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15 """Classes for diagram generation with loop features.
16 """
17
18 import array
19 import copy
20 import itertools
21 import logging
22
23 import madgraph.loop.loop_base_objects as loop_base_objects
24 import madgraph.core.base_objects as base_objects
25 import madgraph.core.diagram_generation as diagram_generation
26 import madgraph.various.misc as misc
27
28 from madgraph import MadGraph5Error
29 from madgraph import InvalidCmd
30 logger = logging.getLogger('madgraph.loop_diagram_generation')
33
34
35
36 if not force: return
37
38 flag = "LoopGenInfo: "
39 if len(msg)>40:
40 logger.debug(flag+msg[:35]+" [...] = %s"%str(val))
41 else:
42 logger.debug(flag+msg+''.join([' ']*(40-len(msg)))+' = %s'%str(val))
43
48 """NLOAmplitude: process + list of diagrams (ordered)
49 Initialize with a process, then call generate_diagrams() to
50 generate the diagrams for the amplitude
51 """
52
76
77 - def __init__(self, argument=None, loop_filter=None):
94
96 """Return diagram property names as a nicely sorted list."""
97
98 return ['process', 'diagrams', 'has_mirror_process', 'born_diagrams',
99 'loop_diagrams','has_born',
100 'structure_repository']
101
102 - def filter(self, name, value):
103 """Filter for valid amplitude property values."""
104
105 if name == 'diagrams':
106 if not isinstance(value, base_objects.DiagramList):
107 raise self.PhysicsObjectError, \
108 "%s is not a valid DiagramList" % str(value)
109 for diag in value:
110 if not isinstance(diag,loop_base_objects.LoopDiagram) and \
111 not isinstance(diag,loop_base_objects.LoopUVCTDiagram):
112 raise self.PhysicsObjectError, \
113 "%s contains a diagram which is not an NLODiagrams." % str(value)
114 if name == 'born_diagrams':
115 if not isinstance(value, base_objects.DiagramList):
116 raise self.PhysicsObjectError, \
117 "%s is not a valid DiagramList" % str(value)
118 for diag in value:
119 if not isinstance(diag,loop_base_objects.LoopDiagram):
120 raise self.PhysicsObjectError, \
121 "%s contains a diagram which is not an NLODiagrams." % str(value)
122 if name == 'loop_diagrams':
123 if not isinstance(value, base_objects.DiagramList):
124 raise self.PhysicsObjectError, \
125 "%s is not a valid DiagramList" % str(value)
126 for diag in value:
127 if not isinstance(diag,loop_base_objects.LoopDiagram):
128 raise self.PhysicsObjectError, \
129 "%s contains a diagram which is not an NLODiagrams." % str(value)
130 if name == 'has_born':
131 if not isinstance(value, bool):
132 raise self.PhysicsObjectError, \
133 "%s is not a valid bool" % str(value)
134 if name == 'structure_repository':
135 if not isinstance(value, loop_base_objects.FDStructureList):
136 raise self.PhysicsObjectError, \
137 "%s is not a valid bool" % str(value)
138
139 else:
140 super(LoopAmplitude, self).filter(name, value)
141
142 return True
143
144 - def set(self, name, value):
160
161 - def get(self, name):
162 """Redefine get for the particular case of '*_diagrams' property"""
163
164 if name == 'diagrams':
165 if self['process'] and self['loop_diagrams'] == None:
166 self.generate_diagrams()
167 return base_objects.DiagramList(self['born_diagrams']+\
168 self['loop_diagrams']+\
169 self['loop_UVCT_diagrams'])
170
171 if name == 'born_diagrams':
172 if self['born_diagrams'] == None:
173
174 if self['process']['has_born']:
175 if self['process']:
176 self.generate_born_diagrams()
177 else:
178 self['born_diagrams']=base_objects.DiagramList()
179
180 return LoopAmplitude.__bases__[0].get(self, name)
181
182
184 """ Choose the configuration of non-perturbed coupling orders to be
185 retained for all diagrams. This is used when the user did not specify
186 any order. """
187 chosen_order_config = {}
188 min_wgt = self['born_diagrams'].get_min_order('WEIGHTED')
189
190
191 min_non_pert_order_wgt = -1
192 for diag in [d for d in self['born_diagrams'] if \
193 d.get_order('WEIGHTED')==min_wgt]:
194 non_pert_order_wgt = min_wgt - sum([diag.get_order(order)*\
195 self['process']['model']['order_hierarchy'][order] for order in \
196 self['process']['perturbation_couplings']])
197 if min_non_pert_order_wgt == -1 or \
198 non_pert_order_wgt<min_non_pert_order_wgt:
199 chosen_order_config = self.get_non_pert_order_config(diag)
200 logger.info("Chosen coupling orders configuration: (%s)"\
201 %self.print_config(chosen_order_config))
202 return chosen_order_config
203
205 """If squared orders (other than WEIGHTED) are defined, then they can be
206 used for determining what is the expected upper bound for the order
207 restricting loop diagram generation."""
