291 research outputs found
Towards More Practical Linear Programming-based Techniques for Algorithmic Mechanism Design
R. Lavy and C. Swamy (FOCS 2005, J. ACM 2011) introduced a general method for
obtaining truthful-in-expectation mechanisms from linear programming based
approximation algorithms. Due to the use of the Ellipsoid method, a direct
implementation of the method is unlikely to be efficient in practice. We
propose to use the much simpler and usually faster multiplicative weights
update method instead. The simplification comes at the cost of slightly weaker
approximation and truthfulness guarantees
Quantum Separability and Entanglement Detection via Entanglement-Witness Search and Global Optimization
We focus on determining the separability of an unknown bipartite quantum
state by invoking a sufficiently large subset of all possible
entanglement witnesses given the expected value of each element of a set of
mutually orthogonal observables. We review the concept of an entanglement
witness from the geometrical point of view and use this geometry to show that
the set of separable states is not a polytope and to characterize the class of
entanglement witnesses (observables) that detect entangled states on opposite
sides of the set of separable states. All this serves to motivate a classical
algorithm which, given the expected values of a subset of an orthogonal basis
of observables of an otherwise unknown quantum state, searches for an
entanglement witness in the span of the subset of observables. The idea of such
an algorithm, which is an efficient reduction of the quantum separability
problem to a global optimization problem, was introduced in PRA 70 060303(R),
where it was shown to be an improvement on the naive approach for the quantum
separability problem (exhaustive search for a decomposition of the given state
into a convex combination of separable states). The last section of the paper
discusses in more generality such algorithms, which, in our case, assume a
subroutine that computes the global maximum of a real function of several
variables. Despite this, we anticipate that such algorithms will perform
sufficiently well on small instances that they will render a feasible test for
separability in some cases of interest (e.g. in 3-by-3 dimensional systems)
Disorder induced rounding of the phase transition in the large q-state Potts model
The phase transition in the q-state Potts model with homogeneous
ferromagnetic couplings is strongly first order for large q, while is rounded
in the presence of quenched disorder. Here we study this phenomenon on
different two-dimensional lattices by using the fact that the partition
function of the model is dominated by a single diagram of the high-temperature
expansion, which is calculated by an efficient combinatorial optimization
algorithm. For a given finite sample with discrete randomness the free energy
is a pice-wise linear function of the temperature, which is rounded after
averaging, however the discontinuity of the internal energy at the transition
point (i.e. the latent heat) stays finite even in the thermodynamic limit. For
a continuous disorder, instead, the latent heat vanishes. At the phase
transition point the dominant diagram percolates and the total magnetic moment
is related to the size of the percolating cluster. Its fractal dimension is
found d_f=(5+\sqrt{5})/4 and it is independent of the type of the lattice and
the form of disorder. We argue that the critical behavior is exclusively
determined by disorder and the corresponding fixed point is the isotropic
version of the so called infinite randomness fixed point, which is realized in
random quantum spin chains. From this mapping we conjecture the values of the
critical exponents as \beta=2-d_f, \beta_s=1/2 and \nu=1.Comment: 12 pages, 12 figures, version as publishe
Testing Consumer Rationality using Perfect Graphs and Oriented Discs
Given a consumer data-set, the axioms of revealed preference proffer a binary
test for rational behaviour. A natural (non-binary) measure of the degree of
rationality exhibited by the consumer is the minimum number of data points
whose removal induces a rationalisable data-set.We study the computational
complexity of the resultant consumer rationality problem in this paper. This
problem is, in the worst case, equivalent (in terms of approximation) to the
directed feedback vertex set problem. Our main result is to obtain an exact
threshold on the number of commodities that separates easy cases and hard
cases. Specifically, for two-commodity markets the consumer rationality problem
is polynomial time solvable; we prove this via a reduction to the vertex cover
problem on perfect graphs. For three-commodity markets, however, the problem is
NP-complete; we prove thisusing a reduction from planar 3-SAT that is based
upon oriented-disc drawings
Approximating Tverberg Points in Linear Time for Any Fixed Dimension
Let P be a d-dimensional n-point set. A Tverberg-partition of P is a
partition of P into r sets P_1, ..., P_r such that the convex hulls conv(P_1),
..., conv(P_r) have non-empty intersection. A point in the intersection of the
conv(P_i)'s is called a Tverberg point of depth r for P. A classic result by
Tverberg implies that there always exists a Tverberg partition of size n/(d+1),
but it is not known how to find such a partition in polynomial time. Therefore,
approximate solutions are of interest.
We describe a deterministic algorithm that finds a Tverberg partition of size
n/4(d+1)^3 in time d^{O(log d)} n. This means that for every fixed dimension we
can compute an approximate Tverberg point (and hence also an approximate
centerpoint) in linear time. Our algorithm is obtained by combining a novel
lifting approach with a recent result by Miller and Sheehy (2010).Comment: 14 pages, 2 figures. A preliminary version appeared in SoCG 2012.
