We report the first measurement of the τ lepton polarization P_{τ}(D^{*}) in the decay B[over ¯]→D^{*}τ^{-}ν[over ¯]_{τ} as well as a new measurement of the ratio of the branching fractions R(D^{*})=B(B[over ¯]→D^{*}τ^{-}ν[over ¯]_{τ})/B(B[over ¯]→D^{*}ℓ^{-}ν[over ¯]_{ℓ}), where ℓ^{-} denotes an electron or a muon, and the τ is reconstructed in the modes τ^{-}→π^{-}ν_{τ} and τ^{-}→ρ^{-}ν_{τ}. We use the full data sample of 772×10^{6} BB[over ¯] pairs recorded with the Belle detector at the KEKB electron-positron collider. Our results, P_{τ}(D^{*})=-0.38±0.51(stat)_{-0.16}^{+0.21}(syst) and R(D^{*})=0.270±0.035(stat)_{-0.025}^{+0.028}(syst), are consistent with the theoretical predictions of the standard model.
We report the first experimental demonstration of quantum entanglement among ten spatially separated single photons. A near-optimal entangled photon-pair source was developed with simultaneously a source brightness of ∼12 MHz/W, a collection efficiency of ∼70%, and an indistinguishability of ∼91% between independent photons, which was used for a step-by-step engineering of multiphoton entanglement. Under a pump power of 0.57 W, the ten-photon count rate was increased by about 2 orders of magnitude compared to previous experiments, while maintaining a state fidelity sufficiently high for proving the genuine ten-particle entanglement. Our work created a state-of-the-art platform for multiphoton experiments, and enabled technologies for challenging optical quantum information tasks, such as the realization of Shor's error correction code and high-efficiency scattershot boson sampling.
Solving linear systems of equations is ubiquitous in all areas of science and engineering. With rapidly growing data sets, such a task can be intractable for classical computers, as the best known classical algorithms require a time proportional to the number of variables N. A recently proposed quantum algorithm shows that quantum computers could solve linear systems in a time scale of order log(N), giving an exponential speedup over classical computers. Here we realize the simplest instance of this algorithm, solving 2×2 linear equations for various input vectors on a quantum computer. We use four quantum bits and four controlled logic gates to implement every subroutine required, demonstrating the working principle of this algorithm.
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