Context. Solar activity plays a quintessential role in affecting the interplanetary medium and space weather around Earth. Remote-sensing instruments on board heliophysics space missions provide a pool of information about solar activity by measuring the solar magnetic field and the emission of light from the multilayered, multithermal, and dynamic solar atmosphere. Extreme-UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, that is, the chromosphere and the corona. Unfortunately, instruments such as the Atmospheric Imaging Assembly (AIA) on board the NASA Solar Dynamics Observatory (SDO), suffer from time-dependent degradation that reduces their sensitivity. The current best calibration techniques rely on flights of sounding rockets to maintain absolute calibration. These flights are infrequent, complex, and limited to a single vantage point, however. Aims. We aim to develop a novel method based on machine learning (ML) that exploits spatial patterns on the solar surface across multiwavelength observations to autocalibrate the instrument degradation. Methods. We established two convolutional neural network (CNN) architectures that take either single-channel or multichannel input and trained the models using the SDOML dataset. The dataset was further augmented by randomly degrading images at each epoch, with the training dataset spanning nonoverlapping months with the test dataset. We also developed a non-ML baseline model to assess the gain of the CNN models. With the best trained models, we reconstructed the AIA multichannel degradation curves of 2010–2020 and compared them with the degradation curves based on sounding-rocket data. Results. Our results indicate that the CNN-based models significantly outperform the non-ML baseline model in calibrating instrument degradation. Moreover, multichannel CNN outperforms the single-channel CNN, which suggests that cross-channel relations between different EUV channels are important to recover the degradation profiles. The CNN-based models reproduce the degradation corrections derived from the sounding-rocket cross-calibration measurements within the experimental measurement uncertainty, indicating that it performs equally well as current techniques. Conclusions. Our approach establishes the framework for a novel technique based on CNNs to calibrate EUV instruments. We envision that this technique can be adapted to other imaging or spectral instruments operating at other wavelengths.
Determining the presence or absence of a past long-lived lunar magnetic field is crucial for understanding how the Moon’s interior and surface evolved. Here, we show that Apollo impact glass associated with a young 2 million–year–old crater records a strong Earth-like magnetization, providing evidence that impacts can impart intense signals to samples recovered from the Moon and other planetary bodies. Moreover, we show that silicate crystals bearing magnetic inclusions from Apollo samples formed at ∼3.9, 3.6, 3.3, and 3.2 billion years ago are capable of recording strong core dynamo–like fields but do not. Together, these data indicate that the Moon did not have a long-lived core dynamo. As a result, the Moon was not sheltered by a sustained paleomagnetosphere, and the lunar regolith should hold buried 3He, water, and other volatile resources acquired from solar winds and Earth’s magnetosphere over some 4 billion years. The Moon lacked a long-lived magnetic field of internal origin, and this allowed solar wind volatiles to accumulate in its soils. The Moon lacked a long-lived magnetic field of internal origin, and this allowed solar wind volatiles to accumulate in its soils.
Terrestrial planets (Mercury, Venus, Earth, and Mars) are differentiated into three layers: a metallic core, a silicate shell (mantle and crust), and a volatile envelope of gases, ices, and, for the Earth, liquid water. Each layer has different dominant elements (e.g., increasing iron content with depth and increasing oxygen content to the surface). Chondrites, the building blocks of the terrestrial planets, have mass and atomic proportions of oxygen, iron, magnesium, and silicon totaling ≥ 90% and variable Mg/Si (∼ 25%), Fe/Si (factor of ≥2), and Fe/O (factor of ≥ 3). What remains an unknown is to what degree did physical processes during nebular disk accretion versus those during post-nebular disk accretion (e.g., impact erosion) influence these planets final bulk compositions. Here we predict terrestrial planet compositions and show that their core mass fractions and uncompressed densities correlate with their heliocentric distance, and follow a simple model of the magnetic field strength in the protoplanetary disk. Our model assesses the distribution of iron in terms of increasing oxidation state, aerodynamics, and a decreasing magnetic field strength outward from the Sun, leading to decreasing core size of the terrestrial planets with radial distance. This distribution enhances habitability in our solar system and may be equally applicable to exoplanetary systems.