This version removes an incorrect example at the end of Section 3.
Complexity of Strong Implementability
We consider the question of implementability of a social choice function in a
classical setting where the preferences of finitely many selfish individuals
with private information have to be aggregated towards a social choice. This is
one of the central questions in mechanism design. If the concept of weak
implementation is considered, the Revelation Principle states that one can
restrict attention to truthful implementations and direct revelation
mechanisms, which implies that implementability of a social choice function is
easy to check. For the concept of strong implementation, however, the
Revelation Principle becomes invalid, and the complexity of deciding whether a
given social choice function is strongly implementable has been open so far. In
this paper, we show by using methods from polyhedral theory that strong
implementability of a social choice function can be decided in polynomial space
and that each of the payments needed for strong implementation can always be
chosen to be of polynomial encoding length. Moreover, we show that strong
implementability of a social choice function involving only a single selfish
individual can be decided in polynomial time via linear programming
Mirror-Descent Methods in Mixed-Integer Convex Optimization
In this paper, we address the problem of minimizing a convex function f over
a convex set, with the extra constraint that some variables must be integer.
This problem, even when f is a piecewise linear function, is NP-hard. We study
an algorithmic approach to this problem, postponing its hardness to the
realization of an oracle. If this oracle can be realized in polynomial time,
then the problem can be solved in polynomial time as well. For problems with
two integer variables, we show that the oracle can be implemented efficiently,
that is, in O(ln(B)) approximate minimizations of f over the continuous
variables, where B is a known bound on the absolute value of the integer
variables.Our algorithm can be adapted to find the second best point of a
purely integer convex optimization problem in two dimensions, and more
generally its k-th best point. This observation allows us to formulate a
finite-time algorithm for mixed-integer convex optimization
Some families of density matrices for which separability is easily tested
We reconsider density matrices of graphs as defined in [quant-ph/0406165].
The density matrix of a graph is the combinatorial laplacian of the graph
normalized to have unit trace. We describe a simple combinatorial condition
(the "degree condition") to test separability of density matrices of graphs.
The condition is directly related to the PPT-criterion. We prove that the
degree condition is necessary for separability and we conjecture that it is
also sufficient. We prove special cases of the conjecture involving nearest
point graphs and perfect matchings. We observe that the degree condition
appears to have value beyond density matrices of graphs. In fact, we point out
that circulant density matrices and other matrices constructed from groups
always satisfy the condition and indeed are separable with respect to any
split. The paper isolates a number of problems and delineates further
generalizations.Comment: 14 pages, 4 figure
Performance of distributed mechanisms for flow admission in wireless adhoc networks
Given a wireless network where some pairs of communication links interfere
with each other, we study sufficient conditions for determining whether a given
set of minimum bandwidth quality-of-service (QoS) requirements can be
satisfied. We are especially interested in algorithms which have low
communication overhead and low processing complexity. The interference in the
network is modeled using a conflict graph whose vertices correspond to the
communication links in the network. Two links are adjacent in this graph if and
only if they interfere with each other due to being in the same vicinity and
hence cannot be simultaneously active. The problem of scheduling the
transmission of the various links is then essentially a fractional, weighted
vertex coloring problem, for which upper bounds on the fractional chromatic
number are sought using only localized information. We recall some distributed
algorithms for this problem, and then assess their worst-case performance. Our
results on this fundamental problem imply that for some well known classes of
networks and interference models, the performance of these distributed
algorithms is within a bounded factor away from that of an optimal, centralized
algorithm. The performance bounds are simple expressions in terms of graph
invariants. It is seen that the induced star number of a network plays an
important role in the design and performance of such networks.Comment: 21 pages, submitted. Journal version of arXiv:0906.378
Complete hierarchies of efficient approximations to problems in entanglement theory
We investigate several problems in entanglement theory from the perspective
of convex optimization. This list of problems comprises (A) the decision
whether a state is multi-party entangled, (B) the minimization of expectation
values of entanglement witnesses with respect to pure product states, (C) the
closely related evaluation of the geometric measure of entanglement to quantify
pure multi-party entanglement, (D) the test whether states are multi-party
entangled on the basis of witnesses based on second moments and on the basis of
linear entropic criteria, and (E) the evaluation of instances of maximal output
purities of quantum channels. We show that these problems can be formulated as
certain optimization problems: as polynomially constrained problems employing
polynomials of degree three or less. We then apply very recently established
known methods from the theory of semi-definite relaxations to the formulated
optimization problems. By this construction we arrive at a hierarchy of
efficiently solvable approximations to the solution, approximating the exact
solution as closely as desired, in a way that is asymptotically complete. For
example, this results in a hierarchy of novel, efficiently decidable sufficient
criteria for multi-particle entanglement, such that every entangled state will
necessarily be detected in some step of the hierarchy. Finally, we present
numerical examples to demonstrate the practical accessibility of this approach.Comment: 14 pages, 3 figures, tiny modifications, version to be published in
Physical Review
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