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Clock Precision beyond the Standard Quantum Limit at 10 −18 Level

Optical atomic clocks with unrivaled precision and accuracy have advanced the frontier of precision measurement science and opened new avenues for exploring fundamental physics. A fundamental limitation on clock precision is the standard quantum limit (SQL), which stems from the uncorrelated projection noise of each atom. State-of-the-art optical lattice clocks interrogate large ensembles to minimize the SQL, but density-dependent frequency shifts pose challenges to scaling the atom number. The SQL can be surpassed, however, by leveraging entanglement, though it remains an open problem to achieve quantum advantage from spin squeezing at state-of-the-art stability levels. Here, we demonstrate clock performance beyond the SQL, achieving a fractional frequency precision of 1.1 × 10 −18 for a single spin-squeezed clock. With cavity-based quantum nondemolition measurements, we prepare two spin-squeezed ensembles of ∼30 000 strontium atoms confined in a two-dimensional optical lattice. A synchronous clock comparison with an interrogation time of 61 ms achieves a metrological improvement of 2.0(2) dB beyond the SQL, after correcting for state preparation and measurement errors. These results establish the most precise entanglement-enhanced clock to date and offer a powerful platform for exploring the interplay of gravity and quantum entanglement.

cavity quantum electrodynamics↗

High-Power Clock Laser Spectrally Tailored for High-Fidelity Quantum State Engineering

Highly frequency-stable lasers are ubiquitous tools for optical-frequency metrology, precision interferometry, and quantum information science. While making a universally applicable laser is unrealistic, spectral noise can be tailored for specific applications. Here we report a high-power 698-nm clock laser with a maximum output of 4W and minimized frequency noise up to a few kHz Fourier frequency, together with long-term instability of 3.5 × 10 −17 at one to thousands of seconds. The laser-frequency noise is precisely characterized with atom-based spectral analysis that employs a pulse sequence designed to suppress sensitivity to intensity noise. This method provides universally applicable tunability of the spectral response and analysis of quantum sensors over a wide frequency range. With the optimized laser system characterized by this technique, we achieve an average single-qubit Clifford gate fidelity of up to 𝐹$^2_1$ = 0.999⁢64⁢(3) when simultaneously driving 3000 optical qubits with a homogeneous Rabi frequency ranging from 10 Hz to 1 kHz. This result represents the highest single optical-qubit-gate fidelity for a large number of atoms.

atomic gases↗

Atomic Coherence of 2 Minutes and Instability of 1.5 × 10 −18 at 1 s in a Wannier-Stark Lattice Clock

We explore the limits of atomic coherence and measurement precision in a 87 Sr optical lattice clock. We perform a detailed characterization of key effects, including lattice Raman scattering and atomic collisions in a shallow lattice configuration, determining a 174(28) s 3 𝑃 0 clock state lifetime. Investigation of atomic coherence across a range of lattice depths and atomic densities reveals decoherence mechanisms related to photon scattering and atomic interaction. At a reduced density, we observe a coherence time of 118(9) s, approaching the fundamental limit set by spontaneous emission. Guided by this coherence understanding, we demonstrate a clock instability for an atomic ensemble of 1.5 × 10 −18 at 1 s in fractional frequency units. Our results are important for further advancing the state of the art of an optical lattice clock for fundamental physics applications.

atomic, optical, & lattice clocks↗

Topographic Characterization of Niobium Films on Copper for SRF Applications

Niobium films on copper substrates are being actively developed as a low-cost alternative to bulk niobium for superconducting radio-frequency (SRF) cavities, offering superior thermal conductivity, reduced material cost, and the potential for scalable cavity fabrication. The performance of such films can be limited by imperfect surfaces that reduce the peak achievable magnetic field. Nb films deposited under varied electron cyclotron resonance conditions were characterized via atomic force microscopy. The films exhibit a corrugated surface morphology which can be characterized by the depth of the corrugation, slope angle, and standard roughness parameters. The influence of this surface roughness on field limitations is examined within the framework of London theory. These measurements and models aid in understanding how ECR deposition conditions influence the nanometer-scale roughness of Nb films on Cu and its impact on high-field SRF cavity performance.

