Robotic Bochum Twin Telescope RoBoTT The Robotic Bochum Twin Telescope (RoBoTT) operated from December 2008 to September 2019 at the Universitaetssternwarte Bochum near Cerro Armazones in the Chilean Atacama desert. It consists of two refractor telescopes (15 cm aperture, 2°42'' × 2°42'' FoV CCDs) attached to the same mount. The fields were observed in Johnson UVBRI, Sloan ugriz, and the narrowband OIII, NB, Halpha, and SII filters. The first batch contains fields that were observed in Johnson U and Sloan z; further RoBoTT fields will be added at a later date. Bochum Galactic Disk Survey (BGDS) images, which were also taken with the RoBoTT, are available separately from ivo://org.gavo.dc/bgds/q/sia. 2025-12-15T12:00:00 20 surveys galaxy-planes milky-way-galaxy variable-stars broad-band-photometry Blex, J.; Ramolla, M.; Westhues, C.; Demleitner, M.; Hackstein, M.; Chini, R. Robotic Bochum Twin Telescope (RoBoTT) Universitätssternwarte Bochum near Cerro Armazones 2026AN....34770087B Research Survey If you use RoBoTT data, please cite :bibcode:`2026AN....34770087B`. Optical //siap2#pgs dl obs_publisher_did //obscore#publishObscoreLike previews \inputRelativePath{True} "\schema.data" "image/jpeg" \splitPreviewPath{.jpeg} "UNKNOWN" { 'B': "Johnson B", 'B_j': "Johnson B", 'Halpha': "Astrodon Halpha", 'Ha': "Astrodon Halpha", 'SII': "Astrodon SII", 'OII': "Astrodon OIII", 'OIII': "Astrodon OIII", 'NB': "Astrodon NB", 'i': "SDSS i'", 'i_s': "SDSS i'", 'g_s': "SDSS g'", 'r': "SDSS r'", 'r_s': "SDSS r'", 'u_s': "SDSS u'", 'R': "Johnson R", 'R_j': "Johnson R", 'U': "Johnson U", 'U_j': "Johnson U", 'V_j': "Johnson V", 'I_j': "Johnson I", 'V': "Johnson V", 'z': "SDSS z'", 'z_s': "SDSS z'", } "FILTER" @FILTER.strip() 2 "image" parseISODT(@DATE_OBS) "RoBoTT" "RoBoTT %s %s %s"%( @TARGET.strip(), @FILTER.strip(), @DATE_OBS) @EXPTIME None RoBoTT Datalink This service lets you access cutouts from RoBoTT images and retrieve scaled versions. data/robott_raw 'bgds/data/robott' False # Check for extra, local and magic pseudo-id coming from # the time series (l_robott.rd, not added yet): MAGIC/field/band/mjd if pubDID.startswith("MAGIC"): # translate to the accref of the closest image with base.getTableConn() as conn: field, filter, dateObs = pubDID.split("/")[1:] if filter.startswith("SDSS ") and not filter.endswith("'"): filter = filter+"'" dateObs = float(dateObs) field = "GDS_"+field res = list(conn.query("select access_url from \schema.data" " where bandpass_id=%(filter)s" " and field=%(field)s" " and t_min between %(dateObs)s-0.007" " and %(dateObs)s+0.007", locals())) if len(res)!=1: raise ValueError("%s matches for %s"%( len(res), pubDID)) pubDID = getStandardPubDID(res[0][0]) return getFITSDescriptor(pubDID, accrefPrefix, cls=descClass) def get_progenitors(prodpath, field): """returns lists of raw, bias, and flat frames for a given robott/bgds path. Pass in the resdir-relative path of the file itself. This was largely contributed by Julia. """ raw, bias, flat = [], [], [] date_path = os.path.basename(prodpath).split(".comb")[0] parts = prodpath.split("/") filter_path, field_path = parts[3], parts[-1] tel_map = { "VYSOS6_a": "_V6a", "VYSOS6_b": "_V6b", "VYSOS6" : "", } with pyfits.open(rd.getAbsPath(prodpath)) as hdul: hdr = hdul[1].header tel = hdr.get("TELESCOP") tel_path = tel_map[tel] for i in range(1, 100): raw_key = f"IMCMB{i:03d}" raw_value = hdr.get(raw_key) if raw_value is None: break count_night = raw_value[11:17] pattern = rd.getAbsPath( f"data/robott_raw/FLAT/{filter_path}/{field_path}/" f"{date_path}_{count_night}_LIGHT*.fit.fz") raw.extend(sorted(glob.glob(pattern))) pattern = rd.getAbsPath( "data/robott_raw/BIAS/" f"{date_path}_*_BIAS{tel_path}.fit.fz") bias.extend(sorted(glob.glob(pattern))) pattern = rd.getAbsPath( "data/robott_raw/FLAT" +"/"+filter_path+"/*/" f"{date_path}_*_FLAT*.fit.fz") flat.extend(sorted(glob.glob(pattern))) return raw, bias, flat raw, bias, flat = get_progenitors( "/".join(descriptor.accref.split("/")[1:]), descriptor.hdr["TARGET"]) for path in raw: yield descriptor.makeLinkFromFile(path, description="A raw frame the co-added image was made from") for path in bias: yield descriptor.makeLinkFromFile(path, description="A bias frame contributing to the master bias" " frame applied to #this", contentType="application/fits") for path in flat: yield descriptor.makeLinkFromFile(path, description="A flat field contributing to the master flat" " applied to #this", contentType="application/fits") yield descriptor.makeLinkFromFile( "static/RoBoTT_Doc.pdf", description="Pipeline documentation", service=base.resolveCrossId("bgds/l2#tsdl")) robott web /bgds/q_robott/sia/info /tap Web access to Robotic Bochum Twin Telescope (RoBoTT) images You can obtain individual cutouts through the datalinks given; for mass operations, prefer the Virtual Observatory access modes (SIAP_ or the ivoa.obscore table in `our TAP service`_; the RoBoTT collection). .. _SIAP: https://dc.g-vo.org/bgds/q_robott/sia/info .. _our TAP service: https://dc.g-vo.org/tap yield T.a(href=getDatalinkMetaLink( rd.getById("dl"), data) )["Datalink"] application/x-votable+xml;content=datalink Datalink return "%.2f,%+.2f"%(data[0], data[1]) robott sia Robotic Bochum Twin Telescope (RoBoTT) images Pointed pos.ra:66.59 pos.dec:8.59 size.ra: 0.01 size.dec: 0.01 web/form self.assertHasStrings( # datalink link "ID=ivo%3A%2F%2Forg.gavo.dc%2F~%3Fbgds%2Fdata%2Frobott%2FRoBoTT_0.80px_1541-0712%2FU_j%2Feq600000ms%2F20180322.comb_avg.0001.fits.fz", # filter name properly mapped, title generation "RoBoTT RoBoTT_0.80px_1541-0712 Johnson U 2018-03-23T08:31:35", # filter selector generated ">Johnson U<") sia/siap2.xml row = self.getFirstVOTableRow() self.assertTrue(row["t_exptime"] is not None, "Empty exposure time?") previewData = utils.urlopenRemote(row["access_url"] +"?preview=True").read() self.assertTrue(b"JFIF" in previewData, "No preview?") dl/dlmeta links = self.datalinkBySemantics() self.assertEqual( set(links.keys()), {'#preview', '#this', '#progenitor', '#documentation', '#proc'}) self.assertEqual( links['#documentation'][0]["content_type"], 'application/pdf') progs = set(r["access_url"].split("/")[-1] for r in links["#progenitor"]) self.assertTrue('20171201_000050_LIGHT_V6b.fit.fz' in progs) self.assertTrue('20171201_000009_BIAS_V6b.fit.fz' in progs)