A magnetic mass spectrograph has been developed for measuring the ion composition of pulsed vacuum arc ion sources at 60 kV extraction voltage. The mass spectrograph is comprised of an ion beam collimator, an einzel lens, a 114 degrees dipole magnet, and a 416-channel Faraday-strip array detector. The main advantages of this mass spectrograph are its high simultaneous mass-to-charge ratio detection range and gapless Faraday-strip array detector. This paper introduces the design of the mass spectrograph and evaluates its performance in terms of resolving power and simultaneous detection range.

DAMPE space-borne cosmic ray experiment has been collecting data since December 2015. Many high-impact results on the ion, electron and photon fluxes were obtained. This submission presents the carbon flux analysis with DAMPE using machine learning techniques. The readout electronics would saturate at energy deposits above several TeV in a single BGO bar of the DAMPE calorimeter. The total energy loss per event due to saturation can sometimes reach over a hundred TeV. We present a convolutional neural network model which can accurately recover the energy lost due to saturation and thus significantly increase the dynamic range of DAMPE. Another machine learning model combines the resolution of the hodoscopic BGO calorimeter and the high-resolution tracker of DAMPE to provide the best possible prediction of the direction of the incoming particle. This allows measuring charges at energies up to several hundred TeV. In this work, we present the application of these methods to carbon flux analysis.

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne experiment, in operation since 2015, aimed at studying cosmic rays and high-energy gamma rays. Proton and helium are the first-and second-most abundant components in cosmic rays. Given their smaller interaction cross sections with the interstellar medium, compared to heavier nuclei, they can travel larger distances, thereby becoming important probes to cosmic-ray sources as well as acceleration and propagation mechanisms. Recently, in the DAMPE collaboration, machine learning (ML) techniques were developed and deployed to improve particle tracking and identification and correct for the calorimeter readout saturation at high energies. This work presents a direct measurement of the energy spectra of cosmic-ray protons and helium nuclei, using 84 and 81 months of data, respectively, recorded by DAMPE. Application of the above-mentioned ML techniques helps in extending the spectra to higher kinetic energies than those previously reported by DAMPE

The DArk Matter Particle Explorer (DAMPE) is a space-borne high-energy particle detector launched on 17 December 2015. It can observe the $\gamma$-ray sky from $\sim 2$ GeV to 10 TeV with the acceptance at most $1800~\rm cm^2\,sr$. With over 7.5 years of continuous operation, DAMPE has surveyed the whole sky for about 15 times and collected more than 300,000 candidate photon events. In the last few years, the understanding of the payload has been improved and the instrumental response functions have been calibrated with the on-board data. Besides, progresses have been made on the $\gamma$-ray line search, point source detection, diffuse emission analysis, and transient source monitoring. In the talk and this accompanying proceeding, the latest results on these topics are reported.

The Dark Matter Particle Explorer (DAMPE) is a space-based Cosmic Ray (CR) observatory with the aim, among others, to study Cosmic Ray Electrons (CREs) up to 10 TeV. Due to the low CRE rate at multi-TeV range, we aim at increasing the acceptance by selecting events outside the fiducial volume. The complex topology of non-fiducial events require special treatment with sophisticated analysis tools. Therefore, we propose a Convolutional Neural Network (CNN) to identify non-fiducial CREs and reject background events, based on their interaction in DAMPE's calorimeter. In the following, we will present the aforementioned method in order to precisely identify such events.

多丝漂移室(MWDC)用于兰州重离子加速器-冷却存储环上外靶实验终端的径迹测量,其前端电子学中放大芯片采用SFE16芯片,目前前端电子学单板通道数较少,且慢控配置模块老旧,无法兼容新设备,配置效率较低.该文对前端板(FEE)进行升级,单板实现 32通道;并设计一种基于现场可编程门阵列(FPGA)的配置板,通过上位机USB接口实现对多块SFE16芯片的快速高效配置.电子学测试实验结果表明,升级后的前端电子学在增加通道数的基础上保证了原有性能,并实现单次对248片SFE16芯片的配置,使用简单,配置效率高,实用性好.

