6,226 research outputs found
N=8 Supergravity on the Light Cone
We construct the generating functional for the light-cone superfield
amplitudes in a chiral momentum superspace. It generates the n-point particle
amplitudes which on shell are equivalent to the covariant ones. Based on the
action depending on unconstrained light-cone chiral scalar superfield, this
functional provides a regular d=4 QFT path integral derivation of the Nair-type
amplitude constructions.
By performing a Fourier transform into the light-cone chiral coordinate
superspace we find that the quantum corrections to the superfield amplitudes
with n legs are non-local in transverse directions for the diagrams with the
number of loops smaller than n(n-1)/2 +1. This suggests the reason why UV
infinities, which are proportional to local vertices, cannot appear at least
before 7 loops in the light-cone supergraph computations. By combining the E7
symmetry with the supersymmetric recursion relations we argue that the
light-cone supergraphs predict all loop finiteness of d=4 N=8 supergravity.Comment: 38
Strategic Decision Making and the Dynamics of Government Debt
National Debt;Deficit Spending;Welfare;Models
Optimisation of stochastic networks with blocking: a functional-form approach
This paper introduces a class of stochastic networks with blocking, motivated
by applications arising in cellular network planning, mobile cloud computing,
and spare parts supply chains. Blocking results in lost revenue due to
customers or jobs being permanently removed from the system. We are interested
in striking a balance between mitigating blocking by increasing service
capacity, and maintaining low costs for service capacity. This problem is
further complicated by the stochastic nature of the system. Owing to the
complexity of the system there are no analytical results available that
formulate and solve the relevant optimization problem in closed form.
Traditional simulation-based methods may work well for small instances, but the
associated computational costs are prohibitive for networks of realistic size.
We propose a hybrid functional-form based approach for finding the optimal
resource allocation, combining the speed of an analytical approach with the
accuracy of simulation-based optimisation. The key insight is to replace the
computationally expensive gradient estimation in simulation optimisation with a
closed-form analytical approximation that is calibrated using a single
simulation run. We develop two implementations of this approach and conduct
extensive computational experiments on complex examples to show that it is
capable of substantially improving system performance. We also provide evidence
that our approach has substantially lower computational costs compared to
stochastic approximation
Optimal Tradeoff Between Exposed and Hidden Nodes in Large Wireless Networks
Wireless networks equipped with the CSMA protocol are subject to collisions
due to interference. For a given interference range we investigate the tradeoff
between collisions (hidden nodes) and unused capacity (exposed nodes). We show
that the sensing range that maximizes throughput critically depends on the
activation rate of nodes. For infinite line networks, we prove the existence of
a threshold: When the activation rate is below this threshold the optimal
sensing range is small (to maximize spatial reuse). When the activation rate is
above the threshold the optimal sensing range is just large enough to preclude
all collisions. Simulations suggest that this threshold policy extends to more
complex linear and non-linear topologies
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