2,959 research outputs found
Semidefinite programming characterization and spectral adversary method for quantum complexity with noncommuting unitary queries
Generalizing earlier work characterizing the quantum query complexity of
computing a function of an unknown classical ``black box'' function drawn from
some set of such black box functions, we investigate a more general quantum
query model in which the goal is to compute functions of N by N ``black box''
unitary matrices drawn from a set of such matrices, a problem with applications
to determining properties of quantum physical systems. We characterize the
existence of an algorithm for such a query problem, with given error and number
of queries, as equivalent to the feasibility of a certain set of semidefinite
programming constraints, or equivalently the infeasibility of a dual of these
constraints, which we construct. Relaxing the primal constraints to correspond
to mere pairwise near-orthogonality of the final states of a quantum computer,
conditional on black-box inputs having distinct function values, rather than
bounded-error determinability of the function value via a single measurement on
the output states, we obtain a relaxed primal program the feasibility of whose
dual still implies the nonexistence of a quantum algorithm. We use this to
obtain a generalization, to our not-necessarily-commutative setting, of the
``spectral adversary method'' for quantum query lower bounds.Comment: Dagstuhl Seminar Proceedings 06391, "Algorithms and Complexity for
Continuous Problems," ed. S. Dahlke, K. Ritter, I. H. Sloan, J. F. Traub
(2006), available electronically at
http://drops.dagstuhl.de/portals/index.php?semnr=0639
Fourier analysis on finite groups and the Lov\'asz theta-number of Cayley graphs
We apply Fourier analysis on finite groups to obtain simplified formulations
for the Lov\'asz theta-number of a Cayley graph. We put these formulations to
use by checking a few cases of a conjecture of Ellis, Friedgut, and Pilpel made
in a recent article proving a version of the Erd\H{o}s-Ko-Rado theorem for
-intersecting families of permutations. We also introduce a -analog of
the notion of -intersecting families of permutations, and we verify a few
cases of the corresponding Erd\H{o}s-Ko-Rado assertion by computer.Comment: 9 pages, 0 figure
Conic Optimization Theory: Convexification Techniques and Numerical Algorithms
Optimization is at the core of control theory and appears in several areas of
this field, such as optimal control, distributed control, system
identification, robust control, state estimation, model predictive control and
dynamic programming. The recent advances in various topics of modern
optimization have also been revamping the area of machine learning. Motivated
by the crucial role of optimization theory in the design, analysis, control and
operation of real-world systems, this tutorial paper offers a detailed overview
of some major advances in this area, namely conic optimization and its emerging
applications. First, we discuss the importance of conic optimization in
different areas. Then, we explain seminal results on the design of hierarchies
of convex relaxations for a wide range of nonconvex problems. Finally, we study
different numerical algorithms for large-scale conic optimization problems.Comment: 18 page
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