A wide variety of astrophysical observations indicate that about 85% of the matter in the universe is non-baryonic and non-luminous. The smallest galaxies are among the most dark matter-dominated objects in the universe. The optical image (yellow) from the Hubble Space Telescope is overlaid with the mass distribution reconstructed from lenses (blue) and the X-rays from the Chandra X-ray Observatory (pink), which make up most of the baryons in the cluster.
The power spectrum of primary temperature anisotropies in the CMB determined from these measurements is shown in Fig. The amplitude and shape of the power spectrum provide clear evidence for the non-baryonic density of dark matter. Dark matter must be abundant: astrophysical measurements show that the density of relict dark matter accounts for ≈85% of the total density of matter in the universe.
These properties rule out baryons or the known neutrinos (and indeed any Standard Model particles) from being the dominant component of dark matter. Furthermore, recent updates to the MSSM parameter space scan from [ 76 , 77 ], including the LHC constraints, raise the lower limit on the neutrino mass to 18 GeV [ 83 ]. The dependence of the spin-independent scattering cross section, σSI, at low mass is shown in Fig. 1b.
Uncertainties in the scattering rate due to our lack of knowledge of the detailed properties.
DAMA/LIBRA
The horizontal axis gives the number of days since January 1 of the first year DAMA/NaI operated. The modulation peaks in the lowest energy bins as expected for a WIMP signal, with no evidence for modulation above 8 keVee. Due to its point contact electrode, the capacitance of the detector is significantly reduced relative to standard.
This geometry also allows for the identification of interactions occurring within ~1 mm of the detector surface due to the slower rising pulses for such events. Further data collection confirmed this excess and provided weak evidence (∼2.8σ, limited by statistics) for a ∼15% annual modulation in the count rate at this excess [189], with a phase and spectrum consistent with that found by DAMA/LIBRA [190, 202]. In this case, the parameter space consistent with a WIMP signal providing the remaining ∼25% of the excess is pushed to WIMP masses, mχ≈10 GeV and σSI ≈2×10−41, thus increasing the agreement with the CRESST-II reported excess is improved (described in section 2.1.4.3 below), but the agreement with DAMA/LIBRA decreases unless ion channeling or local halo substructure is significant [176, 190].
If the modulation reported by CoGeNT is also due to WIMPs, then a modulation fraction of the remaining total WIMP rate of order 50–100% would be required, which is an order of magnitude larger than expected in the SHM become This larger data set will give an improved measurement of the modulation and possibly identify or rule out a background origin for the remaining low-energy excess.
CRESST-II
Due to the uncertainties in the detailed properties of the WIMP-nucleon interaction and the galactic halo presented in Sect. 1.3, accelerators have the ability to constrain dark matter models through direct production of the WIMP or related particles in the laboratory. By measuring the detailed properties of the phonon signal, both the location and energy of the interaction can be determined.
In addition, the ratio of the ionization signal to the phonon signal allows the discrimination of electron recoil. The top side of the detector is patterned with athermal phonon sensors connected in quadrants. The bias voltage is applied through aRb= 40 MΩ resistor to decouple it from the detector on the time scale of the pulse.
The upper part of the detector is modeled with thermal phonon sensors divided into 4 quadrants labeled (A, B, C, D). An example of the ionization yield measured for nuclear returns from the 252Cf calibration source and electron returns from the 133Ba source is shown in Fig. As discussed in the next section, these low-yield events are due to interactions very close to the detector surface, where ionization may be incompletely collected.
As discussed above, most surface events that leak into the nuclear recoil band occur on the phonon side of the detector. 3.1.1, is also soldered to the top of the DIB, illuminating the phonon side of its detector and the charge face of the detector above. The SQUET cards, shown in fig. 3.15c, is located at the top of the tower and consists of two separate components: a.
3.3.3, these systematic variations are taken into account by using a position-dependent calibration of the phonon energy [230]. An example of the charge energy and position calibration for a Ge detector is shown in Fig. Limits on the absolute calibration of the core-recoil energy scale using this function will be presented in [261] .
This leads to an energy scale that is calibrated within 5% of the actual energy in the energy range 0–10 keV. The ionization resolution for the T1–T3 detectors varies from 0.25–0.6 keVee, mainly due to variations in the low-frequency acquisition of the charge readout channels, as shown in Fig. 1 .
For each detector, the distribution of the standard deviation for the prepulse baseline is determined. This makes it difficult to properly account for the width of the electron and nuclear recoil distributions in the ionization yield. The horizontal axis gives the normalized ionization energy, measured as the number σ from the mean of the nuclear recoil distribution.
The cyan dashed lines show the location of the σ nuclear reflection band cut discussed below. All of the cuts described in the sections above have high acceptance (&98% for single-scatter bulk nuclear reflections), with the exception of the nuclear reflection band and fiducial volume cuts, which have efficiencies. The following sections describe the performance calculation for each of these dominant components of signal reception.
The averages of the electron recoil (blue) and nuclear recoil (green) distributions determined from calibration data are also shown. An increasing fraction of these events can leak into the nuclear recoil band at low energies as the signal-to-noise of the ionization measurement decreases. The ionization energy distribution for events in the WIMP search data is shown in a, with the corresponding zero-charge population (red dots) selected as the events that lie within ±2σ of the baseline noise distribution.
This leakage accounts for the majority of the increase in speed over the exponential extrapolation shown in Fig. The zoom shows the arrangement of the interleaved charge (narrow, gray) and phonon (broad, blue) electrodes. This leads to an increase in the kinetic inductance, which pushes the resonant frequency of the circuit lower.
From the relative energy collected in each resonator, the location of the interaction can be determined. A magnified version of the rising edges of the pulses is shown in the inset. 6.4.1, designs that enable direct absorption of quasi-particle energy in MKID are considered.
This coupling is determined by the geometry of the feed line and the distance from the resonator to the feed line. Resonators with the geometry described above were arranged in a 20-element array, as shown in Fig.
