Hilbert space dimension is a key resource for quantum information processing1,2. Not only is a large overall Hilbert space an essential requirement for quantum error correction, but a large local Hilbert space can also be advantageous for realizing gates and algorithms more efficiently3-7. As a result, there has been considerable experimental effort in recent years to develop quantum computing platforms using qudits (d-dimensional quantum systems with d > 2) as the fundamental unit of quantum information8-19. Just as with qubits, quantum error correction of these qudits will be necessary in the long run, but so far, error correction of logical qudits has not been demonstrated experimentally. Here we report the experimental realization of an error-corrected logical qutrit (d = 3) and ququart (d = 4), which was achieved with the Gottesman-Kitaev-Preskill bosonic code20. Using a reinforcement learning agent21,22, we optimized the Gottesman-Kitaev-Preskill qutrit (ququart) as a ternary (quaternary) quantum memory and achieved beyond break-even error correction with a gain of 1.82 ± 0.03 (1.87 ± 0.03). This work represents a novel way of leveraging the large Hilbert space of a harmonic oscillator to realize hardware-efficient quantum error correction.

When two massive objects (black holes, neutron stars or stars) in our universe fly past each other, their gravitational interactions deflect their trajectories1,2. The gravitational waves emitted in the related bound-orbit system-the binary inspiral-are now routinely detected by gravitational-wave observatories3. Theoretical physics needs to provide high-precision templates to make use of unprecedented sensitivity and precision of the data from upcoming gravitational-wave observatories4. Motivated by this challenge, several analytical and numerical techniques have been developed to approximately solve this gravitational two-body problem. Although numerical relativity is accurate5-7, it is too time-consuming to rapidly produce large numbers of gravitational-wave templates. For this, approximate analytical results are also required8-15. Here we report on a new, highest-precision analytical result for the scattering angle, radiated energy and recoil of a black hole or neutron star scattering encounter at the fifth order in Newton's gravitational coupling G, assuming a hierarchy in the two masses. This is achieved by modifying state-of-the-art techniques for the scattering of elementary particles in colliders to this classical physics problem in our universe. Our results show that mathematical functions related to Calabi-Yau (CY) manifolds, 2n-dimensional generalizations of tori, appear in the solution to the radiated energy in these scatterings. We anticipate that our analytical results will allow the development of a new generation of gravitational-wave models, for which the transition to the bound-state problem through analytic continuation and strong-field resummation will need to be performed.

Climate extremes are escalating under anthropogenic climate change1. Yet, how this translates into unprecedented cumulative extreme event exposure in a person's lifetime remains unclear. Here we use climate models, impact models and demographic data to project the number of people experiencing cumulative lifetime exposure to climate extremes above the 99.99th percentile of exposure expected in a pre-industrial climate. We project that the birth cohort fraction facing this unprecedented lifetime exposure to heatwaves, crop failures, river floods, droughts, wildfires and tropical cyclones will at least double from 1960 to 2020 under current mitigation policies aligned with a global warming pathway reaching 2.7 °C above pre-industrial temperatures by 2100. Under a 1.5 °C pathway, 52% of people born in 2020 will experience unprecedented lifetime exposure to heatwaves. If global warming reaches 3.5 °C by 2100, this fraction rises to 92% for heatwaves, 29% for crop failures and 14% for river floods. The chance of facing unprecedented lifetime exposure to heatwaves is substantially larger among population groups characterized by high socioeconomic vulnerabilities. Our results call for deep and sustained greenhouse gas emissions reductions to lower the burden of climate change on current young generations.

Methamphetamine is a growing health problem, as is mental health illness. However, no studies have investigated the combinatory effects of both diseases or characterized national trends over a period of time greater than 10 years. We evaluated US trends in mental health disorder-related hospital admissions (MHD-HAs) and compared them with those with concurrent methamphetamine use (MHD-HA-MUs), comparing the demographic characteristics from 2008 to 2020. Our findings reveal a significant increase in MHD-HA-MUs, increasing 10.5-fold, compared with a 1.4-fold increase in MHD-HAs. We also found a 1.53 times higher adjusted prevalence ratio of MHD-HA-MUs compared with MHD-HAs, even when adjusted for confounding factors. MHD-HA-MUs increased significantly among male patients (13-fold), non-Hispanic Black patients (39-fold), those aged 41-64 years (16-fold), and the South (24-fold). Overall, the data suggest that there are synergistic effects with methamphetamine use and mental health disorder, highlighting this patient group's unique needs, requiring distinct action.

Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies (GWASs) can provide new evidence regarding the aetiology of AUD. We report a multi-ancestry GWAS focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals [102,079 cases; European, 75,583; African, 20,689 (mostly African-American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent]. Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus, and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically-relevant comorbidities.

Addressing climate change requires accelerating the development of sustainable alternatives to energy- and water-intensive technologies, particularly for rapidly growing infrastructure such as data centres and cloud1. Here we present a life cycle assessment study examining the impacts of advanced cooling technologies on cloud infrastructure, from virtual machines to server architecture, data centre buildings and the grid. Life cycle assessment is important for early-stage design decisions, enhancing sustainability outcomes alongside feasibility and cost analysis2. We discuss constructing a life cycle assessment for a complex cloud ecosystem (including software, chips, servers and data centre buildings), analysing how different advanced cooling technologies interact with this ecosystem and evaluating each technology from a sustainability perspective to provide adoption guidelines. Life cycle assessment quantifies the benefits of advanced cooling methods, such as cold plates and immersion cooling, in reducing greenhouse gas emissions (15-21%), energy demand (15-20%) and blue water consumption (31-52%) in data centres. This comprehensive approach demonstrates the transformative potential of life cycle assessment in driving sustainable innovation across resource-intensive technologies.

Nickel is a critical element in the shift to sustainable energy systems, with the demand for nickel projected to exceed 6 million tons annually by 20401-4, largely driven by the electrification of the transport sector. Primary nickel production uses acids and carbon-based reductants, emitting about 20 tons of carbon dioxide per ton of nickel produced5-7. Here we present a method using fossil-free hydrogen-plasma-based reduction to extract nickel from low-grade ore variants known as laterites. We bypass the traditional multistep process and combine calcination, smelting, reduction and refining into a single metallurgical step conducted in one furnace. This approach produces high-grade ferronickel alloys at fast reduction kinetics. Thermodynamic control of the atmosphere of the furnace enables selective nickel reduction, yielding an alloy with minimal impurities (<0.04 wt% silicon, approximately 0.01 wt% phosphorus and <0.09 wt% calcium), eliminating the need for further refining. The proposed method has the potential to be up to about 18% more energy efficient while cutting direct carbon dioxide emissions by up to 84% compared with current practice. Our work thus shows a sustainable approach to help resolve the contradiction between the beneficial use of nickel in sustainable energy technologies and the environmental harm caused by its production.

Hydrogen embrittlement (HE) impairs the durability of aluminium (Al) alloys and hinders their use in a hydrogen economy1-3. Intermetallic compound particles in Al alloys can trap hydrogen and mitigate HE4, but these particles usually form in a low number density compared with conventional strengthening nanoprecipitates. Here we report a size-sieved complex precipitation in Sc-added Al-Mg alloys to achieve a high-density dispersion of both fine Al3Sc nanoprecipitates and in situ formed core-shell Al3(Mg, Sc)2/Al3Sc nanophases with high hydrogen-trapping ability. The two-step heat treatment induces heterogeneous nucleation of the Samson-phase Al3(Mg, Sc)2 on the surface of Al3Sc nanoprecipitates that are only above 10 nm in size. The size dependence is associated with Al3Sc nanoprecipitate incoherency, which leads to local segregation of magnesium and triggers the formation of Al3(Mg, Sc)2. The tailored distribution of dual nanoprecipitates in our Al-Mg-Sc alloy provides about a 40% increase in strength and nearly five times improved HE resistance compared with the Sc-free alloy, reaching a record tensile uniform elongation in Al alloys charged with H up to 7 ppmw. We apply this strategy to other Al-Mg-based alloys, such as Al-Mg-Ti-Zr, Al-Mg-Cu-Sc and Al-Mg-Zn-Sc alloys. Our work showcases a possible route to increase hydrogen resistance in high-strength Al alloys and could be readily adapted to large-scale industrial production.

Marine plastic pollution is a global issue, with microplastics (1 µm-5 mm) dominating the measured plastic count1,2. Although microplastics can be found throughout the oceanic water column3,4, most studies collect microplastics from surface waters (less than about 50-cm depth) using net tows5. Consequently, our understanding of the microplastics distribution across ocean depths is more limited. Here we synthesize depth-profile data from 1,885 stations collected between 2014 and 2024 to provide insights into the distribution and potential transport mechanisms of subsurface (below about 50-cm depth, which is not usually sampled by traditional practices3,6) microplastics throughout the oceanic water column. We find that the abundances of microplastics range from 10-4 to 104 particles per cubic metre. Microplastic size affects their distribution; the abundance of small microplastics (1 µm to 100 µm) decreases gradually with depth, indicating a more even distribution and longer lifespan in the water column compared with larger microplastics (100 µm to 5,000 µm) that tend to concentrate at the stratified layers. Mid-gyre accumulation zones extend into the subsurface ocean but are concentrated in the top 100 m and predominantly consist of larger microplastics. Our analysis suggests that microplastics constitute a measurable fraction of the total particulate organic carbon, increasing from 0.1% at 30 m to 5% at 2,000 m. Although our study establishes a global benchmark, our findings underscore that the lack of standardization creates substantial uncertainties, making it challenging to advance our comprehension of the distribution of microplastics and its impact on the oceanic environment.

