Search for Majorana neutrinos exploiting millikelvin cryogenics with CUORE

Abstract

The possibility that neutrinos may be their own antiparticles, unique among the known fundamental particles, arises from the symmetric theory of fermions proposed by Ettore Majorana in 1937¹. Given the profound consequences of such Majorana neutrinos, among which is a potential explanation for the matter-antimatter asymmetry of the universe via leptogenesis², the Majorana nature of neutrinos commands intense experimental scrutiny globally; one of the primary experimental probes is neutrinoless double beta (0νββ) decay. Here we show results from the search for 0νββ decay of ¹³⁰Te, using the latest advanced cryogenic calorimeters with the CUORE experiment³. CUORE, operating just 10 millikelvin above absolute zero, has pushed the state of the art on three frontiers: the sheer mass held at such ultralow temperatures, operational longevity, and the low levels of ionizing radiation emanating from the cryogenic infrastructure. We find no evidence for 0νββ decay and set a lower bound of the process half-life as 2.2 × 10²⁵ years at a 90 per cent credibility interval. We discuss potential applications of the advances made with CUORE to other fields such as direct dark matter, neutrino and nuclear physics searches and large-scale quantum computing, which can benefit from sustained operation of large payloads in a low-radioactivity, ultralow-temperature cryogenic environment.

Fig. 1. The CUORE detector.

a, Rendering of the six-stage cryostat, with the pulse tubes and dilution unit, the internal low-radioactivity modern and Roman lead shields, and the array of 988 TeO₂ crystals (light blue). b, The detector after installation. The plastic ring was used during assembly for radon protection. c, One of the calorimeters instrumented with an NTD Ge thermistor which measures the temperature increase induced by absorbed radiation. The Si heater is used to inject pulses for thermal gain stabilization. The polytetrafluoroethylene (PTFE) supports and the gold wires instrumenting the NTD and the heater provide the thermal link between the crystal and the heat bath, that is, the Cu frames.

Fig. 2. Cryogenic performance.

a, The exposure accumulated by CUORE (teal), along with the exposure used for this analysis (orange). Parts of 2017 and 2018 were dedicated to maintenance and optimization of the cryogenic set-up. b, Since then, CUORE has been operating stably with a 90% duty cycle (March 2019–October 2020). c, Examples of temperature instabilities induced by external causes. From left to right: blackout (June 2019), earthquake in Albania of magnitude 6.4, 520 km away (November 2019), regular maintenance (July 2020), and insertion of calibration sources (September 2020). d, The temperature stability of CUORE over ~1 yr of continuous operation, shown by a plot of relative temperature fluctuation versus time, and a histogram of the same data. (1 t yr = 1,000 kg yr.).

Fig. 3. Pulse tube phase optimization.

a, Frequency spectrum of the noise for a random combination of the pulse tube phases (orange) and after the active phase tuning (teal). For reference, the frequency spectrum of physical signals is also reported. b, Integral of the power spectrum at the pulse tube frequency (1.4 Hz) and its harmonics before and after active noise cancellation.

Fig. 4. Physics spectrum for 1,038.4 kg yr of TeO₂ exposure.

We separately show the effects of the base cuts, the anti-coincidence (AC) cut, and the pulse shape discrimination (PSD). The most prominent background peaks in the spectrum are highlighted. Inset, the region of interest after all selection cuts, with the best-fit curve (solid red), the best-fit curve with the 0νββ rate fixed to the 90% CI limit (blue), and background-only fit (black) superimposed.

Extended Data Fig. 1. Working principle of the cryogenic calorimeter.

Left, simplified calorimeter thermal model. The detector is modelled as a single object with heat capacity C coupled to the heat bath (with constant temperature T₀) through the thermal conductance G. The NTD thermistor for signal readout is glued to the absorber. Right, example of a CUORE pulse from the 2,615-keV calibration line: T₀ corresponds to the baseline height, the pulse amplitude is proportional to the deposited energy, and the decay time depends on the value of C/G.

Extended Data Fig. 2. Roman lead.

Top left, the recovery of the lead bricks from the Sardinian sea. Bottom left, the ingot inscriptions were cut and preserved, and the ingot bodies were used for the CUORE internal lead shield. Right, lateral view of the internal lead shield.

Extended Data Fig. 3. Pulse shape discrimination.

Effect of the PSD cut on calibration data around the 2,615-keV line (left) and on physics data near Q_ββ (right). In calibration data, the anti-coincidence is not applied in order to maximize the statistics on the γ peaks, and the PSD mostly removes pileup events (events with more than one energy deposit in the time window). In physics data, the PSD mostly eliminates random noise events, which can correspond to either physical events with excessive noise or to noise-induced events with non-physical pulse shapes. Such events appear randomly across the energy spectrum, so the cut mostly acts on the continuum.

Extended Data Fig. 4. Optimum trigger and statistical analysis.

Top left, distribution of energy thresholds at 90% trigger efficiency for the optimum trigger algorithm in a single dataset. The 40-keV analysis threshold is indicated by the vertical line. Top right, 90% CI exclusion limits on $T_{1/2}^{0\nu }$ from an ensemble of 10⁴ toy experiments generated with the background-only model, with background rates obtained from the background-only fit to the data. The median exclusion sensitivity is indicated by the orange line. Bottom left, posterior probability distribution for Γ_0ν obtained from the Bayesian fit, with the 90% CI highlighted. Bottom right, Δχ² values obtained from the profile likelihood of Γ_0ν, with Δχ² = 0 being the most-favoured value. The frequentist limit at 90% confidence level (CL) is indicated.

Extended Data Fig. 5. PCA performance.

Left, example of a normalization fit of the PCA reconstruction error versus energy for a single calorimeter and dataset. The distribution contains only events that passed the other base cuts. The second-order polynomial fit is shown in orange. Right, two example pulses from this calorimeter. The actual pulse is drawn in teal, and the corresponding reconstruction obtained by the PCA is drawn in orange. The top pulse deviates from the expected shape of a good pulse and is rejected, whereas the bottom one conforms to the expected response and is accepted.