搜索结果：Producing

We present a scheme for producing intense $μ^+$ and $μ^-$ lepton beams that could be utilized in a future muon-muon or muon-ion collider, as well as for other applications. The scheme makes use of BACKscattered GAMMas On Nucleons (BACKGAMMON). Current accelerator infrastructures could be utilized to produce the muon beams, such as the Electron-Ion Collider (EIC) at Brookhaven National Laboratory in the United States. We discuss the implementation of BACKGAMMON at the EIC.

In this work, the straight flux rope in the model of giant flares on magnetars (Meng et al. 2014) was replaced with a curved one and the equilibrium behavior of the flux rope was investigated. Two footpoints of the flux rope are anchored to the spherical surface of magnetar. The forces acting on the flux rope include magnetic tension, magnetic pressure, curvature force, gravity. The equilibrium in the flux rope, so as in the global configuration, is achieved as these forces offset each other. Changes in the background environment drive the configuration to evolve through a set of equilibria in a quasi-static fashion until the critical point is reached and the loss of equilibrium in the configuration occurs, invoking a giant flare. We establish a criterion to identify magnetars capable of producing giant flares. Among the four forces, the curvature force as well as the magnetic compression tend to expel the flue rope outward. In a given magnetic configuration, the curvature force and magnetic compression are proportional to the square of the current intensity of the flux rope, which is determined by the frozen-flux condition and background magnetic field strength. We find that only

We demonstrate a tandem lens optical setup, comprising two diffractive optics, that focuses a high-power ultrafast laser with a shaped on-axis intensity profile, producing a meter-long Bessel focus. The intended use of the optical setup is to produce a laser-ionized plasma source for plasma wakefield acceleration. By controlling the on-axis intensity, the density profile of the plasma ramps at the entrance and exit of the plasma can be tailored to optimize matching of the electron beam into the plasma. In addition to demonstrating the optical system, we describe the algorithm used to calculate the lens phases and present detailed calculations of the lenses' expected performance.

Landforms such as sand dunes act as roughness elements to Atmospheric Boundary Layer (ABL) flows, triggering the development of new scales of turbulent motions. These turbulent motions, in turn, energize and kick-up sand particles, influencing sediment transport and ultimately the formation and migration of dunes -- with knock on consequences for dust emission. While feedbacks between flow and form have been studied at the scale of dunes, research has not examined how the development of an Internal Boundary Layer (IBL) over the entire dune field influences sediment-transporting turbulence. Here, we deploy large-eddy simulation of an ABL encountering a natural roughness transition: the sand dunes at White Sands National Park, New Mexico. We analyze turbulence producing motions and how they change as the IBL grows over the dune field. Frequency spectrum and Reynolds shear stress profiles show that IBL thickness determines the largest scales of turbulence. More, the developing IBL enhances the frequency, magnitude and duration of sweep and ejection events -- turbulence producing motions whose peaks systematically migrate away from the wall as the IBL thickens. Because sweep and ejecti

The article focuses on word (or string) attractors, which are sets of positions related to the text compression efficiency of the underlying word. The article presents two combinatorial algorithms based on Suffix automata or Directed Acyclic Word Graphs. The first algorithm decides in linear time whether a set of positions on the word is an attractor of the word. The second algorithm generates an attractor for a given word in a greedy manner. Although this problem is NP-hard, the algorithm is efficient and produces very small attractors for several well-known families of words.