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne particle detector launched on December 17th, 2015, with different scientific objectives, looking for signatures of Dark Matter decay or annihilation, performing gamma-ray astronomy and providing precise measurements of galactic Cosmic Ray (CR) energy spectra. Accurate measurements of hadronic interaction cross sections, playing a key role in the determination of CR fluxes. The survival probabilities have been implemented to study hadronic interaction cross sections with the BGO calorimeter target for Carbon nuclei in a wide kinetic energy range from a few GeV to TeV, by using data collected by the DAMPE experiment. The results have been then compared with Geant4 simulations of the interaction cross-sections performed by adopting the Glauber–Gribov Model. The details of the measured hadronic interaction cross sections are here presented and discussed.

The DArk Matter Particle Explorer (DAMPE) is a pioneering calorimetric experiment that has been successfully operating in space since December 2015, designed to detect cosmic rays up to unprecedentedly high energies thanks to the fine-grained thick BGO calorimeter and relatively large geometric factor. Among the scientific goals of DAMPE are the precise measurements of cosmic-ray electron plus positron spectrum, including the detection of possible indirect dark matter signatures, spectral measurements of primary and secondary cosmic-ray species, and gamma-ray physics. For electrons and gamma rays, it covers an energy range from GeV to about 10 TeV, with an outstanding energy resolution close to 1%. Proton and ion cosmic rays can be measured up to hundreds of TeV in kinetic energy. In this contribution, we first give an overview of the DAMPE mission and its on-orbit operation status. Then, we highlight the key scientific results, including the measurements of the BCNO group, boron-to-carbon ratio, proton plus helium spectrum beyond 100 TeV, gamma-ray physics and more. Finally, the ongoing efforts for lepton, light, and heavy hadron cosmic rays are briefly discussed along with the new data analysis techniques.

Dark Matter Particle Explorer (DAMPE) is a calorimetric-type, satellite-borne detector. One important scientific object of DAMPE is to measure the flux of cosmic ray nuclei, which is fundamental for understanding the cosmic ray origin and propagation mechanism. Heavy nuclei beyond Iron in Cosmic Rays play an important role for studying the outstanding issues in the grand cycle of matter in the Galaxy. Thanks to the good charge resolution of the DAMPE PSD detector (∼0.06e for protons, ∼0.3e for iron), the primary charges in a wide range from proton (Z=1) to Zirconium (Z=40) can be identified. In seven years of data-taking from 2016 to 2022, DAMPE has collected data with more than 3 × 10^6 nuclei with Z≥26. In order to reduce the contamination of Iron in the flux of heavier nuclei in cosmic rays, new charge identification methods have been studied, and the relativistic rise effect has been corrected. Here, such tools and the methods of charge identification aiming to the spectrum measurement will be introduced.

Galactic cosmic rays are mostly made up of energetic nuclei, with less than 1% of electrons (and positrons). Precise measurement of the electron and positron component requires a very efficient method to reject the nuclei background, mainly protons. In this work, we develop an unsupervised machine learning method to identify electrons and positrons from cosmic ray protons for the Dark Matter Particle Explorer (DAMPE) experiment. Compared with the supervised learning method used in the DAMPE experiment, this unsupervised method relies solely on real data except for the background estimation process. As a result, it could effectively reduce the uncertainties from simulations. For three energy ranges of electrons and positrons, 80–128 GeV, 350–700 GeV and 2–5 TeV, the residual background fractions in the electron sample are found to be about (0.45 ± 0.02)%, (0.52 ± 0.04)% and (10.55 ± 1.80)%, and the background rejection power is about (6.21 ± 0.03) × 104, (9.03 ± 0.05) × 104 and (3.06 ± 0.32) × 104, respectively. This method gives a higher background rejection power in all energy ranges than the traditional morphological parameterization method and reaches comparable background rejection performance compared with supervised machine learning methods.