208 for order, value in self['process']['squared_orders'].items():
209 if order.upper()!='WEIGHTED' and order not in self['process']['orders']:
210
211 if self['process'].get('sqorders_types')[order]=='>':
212 continue
213
214 bornminorder=self['born_diagrams'].get_min_order(order)
215 if value>=0:
216 self['process']['orders'][order]=value-bornminorder
217 elif self['process']['has_born']:
218
219
220
221
222
223 self['process']['orders'][order]=bornminorder+2*(-value-1)
224
226 """Guess the upper bound for the orders for loop diagram generation
227 based on either no squared orders or simply 'Weighted'"""
228
229 hierarchy = self['process']['model']['order_hierarchy']
230
231
232 max_pert_wgt = max([hierarchy[order] for order in \
233 self['process']['perturbation_couplings']])
234
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240 user_min_wgt = 0
241
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248
249 min_born_wgt=max(self['born_diagrams'].get_min_order('WEIGHTED'),
250 sum([hierarchy[order]*val for order, val in user_orders.items() \
251 if order!='WEIGHTED']))
252
253 if 'WEIGHTED' not in [key.upper() for key in \
254 self['process']['squared_orders'].keys()]:
255
256 self['process']['squared_orders']['WEIGHTED']= 2*(min_born_wgt+\
257 max_pert_wgt)
258
259
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263
264
265 if self['process']['squared_orders']['WEIGHTED']>=0:
266 trgt_wgt=self['process']['squared_orders']['WEIGHTED']-min_born_wgt
267 else:
268 trgt_wgt=min_born_wgt+(-self['process']['squared_orders']['WEIGHTED']+1)*2
269
270 min_nvert=min([len([1 for vert in diag['vertices'] if vert['id']!=0]) \
271 for diag in self['born_diagrams']])
272
273 min_pert=min([hierarchy[order] for order in \
274 self['process']['perturbation_couplings']])
275
276 for order, value in hierarchy.items():
277 if order not in self['process']['orders']:
278
279
280
281 if order in self['process']['perturbation_couplings']:
282 if value!=1:
283 self['process']['orders'][order]=\
284 int((trgt_wgt-min_nvert-2)/(value-1))
285 else:
286 self['process']['orders'][order]=int(trgt_wgt)
287 else:
288 if value!=1:
289 self['process']['orders'][order]=\
290 int((trgt_wgt-min_nvert-2*min_pert)/(value-1))
291 else:
292 self['process']['orders'][order]=\
293 int(trgt_wgt-2*min_pert)
294
295
296
297
298
299 for order in self['process']['model']['coupling_orders']:
300 neworder=self['born_diagrams'].get_max_order(order)
301 if order in self['process']['perturbation_couplings']:
302 neworder+=2
303 if order not in self['process']['orders'].keys() or \
304 neworder<self['process']['orders'][order]:
305 self['process']['orders'][order]=neworder
306
308 """ Filter diags to select only the diagram with the non perturbed orders
309 configuration config and update discarded_configurations.Diags is the
310 name of the key attribute of this class containing the diagrams to
311 filter."""
312 newdiagselection = base_objects.DiagramList()
313 for diag in self[diags]:
314 diag_config = self.get_non_pert_order_config(diag)
315 if diag_config == config:
316 newdiagselection.append(diag)
317 elif diag_config not in discarded_configurations:
318 discarded_configurations.append(diag_config)
319 self[diags] = newdiagselection
320
322 """ Remove the loops which are zero because of Furry theorem. So as to
323 limit any possible mistake in case of BSM model, I limit myself here to
324 removing SM-quark loops with external legs with an odd number of photons,
325 possibly including exactly two gluons."""
326
327 new_diag_selection = base_objects.DiagramList()
328
329 n_discarded = 0
330 for diag in self['loop_diagrams']:
331 if diag.get('tag')==[]:
332 raise MadGraph5Error, "The loop diagrams should have been tagged"+\
333 " before going through the Furry filter."
334
335 loop_line_pdgs = diag.get_loop_lines_pdgs()
336 attached_pdgs = diag.get_pdgs_attached_to_loop(structs)
337 if (attached_pdgs.count(22)%2==1) and \
338 (attached_pdgs.count(21) in [0,2]) and \
339 (all(pdg in [22,21] for pdg in attached_pdgs)) and \
340 (abs(loop_line_pdgs[0]) in list(range(1,7))) and \
341 (all(abs(pdg)==abs(loop_line_pdgs[0]) for pdg in loop_line_pdgs)):
342 n_discarded += 1
343 else:
344 new_diag_selection.append(diag)
345
346 self['loop_diagrams'] = new_diag_selection
347
348 if n_discarded > 0:
349 logger.debug(("MadLoop discarded %i diagram%s because they appeared"+\
350 " to be zero because of Furry theorem.")%(n_discarded,'' if \
351 n_discarded<=1 else 's'))
352
353 @staticmethod
355 """ Returns a function which applies the filter corresponding to the
356 conditional expression encoded in filterdef."""