Redman, Brandi [Old Dominion Univ., Norfolk, VA (U↗

Visible-to-THz near-field nanoscopy

Optical microscopy has a key role in research, development and quality control across a wide range of scientific, technological and medical fields. However, diffraction limits the spatial resolution of conventional optical instruments to about half the illumination wavelength. A technique that surpasses the diffraction limit in the wide spectral range between visible and terahertz frequencies is scattering-type scanning near-field optical microscopy (s-SNOM). The basis of s-SNOM is an atomic force microscope in which the tip is illuminated with light from the visible to the terahertz spectral range. By recording the elastically tip-scattered light while scanning the sample below the tip, s-SNOM yields near-field optical images with a remarkable resolution of 10 nm, simultaneously with the standard atomic force microscopic topography image. This resolution is independent of the illumination wavelength, rendering s-SNOM a versatile nanoimaging and nanospectroscopy technique for fundamental and applied studies of materials, structures and phenomena. This Review presents an overview of the fundamental principles governing the measurement and interpretation of near-field contrasts and discusses key applications of s-SNOM. We also showcase emerging developments that enable s-SNOM to operate under various environmental conditions, including cryogenic temperatures, electric and magnetic fields, electrical currents, strain and liquid environments. Furthermore, all these recent developments broaden the applicability of s-SNOMs for exploring fundamental solid-state and quantum phenomena, biological matter, catalytic reactions and more.

Hillenbrand, Rainer [CIC nanoGUNE BRTA and Departm↗

PowderJet: Spherical metal powder production via multi-orifice droplet-on-demand metal jetting

Leading metal additive manufacturing techniques, such as laser powder bed fusion and directed energy deposition, rely on high-quality spherical metal powders. However, traditional powder production methods like gas atomization face limitations, including low in-spec yield, asphericity, and internal porosity. We introduce PowderJet, a powder production platform that uses electromagnetic pulses to eject liquid metal droplets from a multi-orifice nozzle. Unlike stochastic methods, PowderJet tightly controls powder size, distribution, and purity through a droplet-on-demand approach. We detail the system’s design, operation, and performance using a combined experimental and computational fluid dynamics (CFD) framework. Initial results with Al4008 and Cu110 alloys demonstrate successful production, yielding unsieved aluminum powder batches with a mean diameter of 200 µm and a narrow size distribution (15 µm standard deviation). The produced powders are highly spherical, achieving a roundness > 0.95. PowderJet operates with a small melt volume (3 mL) and supports continuous refilling, enabling production rates between 30 and 140 cm³/hr depending on jetting frequency, number of orifices and particle size. CFD simulations show that future systems could achieve rates exceeding 1000 cm³/hr for particle sizes as small as 40 µm. PowderJet’s high yield of in-spec powder makes it ideal for producing precious or hazardous materials that are inefficient to manufacture using conventional methods. This platform offers a scalable, precise, and efficient solution for producing high-quality powders tailored for advanced manufacturing applications.

Atomization↗

Impacts of sea ice leads on sea salt aerosols and atmospheric chemistry in the Arctic

Abstract. The processes contributing to Arctic cold-season (November–April) sea salt aerosols (SSAs) remain uncertain. Observations from coastal Alaska suggest that emissions from open leads in sea ice, which are not included in climate models, may play a dominant role. Their Arctic-wide significance has not yet been quantified. Here, we create an emission parameterization of SSAs from leads by combining satellite data of lead area (the Advanced Microwave Scanning Radiometer–Earth Observation System (AMSR-E) product) and a chemical transport model (GEOS-Chem) to quantify pan-Arctic SSA emissions from leads during the cold season from 2002 to 2008 and to predict their impacts on atmospheric chemistry, evaluating the results of our simulated SSAs against in situ observations. The AMSR-E product detects large leads with certainty (> 3 km in size), and, hence, our study is limited to quantifying emissions from large leads. Lead emissions vary seasonally and interannually. Simulated total monthly SSA emissions increase by 1.1 %–1.8 % (≥60° N latitude) and 5.6 %–7.5 % (≥75° N) for the 2002–2008 cold seasons. SSA concentrations primarily increase at the location of leads, where standard model concentrations are low. GEOS-Chem overestimates SSA concentrations at Arctic sites compared to ground observations, even when lead emissions are not included, suggesting underestimation of SSA sinks and/or uncertainties in SSA emissions from blowing snow and the open ocean. Multi-year monthly mean surface bromine atom (Br) concentrations increase by 2.8 %–8.8 % due to SSAs from leads for the 2002–2008 cold seasons. Changes in ozone concentrations are negligible. While leads contribute < 10 % to Arctic-wide SSA emissions in the years 2002–2008, these emissions occur in regions of low background aerosol concentrations. Leads may increase in frequency under future climate change, which could increase SSA emissions from leads.

