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At least 1,747 records · Page 97

Traceable random numbers from a non-local quantum advantage

The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations—the generation processes cannot be fully traced, audited and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol forms the basis for a public traceable and certifiable quantum randomness beacon that we have launched. Over the first 40 days of operation, we completed the protocol 7,434 out of 7,454 attempts—a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error multiplied by actual success probability bounded by 2−64. Further, the generation of certifiable and traceable randomness represents a public service that operates with an entanglement-derived advantage over comparable classical approaches.

97 MATHEMATICS AND COMPUTING↗

Near field excited state imaging via stimulated electron energy gain spectroscopy of localized surface plasmon resonances in plasmonic nanorod antennas

Continuous wave (cw) photon stimulated electron energy loss and gain spectroscopy (sEELS and sEEGS) is used to image the near field of optically stimulated localized surface plasmon resonance (LSPR) modes in nanorod antennas. An optical delivery system equipped with a nanomanipulator and a fiber-coupled laser diode is used to simultaneously irradiate plasmonic nanostructures in a (scanning) transmission electron microscope. The nanorod length is varied such that the m = 1, 2, and 3 LSPR modes are resonant with the laser energy and the optically stimulated near field spectra and images of these modes are measured. Various nanorod orientations are also investigated to explore retardation effects. Optical and electron beam simulations are used to rationalize the observed patterns. As expected, the odd modes are optically bright and result in observed sEEG responses. The m = 2 dark mode does not produce a sEEG response, however, when tilted such that retardation effects are operative, the sEEG signal emerges. Thus, we demonstrate that cw sEEGS is an effective tool in imaging the near field of the full set of nanorod plasmon modes of either parity.

36 MATERIALS SCIENCE↗

An interphase pool of KIF11 localizes at the basal bodies of primary cilia and a reduction in KIF11 expression alters cilia dynamics

KIF11 is a homotetrameric kinesin that peaks in protein expression during mitosis. It is a known mitotic regulator, and it is well-described that KIF11 is necessary for the formation and maintenance of the bipolar spindle. However, there has been a growing appreciation for non-mitotic roles for KIF11. KIF11 has been shown to function in such processes as axon growth and microtubule polymerization. We previously demonstrated that there is an interphase pool of KIF11 present in glioblastoma cancer stem cells that drives tumor cell invasion. Here, we identified a previously unknown association between KIF11 and primary cilia. We confirmed that KIF11 localized to the basal bodies of primary cilia in multiple cell types, including neoplastic and non-neoplastic cells. Further, we determined that KIF11 has a role in regulating cilia dynamics. Upon the reduction of KIF11 expression, the number of ciliated cells in asynchronously growing populations was significantly increased. We rescued this effect by the addition of exogenous KIF11. Lastly, we found that depleting KIF11 resulted in an increase in cilium length and an attenuation in the kinetics of cilia disassembly. These findings establish a previously unknown link between KIF11 and the dynamics of primary cilia and further support non-mitotic functions for this kinesin.

59 BASIC BIOLOGICAL SCIENCES↗

Localized UV emitters on the surface of β-Ga 2 O 3

Abstract Monoclinic gallium oxide (β-Ga 2 O 3 ) is attracting intense focus as a material for power electronics, thanks to its ultra-wide bandgap (4.5–4.8 eV) and ability to be easily doped n -type. Because the holes self-trap, the band-edge luminescence is weak; hence, β-Ga 2 O 3 has not been regarded as a promising material for light emission. In this work, optical and structural imaging methods revealed the presence of localized surface defects that emit in the near-UV (3.27 eV, 380 nm) when excited by sub-bandgap light. The PL emission of these centers is extremely bright—50 times brighter than that of single-crystal ZnO, a direct-gap semiconductor that has been touted as an active material for UV devices.

36 MATERIALS SCIENCE↗

Wind plants can impact long-term local atmospheric conditions

Abstract Long-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30 km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

17 WIND ENERGY↗

Complex magnetic properties associated with competing local and itinerant magnetism in \({\text {Pr}}_2 {\text {Co}}_{0.86} {\text {Si}}_{2.88}\)

