The ZTF Bright Transient Survey


Sample SummaryLatest TransientsUnclassified SN CandidatesCompleteness StatisticsPapersTeamSample Explorer


The Zwicky Transient Facility (ZTF) Bright Transient Survey is by far the largest spectroscopic supernova survey ever conducted. Since June of 2018 we have been surveying the entire nighttime Northern sky every 2-3 nights in two filters and acquiring spectra of (almost) every time-varying, nonmoving object brighter than 18.5 mag that is not a Galactic source or an AGN, providing a complete and unbiased view of the dynamic optical sky. Transients down to 19.0 mag are also targeted when possible (given available spectroscopic resources). Between 2017 and 2020 we catalogued almost 4000 supernovae. Between 2021 and 2024 we expect to increase this total to almost 10000, including hundreds of "exotic" transients: tidal disruption events, superluminous supernovae, and the like. So far we have detected 6790 spectroscopically-confirmed transients (6697 supernovae and 93 transients of other types). The large majority of these classifications were provided by our programs.

Alert data (including preliminary photometry) is released in real time via ZTF Alert Brokers (1,2,3,4) and spectra and classifications are announced nightly via TNS.

Cumulative properties of the sample are compiled here and in our papers. Some properties of the current sample can be explored in detail using the BTS Sample Explorer.


Sample Summary

The statistics below (by class and limiting peak magnitude) are updated daily: numbers in each cell provide the total of publicly-available TNS classifications of each type. Classifications come mostly from our own programs, but also use reports from other groups via TNS. Not all classifications are final and statistics do not include transients with non-public classifications. The table on the right includes every ZTF Northern Sky Survey transient above 19.0 magnitude; the table on the left is specific to events passing a variety of cuts to establish a high-quality statistical sample: see below for details. Plots show a skymap of all confirmed extragalactic transients, and a preliminary luminosity-duration plot for sample transients.

SN-like events passing sample cuts:
mag ≤19.018.518.017.517.0
All typed419126961364738373
All SNe414326571337722362
Ia31241999992546277
Ia-CSM33222
Iax74222
Ib/c237154783720
Ibn2014931
Ic-BL41311564
SLSN-I3415761
II74848926013364
IIb613721116
IIn10574392111
SLSN-II189410
TDE1610733
Gap76432
Ca-rich10000
LRN11000
ILRT22221
LBV33211
Novae23211595
Other22111
All events:
mag ≤19.018.518.017.517.0
All typed6790450123451275643
All SNe6697442822961249627
Ia493432671683929476
Ia-CSM108544
Iax129643
Ib/c3502401326530
Ibn24181262
Ic-BL534122106
SLSN-I552714102
II1358894467245119
IIb915635199
IIn183128673617
SLSN-II3520610
TDE40271654
Gap1512843
Ca-rich31000
LRN22100
ILRT43321
LBV66422
Novae363224168
Other22111
Note: the classes above are not all independent (e.g. the total for Ib/c includes Ibn and Ic-BL; the total for II includes IIb, IIn, and SLSN-II) so the sum of the individual SN counts is greater than the "All SNe" count. BTS classifications are based on low-resolution 2m-class spectra and while basic type classifications are reliable, we are not complete in assigning subtypes (II vs. IIb, Ib vs. Ic, etc.). The table on the left is restricted to events with P48 coverage before and after peak, good visibility, and "SN-like" behavior (a light curve slower than typical CV's or a host association, and faster evolution than AGNs). See completeness for classification completeness statistics. Magnitudes are at the observed peak (in either filter) - for poorly sampled light curves this may underestimate the flux of the true peak.

Latest Transients

The following list shows the most recent candidates saved to the program. No light curve or host-galaxy filtering has been applied, so this may include some false positives such as cataclysmic variables or AGNs.

