Periodic Reporting for period 4 - PeVSPACE (Direct Detection of TeV--PeV Cosmic Rays in Space)
Okres sprawozdawczy: 2024-08-01 do 2025-11-30
Cosmic Rays are charged particles, mostly protons (85-90%), helium (5-10%), heavier nuclei (1%), and electrons (<1%), coming from space and produced in the most energetic events in our Galaxy and beyond, in particular in Supernovae explosions. The exact origin of Cosmic Rays remains a mystery up to now, more than a century since their discovery by Victor Hess in 1912. The absolute majority of cosmic rays have the energy of about a few hundred Megaelectronvolts and are deflected away by the earth's magnetic field. Yet a smaller portion of them can reach energies almost a billion times higher than those of the particles accelerated at the Large Hadron Collider. Comic Rays are the ultimate laboratory of the Universe study, in particular of the events driving the evolution of Galaxies the structure of the interstellar medium, chemical composition and generation of elements in stars. It is generally believed that Galactic sources are capable of accelerating Cosmic Rays up to a few Petaelectronvolt (PeV), while everything with higher energy comes outside the Galaxy. For a long time, a conventional hypothesis dominated that Galactic Cosmic Rays (GCR) are produced in the Supernovae Remnants (SNR) and their spectrum represents a simple power-law with a fixed spectral index. Recent direct measurements performed in the past decade by space missions challenge the conventional models, revealing peculiar structures in the spectrum of various cosmic ray components at the energy of about Teraelectronvolt (TeV). This is suggestive of a new source type of cosmic rays or an unknown acceleration or propagation effect. Further high-precision measurements of spectra of different cosmic ray components beyond the TeV scale are essential for solving the puzzle of GCR origin and will also help to pinpoint the possible Dark Matter signatures, which may manifest themselves in the spectrum of Cosmic Rays, notably electrons. Such measurements, however, are hampered by the systematic uncertainties due to the limited accuracy of Cosmic Ray particle reconstruction and identification techniques, and the relatively low precision of hadronic Monte-Carlo simulation models.
The main objective of this project is to radically improve and optimize the techniques for Cosmic Ray detection at TeV—PeV energy region, including particle reconstruction, identification, and simulation, using a state-of-the-art Artificial Intelligence (AI) approach. As a result, Cosmic Ray spectra and composition will be measured first with the DArk Matte Particle Explorer (DAMPE) space mission and then subsequently with the next-generation space instrument — High Energy Radiation Detector (HERD), with unprecedented precision, which could not be achieved otherwise. There are two main innovations in the project. First, the application of AI techniques in astroparticle physics will be pioneered at the highest energies, in an unconventional use case. Second, the Monte-Carlo hadronic simulation models will be tested and tuned using the detector data, for the first time at such high energies.
In conclusion of the project, the developed AI methods have radically outperformed the classical algorithms, enabling high-precision measurements beyond the previous state-of-the art maximum energy of ~100 TeV. Next, the pioneering measurements of strong interactions in space were performed at the highest energy frontier. Consequently, landmark results in cosmic ray physics were attained, among which is the first direct observation of a universal structure (the so-called spectral softening) in all major primary cosmic rays. It validates a long-established hypothesis: maximum energy of cosmic ray acceleration in astrophysical sources is charge dependent.
The main objective of this project is to radically improve and optimize the techniques for Cosmic Ray detection at TeV—PeV energy region, including particle reconstruction, identification, and simulation, using a state-of-the-art Artificial Intelligence (AI) approach. As a result, Cosmic Ray spectra and composition will be measured first with the DArk Matte Particle Explorer (DAMPE) space mission and then subsequently with the next-generation space instrument — High Energy Radiation Detector (HERD), with unprecedented precision, which could not be achieved otherwise. There are two main innovations in the project. First, the application of AI techniques in astroparticle physics will be pioneered at the highest energies, in an unconventional use case. Second, the Monte-Carlo hadronic simulation models will be tested and tuned using the detector data, for the first time at such high energies.
In conclusion of the project, the developed AI methods have radically outperformed the classical algorithms, enabling high-precision measurements beyond the previous state-of-the art maximum energy of ~100 TeV. Next, the pioneering measurements of strong interactions in space were performed at the highest energy frontier. Consequently, landmark results in cosmic ray physics were attained, among which is the first direct observation of a universal structure (the so-called spectral softening) in all major primary cosmic rays. It validates a long-established hypothesis: maximum energy of cosmic ray acceleration in astrophysical sources is charge dependent.
