Complex modeling for the quantification of nanoscale disorder using genetic algorithms, density functional theory and line-profile analysis
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We demonstrate an optical waveguide device, capable of supporting the high, in-vacuum, optical power necessary for trapping a single atom or a cold atom ensemble with evanescent fields. Our photonic integrated platform, with suspended membrane waveguides, successfully manages optical powers of 6 mW (500 μ m span) to nearly 30 mW (125 μ m span) over an un-tethered waveguide span. This platform is compatible with laser cooling and magneto-optical traps (MOTs) in the vicinity of the suspended waveguide, called the membrane MOT and the needle MOT, a key ingredient for efficient trap loading. We evaluate two novel designs that explore critical thermal management features that enable this large power handling. This work represents a significant step toward an integrated platform for coupling neutral atom quantum systems to photonic and electronic integrated circuits on silicon.
The 1 𝑆 0 − 3 𝑃 0 clock transition in strontium serves as the foundation for the world’s best atomic clocks and for gravitational wave detector concepts in clock atom interferometry. This transition is weakly allowed in the fermionic isotope 87 Sr but strongly forbidden in bosonic isotopes. Here, we demonstrate coherent excitation of the clock transition in bosonic 88 Sr using a novel collinear three-photon process in a weak magnetic field. We observe Rabi oscillations with frequencies of up to 50 kHz using W/cm 2 laser intensities and Gauss-level magnetic field amplitudes. The absence of nuclear spin in bosonic isotopes offers decreased sensitivity to magnetic fields and optical lattice light shifts, enabling atomic clocks with reduced systematic errors. The collinear propagation of the laser fields permits the interrogation of spatially separated atomic ensembles with common laser pulses, a key requirement for dark matter searches and gravitational wave detection with next-generation quantum sensors.
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.
We present a model-assisted density fitting (MADF) basis set generator, an algorithm for generating primitive atomic Gaussian density fitting (DF) basis sets (DFBSs) from a contracted Gaussian orbital basis set (OBS). The MADF algorithm produces DFBSs suitable for accurate robust DF approximation of 2-particle interactions in mean-field and correlated electronic structures. The algorithm is designed to (a) saturate the OBS product space by a large regularized set of primitive solid-harmonic Gaussian shells with nonuniform distribution of exponents, followed by (b) pruning of the shells according to their contributions to the 2- body energy of a correlated atomic ensemble. Building the DFBS generator model almost exclusively on mathematical and physical principles allows one to limit the number of parameters that control the density fitting error to three, with a single set of parameters sufficient for computations with all basis cardinal numbers, with and without correlation of core electrons, with and without scalar and spin-dependent relativistic effects, spanning almost all of the Periodic Table. Performance assessment included basis sets up to quadruple-ζ quality from several major basis set families, using molecules composed of main-group, d-block, and f-block elements. The resulting DF errors in Hartree−Fock and second-order MP2 energies (with relativistic all-electron treatments, when appropriate) were on the order of 20 and 10 μE h per electron, respectively.
X-ray spectroscopic data from high-energy-density laser-produced plasmas has long required thorough, time-consuming analysis to extract meaningful source conditions. There are often confounding factors due to rapidly evolving states and finite spatial gradients (e.g., the existence of multi-temperature, multi-density, multi-ionization states, etc.) that make spectral measurements and analysis difficult. Here, in this paper, we demonstrate how deep learning can be applied to enhance x-ray spectral data analysis in both speed and intricacy. Neural networks (NNs) are trained on ensemble atomic physics simulations so that they can subsequently construct a model capable of extracting plasma parameters directly from experimental spectra. Through deep learning, the models can extract temperature distributions as opposed to single or dual temperature/density fits from standard trial-and-error atomic modeling at a significantly reduced computational cost compared to traditional trial-and-error methods. These NNs are envisioned to be deployed with high repetition rate x-ray spectrometers in order to provide detailed real-time analysis of experimental spectra.
We explore a two-node, entanglement-enhanced sensor network for differential phase sensing that exploits decoherence-free subspaces to suppress common-mode noise, a primary limitation of many state-of-the-art quantum sensors. We identify a class of entangled states that, while not strictly optimal, achieve the same asymptotic sensitivity scaling as optimal states and can be prepared efficiently from initially unentangled atomic ensembles. Importantly, the preparation time decreases with increasing system size, which makes the states compatible with realistic noise processes in present-day quantum sensors that operate with large particle numbers but lack full error correction. We illustrate these ideas using two cavity-mediated preparation protocols: (i) coherent, unitary entanglement generation analogous to bosonic two-mode squeezing, yielding Heisenberg scaling, and (ii) dissipative preparation through collective emission into a shared cavity mode, providing a square-root improvement beyond the standard quantum limit. Numerical simulations show that both approaches remain effective at experimentally realistic cavity cooperativities, establishing a practical path toward scalable, quantum-enhanced differential phase sensing.
