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Register a new userLinear Dimensions of Adsorbed Semiflexible Polymers: What can be learned about their persistence length?
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Conformations of partially or fully adsorbed semiflexible polymer chains are studied varying both contour length $L$, chain stiffness, $kappa$, and the strength of the adsorption potential over a wide range. Molecular Dynamics simulations show that partially adsorbed chains (with tails, surface attached trains and loops) are not described by the Kratky-Porod wormlike chain model. The crossover of the persistence length from its three-dimensional value $(ell_p)$ to the enhanced value in two dimensions $(2ell_p)$ is analyzed, and excluded volume effects are identified for $L gg ell_p$. Consequences for the interpretation of experiments are suggested. We verify the prediction that the adsorption threshold scales as $ell_p^{-1/3}$.
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Using a recently developed bead-spring model for semiflexible polymers that takes into account their natural extensibility, we report an efficient algorithm to simulate the dynamics for polymers like double-stranded DNA (dsDNA) in the absence of hydrodynamic interactions. The dsDNA is modelled with one bead-spring element per basepair, and the polymer dynamics is described by the Langevin equation. The key to efficiency is that we describe the equations of motion for the polymer in terms of the amplitudes of the polymers fluctuation modes, as opposed to the use of the physical positions of the beads. We show that, within an accuracy tolerance level of $5%$ of several key observables, the model allows for single Langevin time steps of $approx1.6$, 8, 16 and 16 ps for a dsDNA model-chain consisting of 64, 128, 256 and 512 basepairs (i.e., chains of 0.55, 1.11, 2.24 and 4.48 persistence lengths) respectively. Correspondingly, in one hour, a standard desktop computer can simulate 0.23, 0.56, 0.56 and 0.26 ms of these dsDNA chains respectively. We compare our results to those obtained from other methods, in particular, the (inextensible discretised) WLC model. Importantly, we demonstrate that at the same level of discretisation, i.e., when each discretisation element is one basepair long, our algorithm gains about 5-6 orders of magnitude in the size of time steps over the inextensible WLC model. Further, we show that our model can be mapped one-on-one to a discretised version of the extensible WLC model; implying that the speed-up we achieve in our model must hold equally well for the latter. We also demonstrate the use of the method by simulating efficiently the tumbling behaviour of a dsDNA segment in a shear flow.
The thermodynamic and elastic properties of a flexible polymer in the presence of dipole interactions are studied via Monte Carlo simulations. The structural coil-globular, solid-globular, and solid-solid transitions are mapped in the hyperphase diagram, parameterized by the dipole concentration, $eta$, and temperature, $T$. Polymer flexibility is usually quantified by the persistent length, $ell_p$, which is defined as the length on which the bond-bond correlation is lost. Non-monotonic flexibility of polymeric complexes as a function of $eta$ has been interpreted as a cooperative effect under the Worm-Like Chain model. Instead of the usual exponential behavior, $langle Cleft(kright)ranglepropto e^{-k/ell_p}$, here we show that the bond-bond correlation follows a power law decay, $langle Cleft(kright)rangleapprox c_0k^{-omega}$. The power law regime holds even at the coil-globular transition, where a Gaussian limit is expected, originated from non-leading terms due to monomer-monomer connectivity. The exponent $omega$ monotonically converges to the mbox{SAW} limit for large $eta$, if the isotherm pathway is constructed at the coil phase. The deviation from ideality in better probed at the chain segment size, and the expected $Theta-$condition at the $(T,eta)$ pathway near the coil-globular transition is not observed.
Fine structure of giant resonances (GR) has been established in recent years as a global phenomenon across the nuclear chart and for different types of resonances. A quantitative description of the fine structure in terms of characteristic scales derived by wavelet techniques is discussed. By comparison with microscpic calculations of GR strength distributions one can extract information on the role of different decay mechanisms contributing to the width of GRs. The observed cross-section fluctuations contain information on the level density (LD) of states with a given spin and parity defined by the multipolarity of the GR.
Numerous models for grounded language understanding have been recently proposed, including (i) generic models that can be easily adapted to any given task and (ii) intuitively appealing modular models that require background knowledge to be instantiated. We compare both types of models in how much they lend themselves to a particular form of systematic generalization. Using a synthetic VQA test, we evaluate which models are capable of reasoning about all possible object pairs after training on only a small subset of them. Our findings show that the generalization of modular models is much more systematic and that it is highly sensitive to the module layout, i.e. to how exactly the modules are connected. We furthermore investigate if modular models that generalize well could be made more end-to-end by learning their layout and parametrization. We find that end-to-end methods from prior work often learn inappropriate layouts or parametrizations that do not facilitate systematic generalization. Our results suggest that, in addition to modularity, systematic generalization in language understanding may require explicit regularizers or priors.
This year marks the thirtieth anniversary of the only supernova from which we have detected neutrinos - SN 1987A. The twenty or so neutrinos that were detected were mined to great depth in order to determine the events that occurred in the explosion and to place limits upon all manner of neutrino properties. Since 1987 the scale and sensitivity of the detectors capable of identifying neutrinos from a Galactic supernova have grown considerably so that current generation detectors are capable of detecting of order ten thousand neutrinos for a supernova at the Galactic Center. Next generation detectors will increase that yield by another order of magnitude. Simultaneous with the growth of neutrino detection capability, our understanding of how massive stars explode and how the neutrino interacts with hot and dense matter has also increased by a tremendous degree. The neutrino signal will contain much information on all manner of physics of interest to a wide community. In this review we describe the expected features of the neutrino signal, the detectors which will detect it, and the signatures one might try to look for in order to get at these physics.
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