An AI-based particle cosmic ray reconstruction algorithm was developed as the replacement of classical methods in the analysis of the DAMPE data. The results were published in Astroparticle Physics. It opened the possibility for identifying proton, helium and heavier cosmic rays, up to iron, at the highest energies accessible by space-borne detectors, with uncertainty not exceeding a few percent. Based on this approach, similar AI techniques were developed to improve the accuracy of energy reconstruction with the DAMPE experiment (submitted for publication in Nuclear Instruments and Methods). These AI breakthroughs unlocked the previously unachievable cosmic ray measurement by DAMPE exceeding ~100 TeV energy. The core AI ideas from the project are released as an open-source tutorials for students and presented at international conferences/schools, including hands-on AI sessions.
New methods of Cosmic Ray Electron (CRE) identification based on the Deep Neural Net (DNN) and Convolutional Neural Net (CNN) techniques were developed: they provide a factor >4 improvement of proton background rejection compared to the standard techniques, which is critical for precise CRE detection at the highest energies. The results were published in two articles in Journal of Instrumentation. A preliminary measurement of the CRE spectrum using these techniques has been performed at unprecedentedly high (~10 TeV) energies —it is under internal review by the DAMPE collaboration.
The first measurements of inelastic hadronic cross sections of hydrogen and helium nuclei at TeV energies in space have been performed and consequently published in Physical Review D. They enable the reduction of hadronic uncertainties that dominate the precision of direct cosmic ray measurement in space at multi-TeV frontier. Among other, these results were highlighted in the recent cross-section-for-cosmic-ray community roadmap published in Physics Reports.
The work is accomplished by the team members on performing the Cosmic Ray proton and helium spectral measurement with DAMPE beyond the previously achieved ~100 TeV limit. These measurements became possible thanks to the AI techniques developed earlier the project, and employed the improved hadronic simulation models, obtained as the result of the proton/helium cross section measurements. These results were presented at multiple top-tier conferences in the field, and are currently submitted for publication in Nature.
New methods of Cosmic Ray Electron (CRE) identification based on the Deep Neural Net (DNN) and Convolutional Neural Net (CNN) techniques were developed: they provide a factor >4 improvement of proton background rejection compared to the standard techniques, which is critical for precise CRE detection at the highest energies. The results were published in two articles in Journal of Instrumentation. A preliminary measurement of the CRE spectrum using these techniques has been performed at unprecedentedly high (~10 TeV) energies —it is under internal review by the DAMPE collaboration.
The first measurements of inelastic hadronic cross sections of hydrogen and helium nuclei at TeV energies in space have been performed and consequently published in Physical Review D. They enable the reduction of hadronic uncertainties that dominate the precision of direct cosmic ray measurement in space at multi-TeV frontier. Among other, these results were highlighted in the recent cross-section-for-cosmic-ray community roadmap published in Physics Reports.
The work is accomplished by the team members on performing the Cosmic Ray proton and helium spectral measurement with DAMPE beyond the previously achieved ~100 TeV limit. These measurements became possible thanks to the AI techniques developed earlier the project, and employed the improved hadronic simulation models, obtained as the result of the proton/helium cross section measurements. These results were presented at multiple top-tier conferences in the field, and are currently submitted for publication in Nature.
For the first time, a Deep Learning (AI) solution is applied for cosmic ray reconstruction in space with astroparticle missions at the high energy frontier. Peer-reviewed results demonstrate drastic performance boost compared to the previous state-of-the-art methods. The developed AI paradigm finds its application beyond the original design goal, in the areas like energy reconstruction, gamma ray identification and more, indicative of its universality and transferability to other adjacent domains.
The project provides a unique measurement of properties of strong interactions which covers an energy and particle type range that cannot be probed with accelerator facilities or ground-based air-shower experiments. This result is of key importance not only for improving radically the precision of spaceborne cosmic ray instruments themselves, but similarly for ground-based cosmic ray detection facilities.
The AI and hadronic results lead to enhancement in both energy reach and accuracy of the cosmic ray measurements with the DAMPE mission. They constitute the core of the the biggest science discovery of the mission —observation of a universal structure at mult-TeV energies in all primary cosmic rays, from hydrogen to iron.
The project provides a unique measurement of properties of strong interactions which covers an energy and particle type range that cannot be probed with accelerator facilities or ground-based air-shower experiments. This result is of key importance not only for improving radically the precision of spaceborne cosmic ray instruments themselves, but similarly for ground-based cosmic ray detection facilities.
The AI and hadronic results lead to enhancement in both energy reach and accuracy of the cosmic ray measurements with the DAMPE mission. They constitute the core of the the biggest science discovery of the mission —observation of a universal structure at mult-TeV energies in all primary cosmic rays, from hydrogen to iron.