Emme, Erin J. (ORCID:0000000268406352)↗

Phonon Olympics: Phonon property and lattice thermal conductivity benchmarking from open-source packages

Three widely used open-source packages for determining phonon properties and lattice thermal conductivities (ALAMODE, phono3py, and ShengBTE) are benchmarked by teams of expert users and the package developers. The phonons for Ge, RbBr, monolayer MoSe 2 , and AlN are modeled at zero temperature, and they scatter through three-phonon and phonon-isotope processes, with thermal conductivities obtained from the linearized Peierls–Boltzmann transport equation with input from density functional theory calculations. Over a wide range of temperatures, the thermal conductivities calculated by the teams fall within at most ±15% of their mean values for each of the four materials. The phonon frequencies, obtained from the harmonic force constants, do not show large differences between the calculations, indicating that the modal heat capacities and group velocities are not responsible for the thermal conductivity variations. It is the lifetimes associated with three-phonon scattering, obtained from the cubic force constants, that drive the variations. The many decisions required to calculate the cubic force constants (e.g., supercell size, atomic displacement, neighbor cutoff, and application of symmetries) make identification of the precise origin of the thermal conductivity variations challenging. The calculated thermal conductivities do not generally show agreement with experimental measurements, which is attributed to the limitations of the density functional theory calculations. Guidance for the development of best practices is provided, which will help to standardize protocols needed for building thermal conductivity databases. The results provide a baseline for future benchmarking of other packages and more advanced calculations.

McGaughey, Alan J. H. [Carnegie Mellon Univ., Pitt↗

Libration of hydroxyl groups in layered aluminum (oxy)hydroxides and other material analogs: insights from inelastic neutron scattering and theory

We analyzed the hydroxyl librational signatures of five structurally related aluminum (oxy)hydroxides, using inelastic neutron scattering (INS) and plane-wave lattice dynamics simulations. A clear trend across these aluminum-containing phases illustrates the relationship between hydrogen bonding, local atomic structure, and the spectral location and profile of the librational bands. The INS spectra have been compared to previous optical spectroscopy and computational studies, highlighting the complementary nature of the INS technique. Taking into account other structurally or chemically related material analogs, we have identified a correlation between a blueshift (to higher energy) of the upper librational band edge and the geometry of the hydrogen bond interactions, mirroring (with opposite correlation) the well-known redshift in the intramolecular O–H stretching energy with increasing hydrogen bond strength. For hydroxyl groups that do not participate in hydrogen bonding effectively, the bending librations occur at lower energies and hybridize with metal–oxygen lattice modes. Standard density functional theory approximations, including dispersion corrections, struggle to correctly predict vibrational frequencies of motions dominated by H but perform well for metal–oxygen modes, allowing us to make detailed mode assignments in several cases, including a demonstration of how layer-to-layer disorder in boehmite hydrogen bond orientations is reflected in the sharp but minor low energy peaks (at ∼70–80 meV) of the INS spectrum.

Wang, Hsiu-Wen [Oak Ridge National Laboratory (ORN↗

First-Principles Insights into the Thermocatalytic Cracking of Ammonia-Hydrogen Blends on Fe(110). 2. Kinetics

