Understanding the evolution of molecular electronic structures is the key to explore and control photochemical reactions and photobiological *** to strong laser fields,electronic holes are formed upon ionization and e...
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Understanding the evolution of molecular electronic structures is the key to explore and control photochemical reactions and photobiological *** to strong laser fields,electronic holes are formed upon ionization and evolve in the attosecond *** is crucial to probe the electronic dynamics in real time with attosecond-temporal and atomic-spatial ***,we present molecular attosecond interferometry that enables the in situ manipulation of holes in carbon dioxide molecules via the interferometry of the phase-locked electrons(propagating in opposite directions)of a laser-triggered rotational wave *** joint measurement on high-harmonic and terahertz spectroscopy(HATS)provides a unique tool for understanding electron dynamics from picoseconds to *** optimum phases of two-color pulses for controlling the electron wave packet are precisely determined owing to the robust reference provided with the terahertz pulse *** is noteworthy that the contribution of HOMO-1 and HOMO-2 increases reflecting the deformation of the hole as the harmonic order *** method can be applied to study hole dynamics of complex molecules and electron correlations during the strong-field *** threefold control through molecular alignment,laser polarization,and the two-color pulse phase delay allows the precise manipulation of the transient hole paving the way for new advances in attochemistry.
To achieve quantum machine learning on imperfect noisy intermediate-scale quantum (NISQ) processors, the entire physical implementation should include as few as possible hand-designed modules with only a few ad hoc pa...
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To achieve quantum machine learning on imperfect noisy intermediate-scale quantum (NISQ) processors, the entire physical implementation should include as few as possible hand-designed modules with only a few ad hoc parameters to be determined. This work presents such a hardware-friendly end-to-end quantum-machine-learning scheme that can be implemented with imperfect NISQ processors. The proposal transforms the machine-learning task to the optimization of controlled quantum dynamics, in which the learning model is parameterized by experimentally tunable control variables. Our design also enables automated feature selection by encoding the raw input to quantum states through agent control variables. Comparing with the gate-based parameterized quantum circuits, the proposed end-to-end quantum-learning model is easy to implement as there are only a few ad hoc parameters to be determined. Numerical simulations on the benchmarking MNIST (Mixed National Institute of Standards and Technology) dataset of handwritten digits demonstrate that the model can achieve high performance using only 3–5 qubits without downsizing the dataset, which shows great potential for accomplishing large-scale real-world learning tasks on NISQ processors.
ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional t...
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As widely known, the basic reproduction number plays a key role in weighing birth/infection and death/recovery processes in several models of population dynamics. In this general setting, its characterization as the s...
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In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective...
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The creation of disordered hyperuniform materials with potentially extraordinary optical properties requires a capacity to synthesize large samples that are effectively hyperuniform down to the nanoscale. Motivated by...
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In this paper, we consider the Cauchy problem for the fractional Schrödinger equation iDtα u + (−∆) β 2 u = 0 with 0 0. We establish the dispersive estimates for the solutions. In particular, we prove that the ...
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Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research area with small-scale laboratory demo...
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This study aimed to determine the potential of coffee skin waste (Coffea robusta L) as a superior compost innovation for the growth of pepper-cutting seedlings (Piper nigrum L). This study used an experimental method ...
This study aimed to determine the potential of coffee skin waste (Coffea robusta L) as a superior compost innovation for the growth of pepper-cutting seedlings (Piper nigrum L). This study used an experimental method with a completely randomized design using five treatments and five repeats, variations in the dose of coffee skin waste used P0 (control), P1 (90 g), P2 (135 g), P3 (180 g), and P4 (225 g). The shoot height, number of leaves, number of roots, and length of roots were measured. The results showed that coffee skin waste compost significantly affected shoot height, especially at P1 (90 g), resulting in an average growth height of 7.24 cm. In addition, the highest number of leaves was found at a concentration of P1 (90 g), with an average of two leaves. Although there was no significant effect on the number of roots, the concentration of P1 (90 g) yielded the best results, with an average of 33 root blades, and the best root length was obtained at the concentration of P1 (90 g), with an average of 44.6 cm. Therefore, coffee skin waste significantly influenced shoot height and the number of leaves on pepper-cut seedlings (Piper nigrum L.) in the P1 treatment (90 g).
KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to Apr...
KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.
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