357
358 def filter(diag, structs, model, id):
359 """ The filter function generated '%s'."""%filterdef
360
361 loop_pdgs = diag.get_loop_lines_pdgs()
362 struct_pdgs = diag.get_pdgs_attached_to_loop(structs)
363 loop_masses = [model.get_particle(pdg).get('mass') for pdg in loop_pdgs]
364 struct_masses = [model.get_particle(pdg).get('mass') for pdg in struct_pdgs]
365 if not eval(filterdef.lower(),{'n':len(loop_pdgs),
366 'loop_pdgs':loop_pdgs,
367 'struct_pdgs':struct_pdgs,
368 'loop_masses':loop_masses,
369 'struct_masses':struct_masses,
370 'id':id}):
371 return False
372 else:
373 return True
374
375 return filter
376
378 """ User-defined user-filter. By default it is not called, but the expert
379 user can turn it on and code here is own filter. Some default examples
380 are provided here.
381 The tagging of the loop diagrams must be performed before using this
382 user loop filter"""
383
384
385
386
387 edit_filter_manually = False
388 if not edit_filter_manually and filter in [None,'None']:
389 return
390 if isinstance(filter,str) and filter.lower() == 'true':
391 edit_filter_manually = True
392 filter=None
393
394
395 if filter not in [None,'None']:
396 filter_func = LoopAmplitude.get_loop_filter(filter)
397 else:
398 filter_func = None
399
400 new_diag_selection = base_objects.DiagramList()
401 discarded_diags = base_objects.DiagramList()
402 i=0
403 for diag in self['loop_diagrams']:
404 if diag.get('tag')==[]:
405 raise MadGraph5Error, "Before using the user_filter, please "+\
406 "make sure that the loop diagrams have been tagged first."
407 valid_diag = True
408 i=i+1
409
410
411 if filter_func:
412 try:
413 valid_diag = filter_func(diag, structs, model, i)
414 except Exception as e:
415 raise InvalidCmd("The user-defined filter '%s' did not"%filter+
416 " returned the following error:\n > %s"%str(e))
417
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481
482 if valid_diag:
483 new_diag_selection.append(diag)
484 else:
485 discarded_diags.append(diag)
486
487 self['loop_diagrams'] = new_diag_selection
488 if filter in [None,'None']:
489 warn_msg = """
490 The user-defined loop diagrams filter is turned on and discarded %d loops."""\
491 %len(discarded_diags)
492 else:
493 warn_msg = """
494 The loop diagrams filter '%s' is turned on and discarded %d loops."""\
495 %(filter,len(discarded_diags))
496 logger.warning(warn_msg)
497
499 """ Filter the loop diagrams to make sure they belong to the class
500 of coupling orders perturbed. """
501
502
503 allowedpart=[]
504 for part in self['process']['model']['particles']:
505 for order in self['process']['perturbation_couplings']:
506 if part.is_perturbating(order,self['process']['model']):
507 allowedpart.append(part.get_pdg_code())
508 break
509
510 newloopselection=base_objects.DiagramList()
511 warned=False
512 warning_msg = ("Some loop diagrams contributing to this process"+\
513 " are discarded because they are not pure (%s)-perturbation.\nMake sure"+\
514 " you did not want to include them.")%\
515 ('+'.join(self['process']['perturbation_couplings']))
516 for i,diag in enumerate(self['loop_diagrams']):
517
518
519 loop_orders=diag.get_loop_orders(self['process']['model'])
520 pert_loop_order=set(loop_orders.keys()).intersection(\
521 set(self['process']['perturbation_couplings']))
522
523
524
525
526 valid_diag=True
527 if (diag.get_loop_line_types()-set(allowedpart))!=set() or \
528 pert_loop_order==set([]):
529 valid_diag=False
530 if not warned:
531 logger.warning(warning_msg)
532 warned=True
533 if len([col for col in [
534 self['process'].get('model').get_particle(pdg).get('color') \
535 for pdg in diag.get_pdgs_attached_to_loop(\
536 self['structure_repository'])] if col!=1])==1:
537 valid_diag=False
538
539 if valid_diag:
540 newloopselection.append(diag)
541 self['loop_diagrams']=newloopselection
542
543
544
545
546
548 """ Makes sure that all non perturbed orders factorize the born diagrams
549 """
550 warning_msg = "All Born diagrams do not factorize the same sum of power(s) "+\
551 "of the the perturbed order(s) %s.\nThis is potentially dangerous"+\
552 " as the real-emission diagrams from aMC@NLO will not be consistent"+\
553 " with these virtual contributions."