Water ice is thought to be trapped in large permanently shadowed regions in the Moon’s polar regions, due to their extremely low temperatures. Here, we show that many unmapped cold traps exist on small spatial scales, substantially augmenting the areas where ice may accumulate. Using theoretical models and data from the Lunar Reconnaissance Orbiter, we estimate the contribution of shadows on scales from 1 km to 1 cm, the smallest distance over which we find cold-trapping to be effective for water ice. Approximately 10–20% of the permanent cold-trap area for water is found to be contained in these micro cold traps, which are the most numerous cold traps on the Moon. Consideration of all spatial scales therefore substantially increases the number of cold traps over previous estimates, for a total area of ~40,000 km2, about 60% of which is in the south. A majority of cold traps for water ice is found at latitudes > 80° because permanent shadows equatorward of 80° are typically too warm to support ice accumulation. Our results suggest that water trapped at the lunar poles may be more widely distributed and accessible as a resource for future missions than previously thought.
Only the two Voyager spacecraft have ever been there, and it took than more than 30 years of supersonic travel. It lies well past the orbit of Pluto, through the rocky Kuiper belt, and on for four times that distance. This realm, marked only by an invisible magnetic boundary, is where Sun-dominated space ends: the closest reaches of interstellar space.
The detection of ~20 ppb of phosphine in Venus clouds by observations in the millimetre-wavelength range from JCMT and ALMA is puzzling, because according to our knowledge of Venus, no phosphine should be there. As the most plausible formation paths do not work, the source could be unknown chemical processes—maybe even life?
Light, asteroid-mass primordial black holes, with lifetimes in the range between hundreds to several millions times the age of the Universe, are well-motivated candidates for the cosmological dark matter. Using archival COMPTEL data, we improve over current constraints on the allowed parameter space of primordial black holes as dark matter by studying their evaporation to soft gamma rays in nearby astrophysical structures. We point out that a new generation of proposed MeV gamma-ray telescopes will offer the unique opportunity to directly detect Hawking evaporation from observations of nearby dark matter dense regions and to constrain, or discover, the primordial black hole dark matter.
Geological evidence shows that ancient Mars had large volumes of liquid water. Models of past hydrogen escape to space, calibrated with observations of the current escape rate, cannot explain the present-day D/H isotope ratio. We simulate volcanic degassing, atmospheric escape, and crustal hydration on Mars, incorporating observational constraints from spacecraft, rovers and meteorites. We find ancient water volumes equivalent to a 100- to 1500-meter global layer are simultaneously compatible with the geological evidence, loss rate estimates, and D/H measurements. In our model, the volume of water participating in the hydrological cycle decreased by 40 to 95% over the Noachian period (~3.7 to 4.1 billion years ago), reaching present-day values by ~3.0 billion years ago. Between 30 and 99% of Martian water was sequestered by crustal hydration, demonstrating that irreversible chemical weathering can increase the aridity of terrestrial planets.
Detection mechanisms for low mass bosonic dark matter candidates, such as the axion or hidden photon, leverage potential interactions with electromagnetic fields, whereby the dark matter (of unknown mass) on rare occasion converts into a single photon. Current dark matter searches operating at microwave frequencies use a resonant cavity to coherently accumulate the field sourced by the dark matter and a near standard quantum limited (SQL) linear amplifier to read out the cavity signal. To further increase sensitivity to the dark matter signal, sub-SQL detection techniques are required. Here we report the development of a novel microwave photon counting technique and a new exclusion limit on hidden photon dark matter. We operate a superconducting qubit to make repeated quantum nondemolition measurements of cavity photons and apply a hidden Markov model analysis to reduce the noise to 15.7 dB below the quantum limit, with overall detector performance limited by a residual background of real photons. With the present device, we perform a hidden photon search and constrain the kinetic mixing angle to ε≤1.68×10−15 in a band around 6.011 GHz (24.86 μeV) with an integration time of 8.33 s. This demonstrated noise reduction technique enables future dark matter searches to be sped up by a factor of 1,300. By coupling a qubit to an arbitrary quantum sensor, more general sub-SQL metrology is possible with the techniques presented in this Letter.