The coupling between electrons and phonons is one of the fundamental interactions in solids, underpinning a wide range of phenomena, such as resistivity, heat conductivity and superconductivity. However, direct measurements of this coupling for individual phonon modes remain a substantial challenge. In this work, we introduce a new technique for mapping phonon dispersions and electron-phonon coupling (EPC) in van der Waals (vdW) materials. By generalizing the quantum twisting microscope1 (QTM) to cryogenic temperatures, we demonstrate its capability to map not only electronic dispersions through elastic momentum-conserving tunnelling but also phononic dispersions through inelastic momentum-conserving tunnelling. Crucially, the inelastic tunnelling strength provides a direct and quantitative measure of the momentum and mode-resolved EPC. We use this technique to measure the phonon spectrum and EPC of twisted bilayer graphene (TBG) with twist angles larger than 6°. Notably, we find that, unlike standard acoustic phonons, whose coupling to electrons diminishes as their momentum tends to zero, TBG exhibits a low-energy mode whose coupling increases with decreasing twist angle. We show that this unusual coupling arises from the modulation of the interlayer tunnelling by a layer-antisymmetric 'phason' mode of the moiré system. The technique demonstrated here opens the way for examining a large variety of other neutral collective modes that couple to electronic tunnelling, including plasmons2, magnons3 and spinons4 in quantum materials.

Beneath oceanic spreading centres, the lithosphere-asthenosphere boundary (LAB) acts as a permeability barrier that focuses the delivery of melt from deep within the mantle towards the spreading axis1. At intermediate-spreading to fast-spreading ridge crests, the multichannel seismic reflection technique has imaged a nearly flat, 1-2-km-wide axial magma lens (AML)2 that defines the uppermost section of the LAB3, but the nature of the LAB deeper into the crust has been more elusive, with some clues gained from tomographic images, providing only a diffuse view of a wider halo of lower-velocity material seated just beneath the AML4. Here we present 3D seismic reflection images of the LAB extending deep (5-6 km) into the crust beneath Axial volcano, located at the intersection of the Juan de Fuca Ridge and the Cobb-Eickelberg hotspot. The 3D shape of the LAB, which is coincident with a thermally controlled magma assimilation front, focuses hotspot-related and mid-ocean-spreading-centre-related magmatism towards the centre of the volcano, controlling both eruption and hydrothermal processes and the chemical composition of erupted lavas5. In this context, the LAB can be viewed as the upper surface of a 'magma domain', a volume within which melt bodies reside (replacing the concept of a single 'magma reservoir')6. Our discovery of a funnel-shaped, crustal LAB suggests that thermally controlled magma assimilation could be occurring along this surface at other volcanic systems, such as Iceland.

Several hydrogen-rich superconductors have been found to show unprecedentedly high critical temperatures1-4, stimulating investigations into the nature of the superconductivity in these materials. Although their macroscopic superconducting properties are established1,5-7, microscopic insights into the pairing mechanism remains unclear. Here we characterize the superconducting gap structure in the high-temperature superconductor H3S and its deuterium counterpart D3S by performing tunnelling spectroscopy measurements. The tunnelling spectra reveal that H3S and D3S both have a fully gapped structure, which could be well described by a single s-wave Dynes model, with gap values 2Δ of approximately 60 meV and 44 meV, respectively. Furthermore, we observed gap features of another likely H-depleted HxS superconducting phase in a poorly synthesized hydrogen sulfide sample. Our work offers direct experimental evidence for superconductivity in the hydrogen-rich superconductor H3S from a microscopic perspective. It validates the phonon-mediated mechanism of superconducting pairing and provides a foundation for further understanding the origins of high-temperature superconductivity in hydrogen-rich compounds.