554 if self['process']['has_born']:
555 trgt_summed_order = sum([self['born_diagrams'][0].get_order(order)
556 for order in self['process']['perturbation_couplings']])
557 for diag in self['born_diagrams'][1:]:
558 if sum([diag.get_order(order) for order in self['process']
559 ['perturbation_couplings']])!=trgt_summed_order:
560 logger.warning(warning_msg%' '.join(self['process']
561 ['perturbation_couplings']))
562 break
563
564 warning_msg = "All born diagrams do not factorize the same power of "+\
565 "the order %s which is not perturbed and for which you have not"+\
566 "specified any amplitude order. \nThis is potentially dangerous"+\
567 " as the real-emission diagrams from aMC@NLO will not be consistent"+\
568 " with these virtual contributions."
569 if self['process']['has_born']:
570 for order in self['process']['model']['coupling_orders']:
571 if order not in self['process']['perturbation_couplings'] and \
572 order not in user_orders.keys():
573 order_power=self['born_diagrams'][0].get_order(order)
574 for diag in self['born_diagrams'][1:]:
575 if diag.get_order(order)!=order_power:
576 logger.warning(warning_msg%order)
577 break
578
579
581 """ Return a dictionary of all the coupling orders of this diagram which
582 are not the perturbed ones."""
583 return dict([(order, diagram.get_order(order)) for \
584 order in self['process']['model']['coupling_orders'] if \
585 not order in self['process']['perturbation_couplings'] ])
586
588 """Return a string describing the coupling order configuration"""
589 res = []
590 for order in self['process']['model']['coupling_orders']:
591 try:
592 res.append('%s=%d'%(order,config[order]))
593 except KeyError:
594 res.append('%s=*'%order)
595 return ','.join(res)
596
598 """ Generates all diagrams relevant to this Loop Process """
599
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621
622 if (not self.loop_filter is None) and (loop_filter is None):
623 loop_filter = self.loop_filter
624
625 logger.debug("Generating %s "\
626 %self['process'].nice_string().replace('Process', 'process'))
627
628
629 model = self['process']['model']
630 hierarchy = model['order_hierarchy']
631
632
633
634
635 user_orders=copy.copy(self['process']['orders'])
636
637 if self['process']['has_born']:
638 bornsuccessful = self.generate_born_diagrams()
639 ldg_debug_info("# born diagrams after first generation",\
640 len(self['born_diagrams']))
641 else:
642 self['born_diagrams'] = base_objects.DiagramList()
643 bornsuccessful = True
644 logger.debug("Born diagrams generation skipped by user request.")
645
646
647 for order in self['process']['orders'].keys()+\
648 self['process']['squared_orders'].keys():
649 if not order in model.get('coupling_orders') and \
650 order != 'WEIGHTED':
651 raise InvalidCmd("Coupling order %s not found"%order +\
652 " in any interaction of the current model %s."%model['name'])
653
654
655
656
657 if self['process']['has_born']:
658 self['process']['has_born'] = self['born_diagrams']!=[]
659 self['has_born'] = self['process']['has_born']
660
661 ldg_debug_info("User input born orders",self['process']['orders'])
662 ldg_debug_info("User input squared orders",
663 self['process']['squared_orders'])
664 ldg_debug_info("User input perturbation",\
665 self['process']['perturbation_couplings'])
666
667
668
669
670
671 user_orders=copy.copy(self['process']['orders'])
672 user_squared_orders=copy.copy(self['process']['squared_orders'])
673
674
675
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678
679
680 chosen_order_config={}
681 if self['process']['squared_orders']=={} and \
682 self['process']['orders']=={} and self['process']['has_born']:
683 chosen_order_config = self.choose_order_config()
684
685 discarded_configurations = []
686
687 if chosen_order_config != {}:
688 self.filter_from_order_config('born_diagrams', \
689 chosen_order_config,discarded_configurations)
690
691
692
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696
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698
699
700
701 self.check_factorization(user_orders)
702
703
704 self.guess_loop_orders_from_squared()
705
706
707
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710
711
712
713 if [k.upper() for k in self['process']['squared_orders'].keys()] in \
714 [[],['WEIGHTED']] and self['process']['has_born']:
715 self.guess_loop_orders(user_orders)
716
717
718
719
720 for order in user_orders.keys():
721 if order in self['process']['perturbation_couplings']:
