Related papers: Optimization of the collimation system for CSNS/RC…
The dual harmonic system has been widely used in high intensity proton synchrotrons to suppress the space charge effect, as well as reduce the beam loss. To investigate the longitudinal beam dynamics in the dual rf system, the potential…
We propose the Block Coordinate Descent Network Simplex (BCDNS) method for solving large-scale discrete Optimal Transport (OT) problems. BCDNS integrates the Network Simplex (NS) algorithm with a block coordinate descent (BCD) strategy,…
The Cold-Neutron Inelastic Spectrometer (CNIS) is a direct-geometry, time-of-flight instrument designed for China Spallation Neutron Source (CSNS) and optimized to probe low-energy lattice and magnetic excitations. The instrument integrates…
Differentiable neural architecture search (DARTS) is a popular method for neural architecture search (NAS), which performs cell-search and utilizes continuous relaxation to improve the search efficiency via gradient-based optimization. The…
Ray effects are the inherent problem of discrete ordinates method. RAY3D, a functional module of ARES which is a discrete ordinates code system, employs a semi-analytic first collision source method to mitigate ray effects. This method…
In Chinese Spallation Neutron Source (CSNS), proton beam is used to hit metal tungsten target, and then high flux neutrons are generated for experiments on instruments. For neutron flux spectrum correction, boron-coated GEM, lithium glass…
The randomized coordinate descent (RCD) method is a classical algorithm with simple, lightweight iterations that is widely used for various optimization problems, including the solution of positive semidefinite linear systems. As a linear…
The primary goal of the COHERENT collaboration is to measure and study coherent elastic neutrino-nucleus scattering (CEvNS) using the high-power, few-tens-of-MeV, pulsed source of neutrinos provided by the Spallation Neutron Source (SNS) at…
Stochastic Optimization is a cornerstone of operations research, providing a framework to solve optimization problems under uncertainty. Despite the development of numerous algorithms to tackle these problems, several persistent challenges…
In this paper, a new cooperation structure for spectrum sensing in cognitive radio networks is proposed which outperforms the existing commonly-used ones in terms of energy efficiency. The efficiency is achieved in the proposed design by…
We develop an online optimisation algorithm for in situ calibration of collision models in simulations of rarefied gas flows. The online optimised collision models are able to achieve similar accuracy to Direct Molecular Simulation (DMS) at…
AC/multi-terminal DC (MTDC) hybrid power systems have emerged as a solution for the large-scale and longdistance accommodation of power produced by renewable energy systems (RESs). To ensure the optimal operation of such hybrid power…
CPU scheduling has valiant effect on resource utilization as well as overall quality of the system. Round Robin algorithm performs optimally in time shared systems, but it performs more number of context switches, larger waiting time and…
This paper presents a centralized recursive optimal scheduling method for a battery system that consists of parallel connected battery modules with different open circuit voltages and battery impedance characteristics. Examples of such a…
The back-streaming white neutron source (Back-n) is a comprehensive neutron experimental platform for nuclear data measurement, nuclear astrophysics, neutron irradiation, detector calibration, etc. In order to meet a variety of experimental…
In the Rapid Cycling Synchrotron(RCS) of China Spallation Neutron Source(CSNS), transverse painting injection is employed to suppress the space-charge effects. The beta-beating caused by edge focusing of the injection bump magnets leads to…
Constraint Optimization Problems (COP) pose intricate challenges in combinatorial problems usually addressed through Branch and Bound (B\&B) methods, which involve maintaining priority queues and iteratively selecting branches to search for…
The Robust Alignment algorithm for the ATLAS silicon detectors is presented. It is an iterative method based on centering residual and overlap residual distributions. Tests on simulated and real data are discussed.
In this paper, based on the limited memory techniques and subspace minimization conjugate gradient (SMCG) methods, a regularized limited memory subspace minimization conjugate gradient method is proposed, which contains two types of…
In this paper we show that chordal structure can be used to devise efficient optimization methods for robust model predictive control problems. The chordal structure is used both for computing search directions efficiently as well as for…