To detect a specific radio-frequency (rf) magnetic field, rf optically pumped magnetometers (OPMs) require a static magnetic field to set the Larmor frequency of the atoms equal to the frequency of interest. However, unshielded and variable magnetic field environments (e.g., an rf OPM on a moving platform) pose a problem for rf OPM operation. Here, we demonstrate the use of a natural-abundance rubidium vapor to make a comagnetometer to address this challenge. Our implementation builds upon the simultaneous application of several OPM techniques within the same vapor cell. First, we use a modified implementation of an OPM variometer based on 87 Rb to detect and actively cancel unwanted external fields at frequencies ≲60 Hz using active feedback to a set of field control coils. In this experiment, we exploit this stabilized field environment to implement a high-sensitivity rf magnetometer using 85 Rb. Using this approach, we demonstrate the ability to measure rf fields with a sensitivity of approximately 9 fT Hz -1/2 inside a magnetic shield in the presence of an applied field of approximately 20 μT along three mutually orthogonal directions. This demonstration opens up a path toward completely unshielded operation of a high-sensitivity rf OPM.
Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.
The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.
The development of efficient, durable, and low-PGM electrocatalysts for the hydrogen evolution reaction (HER) in alkaline media is critical for next-generation electrolysis technologies. We report a facile two-step synthesis of highly dispersed PtNi and PtNi-nitride nanoclusters (NCs) (~2.3 nm) with ultralow Pt content (0.5 at.%) anchored on N-doped Vulcan carbon. Structural and compositional characterization via XAS, XPS, HAADF-STEM, HRTEM, and EDS mapping established key structure–activity relationships across varying Pt/Ni ratios and pyrolysis temperatures. The Pt0.5Ni0.5/C-750 catalyst, an ensemble of PtNi M-N-C type single-atom (SA) moieties with neighboring PtNi nanoclusters (NC), exhibited superior HER performance in alkaline media, achieving overpotentials of 30, 115, and 210 mV at 10, 100, and 500 mA cm−2, respectively. Despite at a lower Pt content, this novel SA–NC ensemble outperformed commercial Pt/C by ~36%. A standardized literature comparison with contemporary Pt- and Ru-doped analogues reveals the as-prepared Pt0.5Ni0.5/C-750 to sit at the apex of Tafel-limited kinetics and low overpotential at 100 mA cm−2. Tafel-limited Tafel slopes in both alkaline and acidic regimes confirm favorable proton recombination kinetics. Mass activities at 200 mV reached 13.8 and 18.84 A mgPt−1 in alkaline and acidic media, respectively. However, excessive nitridation (e.g., at 650 °C) adversely altered Pt electronic structure and HER kinetics. While Ni enhanced alkaline HER, acidic HER favored Ni-free analogues. Pt0.5Ni0.5/C-750 also demonstrated robust temperature responsiveness and 300-h operational stability at high current densities (0.5–1.0 A cm−2) in MEA tests. This work presents a scalable strategy for designing thermally responsive, durable, and compositionally tunable NC catalysts with neighboring SA moieties for alkaline electrolysis.
Ultralight axionlike particles can contribute to the dark matter near the Sun, leading to a distinct, stochastic signature in terrestrial experiments. We search for such particles through their neutron-spin coupling by reanalyzing approximately 40 days of data from a K- 3 He comagnetometer with a new frequency-domain likelihood-based formalism that properly accounts for stochastic effects over all axion coherence times relative to the experimental time span. Assuming that axions make up all of the dark matter in the Sun’s vicinity, we find a median 95% upper limit on the neutron-spin coupling of 2.4 × 10 −10 GeV −1 for most axion masses from 0.4 to 4 feV, which is about 5 orders of magnitude more stringent than previous laboratory bounds in that mass range. Although several peaks in the experiment’s magnetic power spectrum suggest the rejection of a white-noise null hypothesis, further analysis of their line shapes yields no positive evidence for a dark-matter axion.
Creating dual-atom active sites in host metals allows tuning of chemical properties through electronic effects and ensemble effects. In particular, some dual-atom alloys feature molecular-like electronic states.
Heterogeneous catalysis is driven by the interaction of reactant molecules and the catalyst surface. The locus of this interaction as well as the surrounding ensemble of atoms is referred to as the catalyst active site. Active site characterization attempts to distinguish active catalytic sites from inactive surface sites, to elucidate the structural and chemical nature of active sites, and to quantify active site concentration. Numerous techniques have been demonstrated to provide compositional and structural information about the active sites within a catalyst. However, each technique has its own limitations and experimental pitfalls that can lead to data misinterpretation or irreproducible results. Further, this work aims to provide an overview of the types of data that can be collected, to outline common experimental challenges and how to avoid them, and to assemble relevant references for the most used active site characterization techniques. More broadly, we aim to outline best practices for researchers to collect, interpret, and report active site characterization data in a way that provides the most benefit to the broader catalysis community. Increasing the rigor and reproducibility of active site characterization offers a strategy to better link properties with catalytic performance and to enable the community to develop consensus concerning these relationships.