IDTNSIDsavedRAdecΔtlastmlasttypez
ZTF22abjpfplAT2022won2022-10-0204:43:42.45-20:44:00.20.66g = 18.82--
ZTF22abjnuatAT2022woo2022-10-0201:34:11.13+34:42:01.80.70g = 18.80--
ZTF22abiqeriAT2022woz2022-10-0200:53:59.00+36:16:39.90.72g = 19.70--
ZTF22abipvjlAT2022wpa2022-10-0222:45:29.68+01:15:26.30.81r = 19.69--
ZTF22abitawbAT2022wpb2022-10-0205:03:58.96+66:57:33.10.63r = 19.56--
ZTF22abjobnkAT2022wmy2022-10-0200:19:15.81-27:46:45.50.77r = 19.95--
ZTF22abjhhlaAT2022wox2022-10-0202:40:46.58+07:32:33.20.75r = 19.39--
ZTF22abjfiyjAT2022wfy2022-10-0223:21:11.52-12:25:10.90.81r = 19.73--
ZTF22abkdzviAT2022woy2022-10-0221:34:59.28-10:49:46.60.87g = 19.76--
ZTF22abibxztAT2022vpi2022-10-0202:30:37.77+31:03:45.40.69g = 19.71--
ZTF22abkfyswAT2022wph2022-10-0322:00:16.06-25:49:36.80.81r = 19.64--
ZTF22abkfzplAT2022wpi2022-10-0322:01:18.42-24:04:09.80.81r = 19.34--
ZTF22abkfgrtAT2022wpj2022-10-0322:25:12.84-10:34:25.80.81r = 19.70--
ZTF22abkkrsvAT2022wpk2022-10-0304:03:50.56+28:15:46.60.63r = 19.68--
ZTF22abkkvgvAT2022wpl2022-10-0303:51:03.39+23:48:26.40.63r = 19.70--

Supernova Candidates Needing Classification

The following list shows older SN candidates still needing classification, and may be useful to observers with classification programs in need of targets (the most recent ZTF magnitude is provided below). A looser version of the sample cuts has been applied to this list to remove some false positives and poorly-observed SNe. Because the whole light curve is not available yet there may still be a few false positives in this list.

IDTNSIDsavedRAdecΔtlastmlast
ZTF22aavvqyhAT2022pna2022-08-0201:41:55.54-03:17:22.64.69g = 19.54
ZTF22aazbxmiAT2022qzx2022-08-0918:02:17.74+80:06:03.15.96r = 19.54
ZTF22aazjiamAT2022qxc2022-08-1000:18:10.24+01:20:17.03.79r = 19.11
ZTF22abbcnayAT2022rmk2022-08-2122:22:49.14-20:21:01.21.77g = 19.75
ZTF22abemdrvAT2022sup2022-09-0104:24:44.17+29:25:16.97.63r = 19.15
ZTF22abemcpyAT2022rau2022-09-0305:02:53.74-01:17:15.64.59r = 19.27
ZTF22abajudiAT2022lri2022-09-0302:20:08.01-22:43:15.24.61r = 18.89
ZTF22abfnfudAT2022tmo2022-09-0504:35:51.41-13:19:38.12.59r = 17.88
ZTF22abfxmpcAT2022ubf2022-09-1700:42:30.04+41:56:12.50.72g = 19.32
ZTF22abfwihcAT2022ubt2022-09-1719:16:28.78+41:53:21.41.90r = 18.98
ZTF22abfwignAT2022udk2022-09-1719:25:21.89+52:19:34.01.81g = 19.01
ZTF22abfyvhfAT2022uot2022-09-1705:37:10.50+68:34:31.90.63r = 19.35
ZTF22abegjtxAT2022upj2022-09-1700:23:56.86-14:25:23.42.74g = 18.65
ZTF22abfyrxhAT2022uua2022-09-1900:36:27.97+12:26:41.30.79r = 17.28
ZTF22abgbywxAT2022urs2022-09-2019:04:32.10-22:11:10.42.92r = 17.93
ZTF22abgpfwaAT2022vej2022-09-2016:04:10.32+28:20:22.51.91r = 18.33
ZTF22abfyqscAT2022ujq2022-09-2101:07:39.14-06:46:21.82.73g = 18.86
ZTF22abhhxuvAT2022vmi2022-09-2207:46:45.23+23:41:48.11.58g = 18.75
ZTF22abhjdlxAT2022voh2022-09-2306:26:04.99+55:35:00.81.60g = 18.46
ZTF22abhuvqjAT2022vrc2022-09-2404:48:32.96-10:37:09.32.59r = 18.10
ZTF22abhxpttAT2022vwf2022-09-2519:23:50.06+44:15:50.31.84r = 18.75

Completeness

Our goal is to be close to 100% spectroscopically complete for all genuine extragalactic transients brighter than 18.5 magnitude that are detected in more than one imaging epoch in the survey footprint, for which the epoch of maximum light is clearly observed, and which do not set within about a month after maximum light. (Transients that do not meet these cuts are also observed when possible.) Our actual completeness for events meeting all these criteria is about 95%. (The remaining 5% are mostly concentrated in periods of bad weather that affected our spectroscopic follow-up programs.)