Ammonia (NH 3 ) is an energy-rich molecule that is routinely synthesized from nitrogen (N 2 ) and hydrogen (H 2 ). NH 3 ’s more favorable physical properties compared to H 2 suggests it may offer a way to more conveniently store, transport, and, when needed, extract H 2 via thermal decomposition. However, the high kinetic barrier and endoergicity to decompose to H 2 and N 2 require high temperatures. The standard reaction free energy indicates nearly 100% thermodynamic conversion to the diatomic molecules only at ~673 K and higher. However, even at these temperatures, a catalyst, e.g., iron (Fe), is needed for favorable kinetic conversion. Here, in this study, we explore via density functional theory the kinetics of NH 3 decomposition on the most stable facet of body-centered cubic Fe, namely, (110), under typical high-temperature and finite-pressure operando conditions. We predict coverage-dependent energetics of elementary surface reactions, often neglected in atomic-scale modeling. From these models, we find the recombinative desorption of adsorbed N as N 2 is rate-determining at 573.15–773.15 K and even at an extreme case of 1173.15 K. From microkinetic modeling, we find that the steady-state turnover frequencies (TOFs) for N 2 and H 2 generation rates (r$_{H_2}$) depend exponentially on temperature. The catalyst achieves a steady-state TOF of 36.4 s –1 and an r$_{H_2}$ of 0.107 μmol cm –2 s –1 for a feed of 1.8 bar NH 3 with 0.2 bar H 2 at 1173.15 K. However, at 773.15 K, with the same feed composition and velocity, the steady-state TOF and r$_{H_2}$ decrease to 0.14 s –1 and 4.10 × 10 –4 μmol cm –2 s –1 , respectively, as the process is significantly hindered by slow N 2 desorption. Although at first glance counterintuitive, our simulations suggest that surface modifications that reduce Fe’s reactivity toward NH x species should enhance its overall NH 3 decomposition activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin squeezing of macroscopic nuclear spin ensembles

Spin squeezing has been explored in atomic systems as a tool for quantum sensing, improving experimental sensitivity beyond the spin standard quantum limit for certain measurements. To optimize absolute metrological sensitivity, it is beneficial to consider macroscopic spin ensembles, such as nuclear spins in solids and liquids. Coupling a macroscopic spin ensemble to a parametrically-modulated resonant circuit can create collective spin squeezing by generating spin correlations mediated by the circuit. We analyze the squeezing dynamics in the presence of decoherence and finite spin polarization, showing that achieving 7 dB spin squeezing is feasible in several nuclear spin systems. The metrological benefit of squeezing a macroscopic spin ensemble lies in the suppression of technical noise sources in the spin detection system relative to the spin projection noise. This expands the experimental sensitivity bandwidth when searching for signals of unknown frequency and can improve the resonant signal-to-noise ratio. Squeezing macroscopic spin ensembles may prove to be a useful technique for fundamental physics experiments aimed at detecting spin interactions with oscillating background fields, such as ultralight dark matter. Published by the American Physical Society 2025

Boyers, Eric↗

Astigmatism-free 3D optical tweezer control for rapid atom rearrangement

Reconfigurable neutral-atom arrays are a promising platform for quantum computing, quantum simulation, and quantum metrology, but atom transport using frequency-chirped acousto-optic deflectors (AODs) is limited by chirp-induced acoustic lensing and trajectory distortion. We address these limitations using a three-dimensional acousto-optic deflector lens (3D-AODL), a design predicted to reduce long-range transport times by more than a factor of two. We further introduce fading-Shepard waveforms that circumvent finite AOD bandwidth, enabling sustained axial displacement. We demonstrate unrestricted three-dimensional optical-tweezer motion over a 200 μm × 200 μm × 136 μm volume with velocities exceeding 4.2 m/s. Arbitrary three-dimensional control of optical-tweezer trajectories enables rapid atom rearrangement and dynamical engineering of optical potentials in tweezer arrays and optical lattices. This capability advances quantum control and atom manipulation in neutral-atom quantum processors by enabling faster rearrangement, higher clock rates, and scalable sorting in complex geometries.

Lu, Yue-Hui [University of California, Berkeley, C↗

Tracking oxygen vacancy migration in memristor devices using operando hard X-ray photoelectron spectroscopy

Fabrication of ultrathin (sub-2 nm) oxide semiconductor memristors poses the fundamental challenge of achieving oxide growth with atomic precision in terms of electronic structure and defect formation. Recently, ultrathin memristors consisting of bilayers of mixed Al 2 O 3 and MgO atomic layers were fabricated using an in vacuo atomic layer deposition process. This approach offers a unique platform for precise atomic control of oxygen vacancies in the device in which the vacancies are introduced by placing MgO atomic layers between pristine Al 2 O 3 layers. In this work, we present a systematic operando Hard X-ray PhotoElectron Spectroscopy (HAXPES) study of the switching of such memristors, combined with complementary current-voltage and capacitance-voltage (C-V) measurements. We used a memristor stack of Al 2 O 3 /MgO atomic layers, with the MgO-containing oxide deposited on the bottom Al metal electrode and a pure Al 2 O 3 layer below the top Pd electrode. HAXPES analysis shows a substantial change in the chemical shift of the Aluminum oxide when switching between the ”OFF” and ”ON” states indicative of a redistribution of oxygen vacancies in the device active layer. Interestingly, subsequent switching to the OFF state shows hysteretic behavior indicating the retention of some oxygen vacancies in the top Al 2 O 3 layer. This vacancy retention can be correlated with the stochastic behavior of the switching voltage observed in these devices. C–V measurements show a clear frequency-dependent response in the OFF state, consistent with enhanced polarization and vacancy trapping at low frequencies.

