meteo 22.3% 26.2% Average technical failures 2.2% 2.9%

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Total engineering time 6.4% 9.2% Average shutter open ratio 69.0% 45.7%

Fig. 4 One year report as prepared by a python procedure for the annual report to the Telescope Financing Board. Data are aggregated on a weekly bases and for each bin the value of the length of the night (total histogram above, higher during winter), the fraction of bad weather (in blue color, showing two distinct bad seasons), the technical failures (in red, very rarely over 5%), engineering time necessary for observatory maintenance and calibrations (n orange, high during new instrument setups) and shutter-open efficiency (light green, the aim of our job).

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3 DERIVED STATISTICS Besides regular reports, which act as alert system on the averaged observatory behavior, from the databases we can extract various statistics on request.

Open-shutter efficiency

We present here the efficiency measured as fraction of shutter-open for the different instruments, in the period Nov 2011 – May 2014. Fig. 5 clearly shows that there are two kinds of instruments: high resolution, single object spectrographs (HARPS-N and SARG, now decommissioned) and multi purpose imager/spectrographs (DOLORES and NICS). The former has a higher efficiency, with less time used to repoint, read-out, put into slit/fiber. Also, taking advantage from the novelty of Harps-N [3][4], we could differentiate the first and second period finding a 10% increase in efficiency, due to better training of astronomers and increased simplification of the user interface.

Fig. 5 Shutter open fraction of observable time for each instrument. See text for

discussion.

Consecutive good/bad nights.

Another interesting parameter for proposal preparation is the necessity of consecutive good nights for source monitoring. Also the reverse, the presence of consecutive bad nights may in some cases be important to decode the probability of success of a given program. Here we have to define first what a bad or good night is, because for different observations a different fraction of bad weather cab ne acceptable, or not. In Fig. 6 the number of occurrence of a connected group of good (bad) night per semester is shown. A good (bad) night is one where the fraction of good weather is greater (less) than X%, where X is taken to be 0, 20, 50 and 90 in the examples. So if X is closer to 0 this means that a program needs only a few hours to proceed, and vice versa when X is closer to 100 this means that the program needs almost the whole night to be complete. The statistics reported is including around 900 nights, independent of the season.

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Fig. 6 Consecutive good (bad) nights occurrences in a semester.

Duration of observable night

Despite the 3.5 hours difference in the duration of the night at maximum (winter) and minimum (summer), during the months the average observable night does not differ so much. In Fig. 7 the average night length and the average good weather night length is reported. It is evident that the overall seasonal cycle is washed out when considering the meteorological conditions.

Fig. 7 Average length and good weather hours during the months in last 2 years.

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Instrument and operators

Easily we can also correlate the frequency of technical failures in dependence of the instrument used and of the night operator. Fig. 8 shows how the efficiency of each instrument is quite the same and that also the different operators (5 at TNG) do not have preferred (or hated) instrument. The absence of any correlation is signal of good spread of knowledge of the whole system among the night staff.

Fig. 8 Average efficiency (absence of technical failures) divided by instrument (DOL,

NIC, SRG, HAN) and night operator (shown as A, B, C, D and E.

4 REFERENCES

[1] Molinari, E. and Hernandez, N.: 2012, Amsterdam SPIE Conference 8448-79 [2] Guerra, J. et al, 2014, Montreal SPIE Conference 9152-60 [3] Cosentino, R. et al 2012, Amsterdam SPIE Conference 8446-66 [4] Cosentino, R. et al, 2014, Montreal SPIE Conference 9147-314