722 self['process']['orders'][order]=user_orders[order]+2
723 else:
724 self['process']['orders'][order]=user_orders[order]
725 if 'WEIGHTED' in user_orders.keys():
726 self['process']['orders']['WEIGHTED']=user_orders['WEIGHTED']+\
727 2*min([hierarchy[order] for order in \
728 self['process']['perturbation_couplings']])
729
730 ldg_debug_info("Orders used for loop generation",\
731 self['process']['orders'])
732
733
734
735 warning_msg = ("Some loop diagrams contributing to this process might "+\
736 "be discarded because they are not pure (%s)-perturbation.\nMake sure"+\
737 " there are none or that you did not want to include them.")%(\
738 ','.join(self['process']['perturbation_couplings']))
739
740 if self['process']['has_born']:
741 for order in model['coupling_orders']:
742 if order not in self['process']['perturbation_couplings']:
743 try:
744 if self['process']['orders'][order]< \
745 self['born_diagrams'].get_max_order(order):
746 logger.warning(warning_msg)
747 break
748 except KeyError:
749 pass
750
751
752 totloopsuccessful=self.generate_loop_diagrams()
753
754
755 if not self['process']['has_born'] and not self['loop_diagrams']:
756 self['process']['orders'].clear()
757 self['process']['orders'].update(user_orders)
758 return False
759
760
761
762
763 if self['process']['has_born']:
764 self.set_Born_CT()
765
766 ldg_debug_info("#UVCTDiags generated",len(self['loop_UVCT_diagrams']))
767
768
769 self['process']['orders'].clear()
770 self['process']['orders'].update(user_orders)
771
772
773
774
775 if not self['process']['has_born'] and not \
776 self['process']['squared_orders'] and not\
777 self['process']['orders'] and hierarchy:
778 pert_order_weights=[hierarchy[order] for order in \
779 self['process']['perturbation_couplings']]
780 self['process']['squared_orders']['WEIGHTED']=2*(\
781 self['loop_diagrams'].get_min_order('WEIGHTED')+\
782 max(pert_order_weights)-min(pert_order_weights))
783
784 ldg_debug_info("Squared orders after treatment",\
785 self['process']['squared_orders'])
786 ldg_debug_info("#Diags after diagram generation",\
787 len(self['loop_diagrams']))
788
789
790
791
792
793
794 if chosen_order_config != {}:
795 self.filter_from_order_config('loop_diagrams', \
796 chosen_order_config,discarded_configurations)
797
798 if discarded_configurations!=[]:
799 msg = ("The contribution%s of th%s coupling orders "+\
800 "configuration%s %s discarded :%s")%(('s','ese','s','are','\n')\
801 if len(discarded_configurations)>1 else ('','is','','is',' '))
802 msg = msg + '\n'.join(['(%s)'%self.print_config(conf) for conf \
803 in discarded_configurations])
804 msg = msg + "\nManually set the coupling orders to "+\
805 "generate %sthe contribution%s above."%(('any of ','s') if \
806 len(discarded_configurations)>1 else ('',''))
807 logger.info(msg)
808
809
810
811
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813
814
815 regular_constraints = dict([(key,val) for (key,val) in
816 self['process']['squared_orders'].items() if val>=0])
817 negative_constraints = dict([(key,val) for (key,val) in
818 self['process']['squared_orders'].items() if val<0])
819 while True:
820 ndiag_remaining=len(self['loop_diagrams']+self['born_diagrams'])
821 self.check_squared_orders(regular_constraints)
822 if len(self['loop_diagrams']+self['born_diagrams'])==ndiag_remaining:
823 break
824
825 if negative_constraints!={}:
826
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834 self.check_squared_orders(negative_constraints,user_squared_orders)
835
836 ldg_debug_info("#Diags after constraints",len(self['loop_diagrams']))
837 ldg_debug_info("#Born diagrams after constraints",len(self['born_diagrams']))
838 ldg_debug_info("#UVCTDiags after constraints",len(self['loop_UVCT_diagrams']))
839
840
841 tag_selected=[]
842 loop_basis=base_objects.DiagramList()
843 for diag in self['loop_diagrams']:
844 diag.tag(self['structure_repository'],model)
845
846
847 if not diag.is_wf_correction(self['structure_repository'], \
848 model) and not diag.is_vanishing_tadpole(model) and \
849 diag['canonical_tag'] not in tag_selected:
850 loop_basis.append(diag)
851 tag_selected.append(diag['canonical_tag'])
852
853 self['loop_diagrams']=loop_basis
854
855
856
857 self.filter_loop_for_perturbative_orders()
858
859 if len(self['loop_diagrams'])==0 and len(self['born_diagrams'])!=0:
860 raise InvalidCmd('All loop diagrams discarded by user selection.\n'+\
861 'Consider using a tree-level generation or relaxing the coupling'+\
862 ' order constraints.')
