938 research outputs found

    The s-process branching at 185W

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    The neutron capture cross section of the unstable nucleus 185W has been derived from experimental photoactivation data of the inverse reaction 186W(gamma,n)185W. The new result of sigma = (687 +- 110) mbarn confirms the theoretically predicted neutron capture cross section of 185W of sigma = 700 mbarn at kT = 30 keV. A neutron density in the classical s-process of n_n = (3.8 +0.9 -0.8} * 1e8 cm-3 is derived from the new data for the 185W branching. In a stellar s-process model one finds a significant overproduction of the residual s-only nucleus 186Os.Comment: ApJ, in pres

    Stellar neutron capture cross sections of ⁴¹K and ⁴⁵Sc

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    The neutron capture cross sections of light nuclei (

    Stellar (n,γ) cross sections of ²³Na

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    The cross section of the ²³Na(n,γ)²⁴Na reaction has been measured via the activation method at the Karlsruhe 3.7 MV Van de Graaff accelerator. NaCl samples were exposed to quasistellar neutron spectra at kT = 5.1 and 25 keV produced via the ¹⁸O(p,n)¹⁸F and ⁷Li(p,n)⁷Be reactions, respectively. The derived capture cross sections (σ)kT=5keV = 9.1 ± 0.3mb and (σ)kT=25keV = 2.03 ± 0.05 mb are significantly lower than reported in literature. These results were used to substantially revise the radiative width of the first ²³Na resonance and to establish an improved set of Maxwellian average cross sections. The implications of the lower capture cross section for current models of s-process nucleosynthesis are discussed

    Exploring Network-Related Optimization Problems Using Quantum Heuristics

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    Network-related connectivity optimization problems are underlying a wide range of applications and are also of high computational complexity. We consider studying network optimization problems using two types of quantum heuristics.One is quantum annealing, and the other Quantum Alternating Operator Ansatz, an extension of the Quantum Approximate Optimization Algorithms for gate-model quantum computation, in which a cost-function based unitary and a non-commuting mixing unitary are applied alternately. We present problem mappings for problems of finding the spanning-tree or spanning-graph of a graph that optimizes certain costs, and a variant that further requires the spanning-tree be degree-bounded. With quantum annealing, all constraints are cast into penalty terms in the cost Hamiltonian, and the solution is encoded as the ground state of the Hamiltonian. We provide three mappings to the quadratic unconstrained binary optimization (QUBO) form, compare the resource requirements, and analyze the tradeoffs. For QAOA, we give special focus on the design of mixers based on the constraints presented in the problem, such that the system evolution remains in a subspace of the full Hilbert space where all constraints are satisfied. In the spanning-tree problem, one such hard constraint is that a mixer applied to a spanning-tree needs also be a spanning tree. This involves checking the connectivity of a subgraph, which is a global condition common for most network-related problems. We show how this feature can be efficiently represented in the mixer in a quantum coherent way, based on manipulation of a descendant-matrix and an adjacent matrix. We further develop a mixer for the spanning-graphs based on the spanning-tree mixer
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