6,546 research outputs found
Spatial search in a honeycomb network
The spatial search problem consists in minimizing the number of steps
required to find a given site in a network, under the restriction that only
oracle queries or translations to neighboring sites are allowed. In this paper,
a quantum algorithm for the spatial search problem on a honeycomb lattice with
sites and torus-like boundary conditions. The search algorithm is based on
a modified quantum walk on a hexagonal lattice and the general framework
proposed by Ambainis, Kempe and Rivosh is used to show that the time complexity
of this quantum search algorithm is .Comment: 10 pages, 2 figures; Minor typos corrected, one Reference added.
accepted in Math. Structures in Computer Science, special volume on Quantum
Computin
Observation of tunable exchange bias in SrYbRuO
The double perovskite compound, SrYbRuO, displays reversal in the
orientation of magnetic moments along with negative magnetization due to an
underlying magnetic compensation phenomenon. The exchange bias (EB) field below
the compensation temperature could be the usual negative or the positive
depending on the initial cooling field. This EB attribute has the potential of
getting tuned in a preselected manner, as the positive EB field is seen to
crossover from positive to negative value above .Comment: 4 Pages, 4 Figure
Spatial quantum search in a triangular network
The spatial search problem consists in minimizing the number of steps
required to find a given site in a network, under the restriction that only
oracle queries or translations to neighboring sites are allowed. We propose a
quantum algorithm for the spatial search problem on a triangular lattice with N
sites and torus-like boundary conditions. The proposed algortithm is a special
case of the general framework for abstract search proposed by Ambainis, Kempe
and Rivosh [AKR05] (AKR) and Tulsi [Tulsi08], applied to a triangular network.
The AKR-Tulsi formalism was employed to show that the time complexity of the
quantum search on the triangular lattice is O(sqrt(N logN)).Comment: 10 pages, 4 Postscript figures, uses sbc-template.sty, appeared in
Annals of WECIQ 2010, III Workshop of Quantum Computation and Quantum
Informatio
The quantum correlation between the selection of the problem and that of the solution sheds light on the mechanism of the quantum speed up
In classical problem solving, there is of course correlation between the
selection of the problem on the part of Bob (the problem setter) and that of
the solution on the part of Alice (the problem solver). In quantum problem
solving, this correlation becomes quantum. This means that Alice contributes to
selecting 50% of the information that specifies the problem. As the solution is
a function of the problem, this gives to Alice advanced knowledge of 50% of the
information that specifies the solution. Both the quadratic and exponential
speed ups are explained by the fact that quantum algorithms start from this
advanced knowledge.Comment: Earlier version submitted to QIP 2011. Further clarified section 1,
"Outline of the argument", submitted to Phys Rev A, 16 page
Nested quantum search and NP-complete problems
A quantum algorithm is known that solves an unstructured search problem in a
number of iterations of order , where is the dimension of the
search space, whereas any classical algorithm necessarily scales as . It
is shown here that an improved quantum search algorithm can be devised that
exploits the structure of a tree search problem by nesting this standard search
algorithm. The number of iterations required to find the solution of an average
instance of a constraint satisfaction problem scales as , with
a constant depending on the nesting depth and the problem
considered. When applying a single nesting level to a problem with constraints
of size 2 such as the graph coloring problem, this constant is
estimated to be around 0.62 for average instances of maximum difficulty. This
corresponds to a square-root speedup over a classical nested search algorithm,
of which our presented algorithm is the quantum counterpart.Comment: 18 pages RevTeX, 3 Postscript figure
Policy Initiatives by the Government of India to Accelerate the Growth of Installed Nuclear Power Capacity in the Coming Years
AbstractWhen examined from the point of view of the size of its population and economy, India is not well endowed with energy resources. Studies done by the Department of Atomic Energy indicate that even after exploiting full potential of every available source of energy including nuclear energy, India needs to continue to import energy resources. In this backdrop, an initiative was launched by Government of India to open up international civil nuclear commerce so as to enable India to access natural uranium from international market and to set up nuclear reactors in technical cooperation with other countries. The paper provides details of what has been done so far, ongoing steps and likely growth scenario for nuclear installed capacity in the country
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