2,403 research outputs found
Exact variational dynamics of the multimode Bose-Hubbard model based on SU(M) coherent states
We propose a variational approach to the dynamics of the Bose-Hubbard model beyond the mean-field approximation. To develop a numerical scheme, we use a discrete overcomplete set of Glauber coherent states and its connection to the generalized coherent states studied in depth by Perelomov [Perelomov, Generalized Coherent States and Their Applications (Springer-Verlag, Berlin, 1986)]. The variational equations of motion of the generalized coherent state parameters as well as of the coefficients in an expansion of the wave function in terms of those states are derived and solved for many-particle problems with large particle numbers S and increasing mode number M. For M = 6, it is revealed that the number of complex-valued parameters that have to be propagated is more than one order of magnitude less than in an expansion in terms of Fock states
Comprehensive structural model of the mechanochemical cycle of a mitotic motor highlights molecular adaptations in the kinesin family
Kinesins are responsible for a wide variety of microtubule-based, ATP-dependent
functions. Their motor domain drives these activities but the molecular adaptations
that specify these diverse and essential cellular activities are poorly understood. It
has been assumed that the first identified kinesin - the transport motor kinesin-1 – is
the mechanistic paradigm for the entire superfamily, but accumulating evidence
suggests that this is not the case. To address the deficits in our understanding of the
molecular basis of functional divergence within the kinesin superfamily, we studied
kinesin-5s, which are essential mitotic motors whose inhibition blocks cell division.
Using cryo-electron microscopy and subnanometer resolution structure
determination, we have visualised conformations of microtubule-bound human
kinesin-5 motor domain at successive steps in its ATPase cycle. Following ATP
hydrolysis, nucleotide-dependent conformational changes in the active site are
allosterically propagated into rotations of the motor domain and uncurling of the drugbinding
loop L5. In addition, the mechanical neck-linker element that is crucial for
motor stepping undergoes discrete, ordered displacements. We also observed large
reorientations of the motor N-terminus that indicate its importance for kinesin-5
function through control of neck-linker conformation. A kinesin-5 mutant lacking this
N-terminus is enzymatically active, and ATP-dependent neck-linker movement and
motility is defective although not ablated. All these aspects of kinesin-5
mechanochemistry are distinct from kinesin-1. Our findings directly demonstrate the
regulatory role of the kinesin-5 N-terminus in collaboration with the motor’s structured
neck-linker, and highlight the multiple adaptations within kinesin motor domains that
tune their mechanochemistries according to distinct functional requirements
Maximum Resilience of Artificial Neural Networks
The deployment of Artificial Neural Networks (ANNs) in safety-critical
applications poses a number of new verification and certification challenges.
In particular, for ANN-enabled self-driving vehicles it is important to
establish properties about the resilience of ANNs to noisy or even maliciously
manipulated sensory input. We are addressing these challenges by defining
resilience properties of ANN-based classifiers as the maximal amount of input
or sensor perturbation which is still tolerated. This problem of computing
maximal perturbation bounds for ANNs is then reduced to solving mixed integer
optimization problems (MIP). A number of MIP encoding heuristics are developed
for drastically reducing MIP-solver runtimes, and using parallelization of
MIP-solvers results in an almost linear speed-up in the number (up to a certain
limit) of computing cores in our experiments. We demonstrate the effectiveness
and scalability of our approach by means of computing maximal resilience bounds
for a number of ANN benchmark sets ranging from typical image recognition
scenarios to the autonomous maneuvering of robots.Comment: Timestamp research work conducted in the project. version 2: fix some
typos, rephrase the definition, and add some more existing wor
Large electroweak penguin contribution in B -> K pi and pi pi decay modes
We discuss about a possibility of large electroweak penguin contribution in B
-> K pi and pi pi from recent experimental data. The experimental data may be
suggesting that there are some discrepancies between the data and theoretical
estimation in the branching ratios of them. In B -> K pi decays, to explain it,
a large electroweak penguin contribution and large strong phase differences
seem to be needed. The contributions should appear also in B -> pi pi. We show,
as an example, a solution to solve the discrepancies in both B -> K pi and B ->
pi pi. However the magnitude of the parameters and the strong phase estimated
from experimental data are quite large compared with the theoretical
estimations. It may be suggesting some new physics effects are including in
these processes. We will have to discuss about the dependence of the new
physics. To explain both modes at once, we may need large electroweak penguin
contribution with new weak phases and some SU(3) breaking effects by new
physics in both QCD and electroweak penguin type processes.Comment: 23 pages, 9 figure
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