Controlling high-vacuum gas dynamics is critical to many technologies, especially for portable quantum sensors. This article shows how purpose-designed surface textures can influence high-vacuum particle propagation in controlled ways to improve device performance. Using 3D printing to experimentally realize such textures in ultrahigh-vacuum-compatible materials, the authors show an example application in which textured surfaces are able to triple the pumping rate of a nonevaporable getter pump. This approach offers significant technical advantage in numerous high-vacuum settings, and will be of particular benefit to portable quantum technologies.

This work demonstrates a photonic dense associative memory, which is important for high-capacity associative memory, combinatorial optimization, and computer vision. Here scalable, higher-order interactions beyond pairwise couplings would be key to progress. The authors use a spatial light modulator and second-harmonic generated light to implement both two- and four-body interactions. Four-body interactions are shown to increase storage capacity by a factor of 10 for uncorrelated patterns and a factor of up to 50 for correlated patterns, and to yield further benefits as well. These results point to a scalable route for energy-efficient, high-capacity optical neural networks.

Qubits based on hole spins in germanium have seen remarkable progress over the last few years, and are currently one of the most promising spin-qubit platforms for quantum computing. Nevertheless, disorder scatters the charge and spin properties of the qubits within a quantum chip, which poses a challenge for scaling up. The accurate assessment of variability is crucial for establishing reliable roadmaps toward large-scale spin-qubit quantum computers. This study uses numerical simulations to quantify the expected variability of hole-spin qubits in realistic Ge devices, focusing on charge traps at interfaces. It turns out that charge properties don’t vary so much, but spin properties do.

Stochastic magnetic tunnel junctions (MTJs) are promising building blocks for neuromorphic and probabilistic computing, but conventional approaches rely on thermally unstable superparamagnetic devices with limited reliability and tunability. In this work, thermally stable perpendicular MTJs are electrically driven to produce random telegraph noise using nanosecond spin-torque pulses, the response being well described by a simple Poisson process. This approach enables broad, continuous tuning of both fluctuation rate and probability bias in a single device, pointing to a practical route for combining memory elements with programmable stochastic functionality on a single hardware platform.

Superconducting circuits for quantum computation are controlled via microwave signals, which are typically assumed to be too weak to disturb the superconducting material itself. When these microwave drives become sufficiently strong, though, multiple photons can combine to break Cooper pairs of electrons in the device, leading to qubit errors. The authors develop a theoretical framework to predict when this effect occurs, and demonstrate its relevance for emerging qubit designs and readout schemes that rely on strong driving. These results reveal a previously overlooked error mechanism for superconducting qubits, and provide guidance on how to mitigate the effects.

Superconducting resonators are a popular way to study dissipation in superconducting quantum circuits induced by two-level systems (TLS) due to their ease of fabrication, but measuring unsaturated TLS loss in quarter-wave resonators remains difficult due to the intrinsic frequency fluctuations of the TLS and low signal-to-noise ratio of the measurement. This study demonstrates that spatially extending the quarter-wave resonator to be many wavelengths long mitigates these difficulties and significantly reduces measurement uncertainty. This new resonator design provides a tool for researchers to examine the effects of material and fabrication processes on superconducting circuit performance.

Strain engineering and electric field control are key to optimizing the properties of electron-spin qubits hosted in electrostatically defined Si/Si-Ge quantum dots, and compared to thick Si-Ge heterostructures, thin Si/Si-Ge membranes offer more control. This article reports the fabrication of micrometer-thick Si/Si-Ge heterostructures suspended by a silicon substrate over an area of a few hundred micrometers. The authors characterize the elastic properties of these membranes and identify two mechanical modes useful for strain-field engineering, which helps to increase the valley splitting and thus the coherence time and shuttling fidelity of electron spins.