We develop the foundations of a general framework for producing optimal upper and lower bounds on the sum $\sum_p a_p$ over primes $p$, where $(a_n)_{x/2<n\le x}$ is an arbitrary non-negative sequence satisfying Type I and Type II estimates. Our lower bounds on $\sum_p a_p$ depend on a new sieve method, which is non-iterative and uses all of the Type I and Type II information at once. We also give a complementary general procedure for constructing sequences $(a_n)$ satisfying the Type I and Type II estimates, which in many cases proves that our lower bounds on $\sum_p a_p$ are best possible. A key role in both the sieve method and the construction method is played by the geometry of special subsets of $\mathbb{R}^k$. This allows us to determine precisely the ranges of Type I and Type II estimates for which an asymptotic for $\sum_p a_p$ is guaranteed, that a substantial Type II range is always necessary to guarantee a non-trivial lower bound for $\sum_p a_p$, and to determine the optimal bounds in some naturally occurring families of parameters from the literature. We also demonstrate that the optimal upper and lower bounds for $\sum_p a_p$ exhibit many discontinuities with resp

For a prime $p$ congruent to three modulo four, we prove that there exists a smooth curve of genus five in characteristic $p$ that is supersingular. We produce this curve as an unramified double cover of a curve of genus three. We conjecture that the setting of unramified double covers of curves of genus three also produces supersingular curves of genus five when $p$ is congruent to one modulo four, and we computationally verify this conjecture for primes less than $100$. These results can be viewed as a generalization of work of Ekedahl and of Harashita, Kudo, and Senda.

Neural networks are typically black-boxes that remain opaque with regards to their decision mechanisms. Several works in the literature have proposed post-hoc explanation methods to alleviate this issue. This paper proposes LMAC-TD, a post-hoc explanation method that trains a decoder to produce explanations directly in the time domain. This methodology builds upon the foundation of L-MAC, Listenable Maps for Audio Classifiers, a method that produces faithful and listenable explanations. We incorporate SepFormer, a popular transformer-based time-domain source separation architecture. We show through a user study that LMAC-TD significantly improves the audio quality of the produced explanations while not sacrificing from faithfulness.

Software bills of materials (SBOM) promise to become the backbone of software supply chain hardening. We deep-dive into 6 tools and the accuracy of the SBOMs they produce for complex open-source Java projects. Our novel insights reveal some hard challenges for the accurate production and usage of SBOMs.

The mechanism of multinucleon transfer (MNT) reactions for producing neutron-rich heavy nuclei around N = 126 is investigated within two different theoretical frameworks: dinuclear system (DNS) model and isospin-dependent quantum molecular dynamics (IQMD) model. The effects of mass asymmetry relaxation, N=Z equilibration, and shell closures on production cross sections of neutron-rich heavy nuclei are investigated. For the first time, the advantages for producing neutron-rich heavy nuclei around N = 126 is found in MNT reactions based on 238U target. We propose the reactions with 238U target for producing unknown neutron-rich heavy nuclei around N = 126 in the future.

The multinucleon transfer process is one promising approach for producing neutron-rich heavy nuclei. The favorable projectile-target combinations play a key role in experiments. As one important approach to investigate the multinucleon transfer process, one new version of the dinuclear system (DNS) model is developed. The improved version of the DNS model is shown in detail. Based on deformation degree of freedom in the improved DNS model, one way of calculating excitation energies of primary fragments is proposed. And the remarkable improvements for describing experimental data of producing trans-uranium nuclei is noticed. To produce trans-uranium nuclei, the collisions of 48Ca, 136Xe, and 238U projectiles with the 238U target are investigated within the improved DNS model. Based on the potential energy surface, the influence of projectiles on the probabilities of transferring neutrons and protons from the projectiles to the target are studied. One behavior is found that the transfer probabilities strongly depend on the projectiles in the neutron stripping process, while relatively weak projectile dependence is noticed in the proton transferring process. The 136Xe and 238U project

A learning process with the plasticity property often requires reinforcement signals to guide the process. However, in some tasks (e.g. maze-navigation), it is very difficult (or impossible) to measure the performance of an agent (i.e. a fitness value) to provide reinforcements since the position of the goal is not known. This requires finding the correct behavior among a vast number of possible behaviors without having the knowledge of the reinforcement signals. In these cases, an exhaustive search may be needed. However, this might not be feasible especially when optimizing artificial neural networks in continuous domains. In this work, we introduce novelty producing synaptic plasticity (NPSP), where we evolve synaptic plasticity rules to produce as many novel behaviors as possible to find the behavior that can solve the problem. We evaluate the NPSP on maze-navigation on deceptive maze environments that require complex actions and the achievement of subgoals to complete. Our results show that the search heuristic used with the proposed NPSP is indeed capable of producing much more novel behaviors in comparison with a random search taken as baseline.

