882 research outputs found

    Transistor performance of top rough surface of pentacene measured by laminated double insulated-gate supported on a poly(dimethylsiloxanes) base structure

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    We report the fabrication and electrical characterization of pentacene field-effect transistors with a laminated double insulated-gate using poly(dimethylsiloxanes) (PDMS) as their supporting structure. The ability of PDMS to conform to surfaces enables us to directly evaluate the device performance of the top rough surface of the pentacene active layer (the pentacene-air interface). The mobility measured for the top surface was only about 20% slightly lower than that of the bottom surface. Device stability under ambient conditions is evaluated. This device structure is useful for the characterization of electrical transport in both the top and bottom surface of a thin film simultaneously.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87784/2/033502_1.pd

    Quantum information processing architecture with endohedral fullerenes in a carbon nanotube

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    A potential quantum information processor is proposed using a fullerene peapod, i.e., an array of the endohedral fullerenes 15N@C60 or 31P@C60 contained in a single walled carbon nanotube (SWCNT). The qubits are encoded in the nuclear spins of the doped atoms, while the electronic spins are used for initialization and readout, as well as for two-qubit operations.Comment: 8 pages, 8 figure

    No spin-localization phase transition in the spin-boson model without local field

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    We explore the spin-boson model in a special case, i.e., with zero local field. In contrast to previous studies, we find no possibility for quantum phase transition (QPT) happening between the localized and delocalized phases, and the behavior of the model can be fully characterized by the even or odd parity as well as the parity breaking, instead of the QPT, owned by the ground state of the system. Our analytical treatment about the eigensolution of the ground state of the model presents for the first time a rigorous proof of no-degeneracy for the ground state of the model, which is independent of the bath type, the degrees of freedom of the bath and the calculation precision. We argue that the QPT mentioned previously appears due to unreasonable treatment of the ground state of the model or of the infrared divergence existing in the spectral functions for Ohmic and sub-Ohmic dissipations.Comment: 5 pages, 1 figure. Comments are welcom

    Negative Pre-aware for Noisy Cross-modal Matching

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    Cross-modal noise-robust learning is a challenging task since noisy correspondence is hard to recognize and rectify. Due to the cumulative and unavoidable negative impact of unresolved noise, existing methods cannot maintain a stable performance when the noise increases. In this paper, we present a novel Negative Pre-aware Cross-modal (NPC) matching solution for large visual-language model fine-tuning on noisy downstream tasks. It is featured in two aspects: (1) For noise recognition and resistance, previous methods usually directly filter out a noise subset, we propose to estimate the negative impact of each sample. It does not need additional correction mechanisms that may predict unreliable correction results, leading to self-reinforcing error. We assign a confidence weight to each sample according to its negative impact in the training process. This adaptively adjusts the contribution of each sample to avoid noisy accumulation. (2) For maintaining stable performance with increasing noise, we utilize the memorization effect of DNNs by maintaining a memory bank. Specifically, we apply GMM to select high-confident clean samples as the memory entry, where the memory entry is used to estimate the negative impact of each sample. Since clean samples are easier distinguished by GMM with increasing noise, the memory bank can still maintain high quality at a high noise ratio. Compared to the correction mechanism focusing on noise samples, memory bank-based estimation is more robust, which makes the model performance stable on noisy datasets. Extensive experiments demonstrate that our method significantly improves matching accuracy and performance stability at increasing noise ratio. Our approach also surpasses the state-of-the-art methods by a large margin. The code is available at: https://github.com/ZhangXu0963/NPC.Comment: 9 pages, 5 figures, conferenc
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