Time-resolved photoconductivity (PCD) sits at the heart of semiconductor characterization, yet many implementations probe only a narrow slice of the system’s properties—typically using a single microwave frequency paired with a single excitation wavelength. This work presents a versatile, contactless microwave PCD instrument that combines a broadband coplanar-waveguide sensor with flexible readout electronics, enabling an extensive detection range, temperature-dependent studies, and multiphoton excitation. This platform is equally relevant for industrial silicon wafers and emerging quantum materials, from perovskites to wide-band-gap power semiconductors and topological systems.

Controlled conversion between distinct classes of multipartite entangled states is crucial for quantum technologies, but direct interconversion is impossible, due to the states’ inequivalence under local operations. More sophisticated dynamical protocols are required; unfortunately, conventional adiabatic methods face a trade-off between fidelity and speed. This study employs inverse engineering to design accelerated adiabatic passages in a spin-chain system, enabling rapid W-to-GHZ conversion, as experimentally verified on an NMR quantum processor. The work highlights the potential of inverse engineering for efficient quantum state manipulation in many-body systems.

The predictability of quantum measurement outcomes is relevant for developing applications in quantum information, and potential sources of useful quantum correlations now extend even to top-antitop quark pairs produced in high-energy colliders. This study presents a comprehensive framework for assessing predictability, using error measures inherited from statistical learning theory. Building on an existing foundation, the authors propose a modified entanglement-based protocol for quantum key distribution, demonstrating enhanced resilience to noise compared to the standard BB84 protocol, and leveraging the strength and capabilities of quark-pair states as resources for quantum cryptography.

Devising efficient light coupling between optical fibers and silicon nitride photonic integrated circuits is critical in a wide range of applications, but common Gaussian-beam approximations fail to capture the complex physics of lensed fibers. This study employs a comprehensive co-optimization strategy that integrates high-resolution scanning electron microscopy with rigorous three-dimensional simulations to model and experimentally validate the coupling process. The actual emission profile of lensed fibers deviates significantly from the widely assumed paraxial Gaussian beam, a crucial insight that allows the authors to predict and achieve coupling efficiencies exceeding 80% per facet.

Quantum dots emitting in the telecommunication bands are an excellent candidate for deterministic single-photon sources for fiber-based quantum technologies. However, challenges remain in optimizing their optical properties. This Letter presents a detailed study of the optical properties of InAs quantum dots with optimized growth via molecular beam epitaxy. The authors realize high-quality single-photon emitters operating in the telecom O and C bands, and their growth technique is promising for further photonic technologies as well.

The authors propose the concept of a surface-acoustic-wave (SAW) phonon laser that also lases phonon spin. Such a device would be challenging to create, due to the impact of environmental noise on the excited state. By utilizing a dark-state scheme for a silicon-vacancy (Si-$V$) center in diamond, however, destructive interference of excitation amplitudes from two ground states to the excited state leaves the excited state decoupled from the laser system, affording a dissipation-robust phonon laser. Moreover, due to the interplay between phonon and Si-$V$ spins plus the spin-momentum locking of the SAW, phonon-spin-selected unidirectional lasing of coherent SAW phonons is expected.

Quantum dots emitting in the telecommunication bands are an excellent candidate for deterministic single-photon sources for fiber-based quantum technologies. However, challenges remain in optimizing their optical properties. This Letter presents a detailed study of the optical properties of InAs quantum dots with optimized growth via molecular beam epitaxy. The authors realize high-quality single-photon emitters operating in the telecom O and C bands, and their growth technique is promising for further photonic technologies as well.

The superconducting diode effect is attractive for superconducting logic and quantum information technologies, yet key control “knobs” remain limited. This work demonstrates a way to control the efficiency of superconducting diodes by varying the twist angle in NbSe${}_2$/NbSe${}_2$ van der Waals junctions. Twist angles near 30° induce weak coupling and greatly enhance the diode efficiency, whereas angles near 15° or 51° recover strong coupling but suppress nonreciprocity. These results provide an effective and practical means to create superconducting devices with customizable nonreciprocal functionalities.

