Relativistic electrons from sparks in the laboratory

Discharge experiments were carried out at the Eindhoven University of Technology in 2013. The experimental setup was designed to search for electrons produced in meter-scale sparks using a 1 MV Marx generator. Negative voltage was applied to the high voltage (HV) electrode. Five thin (1 mm) plastic detectors (5 $\rm cm^2$ each) were distributed in various configurations close to the spark gap. Earlier studies have shown (for HV negative) that X-rays are produced when a cloud of streamers is developed 30-60 cm from the negative electrode. This indicates that the electrons producing the X-rays are also accelerated at this location, that could be in the strong electric field from counterstreamers of opposite polarity. Comparing our measurements with modeling results, we find that $\sim$300 keV electrons produced about 30-60 cm from the negative electrode are the most likely source of our measurements. A statistical analysis of expected detection of photon bursts by these fiber detectors indicates that only 20%-45% of the detected bursts could be from soft ($\sim$10 keV) photons, which further supports that the majority of detected bursts are produced by relativistic electrons

Evaluation of Monte Carlo tools for high-energy atmospheric physics II: Relativistic runaway electron avalanches

This work is distributed underthe Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)The emerging field of high-energy atmospheric physics studies how high-energy particles are produced in thunderstorms, in the form of terrestrial γ-ray flashes and γ-ray glows (also referred to as thunderstorm ground enhancements). Understanding these phenomena requires appropriate models of the interaction of electrons, positrons and photons with air molecules and electric fields. We investigated the results of three codes used in the community-Geant4, GRanada Relativistic Runaway simulator (GRRR) and Runaway Electron Avalanche Model (REAM)-to simulate relativistic runaway electron avalanches (RREAs). This work continues the study of Rutjes et al. (2016), now also including the effects of uniform electric fields, up to the classical breakdown field, which is about 3.0 MV m at standard temperature and pressure. We first present our theoretical description of the RREA process, which is based on and incremented over previous published works. This analysis confirmed that the avalanche is mainly driven by electric fields and the ionisation and scattering processes determining the minimum energy of electrons that can run away, which was found to be above ≈ 10 keV for any fields up to the classical breakdown field. To investigate this point further, we then evaluated the probability to produce a RREA as a function of the initial electron energy and of the magnitude of the electric field. We found that the stepping methodology in the particle simulation has to be set up very carefully in Geant4. For example, a too-large step size can lead to an avalanche probability reduced by a factor of 10 or to a 40 % overestimation of the average electron energy. When properly set up, both Geant4 models show an overall good agreement (within ≈ 10 %) with REAM and GRRR. Furthermore, the probability that particles below 10 keV accelerate and participate in the high-energy radiation is found to be negligible for electric fields below the classical breakdown value. The added value of accurately tracking low-energy particles (< 10 keV) is minor and mainly visible for fields above 2 MV m. In a second simulation set-up, we compared the physical characteristics of the avalanches produced by the four models: Avalanche (time and length) scales, convergence time to a self-similar state and energy spectra of photons and electrons. The two Geant4 models and REAM showed good agreement on all parameters we tested. GRRR was also found to be consistent with the other codes, except for the electron energy spectra. That is probably because GRRR does not include straggling for the radiative and ionisation energy losses; hence, implementing these two processes is of primary importance to produce accurate RREA spectra. Including precise modelling of the interactions of particles below 10 keV (e.g. by taking into account molecular binding energy of secondary electrons for impact ionisation) also produced only small differences in the recorded spectra. © 2018 Author(s).This work was supported by the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 320839 and the Research Council of Norway under contracts 208028/F50 and 223252/F50 (CoE). For part of the results of this work, it was necessary to use the Fram computer cluster of the UNINETT Sigma2 AS, under project no. NN9526K. Gabriel Diniz is supported by the Brazilian agency CAPES. Casper Rutjes acknowledges funding by FOM project no. 12PR3041, which also supported Gabriel Diniz's 12-month stay in the Netherlands. Ivan S. Ferreira thanks CNPqs grant PDE(234529/2014-08) and also FAPDF grant no. 0193.000868/2015, 03/2015. This material is based in part upon work supported by the Air Force Office of Scientific Research under award no. FA9550-16-1-0396. The authors would like to thank the two referees, Ashot Chilingarian and an anonymous referee, for their valuable comments and suggestions that helped to improve the quality of this work

Evaluation of Monte Carlo tools for high energy atmospheric physics

The emerging field of high energy atmospheric physics (HEAP) includes terrestrial gamma-ray flashes, electron–positron beams and gamma-ray glows from thunderstorms. Similar emissions of high energy particles occur in pulsed high voltage discharges. Understanding these phenomena requires appropriate models for the interaction of electrons, positrons and photons of up to 40 MeV energy with atmospheric air. In this paper, we benchmark the performance of the Monte Carlo codes Geant4, EGS5 and FLUKA developed in other fields of physics and of the custom-made codes GRRR and MC-PEPTITA against each other within the parameter regime relevant for high energy atmospheric physics. We focus on basic tests, namely on the evolution of monoenergetic and directed beams of electrons, positrons and photons with kinetic energies between 100 keV and 40 MeV through homogeneous air in the absence of electric and magnetic fields, using a low energy cutoff of 50 keV. We discuss important differences between the results of the different codes and provide plausible explanations. We also test the computational performance of the codes. The Supplement contains all results, providing a first benchmark for present and future custom-made codes that are more flexible in including electrodynamic interactions

