Do you want to publish a course? Click here

Maximum Likelihood Signal Extraction Method Applied to 3.4 years of CoGeNT Data

98   0   0.0 ( 0 )
 Added by John Orrell
 Publication date 2014
  fields Physics
and research's language is English




Ask ChatGPT about the research

CoGeNT has taken data for over 3 years, with 1136 live days of data accumulated as of April 23, 2013. We report on the results of a maximum likelihood analysis to extract any possible dark matter signal present in the collected data. The maximum likelihood signal extraction uses 2-dimensional probability density functions (PDFs) to characterize the anticipated variations in dark matter interaction rates for given observable nuclear recoil energies during differing periods of the Earths annual orbit around the Sun. Cosmogenic and primordial radioactivity backgrounds are characterized by their energy signatures and in some cases decay half-lives. A third parameterizing variable -- pulse rise-time -- is added to the likelihood analysis to characterize slow rising pulses described in prior analyses. The contribution to each event category is analyzed for various dark matter signal hypotheses including a dark matter standard halo model and a case with free oscillation parameters (i.e., amplitude, period, and phase). The best-fit dark matter signal is in close proximity to previously reported results. We find that the significance of the extracted dark matter signal remains well below evidentiary at 1.7 $sigma$.



rate research

Read More

Weakly Interacting Massive Particles (WIMPs) are well-established dark matter candidates. WIMP interactions with sensitive detectors are expected to display a characteristic annual modulation in rate. We release a dataset spanning 3.4 years of operation from a low-background germanium detector, designed to search for this signature. A previously reported modulation persists, concentrated in a region of the energy spectrum populated by an exponential excess of unknown origin. Its phase and period agree with phenomenological expectations, but its amplitude is a factor $sim$4-7 larger than predicted for a standard WIMP galactic halo. We consider the possibility of a non-Maxwellian local halo velocity distribution as a plausible explanation, able to help reconcile recently reported WIMP search anomalies.
We report on the results of a search for a Weakly Interacting Massive Particle (WIMP) signal in low-energy data of the Cryogenic Dark Matter Search (CDMS~II) experiment using a maximum likelihood analysis. A background model is constructed using GEANT4 to simulate the surface-event background from $^{210}$Pb decay-chain events, while using independent calibration data to model the gamma background. Fitting this background model to the data results in no statistically significant WIMP component. In addition, we perform fits using an analytic ad hoc background model proposed by Collar and Fields, who claimed to find a large excess of signal-like events in our data. We confirm the strong preference for a signal hypothesis in their analysis under these assumptions, but excesses are observed in both single- and multiple-scatter events, which implies the signal is not caused by WIMPs, but rather reflects the inadequacy of their background model.
We have developed a maximum likelihood source detection method capable of detecting ultra-faint streaks with surface brightnesses approximately an order of magnitude fainter than the pixel level noise. Our maximum likelihood detection method is a model based approach that requires no a priori knowledge about the streak location, orientation, length, or surface brightness. This method enables discovery of typically undiscovered objects, and enables the utilization of low-cost sensors (i.e., higher-noise data). The method also easily facilitates multi-epoch co-addition. We will present the results from the application of this method to simulations, as well as real low earth orbit observations.
An annual modulation signal due to the Earth orbiting around the Sun would be one of the strongest indications of the direct detection of dark matter. In 2016, we reported a search for dark matter by looking for this annual modulation with our single-phase liquid xenon XMASS-I detector. That analysis resulted in a slightly negative modulation amplitude at low energy. In this work, we included more than one year of additional data, which more than doubles the exposure to 800 live days with the same 832 kg target mass. When we assume weakly interacting massive particle (WIMP) dark matter elastically scattering on the xenon target, the exclusion upper limit for the WIMP-nucleon cross section was improved by a factor of 2 to 1.9$times$10$^{-41}$cm$^2$ at 8 GeV/c$^2$ at 90% confidence level with our newly implemented data selection through a likelihood method. For the model-independent case, without assuming any specific dark matter model, we obtained more consistency with the null hypothesis than before with a $p$-value of 0.11 in the 1$-$20 keV energy region. This search probed this region with an exposure that was larger than that of DAMA/LIBRA. We also did not find any significant amplitude in the data for periodicity with periods between 50 and 600 days in the energy region between 1 to 6 keV.
A new method of shower-image analysis is presented which appears very powerful as applied to those Cherenkov Imaging Telescopes with very high definition imaging capability. It provides hadron rejection on the basis of a single cut on the image shape, and simultaneously determines the energy of the electromagnetic shower and the position of the shower axis with respect to the detector. The source location is also reconstructed for each individual gamma-ray shower, even with one single telescope, so for a point source the hadron rejection can be further improved. As an example, this new method is applied to data from the CAT (Cherenkov Array at Themis) imaging telescope, which has been operational since Autumn, 1996.
comments
Fetching comments Fetching comments
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا