Qubit noise spectroscopy is an important tool for the experimental investigation of open quantum systems. However, conventional techniques for noise spectroscopy are time-consuming, because they require measurements of the noise spectral density at many different frequencies. Here we describe an alternative approach to noise spectroscopy, which requires fewer resources, and relies on direct measurement of arbitrary linear functionals of the noise spectral density. This method uses random pulse sequences with carefully controlled correlations, which are chosen using algorithms for phase retrieval. These measurements allow us to reconstruct sparse noise spectra via compressed sensing. Our simulations of the performance of the random pulse sequences on a realistic physical system, self-assembled quantum dots, reveal a speedup of an order of magnitude in extracting the noise spectrum, compared to conventional dynamical decoupling approaches.

Hardware-efficient methods for high-fidelity quantum state measurements are crucial for superconducting qubit experiments, as qubit numbers grow and feedback and state reset begin to be employed for quantum error correction. We present a three-dimensional reentrant-cavity filter designed for frequency-multiplexed readout of superconducting qubits. The cavity filter is situated out of the plane of the qubit circuit and capacitively couples to an array of on-chip readout resonators in a manner that can scale to large qubit arrays. The reentrant cavity functions as a large-linewidth bandpass filter with intrinsic Purcell filtering. We demonstrate the concept with a four-qubit multiplexed device in which we achieve an average readout fidelity of 98.6% and measurement-induced crosstalk dephasing rates below 0.15 kHz.

The detection of weak forces is a central problem in physics and engineering, ranging in importance from fundamental pursuits such as precision tests of gravity, gravitational-wave detection, and searches for dark matter to applications such as force microscopy. These pursuits require a low-mass mechanical force transducer with a high quality factor, whose motion can be measured in a quantum-noise-limited manner. Here, we study the ultimate example of such a transducer: a single trapped electron. We propose and analyze in detail a scheme for high-sensitivity continuous force detection using a single trapped electron whose motion is coupled to a microwave cavity field via image currents induced in an antenna. We derive the fundamental and technical limits to the sensitivity of this scheme and show that despite the disparity in size between that of a single electron and the wavelength of the microwave field, it is possible to continuously monitor the charge’s zero-point motion and use it as a force detector with a sensitivity as low as $6\times {10}^{-27}\mathrm{N}/\sqrt{\mathrm{Hz}}$ in the gigahertz regime. This sensitivity improves on the state of the art by 4 orders of magnitude and thus paves the way to experiments with previously unattainable precision.

Spin qubits in $\mathrm{Si}\mathrm{C}$ have become important platforms for quantum information and nanoscale quantum sensing. The performance and sensitivity of these applications greatly depend on the coherence properties of the spin qubits in $\mathrm{Si}\mathrm{C}$. This requires a quantitative understanding of the spin bath noise spectrum, which induces decoherence. In this work, we quantitatively investigate the noise spectrum of PL6 divacancy spins in $\mathrm{Si}\mathrm{C}$ generated by two different implanted doses, utilizing the spectral decomposition technique. First, three types of dynamical decoupling pulse sequences are performed to extend the spin coherence times, and both the Carr-Purcell-Meiboom-Gill (CPMG) and XY types of dynamical decoupling pulse sequences have the optimized effect. The coherence time increases by more than 12-fold as the number of CPMG pulses increases from 1 to 100 for both samples. On this basis, we analyze the noise spectrum using CPMG methods, determining the bath coupling strength and correlation time for the two samples. These experiments provide a foundation for the spectral decomposition technique in investigating spin bath environments of the spin qubits in $\mathrm{Si}\mathrm{C}$.

Two-dimensional van der Waals (vdW) multiferroic tunnel junctions (MFTJs) are very attractive for next-generation multifunctional memory devices due to many advantages. For any MFTJs, a high tunnel electroresistance (TER) and a high magnetoresistance ratio are expected for practical applications. In this work, ${\mathrm{Sc}}_2{\mathrm{CO}}_2$/${\mathrm{V}\mathrm{Se}}_2$-based vdW MFTJs are designed with an inserted $\mathrm{Ni}\mathrm{Cl}\mathrm{Br}$ interlayer. Through the nonequilibrium Green’s function and density functional theory, we theoretically investigate the spin-dependent transport properties of vdW MFTJs. It is found that, with the reversal of the polarization direction of ${\mathrm{Sc}}_2{\mathrm{CO}}_2$ inducing the semiconductor to half-metal transition in $\mathrm{Ni}\mathrm{Cl}\mathrm{Br}$, it is possible to efficiently modulate the tunneling barrier height of the MFTJs, resulting in a TER ratio as high as ${10}^4\mathrm{\%}$, and a maximum tunnel magnetoresistance (TMR) ratio of $3.22\times {10}^4\mathrm{\%}$, which represents a remarkable increase by factors of 32 and 6 in the TER and TMR, respectively, as compared to the MFTJ without the $\mathrm{Ni}\mathrm{Cl}\mathrm{Br}$ interlayer. Moreover, our MFTJs exhibit a spin filtering effect as high as $90\mathrm{\%}$ within the parallel magnetic configuration, spanning a bias voltage range of $-0.5$ to $0.5$ V. Our results indicate that the insertion of a specific interlayer into vdW MFTJs may help to achieve both giant TER and TMR ratios in one system, demonstrating the significance of interlayers in the design of vdW multiferroic heterostructures for the development of next-generation logic and memory devices.