Ternary intermetallic compound \({\text {Pr}}_2 {\text {Co}}_{0.86} {\text {Si}}_{2.88}\) has been synthesized in single phase and characterized by x-ray diffraction, scanning electron microscopy with energy dispersive x-ray spectroscopy (SEM-EDX) analysis, magnetization, heat capacity, neutron diffraction and muon spin rotation/relaxation ( \(\mu\) SR) measurements. The polycrystalline compound was synthesized in single phase by introducing necessary vacancies in Co/Si sites. Magnetic, heat capacity, and zero-field neutron diffraction studies reveal that the system undergoes magnetic transition below \(\sim\) 4 K. Neutron diffraction measurement further reveals that the magnetic ordering is antiferromagnetic in nature with an weak ordered moment. The high temperature magnetic phase has been attributed to glassy in nature consisting of ferromagnetic clusters of itinerant (3 d ) Co moments as evident by the development of internal field in zero-field \(\mu\) SR below 50 K. The density-functional theory (DFT) calculations suggest that the low temperature magnetic transition is associated with antiferromagnetic coupling between Pr 4 f and Co 3 d spins. Pr moments show spin fluctuation along with unconventional orbital moment quenching due to crystal field. The evolution of the symmetry and the crystalline electric field environment of Pr-ions are also studied and compared theoretically between the elemental Pr and when it is coupled with other elements such as Co. The localized moment of Pr 4 f and itinerant moment of Co 3 d compete with each other below \(\sim\) 20 K resulting in an unusual temperature dependence of magnetic coercivity in the system.

36 MATERIALS SCIENCE↗

Survival analysis of localized prostate cancer with deep learning

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics C td over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved C td 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained C td 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.

60 APPLIED LIFE SCIENCES↗

Local Bayesian Dirichlet mixing of imperfect models

Abstract To improve the predictability of complex computational models in the experimentally-unknown domains, we propose a Bayesian statistical machine learning framework utilizing the Dirichlet distribution that combines results of several imperfect models. This framework can be viewed as an extension of Bayesian stacking. To illustrate the method, we study the ability of Bayesian model averaging and mixing techniques to mine nuclear masses. We show that the global and local mixtures of models reach excellent performance on both prediction accuracy and uncertainty quantification and are preferable to classical Bayesian model averaging. Additionally, our statistical analysis indicates that improving model predictions through mixing rather than mixing of corrected models leads to more robust extrapolations.

97 MATHEMATICS AND COMPUTING↗

Local lattice distortions drive the transition of BaIrO 3 into a ferromagnetic insulator state

Using variable temperature total and resonant x-ray scattering at the K edge of Ir species, we study the “bad metal” to insulator transition in BaIrO 3 , a canonical third transition series oxide. The usage of advanced experimental techniques and large-scale computer modeling helps us show that, contrary to the widely accepted view, charge disproportionation leading to the formation of Ir-trimers with a different number of 5d valence electrons already exists at room temperature. The charge disbalance between the trimers does not evolve much with decreasing temperature while local lattice distortions do, suggesting that the latter and not the former make a key contribution to the emergence of the enigmatic ferromagnetic insulator state of BaIrO 3 . The conclusion is supported by DFT calculations based on unmodified experimental structure data. Our work calls for a reconsideration of the role of lattice distortions in determining the electronic properties of third transition series oxides. It also charts a path to assessing these properties on a realistic and not assumed crystal structure basis.

36 MATERIALS SCIENCE↗

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Abstract Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Local structure and distortions of mixed methane-carbon dioxide hydrates

A vast source of methane is found in gas hydrate deposits, which form naturally dispersed throughout ocean sediments and arctic permafrost. Methane may be obtained from hydrates by exchange with hydrocarbon byproduct carbon dioxide. It is imperative for the development of safe methane extraction and carbon dioxide sequestration to understand how methane and carbon dioxide co-occupy the same hydrate structure. Pair distribution functions (PDFs) provide atomic-scale structural insight into intermolecular interactions in methane and carbon dioxide hydrates. We present experimental neutron PDFs of methane, carbon dioxide and mixed methane-carbon dioxide hydrates at 10 K analyzed with complementing classical molecular dynamics simulations and Reverse Monte Carlo fitting. Mixed hydrate, which forms during the exchange process, is more locally disordered than methane or carbon dioxide hydrates. The behavior of mixed gas species cannot be interpolated from properties of pure compounds, and PDF measurements provide important understanding of how the guest composition impacts overall order in the hydrate structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Localized-to-itinerant transition preceding antiferromagnetic quantum critical point and gapless superconductivity in CeRh 0.5 Ir 0.5 In 5

A fundamental problem posed from the study of correlated electron compounds, of which heavy-fermion systems are prototypes, is the need to understand the physics of states near a quantum critical point (QCP). At a QCP, magnetic order is suppressed continuously to zero temperature and unconventional superconductivity often appears. Here, we report pressure ( P )-dependent 115 In nuclear quadrupole resonance (NQR) measurements on heavy-fermion antiferromagnet CeRh 0.5 Ir 0.5 In 5 . These experiments reveal an antiferromagnetic (AF) QCP at \({P}_{{\rm{c}}}^{{\rm{AF}}}=1.2\) GPa where a dome of superconductivity reaches a maximum transition temperature T c . Preceding \({P}_{{\rm{c}}}^{{\rm{AF}}}\) , however, the NQR frequency ν Q undergoes an abrupt increase at \({P}_{{\rm{c}}}^{{\rm{* }}}\) = 0.8 GPa in the zero-temperature limit, indicating a change from localized to itinerant character of cerium’s f -electron and associated small-to-large change in the Fermi surface. At \({P}_{{\rm{c}}}^{{\rm{AF}}}\) where T c is optimized, there is an unusually large fraction of gapless excitations well below T c that implicates spin-singlet, odd-frequency pairing symmetry.

