CYGNUS : Feasibility of a nuclear recoil observatory with directional sensitivity to dark matter and neutrinos

Now that conventional weakly interacting massive particle (WIMP) dark matter searches are approaching the neutrino floor, there has been a resurgence of interest in detectors with sensitivity to nuclear recoil directions. A large-scale directional detector is attractive in that it would have sensitivity below the neutrino floor, be capable of unambiguously establishing the galactic origin of a purported dark matter signal, and could serve a dual purpose as a neutrino observatory. We present the first detailed analysis of a 1000~m3-scale detector capable of measuring a directional nuclear recoil signal at low energies. We propose a modular and multi-site observatory consisting of time projection chambers (TPCs) filled with helium and SF6 at atmospheric pressure. Depending on the TPC readout technology, 10-20 helium recoils above 6 kevr or only 3-4 recoils above 20~\kevr would suffice to distinguish a 10~GeV WIMP signal from the solar neutrino background. High-resolution charge readout also enables powerful electron background rejection capabilities well below 10~keV. We detail background and site requirements at the 1000~m3-scale, and identify materials that require improved radiopurity. The final experiment, which we name CYGNUS-1000, will be able to observe 10-40 neutrinos from the Sun, depending on the final energy threshold. With the same exposure, the sensitivity to spin independent cross sections will extend into presently unexplored sub-10 GeV parameter space. For spin dependent interactions, already a 10~m3-scale experiment could compete with upcoming generation-two detectors, but CYGNUS-1000 would improve upon this considerably. Larger volumes would bring sensitivity to neutrinos from an even wider range of sources, including galactic supernovae, nuclear reactors, and geological processes

Readout technologies for directional WIMP Dark Matter detection

The measurement of the direction of WIMP-induced nuclear recoils is a compelling but technologically challenging strategy to provide an unambiguous signature of the detection of Galactic dark matter. Most directional detectors aim to reconstruct the dark-matter-induced nuclear recoil tracks, either in gas or solid targets. The main challenge with directional detection is the need for high spatial resolution over large volumes, which puts strong requirements on the readout technologies. In this paper we review the various detector readout technologies used by directional detectors. In particular, we summarize the challenges, advantages and drawbacks of each approach, and discuss future prospects for these technologies

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models