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Many-body dynamical phases in an Ising-like quantum spin model with long-range interactions are observed by measuring correlations in single shots, using a quantum simulator composed of 53 qubits. Many bodies on a quantum simulator Richard Feynman proposed the quantum computer in 1982 as a technique for simulating states of matter and the various complex interactions that occur within these systems. In the past few years, quantum simulators have become a reality, with several different qubit approaches. For example, small numbers of individually controlled qubits have already been used to simulate molecules and quantum magnets. However, it has remained a challenge to perform tasks that are beyond the capabilities of classical computers. In this issue, two papers demonstrate quantum simulators with an unprecedentedly high number of controlled qubits. Mikhail Lukin and colleagues used 51 cold Rydberg atoms and Christopher Monroe and colleagues used 53 trapped ions to study phase transitions in Ising-type quantum magnets. Both groups observed novel many-body interactions that are computationally intractable with classical computers. A quantum simulator is a type of quantum computer that controls the interactions between quantum bits (or qubits) in a way that can be mapped to certain quantum many-body problems 1 , 2 . As it becomes possible to exert more control over larger numbers of qubits, such simulators will be able to tackle a wider range of problems, such as materials design and molecular modelling, with the ultimate limit being a universal quantum computer that can solve general classes of hard problems 3 . Here we use a quantum simulator composed of up to 53 qubits to study non-equilibrium dynamics in the transverse-field Ising model with long-range interactions. We observe a dynamical phase transition after a sudden change of the Hamiltonian, in a regime in which conventional statistical mechanics does not apply 4 . The qubits are represented by the spins of trapped ions, which can be prepared in various initial pure states. We apply a global long-range Ising interaction with controllable strength and range, and measure each individual qubit with an efficiency of nearly 99 per cent. Such high efficiency means that arbitrary many-body correlations between qubits can be measured in a single shot, enabling the dynamical phase transition to be probed directly and revealing computationally intractable features that rely on the long-range interactions and high connectivity between qubits.

The influence of stratospheric ozone on the interannual variability and trends in tropospheric ozone is evaluated between 30 and 90° N from 1990–2009 using ozone measurements and a global chemical transport model, the Community Atmospheric Model with chemistry (CAM-chem). Long-term measurements from ozonesondes, at 150 and 500 hPa, and the Measurements of OZone and water vapour by in-service Airbus aircraft programme (MOZAIC), at 500 hPa, are analyzed over Japan, Canada, the Eastern US and Northern and Central Europe. The measurements generally emphasize northern latitudes, although the simulation suggests that measurements over the Canadian, Northern and Central European regions are representative of the large-scale interannual ozone variability from 30 to 90° N at 500 hPa. CAM-chem is run with input meteorology from the National Center for Environmental Prediction; a tagging methodology is used to identify the stratospheric contribution to tropospheric ozone concentrations. A variant of the synthetic ozone tracer (synoz) is used to represent stratospheric ozone. Both the model and measurements indicate that on large spatial scales stratospheric interannual ozone variability drives significant tropospheric variability at 500 hPa and the surface. In particular, the simulation and the measurements suggest large stratospheric influence at the surface sites of Mace Head (Ireland) and Jungfraujoch (Switzerland) as well as many 500 hPa measurement locations. Both the measurements and simulation suggest the stratosphere has contributed to tropospheric ozone trends. In many locations between 30–90° N 500 hPa ozone significantly increased from 1990–2000, but has leveled off since (from 2000–2009). The simulated global ozone budget suggests global stratosphere-troposphere exchange increased in 1998–1999 in association with a global ozone anomaly. Discrepancies between the simulated and measured ozone budget include a large underestimation of measured ozone variability and discrepancies in long-term stratospheric ozone trends. This suggests the need for more sophisticated simulations including better representations of stratospheric chemistry and circulation.

