1,695 research outputs found
Gas permeation through a polymer network
We study the diffusion of gas molecules through a two-dimensional network of
polymers with the help of Monte Carlo simulations. The polymers are modeled as
non-interacting random walks on the bonds of a two-dimensional square lattice,
while the gas particles occupy the lattice cells. When a particle attempts to
jump to a nearest-neighbor empty cell, it has to overcome an energy barrier
which is determined by the number of polymer segments on the bond separating
the two cells. We investigate the gas current as a function of the mean
segment density , the polymer length and the probability
for hopping across segments. Whereas decreases monotonically with
for fixed , its behavior for fixed and increasing
depends strongly on . For small, non-zero , appears to increase
slowly with . In contrast, for , it is dominated by the underlying
percolation problem and can be non-monotonic. We provide heuristic arguments to
put these interesting phenomena into context.Comment: Dedicated to Lothar Schaefer on the occasion of his 60th birthday. 11
pages, 3 figure
Influence of system parameters on the hysteresis characteristics of a horizontal Rijke tube
The influence of system parameters such as heater power, heater location and mass flow rate on the hysteresis characteristics of a horizontal Rijke tube is presented in this paper. It is observed that a hysteresis zone is present for all the mass flow rates considered in the present study. A power law relation is established between the non-dimensional hysteresis width and the Strouhal number, defined as the ratio between convective time scale and acoustic time scale. The transition to instability in a horizontal Rijke tube is found to be subcritical in all the experiments performed in this study. When heater location is chosen as the control parameter, period-2 oscillations are found for specific values of mass flow rate and heater power
Frustration and glassiness in spin models with cavity-mediated interactions
We show that the effective spin-spin interaction between three-level atoms
confined in a multimode optical cavity is long-ranged and sign-changing, like
the RKKY interaction; therefore, ensembles of such atoms subject to frozen-in
positional randomness can realize spin systems having disordered and frustrated
interactions. We argue that, whenever the atoms couple to sufficiently many
cavity modes, the cavity-mediated interactions give rise to a spin glass. In
addition, we show that the quantum dynamics of cavity-confined spin systems is
that of a Bose-Hubbard model with strongly disordered hopping but no on-site
disorder; this model exhibits a random-singlet glass phase, absent in
conventional optical-lattice realizations. We briefly discuss experimental
signatures of the realizable phases.Comment: 5 pages, 2 figure
Genetic identity of Tormalabaricus(Jerdon)(Teleostei : Cyprinidae) as revealed by RAPD markers
Tor malabaricus (Jerdon) is a mahseer species endemic to the Western Ghats. Since its original description, taxonomic position of the species has been extremely confusing. In the present study, Random Amplified polymorphic DNA (RAPD) markers were used to determine the taxonomic status of T.malabaricus collected from Balamore River, Tamil Nadu, India, by comparing its RAPD profile with that of Tor khudreee.15 random oligodecamers were used to amplify DNA from Tor malabaricus and Tor khudree (n=30 each) collected from two geographically isolated localities and a total of 119 amphicons were detected
Interferometric probes of many-body localization
We propose a method for detecting many-body localization (MBL) in disordered
spin systems. The method involves pulsed, coherent spin manipulations that
probe the dephasing of a given spin due to its entanglement with a set of
distant spins. It allows one to distinguish the MBL phase from a
non-interacting localized phase and a delocalized phase. In particular, we show
that for a properly chosen pulse sequence the MBL phase exhibits a
characteristic power-law decay reflecting its slow growth of entanglement. We
find that this power-law decay is robust with respect to thermal and disorder
averaging, provide numerical simulations supporting our results, and discuss
possible experimental realizations in solid-state and cold atom systems.Comment: 5 pages, 4 figure
Spin-Electron-Phonon Excitation in Re-based Half-Metallic Double Perovskites
A remarkable hardening (~ 30 cm-1) of the normal mode of vibration associated
with the symmetric stretching of the oxygen octahedra for the Ba2FeReO6 and
Sr2CrReO6 double perovskites is observed below the corresponding magnetic
ordering temperatures. The very large magnitude of this effect and its absence
for the anti-symmetric stretching mode provide evidence against a conventional
spin-phonon coupling mechanism. Our observations are consistent with a
collective excitation formed by the combination of the vibrational mode with
oscillations of local Fe or Cr 3d and Re 5d occupations and spin magnitudes.Comment: 12 pages, 4 figure
Explainable AI Framework for COVID-19 Prediction in Different Provinces of India
In 2020, covid-19 virus had reached more than 200 countries. Till December
20th 2021, 221 nations in the world had collectively reported 275M confirmed
cases of covid-19 & total death toll of 5.37M. Many countries which include
United States, India, Brazil, United Kingdom, Russia etc were badly affected by