The table at left below presents classification success statistics (by limiting magnitude) for events meeting these criteria (at left) and exhibiting "SN-like behavior" (slow rise and/or fade time, or coincident with a galaxy). The month and peak magnitude are as observed (in either filter). These totals do include unreleased classifications, so they are slightly higher than the totals given in the type-specific table above. The table at right includes all events, including those with poor visibility which could not be classified (many of these are stars).

A visualization of this is also given in the figure at right: large points indicate classification successes (green circle) or failures (red X) for sample transients; small dots show other potential transients that fail our cuts.

SN-like events passing sample cuts:
mag≤19.0≤18.5≤18.0≤17.5≤17.0
2018 May19/23 (82.6%)19/21 (90.5%)7/7 (100%)4/4 (100%)3/3 (100%)
2018 Jun40/43 (93.0%)22/22 (100%)12/12 (100%)7/7 (100%)6/6 (100%)
2018 Jul53/55 (96.4%)30/31 (96.8%)13/13 (100%)4/4 (100%)3/3 (100%)
2018 Aug48/49 (98.0%)27/27 (100%)15/15 (100%)6/6 (100%)2/2 (100%)
2018 Sep28/33 (84.8%)18/20 (90.0%)9/10 (90.0%)4/4 (100%)3/3 (100%)
2018 Oct1/1 (100%)0/00/00/00/0
2018 Nov46/58 (79.3%)26/29 (89.7%)16/17 (94.1%)10/10 (100%)4/4 (100%)
2018 Dec60/79 (75.9%)44/47 (93.6%)24/24 (100%)14/14 (100%)9/9 (100%)
2019 Jan53/115 (46.1%)42/67 (62.7%)31/38 (81.6%)24/25 (96.0%)16/16 (100%)
2019 Feb54/90 (60.0%)40/53 (75.5%)22/23 (95.7%)11/11 (100%)7/7 (100%)
2019 Mar58/76 (76.3%)34/36 (94.4%)23/23 (100%)17/17 (100%)11/11 (100%)
2019 Apr99/133 (74.4%)69/74 (93.2%)35/36 (97.2%)13/13 (100%)2/2 (100%)
2019 May76/106 (71.7%)55/59 (93.2%)37/38 (97.4%)17/17 (100%)8/8 (100%)
2019 Jun95/112 (84.8%)58/58 (100%)30/30 (100%)15/15 (100%)6/6 (100%)
2019 Jul100/113 (88.5%)54/54 (100%)30/30 (100%)12/12 (100%)6/6 (100%)
2019 Aug115/133 (86.5%)60/60 (100%)25/25 (100%)13/13 (100%)6/6 (100%)
2019 Sep122/143 (85.3%)80/81 (98.8%)46/47 (97.9%)22/23 (95.7%)14/14 (100%)
2019 Oct122/158 (77.2%)68/71 (95.8%)31/31 (100%)15/15 (100%)10/10 (100%)
2019 Nov115/163 (70.6%)79/87 (90.8%)41/41 (100%)17/17 (100%)7/7 (100%)
2019 Dec60/85 (70.6%)45/47 (95.7%)25/25 (100%)14/14 (100%)6/6 (100%)
2020 Jan113/153 (73.9%)79/82 (96.3%)35/37 (94.6%)15/16 (93.8%)8/8 (100%)
2020 Feb133/171 (77.8%)83/86 (96.5%)49/50 (98.0%)22/22 (100%)8/8 (100%)
2020 Mar14/15 (93.3%)13/13 (100%)6/6 (100%)2/2 (100%)1/1 (100%)
2020 Apr49/71 (69.0%)37/37 (100%)22/22 (100%)10/10 (100%)6/6 (100%)
2020 May111/155 (71.6%)75/75 (100%)42/42 (100%)22/22 (100%)12/12 (100%)