Interacting quantum systems are expected to thermalize, but in some situations in the presence of disorder they can exist in localized states instead. This many-body localization is studied experimentally in a small system with programmable disorder. When a system thermalizes it loses all memory of its initial conditions. Even within a closed quantum system, subsystems usually thermalize using the rest of the system as a heat bath. Exceptions to quantum thermalization have been observed, but typically require inherent symmetries 1 , 2 or noninteracting particles in the presence of static disorder 3 , 4 , 5 , 6 . However, for strong interactions and high excitation energy there are cases, known as many-body localization (MBL), where disordered quantum systems can fail to thermalize 7 , 8 , 9 , 10 . We experimentally generate MBL states by applying an Ising Hamiltonian with long-range interactions and programmable random disorder to ten spins initialized far from equilibrium. Using experimental and numerical methods we observe the essential signatures of MBL: initial-state memory retention, Poissonian distributed energy level spacings, and evidence of long-time entanglement growth. Our platform can be scaled to more spins, where a detailed modelling of MBL becomes impossible.

A time crystal is a state of matter that shows robust oscillations in time, and although forbidden in equilibrium, a discrete time crystal has now been observed in a periodically driven quantum system. Time crystals aren't forever Much like ordinary crystals, time crystals exhibit a high degree of structural order. But whereas ordinary crystals get their periodicity from the regular repetition of spatial elements, time crystals are an exotic, non-equilibrium state of matter in which the same structures repeat themselves in time. Predicted to exist a few years ago, time crystals have so far resisted experimental demonstration. Now, two groups offer evidence for experimental observation of this elusive form of matter. Jiehang Zhang et al . create a specific kind of time crystal—a discrete time crystal—in a chain of ten trapped ions under the influence of periodic driving. Mikhail Lukin and colleagues achieve a similar feat using approximately one million nitrogen–vacancy spin impurities in diamond as an experimental platform. In both cases, the time-crystalline order is shown to be robust to external perturbations. Such time crystals could potentially find applications in robust quantum memory. Spontaneous symmetry breaking is a fundamental concept in many areas of physics, including cosmology, particle physics and condensed matter 1 . An example is the breaking of spatial translational symmetry, which underlies the formation of crystals and the phase transition from liquid to solid. Using the analogy of crystals in space, the breaking of translational symmetry in time and the emergence of a ‘time crystal’ was recently proposed 2 , 3 , but was later shown to be forbidden in thermal equilibrium 4 , 5 , 6 . However, non-equilibrium Floquet systems, which are subject to a periodic drive, can exhibit persistent time correlations at an emergent subharmonic frequency 7 , 8 , 9 , 10 . This new phase of matter has been dubbed a ‘discrete time crystal’ 10 . Here we present the experimental observation of a discrete time crystal, in an interacting spin chain of trapped atomic ions. We apply a periodic Hamiltonian to the system under many-body localization conditions, and observe a subharmonic temporal response that is robust to external perturbations. The observation of such a time crystal opens the door to the study of systems with long-range spatio-temporal correlations and novel phases of matter that emerge under intrinsically non-equilibrium conditions 7 .

We discuss and evaluate the representation of atmospheric chemistry in the global Community Atmosphere Model (CAM) version 4, the atmospheric component of the Community Earth System Model (CESM). We present a variety of configurations for the representation of tropospheric and stratospheric chemistry, wet removal, and online and offline meteorology. Results from simulations illustrating these configurations are compared with surface, aircraft and satellite observations. Major biases include a negative bias in the high-latitude CO distribution, a positive bias in upper-tropospheric/lower-stratospheric ozone, and a positive bias in summertime surface ozone (over the United States and Europe). The tropospheric net chemical ozone production varies significantly between configurations, partly related to variations in stratosphere-troposphere exchange. Aerosol optical depth tends to be underestimated over most regions, while comparison with aerosol surface measurements over the United States indicate reasonable results for sulfate , especially in the online simulation. Other aerosol species exhibit significant biases. Overall, the model-data comparison indicates that the offline simulation driven by GEOS5 meteorological analyses provides the best simulation, possibly due in part to the increased vertical resolution (52 levels instead of 26 for online dynamics). The CAM-chem code as described in this paper, along with all the necessary datasets needed to perform the simulations described here, are available for download at www.cesm.ucar.edu.

Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects the accuracy of the susceptibility map. We propose QSMGAN: a 3D deep convolutional neural network approach based on a 3D U-Net architecture with increased receptive field of the input phase compared to the output and further refined the network using the WGAN with gradient penalty training strategy. Our method generates accurate QSM maps from single orientation phase maps efficiently and performs significantly better than traditional non-learning-based dipole inversion algorithms. The generalization capability was verified by applying the algorithm to an unseen pathology--brain tumor patients with radiation-induced cerebral microbleeds. •A 3D convolutional neural network was applied to accurately quantify susceptibility.•Increasing the patch receptive field and cropping the output reduced the error.•Generative adversarial networks improved the quality of the susceptibility maps.•Our algorithm resulted in more accurate maps compared to common nonlearning methods.

