In some magnetic materials, spin-wave dispersion relations vary monotonically across the Brillouin zone, allowing wave packets with zero momentum to flow unidirectionally, which points to high-frequency spintronic applications. To get there, though, it is crucial to develop methods that can link a spin wave’s properties to experimentally accessible metrics. To this end, the authors use propagating-spin-wave spectroscopy to precisely measure the dispersion of unidirectional spin waves. Their method identifies the wave vector at a particular frequency, which was a limiting factor in previous studies. This metrological approach is sure to impact the study of thin-film magnetism.

Robust and scalable multiplexed qubit readout is essential for realizing a fault-tolerant quantum computer. Conventional approaches rely on intentional mismatch of the feedline to provide directionality to the readout signal, at the cost of increased variation in resonator linewidth, which ultimately degrades quantum error correction. The authors address this challenge by demonstrating high-fidelity qubit readout using a readout resonator that emits photons preferentially toward the output, across its full bandwidth. By maintaining directional decay of the readout signal without intentional mismatch, this work presents a path toward the design of reliable, modular quantum processors.

Fluctuations in laser frequency affect atomic clock stability (via the so-called light shift) and stabilization is required, typically entailing additional complicated gear. This study shows how to turn the light shift from a nuisance to an amazing resource for compact atomic frequency standards. Exploiting the dispersive behavior of the light shift, the authors stabilize the laser frequency to the same atoms that are involved in the clock’s operation, without the need for any external reference. This technique results in significant hardware simplification, which is quite advantageous for industrial and space applications, where compact and robust automatic laser-frequency stabilization is especially valuable.

Outstanding in the (magnetic) field: The authors demonstrate an alternative, self-stabilized radio-frequency atomic magnetometer (AM) for magnetic induction tomography. In contrast to traditional approaches that require extra devices for bias-field stabilization, this method employs a dual-frequency technique, enabling simultaneous measurement of static and oscillating magnetic fields through nonlinear Zeeman splitting, all with a single atomic sensor. Experimental results reveal marked improvements in sensitivity and stability for AM-based detection of eddy current.

The system’s source noise affects the practical performance of discrete-modulated continuous-variable quantum key distribution. The good news: This noise exists inside the system and cannot be exploited by eavesdroppers, so it can be trusted. However, a lack of appropriate modeling leaves a security-key-rate gap, omitting this trusted noise. The authors propose a model for trusted source noise in the discrete-modulated protocol, successfully mitigating the negative impact of an imperfect source on system performance while maintaining security of the protocol, and thus promoting practical deployment.

The interest in slurries formed by granular filler dispersed in colloidal gel is largely driven by the relevance to batteries, and the recent discovery of flow-switched bistability. This study extends previous investigations to make progress on elucidating the physics of such slurries. Surprisingly, the electrical and mechanical properties of the slurries can be either coupled or decoupled, depending on the conductive properties of the granular fillers. The different coordination numbers required for network rigidity and electrical percolation provide a key to understanding the decoupling, and important insight for optimizing the mixing and processing of industrial slurries.

Silicon carbide MOSFETs are transforming power electronics by enabling higher switching frequencies and lower losses than their silicon-only counterparts. This study uses time-gated optical spectroscopy to investigate defect-assisted recombination in fully processed devices, specifically addressing their well-known hysteresis. The inquiry identifies a local vibrational mode with a very energy of 220 meV, indicating the presence of a carbon-cluster-like defect. This approach to characterizing interface states in MOSFETs reveals possibilities for enhancing device reliability and performance.

Quantum noise spectroscopy (QNS) is a powerful tool to characterize temporally correlated environmental noise, for noise-tailored control in noisy intermediate-scale quantum processors. However, QNS protocols have been limited by their vulnerability to state-preparation-and-measurement (SPAM) errors, and their inability to simultaneously characterize dephasing and relaxation effects. This work overcomes both of these challenges. The authors present a single-qubit QNS protocol utilizing continuous off-axis control for robust estimation of all multiaxis noise spectra, and show that SPAM errors can significantly alter or mask important features of the underlying native noise.