Forbush Decrease (FD) is a rapid decrease and slow recover in the observed galactic cosmic ray intensity, caused by active solar events sweeping low energy galactic cosmic rays (GCRs) away from Earth. Differnet properties of FDs have been observed by different scientific experiment but mostly from worldwide ground based Neutron Monitors (NMS), they focus on secondary neutron from the atmosphere. The Dark Matter Particle Explorer (DAMPE) is a satellite-based cosmic-ray experiment that has been stably operated for more than 7 years. Precise measurements of cosmic ray electrons and positrons from DAMPE make it possible to directly study FDs from a new perspective. We analyze the FD properties, such as decrease amplitude and recover time as a function of energy, observed by DAMPE from 2017 to 2021. Finally we simulate the FDs with a numerical model, and successfully reproduce the FDs. The preliminary result shows that the head-on events causes energy related recover time, while edge-on events causes energy unrelated recover time of FDs.

The DArk Matter Particle Explorer (DAMPE), a space-based high-energy particle detector

A precise measurement of the cosmic-ray spectra provides important information on their origin, acceleration and propagation processes in the Galaxy. The Dark Matter Particle Explorer (DAMPE) is a satellite-based cosmic-ray experiment that has been operational for more than 7 years. Since its launch in December 2015, it is continuously collecting data on high-energy cosmic particles with very good statistics and particle identification capabilities, thanks to a large geometric factor and a good charge resolution. In this contribution, the direct measurement of the intermediate mass cosmic rays is presented, in particular the observation of the cosmic-ray Ne, Mg and Si nuclei, which are thought to be mainly produced and accelerated in astrophysical sources.

The DArk Matter Particle Explorer (DAMPE) space mission is designed to measure cosmic rays and gamma rays. The key sub-detector of DAMPE is the Bismuth Germanium Oxide (BGO) Electromagnetic CALorimeter (ECAL), which measures the energies of electrons/gamma-rays ranging from 5 GeV - 10 TeV. The fluorescence quenching effect has been observed for hadronic shower in the sensitive unit of the BGO ECAL, in which cases the fluorescence yield is no longer proportional to the deposited energies. However, it is still unclear whether there is a quenching effect in BGO ECAL for ~TeV electromagnetic showers with extremely high energy deposition densities. In this presentation, we will introduce the results of a laser test that checks the linearity of the BGO fluorescence response to the energy deposited at the shower centers of 10 TeV-order electrons. The laser test used a high-intensity laser to excite a BGO crystal to mimic the high-density energy deposition of electromagnetic showers. It will reveal whether the BGO fluorescence response remains linear for a ~10 TeV electromagnetic shower. Further study on the response of the BGO crystal located at the shower center in high-energy electromagnetic showers was also assessed through a comparison of data obtained from orbital cosmic ray electrons candidate and Monte Carlo Simulation without a fluorescence quenching effect.

It is currently well established that proton and helium constitute the main component of cosmic radiation in the energy range from tens of GeV to hundreds of TeV. Their direct detection and separation have been carried out in the past years using several space-based instruments and long-flying balloons, while ground-based experiments provided results at high energies but with large systematics due to the limited mass resolution. Surprisingly, two structures were found in the direct measurements of individual proton and helium spectra which deviates from the single power law model, proposed by standard acceleration and propagation mechanisms. Moreover, results from ground-based experiments opened the scenario of a light component (i.e. p+He) knee in the cosmic ray spectrum, even with large uncertainties. The p+He direct measurement, using looser selection cuts compared to individual p and He analyses, besides giving a valuable cross-check, can enlarge the event statistics and then extend the energy range to larger values, covering an overlap region between direct and indirect measurements, and exploring it for the first time with high precision. Among the space-based cosmic ray detectors in operation at present, the DArk Matter Particle Explorer (DAMPE) has the capability of providing results on p+He up to the highest energies, thanks to its large acceptance and deep calorimeter. In this work, the p+He spectrum measured up to 300 TeV, using 6 years of data collected with the DAMPE satellite, will be presented.

