Thin Si films on SiO2 that are completely melted by pulsed laser irradiation cool rapidly and eventually solidify via nucleation and growth of solids. It has been observed that a variety of solidified microstructures ...
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Low aspect ratio designs are proposed for steady-state tokamak reactors. Benefits stem from reduced major radius and lessened stresses in the toroidal field coils, resulting in possible cost savings in the tokamak con...
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We are in the process of developing a new laser annealing method referred to as Spot-Beam Crystallization (SBC). The SBC method, which is potentially well suited for manufacturing advanced ultra-high-resolution AMOLED...
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Carbon nanotubes are explored as a means of coherently converting the orbital angular momentum of light to an excitonic form that is more amenable to quantum information *** analytical analysis,based on dynamical cond...
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Carbon nanotubes are explored as a means of coherently converting the orbital angular momentum of light to an excitonic form that is more amenable to quantum information *** analytical analysis,based on dynamical conductivity,is used to show that orbital angular momentum is conserved,modulo N,for a carbon nanotube illuminated by radially polarized,twisted *** result is numerically demonstrated using real-time time-dependent density functional theory which captures the absorption of twisted light and the subsequent transfer of twisted *** results suggest that carbon nanotubes are promising candidates for constructing optoelectronic circuits in which quantum information is more readily processed while manifested in excitonic form.
We have investigated the solidified microstructure of nucleation-generated grains obtained via complete melting of Si films on SiO2 at high nucleation temperatures. This was achieved using a high-temperature-capable h...
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A deep understanding of the mechanisms underlying many-body quantum chaos is one of the big challenges in contemporary theoretical physics. We tackle this problem in the context of a set of perturbed quadratic Sachdev...
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A deep understanding of the mechanisms underlying many-body quantum chaos is one of the big challenges in contemporary theoretical physics. We tackle this problem in the context of a set of perturbed quadratic Sachdev-Ye-Kitaev (SYK) Hamiltonians defined on graphs. This allows us to disentangle the geometrical properties of the underlying single-particle problem and the importance of the interaction terms, showing that the former is the dominant feature ensuring the single-particle to many-body chaotic transition. Our results are verified numerically with state-of-the-art numerical techniques, capable of extracting eigenvalues in a desired energy window of very large Hamiltonians. Our approach essentially provides a new way of viewing many-body chaos from a single-particle perspective.
Specification of the worst case additive interference for M -ary signaling and receivers using predecision correlation is obtained. The interference is constrained by average power and peak amplitude upper bounds on i...
Specification of the worst case additive interference for M -ary signaling and receivers using predecision correlation is obtained. The interference is constrained by average power and peak amplitude upper bounds on its Fourier transform. In addition, no statistical description is assumed. The performance measure is a weighted (\pm 1) sum of the correlations between the received corrupted signal Fourier transform R_{m}(f) and each member of the signal set Fourier transforms \{S_{m}(f)\} . This measure also depends on the out-of-sync time shift t and the signal present probability p . Functional analysis concepts are utilized to state and solve the resulting generalized Lagrange multiplier problem in L_{2} . The worst case interference function W^{0}(f) is shown to have an average power equal to the average power upper bound and is independent of p , but dependent on t . A key parameter may need numerical techniques for evaluation. This power level is achieved with W^{0} as a clipped multiple of | \sum S_{m}| that follows the phase of \sum S_{m}(f) . The clipping level is the peak amplitude upper bound. The worst case performance is explicitly expressed in terms of W^{0} . Upper and lower bounds are also derived with respect to arbitrary signal sets. Additional bounds are obtained for interference functions independent of the signal set magnitudes or phases. As a recommendation to minimize the worst case performance, the communicator should transmit with a high average probability per signal pM^{-1} for a given fixed {\em sum} \sum S_{m}(f) and \tilde{S}_{m}(f)S_{n}(f)=0, m \neq n , all m,n . However, to weaken the effectiveness of some sub-worst case interference, compared with the worst case. the communicator should transmit with low average probability per signal pM^{-1} and a phase of \sum S_{m}(f) close to \pi . Further investigation of good signal sets is warranted.
This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates f...
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ISBN:
(数字)9798331531591
ISBN:
(纸本)9798331531607
This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.
We describe a semiphenomenological model of single scattering of light in seawater by particles and turbulence, plus a semianalytic Monte Carlo program for treating the multiple scattering. Ample experimental data wer...
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We describe a semiphenomenological model of single scattering of light in seawater by particles and turbulence, plus a semianalytic Monte Carlo program for treating the multiple scattering. Ample experimental data were available for wide-angle scattering, but experimental data were not available for scattering at the small angles (10 −3 rad) most relevant for imaging, hence calculations were performed for a variety of parameter values. The results of the Monte Carlo computations were interpretable as simple scaling rules for angular dispersion as a function of range and medium parameters.
A method for estimating the average speed-of-sound (SOS) in tissue or other materials using automatic registration of electronically steered ultrasound images is presented. A mismatch between the SOS assumed for beam ...
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