Arrays of single atoms trapped in optical tweezers have become a leading platform for quantum science and technology. A challenge at the frontier of the field is to scale up the number of atoms into the thousands. In addition, combining these arrays with a cryogenic environment would come with significant gains in lifetime and fidelity of quantum operations. This study successfully combines large-scale atomic arrays with a cryogenic environment, at a temperature of 6 K. The authors demonstrate the rearrangement of more than 800 atoms within a 2000-site array and discuss possible improvements of the setup, in a key step toward better, larger atom arrays for quantum technologies.

Harnessing spin waves for high-speed computing: In this work an innovative spin-wave reservoir chip, utilizing ferromagnetic permalloy thin films, demonstrates exceptional capabilities. By strategically manipulating spin-wave interference, the authors achieve a multi-input–multi-output reservoir capable of memory retention, nonlinearity enhancement, and accurate magnetic field estimation. This spintronic hardware paves the way for high-speed applications in reservoir computing and signal processing.

High-quality, distributed entanglement forms the foundation for the unequaled level of security that can be assured in quantum key distribution (QKD), but its susceptibility to noise hinders practical implementations. This study experimentally demonstrates that enhancing quantum resources with quantum privacy amplification (QPA) increases the noise resilience of QKD beyond classical limits. Leveraging hyperentanglement in different field-tested degrees of freedom of a photon pair increases the efficiency of QPA, thereby unlocking its advantage for QKD. Here is a method to generate secure keys under noisy conditions, which was previously impossible, paving the way for robust QKD.

Interlayer exchange coupling (IEC) has been incorporated into almost all magnetic thin-film devices in the form of synthetic antiferromagnets, yet how such coupling is affected by the mixing of magnetic atoms into the nonmagnetic spacer layer is often overlooked. The authors show that antiferromagnetic IEC can be achieved and enhanced by spacer layers containing over 60 at.% of magnetic atoms, leading to huge antiferromagnetic bilinear coupling strength in multilayers deposited by magnetron sputtering. The magnetic atoms in these spacers exhibit a large magnetic moment, highlighting not only the importance of free electrons but also the role of magnetic moments in governing IEC.

Laser-written optical waveguides in diamonds are a key technology to enhance coupling between defect centers and light, boosting applications in nanoscale sensing and quantum information processing. However, laser writing of photonic structures produces strain in the diamond lattice, modifying the properties of defect centers in poorly understood ways. This study demonstrates that optically detected magnetic resonance spectroscopy provides sufficient information to fully characterize the spatial distribution of strain in such a device, even without a constant magnetic field. The work yields an accessible tool that could be very useful for advancing diamond-based quantum technologies.

Triferroic multiferroicity, with ferroelectricity, ferromagnetism, and ferroelasticity coexisting in a single phase, is an intriguing phenomenon with promising device applications. Despite their great fundamental and technological importance, triferroic multiferroics remain substantially unexplored—especially those of semiconducting character. This computational study predicts semiconducting triferroic multiferroicity in the layered van der Waals material T′-TiBr2, with ferroelastic control of magnetization orientation and ferroelectric control of the absolute values of spin-polarization-density distributions, which is quite exciting.

Nanomechanical resonators, nanoelectronic systems, amorphous solids, and dark matter searches have each been the subject of recent or proposed experiments at or below 1 mK, but achieving such low cryostat temperatures is challenging. The authors report the performance of an aluminum nuclear demagnetization refrigerator designed to facilitate access to microkelvin temperatures. They found the aluminum refrigerant is well-suited to continuous nuclear demagnetization refrigeration when its natural oxide layer is effectively removed in selected regions. These results will broaden the field of microkelvin physics, accelerating the rate of discovery and increasing its technological potential.

Scaling up cryogenic systems, like arrays of superconducting nanowire single-photon detectors (SNSPDs), requires developing cryogenic coprocessors to minimize the number of cables exiting the cryostat. This work addresses this challenge by demonstrating the ability to read out, process, encode, and store data from SNSPDs using integrated nanowire electronics. The authors design a digital counter based on nanocryotrons—three-terminal nanowire devices—to perform signal processing and digitization at low temperatures. These results suggest that nanowire coprocessors could be developed, which would benefit the application of SNSPD arrays and other superconducting platforms.

