4,514 research outputs found

    Quantum computers can search rapidly by using almost any transformation

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    A quantum computer has a clear advantage over a classical computer for exhaustive search. The quantum mechanical algorithm for exhaustive search was originally derived by using subtle properties of a particular quantum mechanical operation called the Walsh-Hadamard (W-H) transform. This paper shows that this algorithm can be implemented by replacing the W-H transform by almost any quantum mechanical operation. This leads to several new applications where it improves the number of steps by a square-root. It also broadens the scope for implementation since it demonstrates quantum mechanical algorithms that can readily adapt to available technology.Comment: This paper is an adapted version of quant-ph/9711043. It has been modified to make it more readable for physicists. 9 pages, postscrip

    Grover's quantum searching algorithm is optimal

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    I improve the tight bound on quantum searching by Boyer et al. (quant-ph/9605034) to a matching bound, thus showing that for any probability of success Grovers quantum searching algorithm is optimal. E.g. for near certain success we have to query the oracle pi/4 sqrt{N} times, where N is the size of the search space. I also show that unfortunately quantum searching cannot be parallelized better than by assigning different parts of the search space to independent quantum computers. Earlier results left open the possibility of a more efficient parallelization.Comment: 13 pages, LaTeX, essentially published versio

    Realization of generalized quantum searching using nuclear magnetic resonance

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    According to the theoretical results, the quantum searching algorithm can be generalized by replacing the Walsh-Hadamard(W-H) transform by almost any quantum mechanical operation. We have implemented the generalized algorithm using nuclear magnetic resonance techniques with a solution of chloroform molecules. Experimental results show the good agreement between theory and experiment.Comment: 11 pages,3 figure. Accepted by Phys. Rev. A. Scheduled Issue: 01 Mar 200

    Alginate hydrogel has a negative impact on in vitro collagen 1 deposition by fibroblasts

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    Hydrogels have been widely investigated as 3D culture substrates because of their reported structural similarity to the extracellular matrix (ECM). Limited ECM deposition, however, occurs within these materials, so the resulting “tissues” bear little resemblance to those found in the body. Here matrix deposition by fibroblasts encapsulated within a calcium alginate (Ca-alg) hydrogel was investigated. Although the cells transcribed mRNA for coll Iα over a period of 3 weeks, very little collagen protein deposition was observed within the gel by histology or immunohistochemistry (IHC). Although molecular diffusion demonstrated charge dependency, this did not prevent the flux of both positively and negative charged amino acids through the gel, suggesting that the absence of ECM could not be attributed to substrate limitation. The flux of protein, however, was charge-dependent as proteins with a net negative charge passed quickly through the Ca-alg into the medium. The minimal collagen deposition within the Ca-alg was attributed to a combination of rapid movement of negatively charged procollagen through the gel and steric hindrance of fibril formation

    A General SU(2) Formulation for Quantum Searching with Certainty

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    A general quantum search algorithm with arbitrary unitary transformations and an arbitrary initial state is considered in this work. To serach a marked state with certainty, we have derived, using an SU(2) representation: (1) the matching condition relating the phase rotations in the algorithm, (2) a concise formula for evaluating the required number of iterations for the search, and (3) the final state after the search, with a phase angle in its amplitude of unity modulus. Moreover, the optimal choices and modifications of the phase angles in the Grover kernel is also studied.Comment: 8 pages, 2 figure

    Nested quantum search and NP-complete problems

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    A quantum algorithm is known that solves an unstructured search problem in a number of iterations of order d\sqrt{d}, where dd is the dimension of the search space, whereas any classical algorithm necessarily scales as O(d)O(d). 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 dα\sqrt{d^\alpha}, with a constant α<1\alpha<1 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 α\alpha 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

    A General Phase Matching Condition for Quantum Searching Algorithm

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    A general consideration on the phase rotations in quantum searching algorithm is taken in this work. As four phase rotations on the initial state, the marked states, and the states orthogonal to them are taken account, we deduce a phase matching condition for a successful search. The optimal options for these phase are obtained consequently.Comment: 3 pages, 3 figure

    A non-adiabatic approach to entanglement distribution over long distances

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    Entanglement distribution between trapped-atom quantum memories, viz. single atoms in optical cavities, is addressed. In most scenarios, the rate of entanglement distribution depends on the efficiency with which the state of traveling single photons can be transferred to trapped atoms. This loading efficiency is analytically studied for two-level, VV-level, Λ\Lambda-level, and double-Λ\Lambda-level atomic configurations by means of a system-reservoir approach. An off-resonant non-adiabatic approach to loading Λ\Lambda-level trapped-atom memories is proposed, and the ensuing trade-offs between the atom-light coupling rate and input photon bandwidth for achieving a high loading probability are identified. The non-adiabatic approach allows a broad class of optical sources to be used, and in some cases it provides a higher system throughput than what can be achieved by adiabatic loading mechanisms. The analysis is extended to the case of two double-Λ\Lambda trapped-atom memories illuminated by a polarization-entangled biphoton.Comment: 15 pages, 15 figure

    Quantum phase retrieval of a Rydberg wave packet using a half-cycle pulse

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    A terahertz half-cycle pulse was used to retrieve information stored as quantum phase in an NN-state Rydberg atom data register. The register was prepared as a wave packet with one state phase-reversed from the others (the "marked bit"). A half-cycle pulse then drove a significant portion of the electron probability into the flipped state via multimode interference.Comment: accepted by PR

    Fast Quantum Search Algorithms in Protein Sequence Comparison - Quantum Biocomputing

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    Quantum search algorithms are considered in the context of protein sequence comparison in biocomputing. Given a sample protein sequence of length m (i.e m residues), the problem considered is to find an optimal match in a large database containing N residues. Initially, Grover's quantum search algorithm is applied to a simple illustrative case - namely where the database forms a complete set of states over the 2^m basis states of a m qubit register, and thus is known to contain the exact sequence of interest. This example demonstrates explicitly the typical O(sqrt{N}) speedup on the classical O(N) requirements. An algorithm is then presented for the (more realistic) case where the database may contain repeat sequences, and may not necessarily contain an exact match to the sample sequence. In terms of minimizing the Hamming distance between the sample sequence and the database subsequences the algorithm finds an optimal alignment, in O(sqrt{N}) steps, by employing an extension of Grover's algorithm, due to Boyer, Brassard, Hoyer and Tapp for the case when the number of matches is not a priori known.Comment: LaTeX, 5 page
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