Metastability in Spin-Polarized Fermi Gases

We study the role of particle transport and evaporation on the phase separation of an ultracold, spin-polarized atomic Fermi gas. We show that the previously observed deformation of the superfluid paired core is a result of evaporative depolarization of the superfluid due to a combination of enhanced evaporation at the center of the trap and the inhibition of spin transport at the normal-superfluid phase boundary. These factors contribute to a nonequilibrium jump in the chemical potentials at the phase boundary. Once formed, the deformed state is highly metastable, persisting for times of up to 2 s.Comment: 4 pages, 6 figure

Data/model integration for vertical mixing in the stable Arctic boundary layer

This is the final report of a short Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Data on atmospheric trace constituents and the vertical structure of stratus clouds from a 1996 expedition to the central Arctic reveal mechanisms of vertical mixing that have not been observed in mid-latitudes. Time series of the altitude and thickness of summer arctic stratus have been observed using an elastic backscatter lidar aboard an icebreaker. With the ship moored to the pack ice during 14 data collection stations and the lidar staring vertically, the time series represent advected cloud fields. The lidar data reveal a significant amount of vertical undulation in the clouds, strongly suggestive of traveling waves in the buoyantly damped atmosphere that predominates in the high Arctic. Concurrent observations of trace gases associated with the natural sulfur cycle (dimethyl sulfide, SO{sub 2}, NH{sub 3}, H{sub 2}O{sub 2}) and aerosols show evidence of vertical mixing events that coincide with a characteristic signature in the cloud field that may be called dropout or lift out. A segment of a cloud deck appears to be relocated from the otherwise quasicontinuous layer to another altitude a few hundred meters lower or higher. Atmospheric models have been applied to identify the mechanism that cause the dropout phenomenon and connect it dynamically to the surface layer mixing

Coordination of Mobile Mules via Facility Location Strategies

In this paper, we study the problem of wireless sensor network (WSN) maintenance using mobile entities called mules. The mules are deployed in the area of the WSN in such a way that would minimize the time it takes them to reach a failed sensor and fix it. The mules must constantly optimize their collective deployment to account for occupied mules. The objective is to define the optimal deployment and task allocation strategy for the mules, so that the sensors' downtime and the mules' traveling distance are minimized. Our solutions are inspired by research in the field of computational geometry and the design of our algorithms is based on state of the art approximation algorithms for the classical problem of facility location. Our empirical results demonstrate how cooperation enhances the team's performance, and indicate that a combination of k-Median based deployment with closest-available task allocation provides the best results in terms of minimizing the sensors' downtime but is inefficient in terms of the mules' travel distance. A k-Centroid based deployment produces good results in both criteria.Comment: 12 pages, 6 figures, conferenc

Evidence of strong stabilizing effects on the evolution of boreoeutherian (Mammalia) dental proportions.

The dentition is an extremely important organ in mammals with variation in timing and sequence of eruption, crown morphology, and tooth size enabling a range of behavioral, dietary, and functional adaptations across the class. Within this suite of variable mammalian dental phenotypes, relative sizes of teeth reflect variation in the underlying genetic and developmental mechanisms. Two ratios of postcanine tooth lengths capture the relative size of premolars to molars (premolar-molar module, PMM), and among the three molars (molar module component, MMC), and are known to be heritable, independent of body size, and to vary significantly across primates. Here, we explore how these dental traits vary across mammals more broadly, focusing on terrestrial taxa in the clade of Boreoeutheria (Euarchontoglires and Laurasiatheria). We measured the postcanine teeth of N = 1,523 boreoeutherian mammals spanning six orders, 14 families, 36 genera, and 49 species to test hypotheses about associations between dental proportions and phylogenetic relatedness, diet, and life history in mammals. Boreoeutherian postcanine dental proportions sampled in this study carry conserved phylogenetic signal and are not associated with variation in diet. The incorporation of paleontological data provides further evidence that dental proportions may be slower to change than is dietary specialization. These results have implications for our understanding of dental variation and dietary adaptation in mammals

Quantum Computation of Hydrogen Bond Dynamics and Vibrational Spectra

Calculating the observable properties of chemical systems is often classically intractable, and is widely viewed as a promising application of quantum information processing. This is because a full description of chemical behavior relies upon the complex interplay of quantum-mechanical electrons and nuclei, demanding an exponential scaling of computational resources with system size. While considerable progress has been made in mapping electronic-structure calculations to quantum hardware, these approaches are unsuitable for describing the quantum dynamics of nuclei, proton- and hydrogen-transfer processes, or the vibrational spectra of molecules. Here, we use the QSCOUT ion-trap quantum computer to determine the quantum dynamics and vibrational properties of a shared proton within a short-strong hydrogen-bonded system. For a range of initial states, we experimentally drive the ion-trap system to emulate the quantum trajectory of the shared proton wavepacket as it evolves along the potential surface generated by the nuclear frameworks and electronic structure. We then extract the characteristic vibrational frequencies for the shared proton motion to spectroscopic accuracy and determine all energy eigenvalues of the system Hamiltonian to > 99.9% fidelity. Our approach offers a new paradigm for studying the quantum chemical dynamics and vibrational spectra of molecules, and when combined with quantum algorithms for electronic structure, opens the possibility to describe the complete behavior of molecules using exclusively quantum computation techniques.Comment: 10 pages, 4 figure