Bulk acoustic wave (BAW) resonators that generate dynamic lattice strain are important for applications such as filters, sensors, and quantum control, but there is a lack of measurements available to quantify the strain directly. This study uses stroboscopic X-ray diffraction microscopy with correlated optical measurements on an ensemble of nitrogen-vacancy center defects to measure the dynamic strain in a diamond BAW resonator. This unique approach allows for directly imaging BAW resonator strain to improve fabrication and performance and for directly measuring important parameters of quantum defects to improve quantum control.

Perovskite solar cell performance is affected by the rate of charge-carrier transfer into the charge transport layers (CTLs) and interfacial recombination, but these are difficult to distinguish. This study distinguishes them using ultrafast spectroscopy combined with a charge-carrier dynamics model that includes the Coulombic forces arising from the selective extraction of charge carriers. The authors obtain extraction and interface recombination rate constants for three common CTLs and determine the perovskite’s ambipolar diffusivity. These results identify the performance-limiting properties, and could inform the design of superior materials that can be characterized with this method.

The cooling of levitated nanoparticles is a major step in optomechanics, aiming at both fundamental physics experiments and sensing applications, but using nonlinear cooling schemes and electro-optic modulation devices can significantly elevate the cost and complexity of the experiment. The authors implement a practical all-electrical controller capable of cooling the center-of-mass motion of a levitated nanoparticle to sub-Kelvin temperatures. When combined with improved vacuum and detection, this method can provide a simple and direct platform for three-dimensional near-ground-state cooling of the nanoparticle’s motional state.

Chirality can appear at many length scales in nature. In this study the authors introduce planar chirality as a quantitative geometric measure of chirality for two-dimensional objects. They apply this measure to evaluate the chirality of nanometer-sized structures with an electron microscope. They employ an innovative electron-optics device, the orbital-angular-momentum sorter, which applies a log-polar conformal mapping to the electron wave function and reaches near-optimal resolution in orbital angular momentum.

A promising branch of neuromorphic computing aims to perform cognitive operations in hardware, leveraging the physics of efficient and well-established nanodevices. This work presents a reconfigurable classifier, based on a network of magnetic tunnel junctions, that can learn to classify spoken vowels. In this task the hardware network surpasses multilayered software neural networks with the same number of trained parameters. These results, obtained using the same devices and working principle employed in industrial spin-transfer-torque magnetic random-access memory, constitute an important step toward the development of large-scale neuromorphic networks based on established technology.

The authors implement a scheme for sensing magnetic fields using a remotely located dc SQUID embedded in a microwave resonator. This configuration provides a path toward quantum-limited detection of microwave photons. The detector is used to resolve precisely the motion of a magnetically levitated superconducting microsphere. In addition to advancing magnetic field sensing at ultralow temperatures, this innovative platform has the potential to generate and measure nonclassical mechanical states of microgram-scale masses.

Superparamagnetic tunnel junctions (SMTJs) are fundamental elements of many proposed probabilistic computers, but models often fail to capture important statistical features of experimental devices. In particular, the most probable states of real devices are often not the fully magnetized states. The authors develop an efficient, measurement-driven model that agrees with measurements that were not used in the modeling process, including the power-law behavior of dwell-time distributions at subnanosecond timescales. These results open avenues to tackle challenges in modeling high-speed SMTJ circuitry.

Controlled engineering of vortex-pinning sites in cuprate superconductors is a pivotal goal in manufacturing devices based on magnetic flux quanta. This study employs focused helium-ion beams to create ultradense hexagonal arrays of defects in YBa2Cu3O7−δ thin films, achieving lattice spacings as small as 20 nm. Efficient pinning by a remarkably high matching field of 6 T is observed from the critical temperature down to 2 K. This research expands the range of temperatures and magnetic fields for exploring vortex matter using regular artificial vortex-pinning landscapes.

In quantum information science, online Hamiltonian learning emerges as a promising tool to compensate for uncontrolled environmental effects, thereby enhancing qubit quality factors. Several estimation schemes have been proposed to boost learning efficiency, but experimental implementation has been hindered by hardware limitations. Here the authors perform physics-informed, adaptive Bayesian Hamiltonian estimation for a singlet-triplet spin qubit, using a quantum controller powered by a field-programmable gate array. These techniques allow for significantly faster and more accurate real-time tracking of low-frequency noise in solid-state qubits.