36 MATERIALS SCIENCE↗

Atomic-scale manipulation of buried graphene–silicon carbide interface by local electric field

Abstract Precision of scanning tunneling microscopy (STM) enables control of matter at scales of single atoms. However, transition from atomic-scale manipulation strategies to practical devices encounters fundamental problems in protection of the designer structures formed atop the surface. In this context, STM manipulation of subsurface structures on technologically relevant materials is encouraging. Here, we propose a material platform and protocols for precise manipulation of a buried graphene interface. We show that an electric field from the STM tip reversibly controls breaking and restoring of covalent bonds between the graphene buffer layer and the SiC substrate. The process involves charge redistribution at the atomically sharp interface plane under the epitaxial graphene layer(s). This buried manipulation platform is laterally defined by unit cells from the corresponding (6×6) SiC moiré lattice of the epitaxial graphene. Local and reversible electric-field-induced patterning of graphene heterostructures from the bottom interface creates an alternative architecture concept for their applications.

74 ATOMIC AND MOLECULAR PHYSICS↗

Programmable low-coherence wavefronts for enhanced localization

Engineering the properties of electromagnetic wavefronts has become essential to imaging, wireless security, sensing, and wireless communication. In particular, wavefronts that exhibit low spatial coherence can enable sensing functionalities with high accuracy and low latency. The typical use of such wavefronts cannot take advantage of these possibilities, as they require the ability to dynamically reconfigure the wavefront in a controllable and repeatable fashion, over a broad spectral bandwidth. Here, we propose a new approach for generating broadband reconfigurable wavefronts which not only exhibit low spatial coherence at a particular frequency, but are also decorrelated with the wavefronts simultaneously generated at other frequencies. We demonstrate that this frequency-domain decorrelation is a key feature that, in combination with dynamic reconfigurability, enables localization measurements with an order-of-magnitude improvement in accuracy compared to the state of the art.

36 MATERIALS SCIENCE↗

Probing radical–molecule interactions with a second generation energy decomposition analysis of DFT calculations using absolutely localized molecular orbitals

Intermolecular interactions between radicals and closed-shell molecules are ubiquitous in chemical processes, ranging from the benchtop to the atmosphere and extraterrestrial space. While energy decomposition analysis (EDA) schemes for closed-shell molecules can be generalized for studying radical–molecule interactions, they face challenges arising from the unique characteristics of the electronic structure of open-shell species. In this work, we introduce additional steps that are necessary for the proper treatment of radical–molecule interactions to our previously developed unrestricted Absolutely Localized Molecular Orbital (uALMO)-EDA based on density functional theory calculations. A “polarize-then-depolarize” (PtD) scheme is used to remove arbitrariness in the definition of the frozen wavefunction, rendering the ALMO-EDA results independent of the orientation of the unpaired electron obtained from isolated fragment calculations. The contribution of radical rehybridization to polarization energies is evaluated. It is also valuable to monitor the wavefunction stability of each intermediate state, as well as their associated spin density profiles, to ensure the EDA results correspond to a desired electronic state. The examples suggest that this second generation uALMO-EDA is a useful tool for furthering one's understanding of both energetic and property changes associated with radical–molecule interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local electronic structure of histidine in aqueous solution

Here, the local electronic structure of aqueous histidine, an amino acid important in nature and biology, is revealed by aerosol X-ray photoemission spectroscopy. A detailed picture of the photoionization dynamics emerges by tuning the pH of the aqueous solution from which the aerosols are generated, allowing us to report the X-ray photoelectron spectroscopy (XPS) of histidine. Assignment of the experimental photoelectron spectra of the C1s and N1s levels allows the determination of the protonation state of histidine in these aqueous aerosols and is confirmed by density functional calculations. XPS spectra show that at pH = 1, both imidazole and amine group nitrogens are protonated, at pH = 7, the amine group nitrogen is protonated and the carboxyl group carbon is deprotonated resulting in a zwitterionic structure, and at pH = 13, only the carboxyl group remains deprotonated. Comparison of these results with previous experimental and theoretical results suggests that X-ray spectroscopy on aqueous aerosols can provide a convenient and simple way of probing their electronic structure in aqueous solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