Error mitigation, optimization, and extrapolation on a trapped ion testbed

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors around 1% per gate for two-qubit gates. These errors significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called Richardson extrapolation can reduce these errors without incurring a qubit overhead. We demonstrate and optimize this method on the Quantum Scientific Computing Open User Testbed (QSCOUT) trapped-ion device to solve an electronic structure problem. We explore different methods for integrating this error mitigation technique into the Variational Quantum Eigensolver (VQE) optimization algorithm for calculating the ground state of the HeH+ molecule at 0.8 Angstrom. We test two methods of scaling noise for extrapolation: time-stretching the two-qubit gates and inserting two-qubit gate identity operations into the ansatz circuit. We find the former fails to scale the noise on our particular hardware. Scaling our noise with global gate identity insertions and extrapolating only after a variational optimization routine, we achieve an absolute relative error of 0.363% +- 1.06 compared to the true ground state energy of HeH+. This corresponds to an absolute error of 0.01 +- 0.02 Hartree; outside chemical accuracy, but greatly improved over our non error mitigated estimate. We ultimately find that the efficacy of this error mitigation technique depends on choosing the right implementation for a given device architecture and sampling budget.Comment: 16 pages, 11 figure

How to Educate Entrepreneurs?

Entrepreneurship education has two purposes: To improve students’ entrepreneurial skills and to provide impetus to those suited to entrepreneurship while discouraging the rest. While entrepreneurship education helps students to make a vocational decision its effects may conflict for those not suited to entrepreneurship. This study shows that vocational and the skill formation effects of entrepreneurship education can be identified empirically by drawing on the Theory of Planned Behavior. This is embedded in a structural equation model which we estimate and test using a robust 2SLS estimator. We find that the attitudinal factors posited by the Theory of Planned Behavior are positively correlated with students’ entrepreneurial intentions. While conflicting effects of vocational and skill directed course content are observed in some individuals, overall these types of content are complements. This finding contradicts previous results in the literature. We reconcile the conflicting findings and discuss implications for the design of entrepreneurship courses

Revisiting the Local Scaling Hypothesis in Stably Stratified Atmospheric Boundary Layer Turbulence: an Integration of Field and Laboratory Measurements with Large-eddy Simulations

The `local scaling' hypothesis, first introduced by Nieuwstadt two decades ago, describes the turbulence structure of stable boundary layers in a very succinct way and is an integral part of numerous local closure-based numerical weather prediction models. However, the validity of this hypothesis under very stable conditions is a subject of on-going debate. In this work, we attempt to address this controversial issue by performing extensive analyses of turbulence data from several field campaigns, wind-tunnel experiments and large-eddy simulations. Wide range of stabilities, diverse field conditions and a comprehensive set of turbulence statistics make this study distinct

Quantum computing hardware in the cloud : should a computational chemist care?

Within the last decade much progress has been made in the experimental realization of quantum computing hardware based on a variety of physical systems. Rapid progress has been fuelled by the conviction that sufficiently powerful quantum machines will herald enormous computational advantages in many fields, including chemical research. A quantum computer capable of simulating the electronic structures of complex molecules would be a game changer for the design of new drugs and materials. Given the potential implications of this technology, there is a need within the chemistry community to keep abreast with the latest developments as well as becoming involved in experimentation with quantum prototypes. To facilitate this, here we review the types of quantum computing hardware that have been made available to the public through cloud services. We focus on three architectures, namely superconductors, trapped ions and semiconductors. For each one we summarize the basic physical operations, requirements and performance. We discuss to what extent each system has been used for molecular chemistry problems and highlight the most pressing hardware issues to be solved for a chemistry-relevant quantum advantage to eventually emerge

Preparation and Evaluation of Rice Bran-Modified Urea Formaldehyde as Environmental Friendly Wood Adhesive

In this study, defatted rice bran (RB) is used to prepare an environmentally friendly adhesive through chemical modifications. The RB is mixed with distilled water with ratios of 1:5 and 1:4 to prepare Type A and Type B adhesives, respectively having pH of 6, 8 and 10. Type A adhesive is prepared by treating RB with 1% potassium permanganate and 4% poly(vinyl alcohol), whereas Type B is formulated by adding 17.3% formaldehyde and 5.7% urea to RB. Viscosity, gel time, solid content, shear strength, Fourier transform infrared (FTIR) spectroscopy is carried out, and glass transition temperature (T-g), and activation energy (E-a) are determined to evaluate the performance of the adhesives. E-a data reveal that adhesives prepared at mild alkaline (pH 8) form long-chain polymers. Gel time is higher in the fabricated adhesives than that of the commercial urea formaldehyde (UF). FTIR data suggest that functional groups of the raw RB are chemically modified, which enhances the bondability of the adhesives. Shear strength data indicates that bonding strength increases with increasing pH. Similar results are also observed for physical and mechanical properties of fabricated particleboards with the adhesives. The results demonstrate that RB-based adhesives can be used as a potential alternative to currently used UF-based resin