Quantum Computing in Molecular Magnets

Shor and Grover demonstrated that a quantum computer can outperform any classical computer in factoring numbers and in searching a database by exploiting the parallelism of quantum mechanics. Whereas Shor's algorithm requires both superposition and entanglement of a many-particle system, the superposition of single-particle quantum states is sufficient for Grover's algorithm. Recently, the latter has been successfully implemented using Rydberg atoms. Here we propose an implementation of Grover's algorithm that uses molecular magnets, which are solid-state systems with a large spin; their spin eigenstates make them natural candidates for single-particle systems. We show theoretically that molecular magnets can be used to build dense and efficient memory devices based on the Grover algorithm. In particular, one single crystal can serve as a storage unit of a dynamic random access memory device. Fast electron spin resonance pulses can be used to decode and read out stored numbers of up to 10^5, with access times as short as 10^{-10} seconds. We show that our proposal should be feasible using the molecular magnets Fe8 and Mn12.Comment: 13 pages, 2 figures, PDF, version published in Nature, typos correcte

DNA Computation Based Approach for Enhanced Computing Power

DNA computing is a discipline that aims at harnessing individual molecules at the nano-scopic level for computational purposes. Computation with DNA molecules possesses an inherent interest for researchers in computers and biology. Given its vast parallelism and high-density storage, DNA computing approaches are employed to solve many problems. DNA has also been explored as an excellent material and a fundamental building block for building large-scale nanostructures, constructing individual nano-mechanical devices, and performing computations. Molecular-scale autonomous programmable computers are demonstrated allowing both input and output information to be in molecular form. This paper presents a review of recent advancements in DNA computing and presents major achievements and challenges for researchers in the coming future

Quantum computing of molecular magnet Mn12_{12}

Quantum computation in molecular magnets is studied by solving the time-dependent Schr\"{o}dinger equation numerically. Following Leuenberger and Loss (Nature (London) 410, 789(2001)), an external oscillating magnetic field is applied to populate and manipulate the spin coherent states in molecular magnet Mn$_{12}$. The conditions to realize parallel recording and reading data bases of Grover algorithsm in molecular magnets are discussed in details. It is found that an accurate duration time of magnetic pulse as well as the amplitudes are required to design the device of quantum computing.Comment: 3 pages, 1 figur

Parallel computing and molecular dynamics of biological membranes

In this talk I discuss the general question of the portability of Molecular Dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision arithmetics of the today available APE platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on the possible programming strategies. Liquids can be very satisfactorily simulated using the "systolic" method. For more complex systems, like the biological ones at which we are ultimately interested in, the "domain decomposition" approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of elementary components of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed.Comment: 4 pages LaTeX, 2 figures included, espcrc2.sty require

Computing the local pressure in molecular dynamics simulations

Computer simulations of inhomogeneous soft matter systems often require accurate methods for computing the local pressure. We present a simple derivation, based on the virial relation, of two equivalent expressions for the local (atomistic) pressure in a molecular dynamics simulation. One of these expressions, previously derived by other authors via a different route, involves summation over interactions between particles within the region of interest; the other involves summation over interactions across the boundary of the region of interest. We illustrate our derivation using simulations of a simple osmotic system; both expressions produce accurate results even when the region of interest over which the pressure is measured is very small.Comment: 11 pages, 4 figure

Massively parallel computing on an organic molecular layer

Current computers operate at enormous speeds of ~10^13 bits/s, but their principle of sequential logic operation has remained unchanged since the 1950s. Though our brain is much slower on a per-neuron base (~10^3 firings/s), it is capable of remarkable decision-making based on the collective operations of millions of neurons at a time in ever-evolving neural circuitry. Here we use molecular switches to build an assembly where each molecule communicates-like neurons-with many neighbors simultaneously. The assembly's ability to reconfigure itself spontaneously for a new problem allows us to realize conventional computing constructs like logic gates and Voronoi decompositions, as well as to reproduce two natural phenomena: heat diffusion and the mutation of normal cells to cancer cells. This is a shift from the current static computing paradigm of serial bit-processing to a regime in which a large number of bits are processed in parallel in dynamically changing hardware.Comment: 25 pages, 6 figure