covid-19 pandemic due to the large population. The total confirmed cases
reported in this country are 51.7M, 34.7M, 22.2M, 11.3M, 10.2M respectively
till December 20, 2021. This pandemic can be controlled with the help of
precautionary steps by government & civilians of the country. The early
prediction of covid-19 cases helps to track the transmission dynamics & alert
the government to take the necessary precautions. Recurrent Deep learning
algorithms is a data driven model which plays a key role to capture the
patterns present in time series data. In many literatures, the Recurrent Neural
Network (RNN) based model are proposed for the efficient prediction of COVID-19
cases for different provinces. The study in the literature doesnt involve the
interpretation of the model behavior & robustness. In this study, The LSTM
model is proposed for the efficient prediction of active cases in each
provinces of India. The active cases dataset for each province in India is
taken from John Hopkins publicly available dataset for the duration from 10th
June, 2020 to 4th August, 2021. The proposed LSTM model is trained on one state
i.e., Maharashtra and tested for rest of the provinces in India. The concept of
Explainable AI is involved in this study for the better interpretation &
understanding of the model behavior. The proposed model is used to forecast the
active cases in India from 16th December, 2021 to 5th March, 2022. It is
notated that there will be a emergence of third wave on January, 2022 in India.Comment: 12 page
Atom-light crystallization of BECs in multimode cavities: Nonequilibrium classical and quantum phase transitions, emergent lattices, supersolidity, and frustration
The self-organization of a Bose-Einstein condensate in a transversely pumped
optical cavity is a process akin to crystallization: when pumped by a laser of
sufficient intensity, the coupled matter and light fields evolve,
spontaneously, into a spatially modulated pattern, or crystal, whose lattice
structure is dictated by the geometry of the cavity. In cavities having
multiple degenerate modes, the quasi-continuum of possible lattice
arrangements, and the continuous symmetry breaking associated with the adoption
of a particular lattice arrangement, give rise to phenomena such as phonons,
defects, and frustration, which have hitherto been unexplored in ultracold
atomic settings involving neutral atoms. The present work develops a
nonequilibrium field-theoretic approach to explore the self-organization of a
BEC in a pumped, lossy optical cavity. We find that the transition is well
described, in the regime of primary interest, by an effective equilibrium
theory. At nonzero temperatures, the self-organization occurs via a
fluctuation-driven first-order phase transition of the Brazovskii class; this
transition persists to zero temperature, and crosses over into a quantum phase
transition of a new universality class. We make further use of our
field-theoretic description to investigate the role of nonequilibrium
fluctuations on the self-organization transition, as well as to explore the
nucleation of ordered-phase droplets, the nature and energetics of topological
defects, supersolidity in the ordered phase, and the possibility of frustration
controlled by the cavity geometry. In addition, we discuss the range of
experimental parameters for which we expect the phenomena described here to be
observable, along with possible schemes for detecting ordering and fluctuations
via either atomic correlations or the correlations of the light emitted from
the cavity.Comment: 34 pages, 13 figures; follow up to Nat. Phys. 5, 845 (2009
emergent behavior in a coupled economic and coastline model for beach nourishment
Developed coastal areas often exhibit a strong systemic coupling between shoreline dynamics and economic dynamics. Beach nourishment , a common erosion-control practice, involves mechanically depositing sediment from outside the local littoral system onto an actively eroding shoreline to alter shoreline morphology. Natural sediment-transport processes quickly rework the newly engineered beach, causing further changes to the shoreline that in turn affect subsequent beach-nourishment decisions. To the limited extent that this landscape/economic coupling has been considered, evidence suggests that towns tend to employ spatially myopic economic strategies under which individual towns make isolated decisions that do not account for their neighbors. What happens when an optimization strategy that explicitly ignores spatial interactions is incorporated into a physical model that is spatially dynamic? The long-term attractor that develops for the coupled system (the state and behavior to which the system evolves over time) is unclear. We link an economic model, in which town-manager agents choose economically optimal beach-nourishment intervals according to past observations of their immediate shoreline, to a simplified coastal-dynamics model that includes alongshore sediment transport and background erosion (e.g. from sea-level rise). Simulations suggest that feedbacks between these human and natural coastal processes can generate emergent behaviors. When alongshore sediment transport and spatially myopic nourishment decisions are coupled, increases in the rate of sea-level rise can destabilize economically optimal nourishment practices into a regime characterized by the emergence of chaotic shoreline evolution
- …