The discovery of sliding ferroelectricity has introduced a new paradigm of physics: creating material properties such as ferroelectricity on demand. An important step in integrating sliding ferroelectricity into applications is the ability to write domains in these materials. This work focuses on the patterning of domains in the naturally grown sliding ferroelectric compound $(\mathrm{Pb}\mathrm{S}{)}_{1.11}{\mathrm{VS}}_2$ using electron-beam lithography. The written domains are investigated using scanning probe microscopy. Various primary electron energies and dose factors are applied to the samples, and optimal conditions and writing mechanisms are discussed. The different topographic characteristics observed can be explained using the various types of stacking order and dislocations present in the $\mathrm{Pb}\mathrm{S}$ and ${\mathrm{VS}}_2$ layers.

Dual-wavelength laser-sustained plasma (LSP), which absorbs energy from lasers with two different wavelengths, is promising as a high-performance light source for wafer optical inspection; however, the mechanisms of power absorption from two lasers are still not well understood. Here a fully coupled laser-thermal-hydrodynamic fluid model is established to investigate the formation characteristics of dual-wavelength LSP. The model is validated by our comparing the laser power absorption results from the simulation and those from experiments. The simulation results show that the near-infrared (915-nm) laser heats a relatively large area of the LSP. In contrast, the visible (435-nm) laser can penetrate the LSP bulk and deposit energy mainly at the focal point, resulting in a smaller, hotter, and higher-radiance LSP core. The time-dependent evolution of the dual-wavelength LSP and the energy components of laser power absorption are presented; moreover, the coupling effects of the two lasers are observed. The near-infrared laser can sustain a large-area background plasma at a relatively low temperature (approximately 15 000 K), which increases the visible laser power absorption at the LSP core, reaching the highest temperature of approximately 30 000 K. The results from this work indicate that dual-wavelength LSP can be a competitive candidate for developing high-performance broadband and high-intensity radiative light sources.

Altermagnets attract much attention due to their unique spin-splitting energy band and potential applications in spintronics. Ruthenium oxide (${\mathrm{Ru}\mathrm{O}}_2$) has been reported as a metallic altermagnet, exhibiting long-range spin-splitting torque without considerable spin-orbit coupling. However, recently, various independent experimental observations of ${\mathrm{Ru}\mathrm{O}}_2$, including by angle-resolved photoemission spectroscopy and neutron diffraction, suggest the absence of altermagnetic order and a preference for the nonmagnetic phase in ${\mathrm{Ru}\mathrm{O}}_2$. Here we investigate the strain relaxation along the thickness of [101]-oriented ${\mathrm{Ru}\mathrm{O}}_2$ films on ${\mathrm{Ti}\mathrm{O}}_2$ substrates using x-ray diffraction and analyze the potential nonuniform strain-induced net magnetization profile through superconducting quantum interference device magnetometry and polarized neutron reflectometry (PNR). Four models with different constraints were used to fit the PNR data, revealing no significant net magnetization signal in either the film or the interface. Our findings could contribute to the future clarification of the altermagnetic origins of ${\mathrm{Ru}\mathrm{O}}_2$.

Terahertz (THz) magnonics represents the notion of mathematical algebraic operations of magnons such as addition and subtraction in the THz regime—an emergent dissipationless ultrafast alternative to existing data processing technologies. Spin waves on antiferromagnets with a twist in spin-order host, such magnons in the THz regime, possess advantages of higher processing speeds, additional polarization degrees of freedom, and longer propagation lengths compared to gigahertz magnons in ferromagnets. While interactions among THz magnons are the crux of algebra operations, these require magnetic orders with closely spaced magnon modes for easier experimental realization of their interactions. Herein, a rich wealth of magnons spanning a narrow energy range of 0.4–10 meV is unraveled in ${\mathrm{Co}}_4{\mathrm{Ta}}_2{\mathrm{O}}_9$ using magneto-THz spectroscopy. A rare multitude of ten excitation modes, either of magnons or hybrid magnon-phonon modes, is presented. Among other attributes, spin-lattice interactions suggest a correlation among spin and local lattice distortion, magnetostriction, and magnetic exchange interactions, signifying a THz magnetoelectric effect. This unification of structural, magnetic, and dielectric facets, and their magnetic field control in a narrow spectrum unravels the mechanism underneath the system’s complexity, while the manifestation of a multitude of spin-excitation modes is a potential source to design multiple channels in spin-wave computing-based devices.

Chiral excitation flows have attracted significant attention due to their unique unidirectionality. Such flows have been studied in three-node networks with synthetic gauge fields, but the general theory of chiral flows in multinode networks requires further research and development. In this work, we propose a scheme to achieve chiral flows in $n$-node networks, where an auxiliary node is introduced to govern the system. This auxiliary node is coupled to all the network nodes, forming subtriangle structures with interference paths in these networks. We find the implicit chiral symmetry behind the perfect chiral flow and propose universal criteria that incorporate previous models, facilitating the implementation of chiral transmission in various networks. By investigating the symmetries within these models, we present different features of chiral flows in bosonic and spin networks. Furthermore, we extend the four-node model into a ladder network, which is promising for remote state transfer in practical systems with reduced complexity. Our scheme can be realized in state-of-the-art experimental systems, such as superconducting circuits, magnetic photonic lattices, and ultracold atoms, thereby opening up possibilities for future quantum networks.

We report temperature measurements using a transmon qubit by detecting the population of its first three energy levels after applying a sequence of $\pi$ pulses and performing projective dispersive readout. We measure the effective temperature of the qubit and characterize its relaxation and coherence times ${\tau }_1$, ${\tau }_2$ for three devices in the temperature range from 20 to 300 mK. We analyze the process of qubit thermalization to its effective environment consisting of multiple heat baths and support this with experimental data. The signal-to-noise ratio of the temperature measurement depends strongly on ${\tau }_1$, which drops at higher temperatures due to quasiparticle excitations, adversely affecting the measurements and setting an upper bound of the dynamic temperature range of the thermometer. The measurement relies on coherent dynamics of the qubit during the $\pi$ pulses. The effective qubit temperature follows closely that of the cryostat in the range from 100 to 200 mK. We present a numerical model of the qubit population distribution and find hat it compares favorably with the experimental results. Finally, we compare our technique with previous work on qubit thermometry and discuss its application prospects.

An electron confined by a semiconductor quantum dot (QD) can be displaced by changes in electron occupations of surrounding QDs owing to the Coulomb interaction. For a single-spin qubit in an inhomogeneous magnetic field, such a positional displacement of the host electron results in a qubit energy shift, which must be handled carefully for high-fidelity operations. Here, we spectroscopically investigate the qubit energy shift induced by changes in charge occupations of nearby QDs for a silicon single-spin qubit in a magnetic field gradient. Between two different charge configurations of an adjacent double QD, a spin qubit shows an energy shift of about 4 MHz, which necessitates strict management of electron positions over a QD array. We confirm a correlation between the qubit frequency and the charge configuration by using a postselection analysis.

Impurities in quantum materials have provided successful strategies for learning properties of complex states, ranging from unconventional superconductors to topological insulators. In quantum magnetism, inferring the Hamiltonian of an engineered system becomes a challenging open problem in the presence of complex interactions. Here we show how a supervised machine-learning technique can be used to infer Hamiltonian parameters from atomically engineered quantum magnets by inferring fluctuations of the ground states due to the presence of impurities. We demonstrate our methodology both with a fermionic model with spin-orbit coupling, as well as with many-body spin models with long-range exchange and anisotropic exchange interactions. We show that our approach enables performing Hamiltonian extraction in the presence of significant noise, providing a strategy to perform Hamiltonian learning with experimental observables in atomic-scale quantum magnets. Our results establish a strategy to perform Hamiltonian learning by exploiting the impact of impurities in complex quantum many-body states.

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Here, we report a storage efficiency greater than 28% in a $\mathrm{Tm}$${}^{3+}$:YAG crystal (where YAG is yttrium aluminum garnet) at elevated temperatures, achieving this milestone without relying on optical cavities and without compromising memory bandwidth. We introduce different pumping techniques for $\mathrm{Tm}$-based memories that enable multifrequency-window storage and high memory bandwidth reaching 630 MHz, significantly surpassing previous $\mathrm{Tm}$-based memory demonstrations, considering the operating temperature of 3.5 K. Furthermore, we propose a general method for large-bandwidth atomic frequency memory using non-Kramers rare-earth ions (REIs) in solids, paving the way for storage efficiencies and bandwidths approaching fundamental limits. The compatibility of $\mathrm{Tm}$ memories with neutral-atom quantum processors and their seamless integration with scalable photonic platforms, such as lithium niobate on insulator, underscore their potential for distributed quantum computing, hybrid quantum networks, and space-based quantum communication. Our study represents a significant advancement toward practical high-performance quantum memories based on REI-doped crystals, where we predict that gigahertz bandwidth and storage efficiencies exceeding 30% are achievable at lower temperatures.

Quantum entanglement plays an irreplaceable role in various remote quantum information-processing tasks. Here, we present protocols for generating deterministic and heralded $N$-qubit entangled states across multiple network nodes. By utilizing a preshared maximally entangled state and single-qubit operations within an indefinite-causal-order framework, the multiqubit entangled state between distant parties can be generated deterministically. The complex entangled-state measurements and multiple preshared entangled states, are essential in conventional entanglement-swapping techniques but are not required in our approach. This greatly reduces the complexity of the quantum circuit and makes it more experimentally feasible. Furthermore, we develop optical architectures to implement these protocols by encoding qubits in polarization degrees of freedom. The results indicate that our protocols significantly improve the efficiency of long-distance entanglement generation and provide a practical framework for establishing large-scale quantum networks.

A clever choice and design of gate sets can reduce the depth of a quantum circuit, and can improve the quality of the solution one obtains from a quantum algorithm. This is especially important for near-term quantum computers that suffer from various sources of error that propagate with the circuit depth. Parametrized gates in particular have found use in both near-term algorithms and circuit compilation. The one- and two-qubit versions of these gates have been demonstrated on various computing architectures. The neutral-atom platform has the capability to implement native $N$-qubit gates (for $N\ge 2$). However, one needs to first find the control functions that implement these gates on the hardware. We study the numerical optimization of neural networks towards obtaining families of controls—laser pulses to excite an atom to Rydberg states—that implement phase gates with one and two controls, the ${\mathrm{C}}_1\mathrm{P}$ and ${\mathrm{C}}_2\mathrm{P}$ gates, respectively, on neutral-atom hardware. The pulses we obtain have a duration significantly shorter than the loss time scale, set by decay from the Rydberg state. In addition, they do not require single-site addressability and are smooth. Hence, we expect our gates to have immediate benefits for quantum algorithms implemented on current neutral-atom hardware.

Magnetic tunnel junctions (MTJs) have shown great promise as hardware sources for true random number generation (TRNG) due to their intrinsic stochastic switching behavior. However, practical deployment remains challenged by the drift in the switching probability caused by thermal fluctuations, device aging, and environmental instability. This work presents an engineering-oriented, drift-resilient MTJ-based TRNG architecture, enabled by a hybrid control strategy that combines self-stabilizing feedback with pulse width modulation. A key component is the downcalibration-2 scheme, which updates the control parameter every two steps using only integer-resolution timing, ensuring excellent statistical quality without requiring bit discarding, precharacterization, or external calibration. Extensive experimental measurements and numerical simulations demonstrate that this approach maintains stable randomness under dynamic temperature drift, using only simple digital logic. The proposed architecture offers high throughput, robustness, and scalability, making it well-suited for secure hardware applications, embedded systems, and edge computing environments.

This study provides a comprehensive theoretical investigation of amorphous selenium-doped tellurium oxide ($\mathrm{Se}$-doped ${\mathrm{Te}\mathrm{O}}_x$), a novel $p$-type oxide semiconductor, using a multiscale modeling approach that combines first-principles calculations with device-level technology computer-aided design (TCAD) simulations. Our analysis shows that oxygen vacancies significantly modulate the electronic structure of amorphous tellurium oxide ($a$-${\mathrm{Te}\mathrm{O}}_x$) by narrowing the band gap and introducing shallow acceptor states, which enhance $p$-type conductivity. Selenium doping further tunes the material’s electrical properties by widening the band gap and altering subgate defect states. While optimal doping reduces leakage current and improves switching behavior, excessive doping leads to a deterioration of $I$-$V$ characteristics, emphasizing the importance of careful $\mathrm{Se}$ doping level optimization. TCAD simulations of ${\mathrm{Se}}_x{\mathrm{Te}}_{1-x}{\mathrm{O}}_{1.2}p$-MOSFETs demonstrate a strong correlation between a material’s electronic structure and device $I$-$V$ characteristics, highlighting the need to balance selenium concentration for optimal device performance. These findings provide valuable insights for developing high-performance oxide-based $p$-channel transistors and other semiconductor applications, guiding future experimental and theoretical works in this field.