2020 Jun102/128 (79.7%)60/61 (98.4%)30/31 (96.8%)20/20 (100%)8/8 (100%)
2020 Jul76/105 (72.4%)42/44 (95.5%)26/27 (96.3%)12/12 (100%)6/6 (100%)
2020 Aug79/89 (88.8%)44/46 (95.7%)18/19 (94.7%)10/11 (90.9%)5/5 (100%)
2020 Sep99/119 (83.2%)58/59 (98.3%)28/28 (100%)18/18 (100%)9/9 (100%)
2020 Oct138/170 (81.2%)82/83 (98.8%)41/41 (100%)24/24 (100%)11/11 (100%)
2020 Nov134/180 (74.4%)82/86 (95.3%)36/36 (100%)22/22 (100%)12/12 (100%)
2020 Dec130/193 (67.4%)95/95 (100%)40/40 (100%)24/24 (100%)11/11 (100%)
2021 Jan91/133 (68.4%)67/69 (97.1%)39/39 (100%)24/24 (100%)9/9 (100%)
2021 Feb112/151 (74.2%)75/76 (98.7%)36/36 (100%)20/20 (100%)11/11 (100%)
2021 Mar103/157 (65.6%)76/76 (100%)31/31 (100%)13/13 (100%)8/8 (100%)
2021 Apr140/175 (80.0%)94/95 (98.9%)47/48 (97.9%)32/32 (100%)13/13 (100%)
2021 May113/144 (78.5%)59/60 (98.3%)31/32 (96.9%)15/16 (93.8%)8/8 (100%)
2021 Jun94/127 (74.0%)63/64 (98.4%)27/27 (100%)15/15 (100%)8/8 (100%)
2021 Jul106/142 (74.6%)73/78 (93.6%)35/35 (100%)17/17 (100%)7/7 (100%)
2021 Aug101/127 (79.5%)60/60 (100%)38/38 (100%)21/21 (100%)8/8 (100%)
2021 Sep132/153 (86.3%)74/78 (94.9%)32/34 (94.1%)17/17 (100%)6/6 (100%)
2021 Oct99/135 (73.3%)62/67 (92.5%)34/34 (100%)26/26 (100%)12/12 (100%)
2021 Nov89/128 (69.5%)55/57 (96.5%)24/24 (100%)13/13 (100%)8/8 (100%)
2021 Dec0/00/00/00/00/0
2022 Jan0/00/00/00/00/0
2022 Feb0/6 (0.0%)0/1 (0.0%)0/00/00/0
2022 Mar0/00/00/00/00/0
2022 Apr67/113 (59.3%)52/54 (96.3%)24/24 (100%)17/17 (100%)10/10 (100%)
2022 May87/141 (61.7%)65/67 (97.0%)27/28 (96.4%)11/12 (91.7%)8/8 (100%)
2022 Jun99/129 (76.7%)62/63 (98.4%)30/30 (100%)17/17 (100%)11/11 (100%)
2022 Jul94/118 (79.7%)56/56 (100%)30/30 (100%)16/16 (100%)8/8 (100%)
2022 Aug96/125 (76.8%)53/56 (94.6%)24/24 (100%)17/17 (100%)10/10 (100%)
2022 Sep75/96 (78.1%)49/54 (90.7%)16/18 (88.9%)9/10 (90.0%)3/4 (75.0%)
2022 Oct0/00/00/00/00/0
all4240/5617
(75.5%)
2715/2842
(95.5%)
1370/1396
(98.1%)
740/747
(99.1%)
374/375
(99.7%)
All events (includes many unclassified variables):
mag≤19.0≤18.5≤18.0≤17.5≤17.0
2018 May61/67 (91.0%)44/47 (93.6%)22/22 (100%)9/9 (100%)7/7 (100%)
2018 Jun80/91 (87.9%)44/46 (95.7%)21/22 (95.5%)11/11 (100%)8/8 (100%)
2018 Jul85/93 (91.4%)56/59 (94.9%)27/27 (100%)13/13 (100%)6/6 (100%)
2018 Aug81/91 (89.0%)55/61 (90.2%)31/35 (88.6%)17/20 (85.0%)7/8 (87.5%)
2018 Sep137/164 (83.5%)80/91 (87.9%)37/43 (86.0%)17/20 (85.0%)8/10 (80.0%)
2018 Oct19/22 (86.4%)12/14 (85.7%)7/9 (77.8%)7/9 (77.8%)3/4 (75.0%)
2018 Nov170/212 (80.2%)107/125 (85.6%)66/78 (84.6%)37/39 (94.9%)18/19 (94.7%)
2018 Dec133/198 (67.2%)98/124 (79.0%)50/59 (84.7%)29/32 (90.6%)20/20 (100%)