863
864 if not self['process']['has_born'] and not self['loop_diagrams']:
865 self['process']['squared_orders'].clear()
866 self['process']['squared_orders'].update(user_squared_orders)
867 return False
868
869
870
871 self.remove_Furry_loops(model,self['structure_repository'])
872
873
874
875
876
877 self.user_filter(model,self['structure_repository'], filter=loop_filter)
878
879
880 self.set_LoopCT_vertices()
881
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885
886
887
888
889
890
891
892 self['process']['squared_orders'].clear()
893 self['process']['squared_orders'].update(user_squared_orders)
894
895
896
897 self.print_split_order_infos()
898
899
900 nLoopDiag = 0
901 nCT={'UV':0,'R2':0}
902 for ldiag in self['loop_UVCT_diagrams']:
903 nCT[ldiag['type'][:2]]+=len(ldiag['UVCT_couplings'])
904 for ldiag in self['loop_diagrams']:
905 nLoopDiag+=1
906 nCT['UV']+=len(ldiag.get_CT(model,'UV'))
907 nCT['R2']+=len(ldiag.get_CT(model,'R2'))
908
909
910
911
912 nLoopsIdentified = self.identify_loop_diagrams()
913 if nLoopsIdentified > 0:
914 logger.debug("A total of %d loop diagrams "%nLoopsIdentified+\
915 "were identified with equivalent ones.")
916 logger.info("Contributing diagrams generated: "+\
917 "%d Born, %d%s loops, %d R2, %d UV"%(len(self['born_diagrams']),
918 len(self['loop_diagrams']),'(+%d)'%nLoopsIdentified \
919 if nLoopsIdentified>0 else '' ,nCT['R2'],nCT['UV']))
920
921 ldg_debug_info("#Diags after filtering",len(self['loop_diagrams']))
922 ldg_debug_info("# of different structures identified",\
923 len(self['structure_repository']))
924
925 return (bornsuccessful or totloopsuccessful)
926
928 """ Uses a loop_tag characterizing the loop with only physical
929 information about it (mass, coupling, width, color, etc...) so as to
930 recognize numerically equivalent diagrams and group them together,
931 such as massless quark loops in pure QCD gluon loop amplitudes."""
932
933
934
935
936
937
938
939
940
941 diagram_identification = {}
942
943 for i, loop_diag in enumerate(self['loop_diagrams']):
944 loop_tag = loop_diag.build_loop_tag_for_diagram_identification(
945 self['process']['model'], self.get('structure_repository'),
946 use_FDStructure_ID_for_tag = True)
947
948
949
950 try:
951 diagram_identification[loop_tag].append((i+1,loop_diag))
952 except KeyError:
953 diagram_identification[loop_tag] = [(i+1,loop_diag)]
954
955
956 sorted_loop_tag_keys = sorted(diagram_identification.keys(),
957 key=lambda k:diagram_identification[k][0][0])
958
959 new_loop_diagram_base = base_objects.DiagramList([])
960 n_loops_identified = 0
961 for loop_tag in sorted_loop_tag_keys:
962 n_diag_in_class = len(diagram_identification[loop_tag])
963 n_loops_identified += n_diag_in_class-1
964 new_loop_diagram_base.append(diagram_identification[loop_tag][0][1])
965
966
967 new_loop_diagram_base[-1]['multiplier'] = n_diag_in_class
968 for ldiag in diagram_identification[loop_tag][1:]:
969 new_loop_diagram_base[-1].get('CT_vertices').extend(
970 copy.copy(ldiag[1].get('CT_vertices')))
971 if n_diag_in_class > 1:
972 ldg_debug_info("# Diagram equivalence class detected","#(%s) -> #%d"\
973 %(','.join('%d'%diag[0] for diag in diagram_identification[loop_tag][1:])+
974 (',' if n_diag_in_class==2 else ''),diagram_identification[loop_tag][0][0]))
975
976
977 self.set('loop_diagrams',new_loop_diagram_base)
978 return n_loops_identified
979
