String 21 Flashers String 21 Flashers and AMANDAand AMANDA

Michelangelo D’AgostinoMichelangelo D’Agostino

UC BerkeleyUC Berkeley

London Collaboration MeetingLondon Collaboration Meeting

M. D’Agostino

ThanksThanks

Dave Hardtke: for doing the first Dave Hardtke: for doing the first work on thiswork on this

Kurt: for being the ice guruKurt: for being the ice guru John Pretz: for writing his John Pretz: for writing his

wonderful, bugless merging wonderful, bugless merging module for the rest of us to usemodule for the rest of us to use

IceTray

M. D’Agostino

OutlineOutline

Are the String 21 flashers bright Are the String 21 flashers bright enough to be seen by AMANDA?enough to be seen by AMANDA?

What do these events look like?What do these events look like? Can such flasher events be used Can such flasher events be used

for any calibration or ice property for any calibration or ice property measurements?measurements?

M. D’Agostino

The Verdict:The Verdict:

Yes!Yes! up to 60% ofup to 60% offlashes trigger flashes trigger AMANDAAMANDA Roughly 40 toRoughly 40 to50% of the 50% of the AMANDA events AMANDA events were string-were string-triggeredtriggered

closest AMANDA strings

M. D’Agostino

What do the events What do the events look like?look like?

DOM 23 flashing

M. D’Agostino

What do the events What do the events look like?look like?

DOM 23 flashing

M. D’Agostino

What do the events What do the events look like?look like?

910 16

Stuck String

M. D’Agostino

What do the events What do the events look like?look like? DOM 23 z position

M. D’Agostino

Up and Down String 21Up and Down String 21

DOM 12

DOM 23

DOM 32

M. D’Agostino

Analysis DetailsAnalysis Details

in July, flasher runs were taken for in July, flasher runs were taken for all DOM’s on string 21all DOM’s on string 21

10 Hz, full brightness, all 12 LED’s10 Hz, full brightness, all 12 LED’s run monolith offline, requiring a run monolith offline, requiring a

simple multiplicity of 10 string 21 simple multiplicity of 10 string 21 hits in a 5000 ns windowhits in a 5000 ns window

M. D’Agostino

Analysis DetailsAnalysis Details

use John’s Icetray merging module use John’s Icetray merging module to look for AMANDA triggers with -20 to look for AMANDA triggers with -20 s < s < t < -5 t < -5 s of a String 21 triggers of a String 21 trigger

filter out muons (about 1/4 of filter out muons (about 1/4 of events): require that the flashing events): require that the flashing DOM be present in the event and DOM be present in the event and that ATWD channel 3 has a digitized that ATWD channel 3 has a digitized current pulse current pulse

M. D’Agostino

DOM 23

what’s going on here? DOM 16

Up and Down String 21Up and Down String 21Ryan’s dustlogger data for String 21

M. D’Agostino

Ice Properties: Fluence Ice Properties: Fluence AnalysisAnalysis from Poissonian statistics, the average from Poissonian statistics, the average

number of received photons in the number of received photons in the diffusive regime is given by <Ndiffusive regime is given by <N>=->=-log[P(0)], where P(0) is the probability log[P(0)], where P(0) is the probability that the receiver is not hitthat the receiver is not hit

1/1/λλ, where , where λλ is the propagation length, is the propagation length, is given by the slope of log[<N>d] vs. is given by the slope of log[<N>d] vs. d, where d is distance from the light d, where d is distance from the light sourcesource

M. D’Agostino

Ice PropertiesIce Properties3 closest strings

restrict z to +-5 m of the flashing DOM to probe a narrower ice layer

corresponds to a corresponds to a λλ of 45.3 m +- of 45.3 m +-11.8 m11.8 m

photons all the way to ~400 m

DOM 16 flashing

M. D’Agostino

Ice PropertiesIce Properties

M. D’Agostino

Ice PropertiesIce Properties

dip from previous graph

maximum from previous graph

M. D’Agostino

Ice PropertiesIce Properties

we have a biased sample though, since we have a biased sample though, since AMANDA had to be triggered to see the AMANDA had to be triggered to see the OM hits; the data is L1 filtered as wellOM hits; the data is L1 filtered as well

P(0) is an overestimate <N> is an P(0) is an overestimate <N> is an underestimate that varies with distanceunderestimate that varies with distance

thus, these are thus, these are upper limits upper limits on the on the propagation lengthspropagation lengths

flasher variability is more likely the culprit flasher variability is more likely the culprit for the suspicious dip (cf. Chris Wendt’s for the suspicious dip (cf. Chris Wendt’s talk); longer width runs are needed to telltalk); longer width runs are needed to tell

M. D’Agostino

ConclusionsConclusions

the flashers are pretty damn brightthe flashers are pretty damn bright ice properties have been measured ice properties have been measured

over a greater horizontal distance and over a greater horizontal distance and give reasonable agreementgive reasonable agreement

since flashers should be seen in ~9 since flashers should be seen in ~9 IceCube strings, such a method will be IceCube strings, such a method will be much more useful in the future for much more useful in the future for measuring local ice properties, measuring local ice properties, especially with a unified trigger systemespecially with a unified trigger system

M. D’Agostino

ConclusionsConclusions

flasher coincidences might also flasher coincidences might also be useful in AMANDA simulation—be useful in AMANDA simulation—a simulation capable of a simulation capable of reproducing the depth variation in reproducing the depth variation in this simple flasher system would this simple flasher system would surely have a better handle on surely have a better handle on systematics (COGz?)systematics (COGz?)