2019 Jan83/180 (46.1%)66/111 (59.5%)46/62 (74.2%)30/34 (88.2%)17/18 (94.4%)
2019 Feb106/179 (59.2%)78/116 (67.2%)44/51 (86.3%)26/27 (96.3%)13/14 (92.9%)
2019 Mar115/160 (71.9%)67/85 (78.8%)39/48 (81.3%)28/31 (90.3%)18/20 (90.0%)
2019 Apr127/194 (65.5%)88/112 (78.6%)41/50 (82.0%)16/22 (72.7%)4/7 (57.1%)
2019 May114/177 (64.4%)85/98 (86.7%)48/51 (94.1%)28/28 (100%)13/13 (100%)
2019 Jun162/212 (76.4%)116/123 (94.3%)55/57 (96.5%)30/31 (96.8%)14/14 (100%)
2019 Jul145/182 (79.7%)82/90 (91.1%)42/46 (91.3%)17/21 (81.0%)9/11 (81.8%)
2019 Aug150/194 (77.3%)83/92 (90.2%)37/42 (88.1%)17/20 (85.0%)6/9 (66.7%)
2019 Sep143/198 (72.2%)96/106 (90.6%)56/62 (90.3%)28/31 (90.3%)17/17 (100%)
2019 Oct165/256 (64.5%)100/126 (79.4%)48/59 (81.4%)27/32 (84.4%)17/21 (81.0%)
2019 Nov169/274 (61.7%)121/155 (78.1%)64/79 (81.0%)28/35 (80.0%)14/19 (73.7%)
2019 Dec119/183 (65.0%)92/108 (85.2%)50/54 (92.6%)25/27 (92.6%)11/12 (91.7%)
2020 Jan173/267 (64.8%)119/142 (83.8%)56/66 (84.8%)22/25 (88.0%)12/13 (92.3%)
2020 Feb177/258 (68.6%)118/137 (86.1%)70/76 (92.1%)34/36 (94.4%)14/16 (87.5%)
2020 Mar78/122 (63.9%)60/73 (82.2%)33/35 (94.3%)16/17 (94.1%)11/11 (100%)
2020 Apr107/221 (48.4%)85/111 (76.6%)51/67 (76.1%)30/36 (83.3%)20/24 (83.3%)
2020 May136/224 (60.7%)97/120 (80.8%)53/63 (84.1%)26/30 (86.7%)15/18 (83.3%)
2020 Jun130/199 (65.3%)86/105 (81.9%)47/56 (83.9%)29/32 (90.6%)10/12 (83.3%)
2020 Jul120/204 (58.8%)73/101 (72.3%)39/54 (72.2%)17/27 (63.0%)10/13 (76.9%)
2020 Aug103/138 (74.6%)61/74 (82.4%)27/32 (84.4%)14/17 (82.4%)6/7 (85.7%)
2020 Sep133/198 (67.2%)86/109 (78.9%)46/60 (76.7%)28/34 (82.4%)16/19 (84.2%)
2020 Oct177/279 (63.4%)105/142 (73.9%)61/84 (72.6%)34/51 (66.7%)18/28 (64.3%)
2020 Nov166/282 (58.9%)105/137 (76.6%)52/64 (81.3%)32/36 (88.9%)20/23 (87.0%)
2020 Dec170/297 (57.2%)125/159 (78.6%)56/73 (76.7%)30/38 (78.9%)13/18 (72.2%)
2021 Jan162/281 (57.7%)116/148 (78.4%)64/78 (82.1%)31/40 (77.5%)14/18 (77.8%)
2021 Feb186/312 (59.6%)128/163 (78.5%)69/83 (83.1%)38/47 (80.9%)19/24 (79.2%)
2021 Mar128/240 (53.3%)93/122 (76.2%)40/54 (74.1%)20/29 (69.0%)9/14 (64.3%)
2021 Apr157/241 (65.1%)106/128 (82.8%)55/67 (82.1%)36/43 (83.7%)15/19 (78.9%)
2021 May154/236 (65.3%)88/112 (78.6%)50/60 (83.3%)25/31 (80.6%)13/16 (81.3%)
2021 Jun129/215 (60.0%)90/113 (79.6%)42/49 (85.7%)23/25 (92.0%)13/14 (92.9%)
2021 Jul133/204 (65.2%)91/107 (85.0%)47/55 (85.5%)23/25 (92.0%)9/10 (90.0%)
2021 Aug140/198 (70.7%)83/95 (87.4%)51/55 (92.7%)23/23 (100%)9/9 (100%)
2021 Sep154/211 (73.0%)90/103 (87.4%)43/47 (91.5%)22/23 (95.7%)9/9 (100%)
2021 Oct135/230 (58.7%)88/115 (76.5%)55/66 (83.3%)40/44 (90.9%)20/23 (87.0%)