Fires are a global phenomenon that impact climate and biogeochemical cycles, and interact with the biosphere, atmosphere and cryosphere. These impacts occur on a range of temporal and spatial scales and are difficult to quantify globally based solely on observations. Here we assess the role of fires in the climate system using model estimates of radiative forcing (RF) from global fires in pre-industrial, present day, and future time periods. Fire emissions of trace gases and aerosols are derived from Community Land Model simulations and then used in a series of Community Atmosphere Model simulations with representative emissions from the years 1850, 2000, and 2100. Additional simulations are carried out with fire emissions from the Global Fire Emission Database for a present-day comparison. These results are compared against the results of simulations with no fire emissions to compute the contribution from fires. We consider the impacts of fire on greenhouse gas concentrations, aerosol effects (including aerosol effects on biogeochemical cycles), and land and snow surface albedo. Overall, we estimate that pre-industrial fires were responsible for a RF of −1 W m−2 with respect to a pre-industrial climate without fires. The largest magnitude pre-industrial forcing from fires was the indirect aerosol effect on clouds (−1.6 W m−2). This was balanced in part by an increase in carbon dioxide concentrations due to fires (+0.83 W m−2). The RF of fires increases by 0.5 W m−2 from 1850 to 2000 and 0.2 W m−2 from 1850 to 2100 in the model representation from a combination of changes in fire activity and changes in the background environment in which fires occur, especially increases and decreases in the anthropogenic aerosol burden. Thus, fires play an important role in both the natural equilibrium climate and the climate perturbed by anthropogenic activity and need to be considered in future climate projections.

The Standard Model of particle physics is known to be incomplete. Extensions to the Standard Model, such as weak-scale supersymmetry, posit the existence of new particles and interactions that are asymmetric under time reversal (T) and nearly always predict a small yet potentially measurable electron electric dipole moment (EDM), de, in the range of 10⁻²⁷ to 10⁻³⁰ e.cm. The EDM is an asymmetric charge distribution along the electron spin $(\\vec s)$ that is also asymmetric under T. Using the polar molecule thorium monoxide, we measured de = (-2.1 ± 3.7stat ± 2.5syst) × 10⁻²⁹ e.cm. This corresponds to an upper limit of |de| <8.7 × 10⁻²⁹ e.cm with 90% confidence, an order of magnitude improvement in sensitivity relative to the previous best limit. Our result constrains T-violating physics at the TeV energy scale.

Remote observations of the solar photospheric light scattered by electrons (the K-corona) and dust (the F-corona or zodiacal light) have been made from the ground during eclipses 1 and from space at distances as small as 0.3 astronomical units 2 – 5 to the Sun. Previous observations 6 – 8 of dust scattering have not confirmed the existence of the theoretically predicted dust-free zone near the Sun 9 – 11 . The transient nature of the corona has been well characterized for large events, but questions still remain (for example, about the initiation of the corona 12 and the production of solar energetic particles 13 ) and for small events even its structure is uncertain 14 . Here we report imaging of the solar corona 15 during the first two perihelion passes (0.16–0.25 astronomical units) of the Parker Solar Probe spacecraft 13 , each lasting ten days. The view from these distances is qualitatively similar to the historical views from ground and space, but there are some notable differences. At short elongations, we observe a decrease in the intensity of the F-coronal intensity, which is suggestive of the long-sought dust free zone 9 – 11 . We also resolve the fine-scale plasma structure of very small eruptions, which are frequently ejected from the Sun. These take two forms: the frequently observed magnetic flux ropes 12 , 16 and the predicted, but not yet observed, magnetic islands 17 , 18 arising from the tearing-mode instability in the current sheet. Our observations of the coronal streamer evolution confirm the large-scale topology of the solar corona, but also reveal that, as recently predicted 19 , streamers are composed of yet smaller substreamers channelling continual density fluctuations at all visible scales. Observations of the solar corona by the Parker Solar Probe reveal evidence for the predicted dust-free zone and confirm that streamers comprise smaller substreamers that channel continuous multiscale density fluctuations.