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author | tlatorre <tlatorre@uchicago.edu> | 2020-06-02 16:17:37 -0500 |
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committer | tlatorre <tlatorre@uchicago.edu> | 2020-06-02 16:17:37 -0500 |
commit | a76c9220dc5843630ce1ea648fe14a89bb1adb4b (patch) | |
tree | 3ee9c5bb13e5c19b62960c2416d84e3a2d5878dd /utils | |
parent | 9c8b5cd9ef0a359e617bb41488c24c414acce0a8 (diff) | |
download | sddm-a76c9220dc5843630ce1ea648fe14a89bb1adb4b.tar.gz sddm-a76c9220dc5843630ce1ea648fe14a89bb1adb4b.tar.bz2 sddm-a76c9220dc5843630ce1ea648fe14a89bb1adb4b.zip |
add an option to specify kinetic energy to gen-dark-matter
Diffstat (limited to 'utils')
-rwxr-xr-x | utils/gen-dark-matter | 13 |
1 files changed, 10 insertions, 3 deletions
diff --git a/utils/gen-dark-matter b/utils/gen-dark-matter index 04ffeee..c37650c 100755 --- a/utils/gen-dark-matter +++ b/utils/gen-dark-matter @@ -325,8 +325,10 @@ if __name__ == '__main__': parser = argparse.ArgumentParser("generate MCPL files for self destructing dark matter") parser.add_argument("-M", type=float, default=100.0, help="mass of mediator") - parser.add_argument("-E", type=float, default=100.0, + parser.add_argument("-E", type=float, default=None, help="total energy of mediator") + parser.add_argument("-T", type=float, default=0.0, + help="kinetic energy of mediator") parser.add_argument("-p1", type=int, default=20, help="SNOMAN particle ID for 1st decay product") parser.add_argument("-p2", type=int, default=21, @@ -353,7 +355,12 @@ if __name__ == '__main__': print("mediator mass must be greater than sum of decay product masses",file=sys.stderr) sys.exit(1) - if args.E < args.M: + if args.E is not None: + E = args.E + else: + E = args.T + args.M + + if E < args.M: print("mediator energy must be greater than or equal to the mass",file=sys.stderr) sys.exit(1) @@ -387,7 +394,7 @@ if __name__ == '__main__': with open(mcpl_filename, "w") as f: f.write("%i %i\n" % (args.n, 10)) - for v1, v2 in islice(gen_decay(args.M,args.E,m1,m2),args.n): + for v1, v2 in islice(gen_decay(args.M,E,m1,m2),args.n): pos = rand_ball(PSUP_RADIUS) p1 = np.linalg.norm(v1[1:]) p2 = np.linalg.norm(v2[1:]) |