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DOE OSTI2021

Spinning no-scale $${\mathcal {F}}$$-SU(5) in the right direction

Abstract The Fermi National Accelerator Laboratory (FNAL) recently announced confirmation of the Brookhaven National Lab (BNL) measurements of the $$g-2$$ g - 2 of the muon that uncovered a discrepancy with the theoretically calculated Standard Model value. We suggest an explanation for the combined BNL+FNAL 4.2 $$\sigma $$ σ deviation within the supersymmetric grand unification theory (GUT) model No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) supplemented with a string derived TeV-scale extra $$10+\overline{10}$$ 10 + 10 ¯ vector-like multiplet and charged vector-like singlet $$(XE,XE^c)$$ ( X E , X E c ) , dubbed flippons. We introduced these vector-like particles into No-Scale Flipped SU (5) many years ago, and as a result, the renormalization group equation (RGE) running was immediately shaped to produce a distinctive and rather beneficial two-stage gauge coupling unification process to avoid the Landau pole and lift unification to the string scale, in addition to contributing through 1-loop to the light Higgs boson mass. The flippons have long stood ready to tackle another challenge, and now do so yet again, where the charged vector-like “lepton”/singlet couples with the muon, the supersymmetric down-type Higgs $$H_d$$ H d , and a singlet S , using a chirality flip to easily accommodate the muonic $$g-2$$ g - 2 discrepancy in No-Scale $${\mathcal {F}}$$ F - $$SU(5)$$ S U ( 5 ) . Considering the phenomenological success of this string derived model over the prior 11 years that remains accommodative of all presently available LHC limits plus all other experimental constraints, including no fine-tuning, and the fact that for the first time a Starobinsky-like inflationary model consistent with all cosmological data was derived from superstring theory in No-Scale Flipped SU (5), we believe it is imperative to reconcile the BNL+FNAL developments within the model space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

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↗

DOE OSTI2021

Search for the doubly charmed baryon $ {\varXi}_{cc}^{+} $ in the $ {\varXi}_c^{+}{\pi}^{-}{\pi}^{+} $ final state

A search for the doubly charmed baryon $ {\varXi}_{cc}^{+} $ is performed in the $ {\varXi}_c^{+}{\pi}^{-}{\pi}^{+} $ invariant-mass spectrum, where the $ {\varXi}_c^{+} $ baryon is reconstructed in the pK - π + final state. The study uses proton-proton collision data collected with the LHCb detector at a centre- of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 5.4 fb -1 . No significant signal is observed in the invariant-mass range of 3.4–3.8 GeV/ c 2 . Upper limits are set on the ratio of branching fractions multiplied by the production cross-section with respect to the $ {\varXi}_{cc}^{++} $ →( $ {\varXi}_c^{+} $ → pK - π + ) π + decay for different $ {\varXi}_{cc}^{+} $ mass and lifetime hypotheses in the rapidity range from 2.0 to 4.5 and the transverse momentum range from 2.5 to 25 GeV/ c . The results from this search are combined with a previously published search for the $ {\varXi}_{cc}^{+} $ → $ {\varLambda}_c^{+} $ K - π + decay mode, yielding a maximum local significance of 4.0 standard deviations around the mass of 3620 MeV/ c 2 , including systematic uncertainties. Taking into account the look-elsewhere effect in the 3.5–3.7 GeV/ c 2 mass window, the combined global significance is 2.9 standard deviations including systematic uncertainties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

The solenoidal large intensity device (SoLID) for JLab 12 GeV

The solenoidal large intensity device (SoLID) is a new experimental apparatus planned for Hall A at the Thomas Jefferson National Accelerator Facility (JLab). SoLID will combine large angular and momentum acceptance with the capability to handle very high data rates at high luminosity. With a slate of approved high-impact physics experiments, SoLID will push JLab to a new limit at the QCD intensity frontier that will exploit the full potential of its 12 GeV electron beam. In this paper, we present an overview of the rich physics program that can be realized with SoLID, which encompasses the tomography of the nucleon in 3D momentum space from semi-inclusive deep inelastic scattering, expanding the phase space in the search for new physics and novel hadronic effects in parity-violating DIS, a precision measurement of J/ψ production at threshold that probes the gluon field and its contribution to the proton mass, tomography of the nucleon in combined coordinate and momentum space with deep exclusive reactions, and more. To meet the challenging requirements, the design of SoLID described here takes full advantage of recent progress in detector, data acquisition and computing technologies. In addition, we outline potential experiments beyond the currently approved program and discuss the physics that could be explored should upgrades of CEBAF become a reality in the future.