2021 Nov155/263 (58.9%)99/132 (75.0%)46/63 (73.0%)26/35 (74.3%)12/17 (70.6%)
2021 Dec30/45 (66.7%)17/25 (68.0%)12/17 (70.6%)6/9 (66.7%)3/4 (75.0%)
2022 Jan25/37 (67.6%)13/15 (86.7%)8/8 (100%)3/3 (100%)0/0
2022 Feb152/271 (56.1%)110/144 (76.4%)58/72 (80.6%)32/39 (82.1%)12/15 (80.0%)
2022 Mar49/75 (65.3%)27/34 (79.4%)10/13 (76.9%)4/5 (80.0%)1/2 (50.0%)
2022 Apr148/301 (49.2%)110/157 (70.1%)53/71 (74.6%)38/44 (86.4%)21/24 (87.5%)
2022 May113/229 (49.3%)84/111 (75.7%)40/52 (76.9%)19/26 (73.1%)14/17 (82.4%)
2022 Jun135/215 (62.8%)88/107 (82.2%)45/53 (84.9%)30/34 (88.2%)15/15 (100%)
2022 Jul127/170 (74.7%)79/86 (91.9%)40/44 (90.9%)25/28 (89.3%)14/16 (87.5%)
2022 Aug116/177 (65.5%)68/86 (79.1%)31/38 (81.6%)21/24 (87.5%)13/13 (100%)
2022 Sep166/253 (65.6%)106/128 (82.8%)45/54 (83.3%)25/30 (83.3%)9/12 (75.0%)
2022 Oct21/51 (41.2%)15/24 (62.5%)7/10 (70.0%)4/4 (100%)1/1 (100%)
all6772/10495
(64.5%)
4497/5572
(80.7%)
2342/2804
(83.5%)
1273/1489
(85.5%)
643/754
(85.3%)
Note: Months correspond to equal divisions of the calendar year into 12 segments rather than standard calendar months. Sky-area coverage during summer 2018 was much reduced due to reference-building. P48 was closed for maintenance for almost all of October 2018. Most of March 2020 was lost due to weather (3 consecutive weeks of rain/cloud) and few events met the sample criteria. Extensive camera downtime between Dec 2021 and Apr 2022 meant that no events had sufficient coverage to pass the sample criteria in this period. The most recent 1-2 months are generally undercounts, since classifications of declining objects are still being performed. These statistics include some events for which classifications have not yet been publicly released.

BTS Papers


Team Members and Current Contributors

Christoffer Fremling (Caltech)
Daniel Perley (LJMU)
Adam Miller (Northwestern)
Shri Kulkarni (Caltech)
Aishwarya Dahiwale (Caltech)
Yashvi Sharma (Caltech)
Don Neill (Caltech)
Jesper Sollerman (Stockholm)
Xander Hall (Caltech)
K-Ryan Hinds (LJMU)
Mat Smith (IN2P3)
Matt Chu (Caltech)
Yujing Qin (Caltech)
Nabeel Rehemtulla (Northwestern)
Christopher Phillips (Washington)
Suhail Dhawan (Stockholm)
Ariel Goobar (Stockholm)
Rahul Biswas (Stockholm)
Melissa Graham (Washington)
Jakob Nordin (Humboldt)
Rachel Bruch (Weizmann)
Steve Schulze (Weizmann)
Ido Irani (Weizmann)
Erez Zimmerman (Weizmann)
Alex Filippenko (UCB)
Kishore Patra (UCB)
Shaunak Modak (UCB)
Andrew Hoffman (UCB)
Jannis Necker (DESY)
Ludwig Rauch (DESY)
Samantha Goldwasser (DESY)
Michael May (UCB)