661 research outputs found
Hypergraph Acyclicity and Propositional Model Counting
We show that the propositional model counting problem #SAT for CNF- formulas
with hypergraphs that allow a disjoint branches decomposition can be solved in
polynomial time. We show that this class of hypergraphs is incomparable to
hypergraphs of bounded incidence cliquewidth which were the biggest class of
hypergraphs for which #SAT was known to be solvable in polynomial time so far.
Furthermore, we present a polynomial time algorithm that computes a disjoint
branches decomposition of a given hypergraph if it exists and rejects
otherwise. Finally, we show that some slight extensions of the class of
hypergraphs with disjoint branches decompositions lead to intractable #SAT,
leaving open how to generalize the counting result of this paper
Parameterized Compilation Lower Bounds for Restricted CNF-formulas
We show unconditional parameterized lower bounds in the area of knowledge
compilation, more specifically on the size of circuits in decomposable negation
normal form (DNNF) that encode CNF-formulas restricted by several graph width
measures. In particular, we show that
- there are CNF formulas of size and modular incidence treewidth
whose smallest DNNF-encoding has size , and
- there are CNF formulas of size and incidence neighborhood diversity
whose smallest DNNF-encoding has size .
These results complement recent upper bounds for compiling CNF into DNNF and
strengthen---quantitatively and qualitatively---known conditional low\-er
bounds for cliquewidth. Moreover, they show that, unlike for many graph
problems, the parameters considered here behave significantly differently from
treewidth
The Range of Topological Effects on Communication
We continue the study of communication cost of computing functions when
inputs are distributed among processors, each of which is located at one
vertex of a network/graph called a terminal. Every other node of the network
also has a processor, with no input. The communication is point-to-point and
the cost is the total number of bits exchanged by the protocol, in the worst
case, on all edges.
Chattopadhyay, Radhakrishnan and Rudra (FOCS'14) recently initiated a study
of the effect of topology of the network on the total communication cost using
tools from embeddings. Their techniques provided tight bounds for simple
functions like Element-Distinctness (ED), which depend on the 1-median of the
graph. This work addresses two other kinds of natural functions. We show that
for a large class of natural functions like Set-Disjointness the communication
cost is essentially times the cost of the optimal Steiner tree connecting
the terminals. Further, we show for natural composed functions like and , the naive protocols
suggested by their definition is optimal for general networks. Interestingly,
the bounds for these functions depend on more involved topological parameters
that are a combination of Steiner tree and 1-median costs.
To obtain our results, we use some new tools in addition to ones used in
Chattopadhyay et. al. These include (i) viewing the communication constraints
via a linear program; (ii) using tools from the theory of tree embeddings to
prove topology sensitive direct sum results that handle the case of composed
functions and (iii) representing the communication constraints of certain
problems as a family of collection of multiway cuts, where each multiway cut
simulates the hardness of computing the function on the star topology
Physics-informed Gaussian Process for Online Optimization of Particle Accelerators
High-dimensional optimization is a critical challenge for operating
large-scale scientific facilities. We apply a physics-informed Gaussian process
(GP) optimizer to tune a complex system by conducting efficient global search.
Typical GP models learn from past observations to make predictions, but this
reduces their applicability to new systems where archive data is not available.
Instead, here we use a fast approximate model from physics simulations to
design the GP model. The GP is then employed to make inferences from sequential
online observations in order to optimize the system. Simulation and
experimental studies were carried out to demonstrate the method for online
control of a storage ring. We show that the physics-informed GP outperforms
current routinely used online optimizers in terms of convergence speed, and
robustness on this task. The ability to inform the machine-learning model with
physics may have wide applications in science
Enhanced ultrafast X-ray diffraction by transient resonances
Diffraction-before-destruction imaging with single ultrashort X-ray pulses
has the potential to visualise non-equilibrium processes, such as chemical
reactions, at the nanoscale with sub-femtosecond resolution in the native
environment without the need of crystallization. Here, a nanospecimen partially
diffracts a single X-ray flash before sample damage occurs. The structural
information of the sample can be reconstructed from the coherent X-ray
interference image. State-of-art spatial resolution of such snapshots from
individual heavy element nanoparticles is limited to a few nanometers. Further
improvement of spatial resolution requires higher image brightness which is
ultimately limited by bleaching effects of the sample. We compared snapshots
from individual 100 nm Xe nanoparticles as a function of the X-ray pulse
duration and incoming X-ray intensity in the vicinity of the Xe M-shell
resonance. Surprisingly, images recorded with few femtosecond and
sub-femtosecond pulses are up to 10 times brighter than the static linear model
predicts. Our Monte-Carlo simulation and statistical analysis of the entire
data set confirms these findings and attributes the effect to transient
resonances. Our simulation suggests that ultrafast form factor changes during
the exposure can increase the brightness of X-ray images by several orders of
magnitude. Our study guides the way towards imaging with unprecedented
combination of spatial and temporal resolution at the nanoscale
Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV
A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay
channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7
TeV is presented. The data were collected at the LHC, with the CMS detector,
and correspond to an integrated luminosity of 4.6 inverse femtobarns. No
significant excess is observed above the background expectation, and upper
limits are set on the Higgs boson production cross section. The presence of the
standard model Higgs boson with a mass in the 270-440 GeV range is excluded at
95% confidence level.Comment: Submitted to JHE
Combined search for the quarks of a sequential fourth generation
Results are presented from a search for a fourth generation of quarks
produced singly or in pairs in a data set corresponding to an integrated
luminosity of 5 inverse femtobarns recorded by the CMS experiment at the LHC in
2011. A novel strategy has been developed for a combined search for quarks of
the up and down type in decay channels with at least one isolated muon or
electron. Limits on the mass of the fourth-generation quarks and the relevant
Cabibbo-Kobayashi-Maskawa matrix elements are derived in the context of a
simple extension of the standard model with a sequential fourth generation of
fermions. The existence of mass-degenerate fourth-generation quarks with masses
below 685 GeV is excluded at 95% confidence level for minimal off-diagonal
mixing between the third- and the fourth-generation quarks. With a mass
difference of 25 GeV between the quark masses, the obtained limit on the masses
of the fourth-generation quarks shifts by about +/- 20 GeV. These results
significantly reduce the allowed parameter space for a fourth generation of
fermions.Comment: Replaced with published version. Added journal reference and DO
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