This report presents the results of the 2012-2013 NASA Institute for Advanced Concepts (NIAC) Phase 1 "Atom Interferometry for Detection of Gravitational Waves" project. The origin of this GW (Gravitational Wave) detection concept using atoms can be traced to theoretical work that first appeared in 2008 and also to a satellite mission-focused followup study that was done in 2011. The goal of the current project was to explore both theoretical and technical issues surrounding the implementation of this idea, as well as to begin performing proof-of-concept experiments to validate critical aspects of the proposal.The top level trade space for the detector design is driven by the strategy employed to mitigate laser frequency noise, which, if uncontrolled, can mask GW signatures. One of the advantages of the atom interferometric approach is the possibility of single baseline detection (Fig. 1.1), even in the presence of laser noise. This is enabled by the differential measurement between the two ensembles of atoms, which can result in substantial laser noise suppression. The details of this suppression depend on the atomic physics techniques used to implement the atom interferometry. Specifically, we considered the effect on noise suppression that results from using traditional two-photon Raman transitions (with alkali atoms) and also single-photon transitions (with alkaline earth-like atoms).The interferometers shown in Fig 1.1(b) take advantage of single-photon transitions (as opposed to traditional Raman transitions) because using light pulses from one direction at a time allows for near perfect common-mode cancellation of laser phase noise, even for long baselines. This calls for the use of atomic transitions with an (ideally large) optical energy level difference with a long (greater than 1 second) lifetime, such as high-transitions routinely used for optical atomic clocks in species like Sr, Ca and Yb. Notably, large momentum transfer (LMT) atom optics - and the sensitivity enhancement they confer – can still be realized by simply adding additional pairs of alternating pulses to each beam splitter process. Section 3 reports on the theoretical work we performed to justify this GW detection protocol using single-photon transitions. This approach represents a new method for GW detection using atoms that is distinct from the original proposal from 2008. At the system level, we evaluated three architectures, each of which implements a different solution to the laser frequency noise issue. The first two designs are based on two-photon Raman transitions with Rb atoms. One of these is a three-satellite, multiple baseline design while the other is a two-satellite, single baseline design. The third proposal is a two-satellite, single baseline design that uses single-photon transitions with Sr atoms. These three architectures are described in more detail in Section 2. There are a number of known technical issues that we have started to address using ground-based experiments. These issues include atom technology development needs such as, for example, lower ensemble temperature requirements and large momentum transfer (LMT) atom optics. To this end, we have built a 10-meter scale atom drop tower, where we can perform proof-of-principle demonstrations of the proposed AGIS detector in an environment that permits more than 2.5 seconds of free-fall time. This facility allows for demonstration of atom interferometry with long interrogation time (seconds) and large atom wavepacket
The vibrational entropy of a solid at finite temperature is investigated from the perspective of information theory. Ab initio molecular dynamics (AIMD) simulations generate ensembles of atomic configurations at finite temperature from which we obtain the N-body distribution of atomic displacements, ρN. We calculate the information-theoretic entropy from the expectation value of lnρN. At a first level of approximation, treating individual atomic displacements independently, our method may be applied using Debye–Waller B-factors, allowing diffraction experiments to obtain an upper bound on the thermodynamic entropy. At the next level of approximation we correct the overestimation through inclusion of displacement covariances. We apply this approach to elemental body-centered cubic sodium and face-centered cubic aluminum, showing good agreement with experimental values above the Debye temperatures of the metals. Below the Debye temperatures, we extract an effective vibrational density of states from eigenvalues of the covariance matrix, and then evaluate the entropy quantum mechanically, again yielding good agreement with experiment down to low temperatures. Our method readily generalizes to complex solids, as we demonstrate for a high entropy alloy. Further, our method applies in cases where the quasiharmonic approximation fails, as we demonstrate by calculating the HCP/BCC transition in Ti.
We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which combines the mean-field dynamics of a spin ensemble with a Monte Carlo sampling of discrete initial spin values to account for quantum correlations. Here we show how this approach can be generalized for dissipative spin systems by replacing the deterministic mean-field evolution by a stochastic process, which describes the decay of coherences and populations while preserving the length of each spin. We demonstrate the application of this technique for simulating nonclassical spin-squeezing effects or the dynamics and steady states of cavity QED models with 10 5 interacting two-level systems. This opens up the possibility to perform accurate real-scale simulations of a diverse range of experiments in quantum optics or with solid-state spin ensembles under realistic laboratory conditions.