Use of ERTS-1 data to assess and monitor change in the Southern California environment

There are no author-identified significant results in this report

Isomeric Xylene Molecules in the Terahertz Far Infrared Regime Computational Chemistry and Spectral Modeling View

The theoretical assignments of spectral peaks of liquid phase ortho , meta , and para xylene recorded with far infrared FIR and THz spectroscopy in the spectral range between 550 and 50 cm amp; 8722;1 is done with density functional theory DFT calculations. As THz spectroscopic techniques drastically evolved in recent years, the critical focus of this paper lies on the applicability of theoretical concepts, used as computational standard in near and mid IR spectra, to the FIR THz region. An evaluation of the choice of functionals, basis sets, and appropriate scaling factors as well as the tractability of the liquid phase in a polarizable continuum model is performed. Alongside a new analysis procedure based on spectral Hard Modeling has been developed. DFT line spectra are fitted to experimental FIR spectra where a quantitative track record allows for meaningful comparisons. With all these tools we are able to reproduce experimental spectra in an optically appealing way and we can explain trends for each spectrum as well as across the row of the isomer

Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution

The accurate computation of Hamiltonian ground, excited and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared with their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analogue of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit

Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution

The accurate computation of Hamiltonian ground, excited, and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared to their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analog of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit.Comment: 18 pages, 7 figures; improved figures and tex

An efficient algorithm to calculate intrinsic thermoelectric parameters based on Landauer approach

The Landauer approach provides a conceptually simple way to calculate the intrinsic thermoelectric (TE) parameters of materials from the ballistic to the diffusive transport regime. This method relies on the calculation of the number of propagating modes and the scattering rate for each mode. The modes are calculated from the energy dispersion (E(k)) of the materials which require heavy computation and often supply energy relation on sparse momentum (k) grids. Here an efficient method to calculate the distribution of modes (DOM) from a given E(k) relationship is presented. The main features of this algorithm are, (i) its ability to work on sparse dispersion data, and (ii) creation of an energy grid for the DOM that is almost independent of the dispersion data therefore allowing for efficient and fast calculation of TE parameters. The inclusion of scattering effects is also straight forward. The effect of k-grid sparsity on the compute time for DOM and on the sensitivity of the calculated TE results are provided. The algorithm calculates the TE parameters within 5% accuracy when the K-grid sparsity is increased up to 60% for all the dimensions (3D, 2D and 1D). The time taken for the DOM calculation is strongly influenced by the transverse K density (K perpendicular to transport direction) but is almost independent of the transport K density (along the transport direction). The DOM and TE results from the algorithm are bench-marked with, (i) analytical calculations for parabolic bands, and (ii) realistic electronic and phonon results for $Bi_{2}Te_{3}$.Comment: 16 Figures, 3 Tables, submitted to Journal of Computational electronic

Thermoelectric properties of lead chalcogenide core-shell nanostructures

We present the full thermoelectric characterization of nanostructured bulk PbTe and PbTe-PbSe samples fabricated from colloidal core-shell nanoparticles followed by spark plasma sintering. An unusually large thermopower is found in both materials, and the possibility of energy filtering as opposed to grain boundary scattering as an explanation is discussed. A decreased Debye temperature and an increased molar specific heat are in accordance with recent predictions for nanostructured materials. On the basis of these results we propose suitable core-shell material combinations for future thermoelectric materials of large electric conductivities in combination with an increased thermopower by energy filtering.Comment: 12 pages, 8 figure

Simulation of dimensionality effects in thermal transport

The discovery of nanostructures and the development of growth and fabrication techniques of one- and two-dimensional materials provide the possibility to probe experimentally heat transport in low-dimensional systems. Nevertheless measuring the thermal conductivity of these systems is extremely challenging and subject to large uncertainties, thus hindering the chance for a direct comparison between experiments and statistical physics models. Atomistic simulations of realistic nanostructures provide the ideal bridge between abstract models and experiments. After briefly introducing the state of the art of heat transport measurement in nanostructures, and numerical techniques to simulate realistic systems at atomistic level, we review the contribution of lattice dynamics and molecular dynamics simulation to understanding nanoscale thermal transport in systems with reduced dimensionality. We focus on the effect of dimensionality in determining the phononic properties of carbon and semiconducting nanostructures, specifically considering the cases of carbon nanotubes, graphene and of silicon nanowires and ultra-thin membranes, underlying analogies and differences with abstract lattice models.Comment: 30 pages, 21 figures. Review paper, to appear in the Springer Lecture Notes in Physics volume "Thermal transport in low dimensions: from statistical physics to nanoscale heat transfer" (S. Lepri ed.