Ocean submesoscale (1-100 km) processes and their substantial impact on Earth's climate system have been increasingly emphasized in recent decades by high-resolution numerical models and regional observations1-11. However, the dynamics and energy associated with these processes, including submesoscale eddies and nonlinear internal waves, have never been observed from a global perspective. Where, when and how much do these submesoscale processes contribute to the large-scale ocean circulation and climate system? Here we show data from the recently launched Surface Water and Ocean Topography (SWOT) satellite12 that not only confirm the characteristics of submesoscale eddies and waves but also suggest that their potential impacts on ocean energetics, the marine ecosystem, atmospheric weather and Earth's climate system are much larger than anticipated. SWOT ushers in a new era of global ocean observing, placing submesoscale ocean dynamics as a critical element of the Earth's climate system.

The formation of accessible chromatin around DNA double-strand breaks is essential for their efficient repair1. Although the linker histone H1 is known to facilitate higher-order chromatin compaction2,3, the mechanisms by which H1 modifications regulate chromatin relaxation in response to DNA damage are unclear. Here we show that CTP synthase 1 (CTPS1)-catalysed deamidation of H1 asparagine residues 76 and 77 triggers the sequential acetylation of lysine 75 following DNA damage, and this dual modification of H1 is associated with chromatin opening. Mechanistically, the histone acetyltransferase p300 showed a preference for deamidated H1 as a substrate, establishing H1 deamidation as a prerequisite for subsequent acetylation. Moreover, high expression of CTPS1 was associated with resistance to cancer radiotherapy, in both mouse xenograft models and clinical cohorts. These findings provide new insights into how linker histones regulate dynamic chromatin alterations in the DNA damage response.

The pursuit of non-volatile memory with program speeds below one nanosecond, beyond the capabilities of non-volatile flash and high-speed volatile static random-access memory, remains a longstanding challenge in the field of memory technology1. Utilizing fundamental physics innovation enabled by advanced materials, series of emerging memories2-5 are being developed to overcome the speed bottleneck of non-volatile memory. As the most extensively applied non-volatile memory, the speed of flash is limited by the low efficiency of the electric-field-assisted program, with reported speeds6-10 much slower than sub-one nanosecond. Here we report a two-dimensional Dirac graphene-channel flash memory based on a two-dimensional-enhanced hot-carrier-injection mechanism, supporting both electron and hole injection. The Dirac channel flash shows a program speed of 400 picoseconds, non-volatile storage and robust endurance over 5.5 × 106 cycles. Our results confirm that the thin-body channel can optimize the horizontal electric-field (Ey) distribution, and the improved Ey-assisted program efficiency increases the injection current to 60.4 pA μm-1 at |VDS| = 3.7 V. We also find that the two-dimensional semiconductor tungsten diselenide has two-dimensional-enhanced hot-hole injection, but with different injection behaviour. This work demonstrates that the speed of non-volatile flash memory can exceed that of the fastest volatile static random-access memory with the same channel length.

A common behavior in natural environments is foraging for rewards. However, this is often in the presence of predators. Therefore, one of the most fundamental decisions for humans, as for other animals, is how to apportion time between reward-motivated pursuit behavior and threat-motivated checking behavior. To understand what affects how people strike this balance, we developed an ecologically inspired task and looked at both within-participant dynamics (moods) and between-participant individual differences (questionnaires about real-life behaviors) in two large internet samples (n = 374 and n = 702) in a cross-sectional design. For the within-participant dynamics, we found that people regulate task-evoked stress homeostatically by changing behavior (increasing foraging and hiding). Individual differences, even in superficially related traits (apathy-anhedonia and anxiety-compulsive checking) reliably mapped onto unique behaviors. Worse task performance, due to maladaptive checking, was linked to gender (women checked excessively) and specific anxiety-related traits: somatic anxiety (reduced self-reported checking due to worry) and compulsivity (self-reported disorganized checking). While anhedonia decreased self-reported task engagement, apathy, strikingly, improved overall task performance by reducing excessive checking. In summary, we provide a multifaceted paradigm for assessment of checking for threat in a naturalistic task that is sensitive to both moods as they change throughout the task and clinical dimensions. Thus, it could serve as an objective measurement tool for future clinical studies interested in threat, vigilance or behavior-emotion interactions in contexts requiring both reward seeking and threat avoidance.

Gender inequality substantially impacts society, disproportionately disadvantaging women, especially in the Global South. This inequality correlates with brain health outcomes for women, including a higher risk of cognitive decline and dementia. This perspective highlights how sex-linked biology and gender disparities affect women's brain health in the Global South through various pathways, such as differential exposome, health behaviors, and gender biases in research and healthcare systems. Alzheimer's disease and other brain health conditions exemplify how sex-specific risk factors and gender-related health barriers interact to influence brain health. We advocate for incorporating sex/gender considerations in research, policy, and clinical practice to improve brain health interventions in the Global South. Additionally, we propose using the patient and public involvement framework to effectively tailor health strategies that address these factors.