This is the second paper in a series where we examine the physics of pair producing gaps in low-luminosity accreting supermassive black hole systems. In this paper, we carry out time-dependent self-consistent fully general relativistic 1D PIC simulations of the gap, including full inverse Compton scattering and photon tracking. Similar to the previous paper, we find a highly time-dependent solution where a macroscopic vacuum gap can open quasi-periodically, producing bursts of $e^\pm$ pairs and high energy radiation. We present the light curve, particle and photon spectra from this process. Using an empirical scaling relation, we rescale the parameters to the inferred values at the base of the jet in M87, and find that the observed TeV flares could potentially be explained by this model under certain parameter assumptions.

We present a statistical result on the properties of solar source regions that have produced 57 fastest front-side coronal mass ejections (CMEs) (speed 1500 km/s) occurred from 1996 June to 2007 January. The properties of these fast-CME-producing regions, 35 in total, are compared with those of all 1143 active regions (ARs) in the period studied. An automated method, based on SOHO/MDI magnetic synoptic charts, is used to select and characterize the ARs. For each AR, a set of parameters are derived including the areas (positive, negative and total, denoted by A_P, A_N and A_T respectively), the magnetic fluxes (positive, negative and total, F_P, F_N and F_T respectively), the average magnetic field strength (B_avg), quasi-elongation (e) characterizing the overall shape of the AR, the number and length of polarity inversion lines (PILs, or neutral lines, N_PIL and L_PIL respectively), and the average and maximum of magnetic gradient on the PILs (GOP_avg and GOP_max respectively). Our statistical analysis shows a general trend between the scales of an AR and the likelihood of producing a fast CME, i.e., the larger the geometric size (A_T), the larger the magnetic flux (F_T), the stron

We propose a novel method for producing very-neutron-rich hypernuclei and corresponding resonance states by employing charge-exchange reactions via pp($^{12}$C, $^{12}$N $K^+$)n$Λ$ with single-charge-exchange and ppp($^{9}$Be, $^{9}$C $K^+$)nn$Λ$ with double-charge-exchange, both of which produce $ΛK^+$ in a target nucleus. The feasibility of producing very-neutron-rich hypernuclei using the proposed method was analysed by applying an ultra-relativistic quantum molecular dynamics model to a $^6$Li+$^{12}$C reaction at 2 $A$ GeV. The yields of very-neutron-rich hypernuclei, signal-to-background ratios, and background contributions were investigated. The proposed method is a powerful tool for studying very-neutron-rich hypernuclei and resonance states with a hyperon for experiments employing the Super-FRS facility at FAIR and HFRS facility at HIAF.

Current approaches to explaining the decisions of deep learning systems for medical tasks have focused on visualising the elements that have contributed to each decision. We argue that such approaches are not enough to "open the black box" of medical decision making systems because they are missing a key component that has been used as a standard communication tool between doctors for centuries: language. We propose a model-agnostic interpretability method that involves training a simple recurrent neural network model to produce descriptive sentences to clarify the decision of deep learning classifiers. We test our method on the task of detecting hip fractures from frontal pelvic x-rays. This process requires minimal additional labelling despite producing text containing elements that the original deep learning classification model was not specifically trained to detect. The experimental results show that: 1) the sentences produced by our method consistently contain the desired information, 2) the generated sentences are preferred by doctors compared to current tools that create saliency maps, and 3) the combination of visualisations and generated text is better than either alone.