Stochastic Collisional Quantum Thermometry

We extend collisional quantum thermometry schemes to allow for stochasticity in the waiting time between successive collisions. We establish that introducing randomness through a suitable waiting time distribution, the Weibull distribution, allows us to significantly extend the parameter range for which an advantage over the thermal Fisher information is attained. These results are explicitly demonstrated for dephasing interactions and also hold for partial swap interactions. Furthermore, we show that the optimal measurements can be performed locally, thus implying that genuine quantum correlations do not play a role in achieving this advantage. We explicitly confirm this by examining the correlation properties for the deterministic collisional model.

A new likelihood model for analyses of pharmacoepidemiologic case–control studies which avoids decision rules for determining latent exposure status

Background Case–control studies based on pharmaco-epidemiological databases typically use decision rules to determine exposure status from information on dates of prescription redemptions, although this induces misclassification. The reverse Waiting Time Distribution has been suggested as a likelihood based model to estimate the latent exposure status, and we therefore suggest to extend this into a joint likelihood based model, which incorporates both the latent exposure status and the exposure-outcome association. This will achieve consistency and efficiency of the estimates, i.e. they can be expected to be asymptotically unbiased and have optimal precision. Methods We established a joint likelihood for the observed case–control status and last prescription redemption before the index date. The likelihood combines the ordinary logistic regression likelihood and the reverse Waiting Time Distribution, and allows inclusion of covariates in both parts to adjust for observed confounders. We conducted a simulation study of the new model and standard models based on decision rules for exposure and the probability of being exposed, respectively, to assess the relative bias and variability of estimates. Lastly, we applied the models to a case–control study on use of nonsteroidal anti-inflammatory drugs and risk of upper-gastrointestinal bleeding. Results In simulation studies the new model had low relative bias (< 1.4%) and largely retained nominal coverage probabilities (90.2% to 95.1% of nominal 95% confidence intervals), also when moderate misspecification was introduced. All standard methods generally had substantial bias (-21.1% to 17.0%) and low coverage probabilities (0.0% to 68.9%). When analyzing the empirical case–control study, the new method estimated the effect of nonsteroidal anti-inflammatory drugs on risk of with upper-gastrointestinal bleeding hospitalization to 2.52 (1.59 – 3.45), whereas the other methods had estimates ranging from 3.52 (2.19 – 5.65) to 5.17 (2.40 – 11.11). Conclusions Unlike standard methods, the proposed model gave nearly unbiased estimates with adequate coverage probabilities in simulation studies. The developed model demonstrates the potential for the reverse Waiting Time Distribution to be integrated with existing likelihood based analyses in pharmacoepidemiological studies.

Effect of Ergodic and Non-Ergodic Fluctuations on a Charge Diffusing in a Stochastic Magnetic Field

In this paper, we study the basic problem of a charged particle in a stochastic magnetic field. We consider dichotomous fluctuations of the magnetic field where the sojourn time in one of the two states are distributed according to a given waiting-time distribution either with Poisson or non-Poisson statistics, including as well the case of distributions with diverging mean time between changes of the field, corresponding to an ergodicity breaking condition. We provide analytical and numerical results for all cases evaluating the average and the second moment of the position and velocity of the particle. We show that the field fluctuations induce diffusion of the charge with either normal or anomalous properties, depending on the statistics of the fluctuations, with distinct regimes from those observed, e.g., in standard Continuous-Time Random Walk models.

Study of individual pulses at the Antarctic high-altitude neutron monitor DOMC

A pair of neutron monitors (NMs) is installed on the high Central Antarctic plateau, at the Concordia station (3200 m altitude) and measures the nucleonic component of nucleonic-muon-electromagnetic cascades in- duced by high-energy cosmic rays in the atmosphere. The installation includes two NMs: DOMC, a standard mini-NM, and a bare (lead-free) DOMB NM. The newly installed data acquisition (DAQ) system records in- dividual pulses corresponding to mostly neutrons in the detector’s counting tube. Here we analyze different types of pulses and study the distribution of the waiting times between individual pulses as well as the pulse height, recorded by the DOMC NM during a quiet period of January 2020. The distribution appears double- peaked with peaks corresponding to the frequency of individual atmospheric cascades and the intra-cascade variability, respectively. We discuss also the nature of different components contributing to the pulses and se - paration of the signal from noise. It is shown that the waiting-time distribution has distinguished timescales, >30 ms defined by the cosmic-ray induced atmospheric cascades, and < 10 ms reflecting the intra-cascade variability. The new DAQ system allows one to study the development of the atmospheric cascade.