47 OTHER INSTRUMENTATION↗

Radiation modeling and experimental validation of sub-cyclotron frequency microwave synchrotron radiation as a diagnostic tool for runaway electrons in present and future tokamaks

The microwave synchrotron radiation in the sub-cyclotron frequency region has been systematically validated as a diagnostic method for runaway electrons (>1 MeV) with radiation modeling and experiments on the DIII-D tokamak. Experimental observations reveal that sub-cyclotron frequency microwave radiation emerges only after runaway electrons are excited during plasma disruptions. Electron gyro-magnetic radiation modeling confirms that only runaway electrons with energies exceeding 1 MeV can emit radiation in the observed sub-cyclotron frequency band on DIII-D. The synchrotron Razin and Beaming effects are modeled in both the sub-cyclotron and standard Electron Cyclotron Emission (ECE) frequency region. Due to the pronounced beaming effect, the modeling supports that a standard ECE system is insensitive to synchrotron radiation from beamed runaway electrons (p ∥ >> p ⟂ ), but very sensitive to ECE radiation from isotropic suprathermal electrons (100 keV or less). DIII-D experiments further show that combining ECE and sub-cyclotron receivers reveals new insights into transient runaway dynamics during the plateau phase. Certain transient crash events appear only in the sub-cyclotron band or lead to opposite changes on the sub-cyclotron and standard ECE signals, supporting models where transient MHD events can exert a different effect on electrons of different energy levels. This novel diagnostic technique offers a powerful tool for studying and detecting runaway electron dynamics in both present-day and high-field future tokamaks. The diagnostic approach has been extrapolated to the SPARC tokamak, where sub-cyclotron radiation is predicted to respond sensitively and solely to runaway electrons during SPARC’s L-mode startup phase.

Yu, Guanying [Hefei Comprehensive National Science↗

Neural network-based classification and regression of magnetohydrodynamic modes in tokamaks

We present a machine learning-based magnetohydrodynamic (MHD) classifier and regressor that utilizes real or complex-valued 3D magnetic sensor array data to determine neoclassical tearing mode (NTM) onset times in tokamaks with millisecond accuracy. The input dataset consists of poloidal profiles of complex Fourier amplitudes with an n = 1 toroidal mode number from 144 human-labeled ITER Baseline Scenario discharges in the DIII-D tokamak, spanning both tearing-dominated and sawtooth-dominated regimes. Since m, n = 2,1 NTMs frequently emerge alongside sawteeth at the same frequency in this scenario, the focus is on isolating the m = 1 and m = 2 components of the n = 1 MHD mode near the tearing onset. To improve model regularization and prediction stability, singular value decomposition was applied to balance the sawtooth and tearing datasets. The enriched datasets facilitated training neural networks that learn the key distinguishing features of sawtooth and tearing modes in the poloidal profiles of their magnetic amplitude and phase. When the modes occur independently, the networks achieve perfect classification due to the modes’ distinct characteristics and low measurement noise. In the more experimentally relevant case where both modes coexist, the networks maintain exceptional performance across key metrics. Tests on synthetic data with known ground truth demonstrate the superior accuracy of the neural network trained on complex-valued input compared to models using real amplitude, phase, or pseudo-complex data, achieving both a mean time delay and standard deviation below 1 ms. Notably, standard linear regression methods fitting the dominant singular modes to the data closely match the neural network’s performance. Applying these methods across a broad range of H-mode scenarios will enable future studies to systematically identify dominant NTM triggers as scenario-specific variables, paving the way for more effective tearing mode avoidance strategies in future fusion reactor designs.

machine learning↗