Determining photon statistics is crucial in quantum technology and optics, and doing so with a single threshold detector is both highly desirable and a persistent challenge. The authors utilize the rotational Doppler effect to induce an n-fold frequency shift on an n‑photon Fock state, exploiting the particle nature of light to allow the photon-number distribution to be resolved using only one threshold detector, without any spatial or temporal multiplexing. This resource‑efficient approach to characterizing photon statistics opens possibilities for photon‑number detection, with promising applications across quantum optics and quantum information processing.

An important nonlinear effect in magnonics is three-magnon splitting, where a high-frequency magnon splits into two magnons of lower frequencies, but the technical difficulty of efficiently generating and measuring spin waves has stymied widespread use of their nonlinear properties. Using inductive spectroscopy and Brillouin light scattering, the authors show that nanostructures patterned from a synthetic antiferromagnet film are suitable for hosting three-magnon splitting, and collecting the resulting split waves. This enables the use of spin waves in nonlinear microwave signal processing, including frequency conversion without the need for a microwave mixer and local oscillator.

This work demonstrates a photonic dense associative memory, which is important for high-capacity associative memory, combinatorial optimization, and computer vision. Here scalable, higher-order interactions beyond pairwise couplings would be key to progress. The authors use a spatial light modulator and second-harmonic generated light to implement both two- and four-body interactions. Four-body interactions are shown to increase storage capacity by a factor of 10 for uncorrelated patterns and a factor of up to 50 for correlated patterns, and to yield further benefits as well. These results point to a scalable route for energy-efficient, high-capacity optical neural networks.

Qubits based on hole spins in germanium have seen remarkable progress over the last few years, and are currently one of the most promising spin-qubit platforms for quantum computing. Nevertheless, disorder scatters the charge and spin properties of the qubits within a quantum chip, which poses a challenge for scaling up. The accurate assessment of variability is crucial for establishing reliable roadmaps toward large-scale spin-qubit quantum computers. This study uses numerical simulations to quantify the expected variability of hole-spin qubits in realistic Ge devices, focusing on charge traps at interfaces. It turns out that charge properties don’t vary so much, but spin properties do.

Zero-frequency and zero-wave-number band gaps are highly desirable for controlling low-frequency elastic waves, but are fundamentally forbidden in conventional passive elastic systems. The authors show that optomechanical trapping with optical tweezers based on a metasurface introduces tunable, contactless stiffness in a mass-spring chain, enabling the realization of both types of band gaps. This approach overcomes long-standing physical constraints and opens possibilities for active and reconfigurable elastic metamaterials.

Stochastic magnetic tunnel junctions (MTJs) are promising building blocks for neuromorphic and probabilistic computing, but conventional approaches rely on thermally unstable superparamagnetic devices with limited reliability and tunability. In this work, thermally stable perpendicular MTJs are electrically driven to produce random telegraph noise using nanosecond spin-torque pulses, the response being well described by a simple Poisson process. This approach enables broad, continuous tuning of both fluctuation rate and probability bias in a single device, pointing to a practical route for combining memory elements with programmable stochastic functionality on a single hardware platform.

Superconducting circuits for quantum computation are controlled via microwave signals, which are typically assumed to be too weak to disturb the superconducting material itself. When these microwave drives become sufficiently strong, though, multiple photons can combine to break Cooper pairs of electrons in the device, leading to qubit errors. The authors develop a theoretical framework to predict when this effect occurs, and demonstrate its relevance for emerging qubit designs and readout schemes that rely on strong driving. These results reveal a previously overlooked error mechanism for superconducting qubits, and provide guidance on how to mitigate the effects.

Superconducting resonators are a popular way to study dissipation in superconducting quantum circuits induced by two-level systems (TLS) due to their ease of fabrication, but measuring unsaturated TLS loss in quarter-wave resonators remains difficult due to the intrinsic frequency fluctuations of the TLS and low signal-to-noise ratio of the measurement. This study demonstrates that spatially extending the quarter-wave resonator to be many wavelengths long mitigates these difficulties and significantly reduces measurement uncertainty. This new resonator design provides a tool for researchers to examine the effects of material and fabrication processes on superconducting circuit performance.