981 """This function is solely for monitoring purposes. It reports what are
982 the coupling order combination which are obtained with the diagram
983 genarated and among those which ones correspond to those selected by
984 the process definition and which ones are the extra combinations which
985 comes as a byproduct of the computation of the desired one. The typical
986 example is that if you ask for d d~ > u u~ QCD^2==2 [virt=QCD, QED],
987 you will not only get (QCD,QED)=(2,2);(2,4) which are the desired ones
988 but the code output will in principle also be able to return
989 (QCD,QED)=(4,0);(4,2);(0,4);(0,6) because they involve the same amplitudes
990 """
991
992 hierarchy = self['process']['model']['order_hierarchy']
993
994 sqorders_types=copy.copy(self['process'].get('sqorders_types'))
995
996
997 if 'WEIGHTED' not in sqorders_types:
998 sqorders_types['WEIGHTED']='<='
999
1000 sorted_hierarchy = [order[0] for order in \
1001 sorted(hierarchy.items(), key=lambda el: el[1])]
1002
1003 loop_SOs = set(tuple([d.get_order(order) for order in sorted_hierarchy])
1004 for d in self['loop_diagrams']+self['loop_UVCT_diagrams'])
1005
1006 if self['process']['has_born']:
1007 born_SOs = set(tuple([d.get_order(order) for order in \
1008 sorted_hierarchy]) for d in self['born_diagrams'])
1009 else:
1010 born_SOs = set([])
1011
1012 born_sqSOs = set(tuple([x + y for x, y in zip(b1_SO, b2_SO)]) for b1_SO
1013 in born_SOs for b2_SO in born_SOs)
1014 if self['process']['has_born']:
1015 ref_amps = born_SOs
1016 else:
1017 ref_amps = loop_SOs
1018 loop_sqSOs = set(tuple([x + y for x, y in zip(b_SO, l_SO)]) for b_SO in
1019 ref_amps for l_SO in loop_SOs)
1020
1021
1022 sorted_hierarchy.append('WEIGHTED')
1023 born_sqSOs = sorted([b_sqso+(sum([b*hierarchy[sorted_hierarchy[i]] for
1024 i, b in enumerate(b_sqso)]),) for b_sqso in born_sqSOs],
1025 key=lambda el: el[1])
1026 loop_sqSOs = sorted([l_sqso+(sum([l*hierarchy[sorted_hierarchy[i]] for
1027 i, l in enumerate(l_sqso)]),) for l_sqso in loop_sqSOs],
1028 key=lambda el: el[1])
1029
1030
1031 logger.debug("Coupling order combinations considered:"+\
1032 " (%s)"%','.join(sorted_hierarchy))
1033
1034
1035 born_considered = []
1036 loop_considered = []
1037 for i, sqSOList in enumerate([born_sqSOs,loop_sqSOs]):
1038 considered = []
1039 extra = []
1040 for sqSO in sqSOList:
1041 for sqo, constraint in self['process']['squared_orders'].items():
1042 sqo_index = sorted_hierarchy.index(sqo)
1043
1044
1045
1046 if (sqorders_types[sqo]=='==' and
1047 sqSO[sqo_index]!=constraint ) or \
1048 (sqorders_types[sqo] in ['=','<='] and
1049 sqSO[sqo_index]>constraint) or \
1050 (sqorders_types[sqo] in ['>'] and
1051 sqSO[sqo_index]<=constraint):
1052 extra.append(sqSO)
1053 break;
1054
1055
1056 considered = [sqSO for sqSO in sqSOList if sqSO not in extra]
1057
1058 if i==0:
1059 born_considered = considered
1060 name = "Born"
1061 if not self['process']['has_born']:
1062 logger.debug(" > No Born contributions for this process.")
1063 continue
1064 elif i==1:
1065 loop_considered = considered
1066 name = "loop"
1067
1068 if len(considered)==0:
1069 logger.debug(" > %s : None"%name)
1070 else:
1071 logger.debug(" > %s : %s"%(name,' '.join(['(%s,W%d)'%(
1072 ','.join(list('%d'%s for s in c[:-1])),c[-1])
1073 for c in considered])))
1074
1075 if len(extra)!=0:
1076 logger.debug(" > %s (not selected but available): %s"%(name,' '.