DAMPE (DArk Matter Particle Explorer) is a space-based particle detector that has been continuously taking data since its successful launch in December 2015. Its primary scientific goals include the indirect search of dark matter, the study of galactic cosmic rays with energy from few tens of GeV up to hundreds of TeV and high-energy gamma-ray astronomy. Spectral measurements of secondary nuclei such as lithium, beryllium and boron and ratios to primary fluxes are fundamental to improve our understanding of cosmic ray acceleration and propagation. In this work, first preliminary results on DAMPE data analysis of these elements will be presented.

Thanks to its large calorimeter, the DArk Matter Particle Explorer (DAMPE) satellite experiment is ideally suited for the direct detection of cosmic rays (CRs) up to the knee. At these TeV to PeV energies, the main uncertainty on the CR flux measurements comes from the hadronic cross sections, which are largely experimentally unconstrained. We developed novel machine learning (ML) tools that are able to probe the depth at which CRs inelastically interact inside the DAMPE experiment. Applying these techniques to 7 years of DAMPE data, and comparing the results to predictions made by CR simulation frameworks such as Geant4 and FLUKA, we demonstrate how DAMPE data can be used to constrain the hadronic cross sections. Our results thus provide an important step towards reducing the uncertainties of CR flux measurements. Additionally, they form a pathfinder for similar studies with future experiments.

The Multi-purpose Time Projection Chamber (TPC) for nuclear AsTrophysical and Exotic beam experiments (MATE) is being upgraded for the decay and active target experiments at the Heavy Ion Research Facility in Lanzhou (HIRFL). We have developed a gating grid driver to control the transitions between the closed and open states of the gating grid of the MATE-TPC to detect interesting rare decay events from a large amount of implanted ions. The gating grid driver is mainly composed of a digital control unit and a high-voltage switch unit. The digital control unit responds to the external trigger and generates control signals for the operation of the high-voltage control part based on the presetting instruction. The high-voltage switch unit is connected to two negative high voltages with different values and changes the voltages of neighboring wires of the gating grid based on the request for closing or opening the gate. A 500 ns switching time of the gating grid driver has been achieved from the closed to open state. The duration of the open state can be adjusted from 1 µs to 99 ms based on the experimental requirements. This gating grid driver can be used in a particle detector with a high voltage bias of up to ± 3000 V.

The in-beam positron emission tomography (ibPET) is dedicated to radiotherapy imaging of the heavy-ion medical machine (HIMM), which requires precise online measurement, as well as real-time signal processing capability of the electronics. In this paper, we present the implementation of real-time digital signal processing in the data acquisition unit (DAQU) for an ibPET system based on the photomultiplier tube (PMT) readout of lutetium-yttrium oxyorthosilicate (LYSO) scintillator crystals. We have designed 10-channel customized signal processing circuit on a high-performance FPGA, which supports 3 working modes (single event processing mode, self-calibration mode and raw ADC data mode), position calculation, crystal locating, event sorting, and etc. Moreover, the implementation of real-time corrections is capable of dealing with photon peak correction to 511 keV and crystal ID-based time correction. The implemented real-time ibPET system can achieve 46% data compression and beyond 1,000,000 events/sec/channel signal processing capabilities. A series of initial tests is conducted, and the results indicate that this design meets the application requirement on online processing.

Boron nuclei in cosmic rays (CRs) are believed to be mainly produced by the fragmentation of heavier nuclei, such as carbon and oxygen, via collisions with the interstellar matter. Therefore, the boron-to-carbon flux ratio (B/C) and the boron-to-oxygen flux ratio (B/O) are very essential probes of the CR propagation. With a large geometric factor and a good charge resolution, the DArk Matter Particle Explorer (DAMPE)