A Machian Model of Dark Energy

Einstein believed that Mach's principle should play a major role in finding a meaningful spacetime geometry, though it was discovered later that his field equations gave some solutions which were not Machian. It is shown, in this essay, that the kinematical $\Lambda$ models, which are invoked to solve the cosmological constant problem, are in fact consistent with Mach's ideas. One particular model in this category is described which results from the microstructure of spacetime and seems to explain the current observations successfully and also has some benefits over the conventional models. This forces one to think whether the Mach's ideas and the cosmological constant are interrelated in some way.Comment: Received an Honorable mention in the Essay Contest-2002 sponsored by the Gravity Research Foundation; A paragraph added on how the model can explain the CMB anisotropy observations; To appear in the Classical and Quantum Gravit

On the Relativistic Formulation of Matter

A critical analysis of the relativistic formulation of matter reveals some surprising inconsistencies and paradoxes. Corrections are discovered which lead to the long-sought-after equality of the gravitational and inertial masses, which are otherwise different in general relativity. Realizing the potentially great impact of the discovered corrections, an overview of the situation is provided resulting from the newly discovered crisis, amid the evidences defending the theory.Comment: In press with Astrophys. Space Sci. (The final publication can be seen at springerlink.com

Non-monotonic diffusion rates in atom-optics L\'{e}vy kicked rotor

The dynamics of chaotic Hamiltonian systems such as the kicked rotor continues to guide our understanding of transport and localization processes. The localized states of the quantum kicked rotor decay due to decoherence effects if subjected to stationary noise. The associated quantum diffusion increases monotonically as a function of a parameter characterising the noise distribution. In this work, for the Levy kicked atom-optics rotor, it is experimentally shown that by tuning a parameter characterizing the Levy distribution, quantum diffusion displays non-monotonic behaviour. The parameters for optimal diffusion rates are analytically obtained and they reveal a good agreement with the cold atom experiments and numerics. The non-monotonicity is shown to be a quantum effect that vanishes in the classical limit.Comment: 5 pages, revte

Modeling Repulsive Gravity with Creation

There is a growing interest in the cosmologists for theories with negative energy scalar fields and creation, in order to model a repulsive gravity. The classical steady state cosmology proposed by Bondi, Gold and Hoyle in 1948, was the first such theory which used a negative kinetic energy creation field to invoke creation of matter. We emphasize that creation plays very crucial role in cosmology and provides a natural explanation to the various explosive phenomena occurring in local (z<0.1) and extra galactic universe. We exemplify this point of view by considering the resurrected version of this theory - the quasi-steady state theory, which tries to relate creation events directly to the large scale dynamics of the universe and supplies more natural explanations of the observed phenomena. Although the theory predicts a decelerating universe at the present era, it explains successfully the recent SNe Ia observations (which require an accelerating universe in the standard cosmology), as we show in this paper by performing a Bayesian analysis of the data.Comment: The paper uses an old SNeIa dataset. With the new improved data, for example the updated gold sample (Riess et al, astro-ph/0611572), the fit improves considerably (\chi^2/DoF=197/180 and a probability of goodness-of-fit=18%

Morpho-biochemical characterization of Psidium species

Several Psidium species are available with many important traits, lack of intensive characterization limits their use in guava improvement. Therefore, the present study was carried out to characterize five wild Psidium species (P. molle, P. chinensis, P. guineense, P. cattleianum var. cattleianum and P. cattleianum var. lucidum) and two P. guajava genotypes (cv. ‘Arka Poorna’ and ‘H 12-5’), based on morphological and biochemical traits. Among morphological traits, fruit weight was ranged from 5.22 g (P. cattleianum var. cattleianum) to 225.14 g (‘H 12-5’), however, among biochemical traits, highest TSS (12.06 ºBrix) and total sugars (9.98%) were recorded in cv. ‘Arka Poorna’, while, lowest recorded in P. cattleianum var. lucidum. Highest ascorbic acid was recorded in P. chinensis (205.33 mg/100 g), whereas, lowest recorded in P. guineense (60.83 mg/100 g). A positive correlation was observed among wild Psidium species but none had correlation with P. guajava genotypes for quantitative traits

Sparsity-based autoencoders for denoising cluttered radar signatures

Narrowband and broadband indoor radar images significantly deteriorate in the presence of target-dependent and target-independent static and dynamic clutter arising from walls. A stacked and sparse denoising autoencoder (StackedSDAE) is proposed for mitigating the wall clutter in indoor radar images. The algorithm relies on the availability of clean images and the corresponding noisy images during training and requires no additional information regarding the wall characteristics. The algorithm is evaluated on simulated Doppler-time spectrograms and high-range resolution profiles generated for diverse radar frequencies and wall characteristics in around-the-corner radar (ACR) scenarios. Additional experiments are performed on range-enhanced frontal images generated from measurements gathered from a wideband radio frequency imaging sensor. The results from the experiments show that the StackedSDAE successfully reconstructs images that closely resemble those that would be obtained in free space conditions. Furthermore, the incorporation of sparsity and depth in the hidden layer representations within the autoencoder makes the algorithm more robust to low signal-to-noise ratio (SNR) and label mismatch between clean and corrupt data during training than the conventional single-layer DAE. For example, the denoised ACR signatures show a structural similarity above 0.75 to clean free space images at SNR of −10 dB and label mismatch error of 50%