Controlling high-vacuum gas dynamics is critical to many technologies, especially for portable quantum sensors. This article shows how purpose-designed surface textures can influence high-vacuum particle propagation in controlled ways to improve device performance. Using 3D printing to experimentally realize such textures in ultrahigh-vacuum-compatible materials, the authors show an example application in which textured surfaces are able to triple the pumping rate of a nonevaporable getter pump. This approach offers significant technical advantage in numerous high-vacuum settings, and will be of particular benefit to portable quantum technologies.

Physics-based memcomputing is of interest for solving hard combinatorial-optimization problems in computer science, engineering, and physics by embedding a problem directly into the dynamics of a nonlinear system with memory. Few studies, however, have addressed how the phase-space structure controls performance and scalability. This work uses systematic phase-space engineering and simulations of memcomputing machines to identify the dynamical mechanisms that enable efficient solution-finding. Its insights into how memory-driven collective behavior influences phase-space geometry could help in designing more reliable and scalable physics-inspired devices for hard computational problems.

Strain engineering and electric field control are key to optimizing the properties of electron-spin qubits hosted in electrostatically defined Si/Si-Ge quantum dots, and compared to thick Si-Ge heterostructures, thin Si/Si-Ge membranes offer more control. This article reports the fabrication of micrometer-thick Si/Si-Ge heterostructures suspended by a silicon substrate over an area of a few hundred micrometers. The authors characterize the elastic properties of these membranes and identify two mechanical modes useful for strain-field engineering, which helps to increase the valley splitting and thus the coherence time and shuttling fidelity of electron spins.

Time-resolved photoconductivity (PCD) sits at the heart of semiconductor characterization, yet many implementations probe only a narrow slice of the system’s properties—typically using a single microwave frequency paired with a single excitation wavelength. This work presents a versatile, contactless microwave PCD instrument that combines a broadband coplanar-waveguide sensor with flexible readout electronics, enabling an extensive detection range, temperature-dependent studies, and multiphoton excitation. This platform is equally relevant for industrial silicon wafers and emerging quantum materials, from perovskites to wide-band-gap power semiconductors and topological systems.

Controlled conversion between distinct classes of multipartite entangled states is crucial for quantum technologies, but direct interconversion is impossible, due to the states’ inequivalence under local operations. More sophisticated dynamical protocols are required; unfortunately, conventional adiabatic methods face a trade-off between fidelity and speed. This study employs inverse engineering to design accelerated adiabatic passages in a spin-chain system, enabling rapid W-to-GHZ conversion, as experimentally verified on an NMR quantum processor. The work highlights the potential of inverse engineering for efficient quantum state manipulation in many-body systems.

The predictability of quantum measurement outcomes is relevant for developing applications in quantum information, and potential sources of useful quantum correlations now extend even to top-antitop quark pairs produced in high-energy colliders. This study presents a comprehensive framework for assessing predictability, using error measures inherited from statistical learning theory. Building on an existing foundation, the authors propose a modified entanglement-based protocol for quantum key distribution, demonstrating enhanced resilience to noise compared to the standard BB84 protocol, and leveraging the strength and capabilities of quark-pair states as resources for quantum cryptography.

Devising efficient light coupling between optical fibers and silicon nitride photonic integrated circuits is critical in a wide range of applications, but common Gaussian-beam approximations fail to capture the complex physics of lensed fibers. This study employs a comprehensive co-optimization strategy that integrates high-resolution scanning electron microscopy with rigorous three-dimensional simulations to model and experimentally validate the coupling process. The actual emission profile of lensed fibers deviates significantly from the widely assumed paraxial Gaussian beam, a crucial insight that allows the authors to predict and achieve coupling efficiencies exceeding 80% per facet.