Evaluation of Monte Carlo tools for high-energy atmospheric physics II: Relativistic runaway electron avalanches

The emerging field of high-energy atmospheric physics studies how high-energy particles are produced in thunderstorms, in the form of terrestrial γ-ray flashes and γ-ray glows (also referred to as thunderstorm ground enhancements). Understanding these phenomena requires appropriate models of the interaction of electrons, positrons and photons with air molecules and electric fields. We investigated the results of three codes used in the community-Geant4, GRanada Relativistic Runaway simulator (GRRR) and Runaway Electron Avalanche Model (REAM)-to simulate relativistic runaway electron avalanches (RREAs). This work continues the study of Rutjes et al. (2016), now also including the effects of uniform electric fields, up to the classical breakdown field, which is about 3.0 MV m-1 at standard temperature and pressure. We first present our theoretical description of the RREA process, which is based on and incremented over previous published works. This analysis confirmed that the avalanche is mainly driven by electric fields and the ionisation and scattering processes determining the minimum energy of electrons that can run away, which was found to be above ≈ 10 keV for any fields up to the classical breakdown field. To investigate this point further, we then evaluated the probability to produce a RREA as a function of the initial electron energy and of the magnitude of the electric field. We found that the stepping methodology in the particle simulation has to be set up very carefully in Geant4. For example, a too-large step size can lead to an avalanche probability reduced by a factor of 10 or to a 40 % overestimation of the average electron energy. When properly set up, both Geant4 models show an overall good agreement (within ≈ 10 %) with REAM and GRRR. Furthermore, the probability that particles below 10 keV accelerate and participate in the high-energy radiation is found to be negligible for electric fields below the classical breakdown value. The added value of accurately tracking low-energy particles (< 10 keV) is minor and mainly visible for fields above 2 MV m-1. In a second simulation set-up, we compared the physical characteristics of the avalanches produced by the four models: Avalanche (time and length) scales, convergence time to a self-similar state and energy spectra of photons and electrons. The two Geant4 models and REAM showed good agreement on all parameters we tested. GRRR was also found to be consistent with the other codes, except for the electron energy spectra. That is probably because GRRR does not include straggling for the radiative and ionisation energy losses; hence, implementing these two processes is of primary importance to produce accurate RREA spectra. Including precise modelling of the interactions of particles below 10 keV (e.g. by taking into account molecular binding energy of secondary electrons for impact ionisation) also produced only small differences in the recorded spectra

Bispecific T cell-engager targeting oncofetal chondroitin sulfate induces complete tumor regression and protective immune memory in mice

Abstract Background The malaria protein VAR2CSA binds oncofetal chondroitin sulfate (ofCS), a unique chondroitin sulfate, expressed on almost all mammalian cancer cells. Previously, we produced a bispecific construct targeting ofCS and human T cells based on VAR2CSA and anti-CD3 (V-aCD3Hu). V-aCD3Hu showed efficacy against xenografted tumors in immunocompromised mice injected with human immune cells at the tumor site. However, the complex effects potentially exerted by the immune system as a result of the treatment cannot occur in mice without an immune system. Here we investigate the efficacy of V-aCD3Mu as a monotherapy and combined with immune checkpoint inhibitors in mice with a fully functional immune system. Methods We produced a bispecific construct consisting of a recombinant version of VAR2CSA coupled to an anti-murine CD3 single-chain variable fragment. Flow cytometry and ELISA were used to check cell binding capabilities and the therapeutic effect was evaluated in vitro in a killing assay. The in vivo efficacy of V-aCD3Mu was then investigated in mice with a functional immune system and established or primary syngeneic tumors in the immunologically “cold” 4T1 mammary carcinoma, B16-F10 malignant melanoma, the pancreatic KPC mouse model, and in the immunologically “hot” CT26 colon carcinoma model. Results V-aCD3Mu had efficacy as a monotherapy, and the combined treatment of V-aCD3Mu and an immune checkpoint inhibitor showed enhanced effects resulting in the complete elimination of solid tumors in the 4T1, B16-F10, and CT26 models. This anti-tumor effect was abscopal and accompanied by a systemic increase in memory and activated cytotoxic and helper T cells. The combined treatment also led to a higher percentage of memory T cells in the tumor without an increase in regulatory T cells. In addition, we observed partial protection against re-challenge in a melanoma model and full protection in a breast cancer model. Conclusions Our findings suggest that V-aCD3Mu combined with an immune checkpoint inhibitor renders immunologically “cold” tumors “hot” and results in tumor elimination. Taken together, these data provide proof of concept for the further clinical development of V-aCD3 as a broad cancer therapy in combination with an immune checkpoint inhibitor