3D imaging↗

DOE OSTI2026

Pb-Apatite Framework as a Generator of Novel Flat-Band CuO-Based Physics

Based upon density functional theory (DFT) calculations, we present the basic electronic structure of CuPb 9 (PO 4 ) 6 O (Cu-doped lead apatite, aka LK-99), in two scenarios: (1) where the structure is constrained to the P3 symmetry and (2) where no symmetry is imposed. At the DFT level, the former is predicted to be metallic while the latter is found to be a charge-transfer insulator. In both cases the filling of these states is nominally d 9 , consistent with the standard Cu 2+ valence state, and Cu with a local magnetic moment of order 0.7 μ B . In the metallic case we find these states to be unusually flat (∼0.2 eV dispersion), giving a very high density of electronic states (DOS) at the Fermi level that we argue can be a host for novel electronic physics. The flatness of the bands is the likely origin of symmetry-lowering gapping possibilities that would remove the spectral weight from E F . Motivated by some initial experimental observations of metallic or semiconducting behavior, we propose that disorder (likely structural) is responsible for closing the gap. Here, we consider a variety of possibilities that could possibly close the charge-transfer gap but limit consideration to kinds of disorder that preserve electron count. Of the possible kinds we considered (spin disorder, O populating vacancy sites, and Cu on less energetically favorable Pb sites), the local Cu moment, and consequently the charge-transfer gap, remains robust. We conclude that disorder responsible for metallic behavior entails some kind of doping where the electron count changes. Further, we claim that the emergence of the flat bands should be due to weak wave function overlap between the orbitals on Cu and O sites, owing to the directional character of the constituent orbitals. Therefore, finding an appropriate host structure for minimizing hybridization between Cu and O while allowing them to still weakly interact should be a promising route for generating flat bands at E F which can lead to interesting electronic phenomena, regardless of whether LK-99 is a superconductor.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Measurement Uncertainty in One-Of-A-Kind Event Data Analysis

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable, have unavoidable built-in differences resulting in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates over the measurement uncertainty. Range of true values depends on built-in differences in physics of the experiment. Stochastic physical processes result typically in a broader range of true values than non-stochastic processes do. Measurement uncertainty depends on a measurement method (properties of the detector not of the experiment). Modern measurement methods, including digital ones, frequently make the measurement uncertainty very small. When data from one–of –a kind experiment are analyzed, only the measurement uncertainty is reported. It provides no information about the range of true experimental values, neither about reliability of a reported data point. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable. Methods for data analysis from an experiment repeated statistically significant number of times are very well developed. They do not require a detailed expertise in physics of an experiment, nor in the properties of the measurement system used, and meaning of the reported uncertainty is well understood in any scientific community. It all changes when data from one-of-a-kind experiment is analyzed. Analyst’s expertise is required both in the physics of the experiment and in all aspects of the measurement system, all possible malfunctions. Data users must remember that only measurement uncertainty is reported from any one-of-a-kind experiment. Theory with simulations may provide estimation of expected built-in differences in the experiment, and by this of expected range of true values for a given experiment; yet measurement uncertainty can never be used in place of the range of true experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to arbitrary locations in each exposure. We introduce an extension to standard GPR techniques that exploits the knowledge that the 2D distortion field is curl-free. Applied to several hundred 90 s exposures from the Dark Energy Survey as a test bed, we find that the GPR correction reduces the variance of the turbulent astrometric distortions ≈12× , on average, with better performance in denser regions of the Gaia catalog. The rms per-coordinate distortion in the riz bands is typically ≈7 mas before any correction and ≈2 mas after application of the GPR model. The GPR astrometric corrections are validated by the observation that their use reduces, from 10 to 5 mas rms, the residuals to an orbit fit to riz-band observations over 5 yr of the r = 18.5 trans-Neptunian object Eris. We also propose a GPR method, not yet implemented, for simultaneously estimating the turbulence fields and the 5D stellar solutions in a stack of overlapping exposures, which should yield further turbulence reductions in future deep surveys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Search for solar axions produced through the axion-electron coupling gae using a new GridPix detector at CAST

We present a search for solar axions produced through the axion-electron coupling (g ae ) using data from a novel 7-GridPix detector installed at the CERN Axion Solar Telescope (CAST). The detector, featuring ultra-thin silicon nitride windows and multiple veto systems, collected approximately 160 hours of solar tracking data between 2017–2018. Using machine learning techniques and the veto systems, we achieved a background rate of 1.06 × 10 −5 keV −1 cm −2 s −1 at a signal efficiency of about 80% in the 0.2 to 8 keV range. Analysis of the data yielded no significant excess above background, allowing us to set a new upper limit on the product of the axion-electron and axion-photon couplings of g ae · g aγ < 7.35 × 10 −23 GeV −1 at 95% confidence level for axion masses below 10 meV. This result improves upon the previous best helioscope limit and demonstrates the potential of GridPix technology for rare event searches. Additionally, we derived a limit on the axion-photon coupling of g aγ < 9.0 × 10 −11 GeV −1 at 95% CL, which, while not surpassing CAST’s best limit, provides complementary constraints on axion models.

Beyond Standard Model↗