72,894 research outputs found
Low-frequency method for magnetothermopower and Nernst effect measurements on single crystal samples at low temperatures and high magnetic fields
We describe an AC method for the measurement of the longitudinal (Sxx) and
transverse (Sxy, i.e. Nernst) thermopower of mm-size single crystal samples at
low temperatures (T30 T). A low-frequency (33
mHz) heating method is used to increase the resolution, and to determine the
temperature gradient reliably in high magnetic fields. Samples are mounted
between two thermal blocks which are heated by a sinusoidal frequency f0 with a
p/2 phase difference. The phase difference between two heater currents gives a
temperature gradient at 2f0. The corresponding thermopower and Nernst effect
signals are extracted by using a digital signal processing method due. An
important component of the method involves a superconducting link, YBa2Cu3O7+d
(YBCO), which is mounted in parallel with sample to remove the background
magnetothermopower of the lead wires. The method is demonstrated for the quasi
two-dimensional organic conductor a-(BEDT-TTF)2KHg(SCN)4, which exhibits a
complex, magnetic field dependent ground state above 22.5 T at low
temperatures.Comment: 11 pages, 6 figures, 15 reference
Symbol error rate analysis for M-QAM modulated physical-layer network coding with phase errors
Recent theoretical studies of physical-layer network coding (PNC) show much interest on high-level modulation, such as M-ary quadrature amplitude modulation (M-QAM), and most related works are based on the assumption of phase synchrony. The possible presence of synchronization error and channel estimation error highlight the demand of analyzing the symbol error rate (SER) performance of PNC under different phase errors. Assuming synchronization and a general constellation mapping method, which maps the superposed signal into a set of M coded symbols, in this paper, we analytically derive the SER for M-QAM modulated PNC under different phase errors. We obtain an approximation of SER for general M-QAM modulations, as well as exact SER for quadrature phase-shift keying (QPSK), i.e. 4-QAM. Afterwards, theoretical results are verified by Monte Carlo simulations. The results in this paper can be used as benchmarks for designing practical systems supporting PNC. © 2012 IEEE
Consistency test of general relativity from large scale structure of the Universe
We construct a consistency test of General Relativity (GR) on cosmological
scales. This test enables us to distinguish between the two alternatives to
explain the late-time accelerated expansion of the universe, that is, dark
energy models based on GR and modified gravity models without dark energy. We
derive the consistency relation in GR which is written only in terms of
observables - the Hubble parameter, the density perturbations, the peculiar
velocities and the lensing potential. The breakdown of this consistency
relation implies that the Newton constant which governs large-scale structure
is different from that in the background cosmology, which is a typical feature
in modified gravity models. We propose a method to perform this test by
reconstructing the weak lensing spectrum from measured density perturbations
and peculiar velocities. This reconstruction relies on Poisson's equation in GR
to convert the density perturbations to the lensing potential. Hence any
inconsistency between the reconstructed lensing spectrum and the measured
lensing spectrum indicates the failure of GR on cosmological scales. The
difficulties in performing this test using actual observations are discussed.Comment: 7 pages, 1 figur
Fine-grained sketch-based image retrieval by matching deformable part models
(c) 2014. The copyright of this document resides with its authors.
It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors. An important characteristic of sketches, compared with text, rests with their ability to intrinsically capture object appearance and structure. Nonetheless, akin to traditional text-based image retrieval, conventional sketch-based image retrieval (SBIR) principally focuses on retrieving images of the same category, neglecting the fine-grained characteristics of sketches. In this paper, we advocate the expressiveness of sketches and examine their efficacy under a novel fine-grained SBIR framework. In particular, we study how sketches enable fine-grained retrieval within object categories. Key to this problem is introducing a mid-level sketch representation that not only captures object pose, but also possesses the ability to traverse sketch and image domains. Specifically, we learn deformable part-based model (DPM) as a mid-level representation to discover and encode the various poses in sketch and image domains independently, after which graph matching is performed on DPMs to establish pose correspondences across the two domains. We further propose an SBIR dataset that covers the unique aspects of fine-grained SBIR. Through in-depth experiments, we demonstrate the superior performance of our SBIR framework, and showcase its unique ability in fine-grained retrieval
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