Imaginary-time path integral (PI) is a rigorous tool to treat nuclear quantum effects in static properties. However, with its high computational demand, it is crucial to devise precise estimators. We introduce generalized PI estimators for the energy and heat capacity that utilize coordinate mapping. While it can reduce to the standard thermodynamic and centroid virial (CVir) estimators, the formulation can also take advantage of harmonic character of quantum oscillators and crystals to construct a coordinate mapping. This yields harmonically mapped averaging (HMA) estimators, with mappings that decouple (HMAc) or couple (HMAq) the centroid and internal modes. The HMAq is constructed with normal mode coordinates (HMAq-NM) with quadratic scaling of cost or harmonic oscillator staging (HMAq-SG) coordinates with linear scaling. The estimator performance is examined for a 1D anharmonic oscillator and a 3D Lennard-Jones crystal using path integral molecular dynamics (PIMD) simulation. The HMA estimators consistently provide more precise estimates compared to CVir, with the best performance obtained by HMAq-NM, followed by HMAq-SG, and then HMAc. We also examine the effect of anharmonici
In this paper, we investigate the dark matter halo density profile of M33. We find that the HI rotation curve of M33 is best described by a NFW dark matter halo density profile model, with a halo concentration of cvir = 4.0\pm1.0 and a virial mass of Mvir = (2.2\pm0.1)\times10^11 Msun. We go on to use the NFW concentration (cvir)of M33, along with the values derived for other galaxies (as found in the literature), to show that cvir correlates with both spiral arm pitch angle and supermassive black hole mass.
Cross-modal retrieval aims to measure the content similarity between different types of data. The idea has been previously applied to visual, text, and speech data. In this paper, we present a novel cross-modal retrieval method specifically for multi-view images, called Cross-view Image Retrieval CVIR. Our approach aims to find a feature space as well as an embedding space in which samples from street-view images are compared directly to satellite-view images (and vice-versa). For this comparison, a novel deep metric learning based solution "DeepCVIR" has been proposed. Previous cross-view image datasets are deficient in that they (1) lack class information; (2) were originally collected for cross-view image geolocalization task with coupled images; (3) do not include any images from off-street locations. To train, compare, and evaluate the performance of cross-view image retrieval, we present a new 6 class cross-view image dataset termed as CrossViewRet which comprises of images including freeway, mountain, palace, river, ship, and stadium with 700 high-resolution dual-view images for each class. Results show that the proposed DeepCVIR outperforms conventional matching approaches
On the basis of a new convergence study of high-resolution N-body simulations, my colleagues and I now agree that the Navarro, Frenk, & White (1996) density profile $ρ_{NFW}(r) \propto r^{-1} (r+r_s)^{-2}$ is a good representation of typical dark matter halos of galactic mass. Comparing simulations of the same halo with numbers of particles ranging from $\sim10^3$ to $\sim10^6$, we have also shown that $r_s$, the radius where the log-slope is -2, can be determined accurately for halos with as few as $\sim10^3$ particles. Based on a study of thousands of halos at many redshifts in an Adaptive Refinement Tree (ART) simulation of a cosmological volume in a $Λ$CDM cosmology, we have found that the concentration $\cvir \equiv \Rvir/\rs$ has a log-normal distribution, with $1σ$ $Δ(\log \cvir) = 0.18$ at a given mass, corresponding to a scatter in maximum rotation velocities of $Δ\Vmax/\Vmax = 0.12$. The average concentration declines with redshift at fixed mass as $\cvir(z) \propto (1+z)^{-1}$. This may have important implications for galaxy rotation curves. Finally, we have found that the velocity function determined from galaxy luminosity functions plus luminosity-velocity relation
We construct vertex operator representations for the full (N+1)-toroidal Lie algebra g. We associate with g a toroidal vertex operator algebra, which is a tensor product of an affine VOA, a sub-VOA of a hyperbolic lattice VOA, affine sl(N) VOA and a twisted Heisenberg-Virasoro VOA. The modules for the toroidal VOA are also modules for the toroidal Lie algebra g. We also construct irreducible modules for an important subalgebra gdiv of the toroidal Lie algebra that corresponds to the divergence free vector fields. This subalgebra carries a non-degenerate invariant bilinear form. The VOA that controls the representation theory of gdiv is a tensor product of an affine VOA Vaff(c) at level c, a sub-VOA of a hyperbolic lattice VOA, affine sl(N) VOA and a Virasoro VOA at level cvir with the following condition on the central charges: 2(N+1) + rank Vaff(c) + cvir = 26.
We present a strong lensing mass model of Abell 1689 which resolves substructures ~25 kpc across (including about ten individual galaxy subhalos) within the central ~400 kpc diameter. We achieve this resolution by perfectly reproducing the observed (strongly lensed) input positions of 168 multiple images of 55 knots residing within 135 images of 42 galaxies. Our model makes no assumptions about light tracing mass, yet we reproduce the brightest visible structures with some slight deviations. A1689 remains one of the strongest known lenses on the sky, with an Einstein radius of RE = 47.0" +/- 1.2" (143 +3/-4 kpc) for a lensed source at zs = 2. We find a single NFW or Sersic prole yields a good fit simultaneously (with only slight tension) to both our strong lensing (SL) mass model and published weak lensing (WL) measurements at larger radius (out to the virial radius). According to this NFW fit, A1689 has a mass of Mvir = 2.0 +0.5/-0.3 x 10^15 Msun / h70 (M200 = 1.8 +0.4/-0.3 x 10^15 Msun / h70) within the virial radius rvir = 3.0 +/- 0.2 Mpc / h70 (r200 = 2.4 +0.1/-0.2 Mpc / h70), and a central concentration cvir = 11.5 +1.5/-1.4 (c200 = 9.2 +/- 1.2). Our SL model prefers slightly
We present a stacked weak-lensing analysis of an approximately mass-selected sample of 50 galaxy clusters at 0.15<z<0.3, based on observations with Suprime-Cam on the Subaru Telescope. We develop a new method for selecting lensed background galaxies from which we estimate that our sample of red background galaxies suffers just 1% contamination. We detect the stacked tangential shear signal from the full sample of 50 clusters, based on this red sample of background galaxies, at a total signal-to-noise ratio of S/N=32.7. The Navarro-Frenk-White model is an excellent fit to the data, yielding sub-10% statistical precision on mass and concentration: Mvir=7.19^{+0.53}_{-0.50}\times10^{14}h^{-1}Msol, cvir=5.41^{+0.49}_{-0.45} (c_{200}=4.22^{+0.40}_{-0.36}). Tests of a range of possible systematic errors, including shear calibration and stacking-related issues, indicate that they are sub-dominant to the statistical errors. The concentration parameter obtained from stacking our approximately mass-selected cluster sample is broadly in line with theoretical predictions. Moreover, the uncertainty on our measurement is comparable with the differences between the different predictions in
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