1077 join(['(%s,W%d)'%(','.join(list('%d'%s for s in e[:-1])),
1078 e[-1]) for e in extra])))
1079
1080
1081
1082 return (born_considered,
1083 [sqSO for sqSO in born_sqSOs if sqSO not in born_considered],
1084 loop_considered,
1085 [sqSO for sqSO in loop_sqSOs if sqSO not in loop_considered])
1086
1087
1095
1097 """ Generates all loop diagrams relevant to this NLO Process """
1098
1099
1100 self['loop_diagrams']=base_objects.DiagramList()
1101 totloopsuccessful=False
1102
1103
1104 self.lcutpartemployed=[]
1105
1106 for order in self['process']['perturbation_couplings']:
1107 ldg_debug_info("Perturbation coupling generated now ",order)
1108 lcutPart=[particle for particle in \
1109 self['process']['model']['particles'] if \
1110 (particle.is_perturbating(order, self['process']['model']) and \
1111 particle.get_pdg_code() not in \
1112 self['process']['forbidden_particles'])]
1113
1114
1115 for part in lcutPart:
1116 if part.get_pdg_code() not in self.lcutpartemployed:
1117
1118
1119
1120
1121
1122
1123
1124
1125 ldg_debug_info("Generating loop diagram with L-cut type",\
1126 part.get_name())
1127 lcutone=base_objects.Leg({'id': part.get_pdg_code(),
1128 'state': True,
1129 'loop_line': True})
1130 lcuttwo=base_objects.Leg({'id': part.get_anti_pdg_code(),
1131 'state': True,
1132 'loop_line': True})
1133 self['process'].get('legs').extend([lcutone,lcuttwo])
1134
1135
1136
1137
1138
1139
1140
1141 loopsuccessful, lcutdiaglist = \
1142 super(LoopAmplitude, self).generate_diagrams(True)
1143
1144
1145 leg_to_remove=[leg for leg in self['process']['legs'] \
1146 if leg['loop_line']]
1147 for leg in leg_to_remove:
1148 self['process']['legs'].remove(leg)
1149
1150
1151 for diag in lcutdiaglist:
1152 diag.set('type',part.get_pdg_code())
1153 self['loop_diagrams']+=lcutdiaglist
1154
1155
1156
1157 self.lcutpartemployed.append(part.get_pdg_code())
1158 self.lcutpartemployed.append(part.get_anti_pdg_code())
1159
1160 ldg_debug_info("#Diags generated w/ this L-cut particle",\
1161 len(lcutdiaglist))
1162
1163 if loopsuccessful:
1164 totloopsuccessful=True
1165
1166
1167 self.lcutpartemployed=[]
1168
1169 return totloopsuccessful
1170
1171
1173 """ Scan all born diagrams and add for each all the corresponding UV
1174 counterterms. It creates one LoopUVCTDiagram per born diagram and set
1175 of possible coupling_order (so that QCD and QED wavefunction corrections
1176 are not in the same LoopUVCTDiagram for example). Notice that this takes
1177 care only of the UV counterterm which factorize with the born and the
1178 other contributions like the UV mass renormalization are added in the
1179 function setLoopCTVertices"""
1180
1181
1182
1183
1184
1185
1186
1187
1188 UVCTvertex_interactions = base_objects.InteractionList()
1189 for inter in self['process']['model']['interactions'].get_UV():
1190 if inter.is_UVtree() and len(inter['particles'])>1 and \
1191 inter.is_perturbating(self['process']['perturbation_couplings']) \
1192 and (set(inter['orders'].keys()).intersection(\
1193 set(self['process']['perturbation_couplings'])))!=set([]) and \
1194 (any([set(loop_parts).intersection(set(self['process']\
1195 ['forbidden_particles']))==set([]) for loop_parts in \
1196 inter.get('loop_particles')]) or \
1197 inter.get('loop_particles')==[[]]):
1198 UVCTvertex_interactions.append(inter)
1199
1200
1201 self['process']['model'].get('order_hierarchy')['UVCT_SPECIAL']=0
1202 self['process']['model'].get('coupling_orders').add('UVCT_SPECIAL')
1203 for inter in UVCTvertex_interactions:
1204 neworders=copy.copy(inter.get('orders'))
1205 neworders['UVCT_SPECIAL']=1
1206 inter.set('orders',neworders)
1207
1208
1209 self['process']['model'].actualize_dictionaries(useUVCT=True)
1210
1211
1212
1213 self['process']['orders']['UVCT_SPECIAL']=1
1214
1215 UVCTsuccessful, UVCTdiagrams = \
1216 super(LoopAmplitude, self).generate_diagrams(True)
1217
1218 for UVCTdiag in UVCTdiagrams:
1219 if UVCTdiag.get_order('UVCT_SPECIAL')==1:
1220 newUVCTDiag = loop_base_objects.LoopUVCTDiagram({\
1221 'vertices':copy.deepcopy(UVCTdiag['vertices'])})
1222 UVCTinter = newUVCTDiag.get_UVCTinteraction(self['process']['model'])
1223 newUVCTDiag.set('type',UVCTinter.get('type'))
1224
1225
1226
1227 newUVCTDiag.get('UVCT_couplings').append((len([1 for loop_parts \
1228 in UVCTinter.get('loop_particles') if set(loop_parts).intersection(\
1229 set(self['process']['forbidden_particles']))==set([])])) if
1230 loop_parts!=[[]] else 1)
1231 self['loop_UVCT_diagrams'].append(newUVCTDiag)
1232
1233
1234
1235 del self['process']['orders']['UVCT_SPECIAL']
1236
1237 del self['process']['model'].get('order_hierarchy')['UVCT_SPECIAL']
1238 self['process']['model'].get('coupling_orders').remove('UVCT_SPECIAL')
1239 for inter in UVCTvertex_interactions:
1240 del inter.get('orders')['UVCT_SPECIAL']
1241
1242 self['process']['model'].actualize_dictionaries(useUVCT=False)
1243
1244
1245 for UVCTdiag in self['loop_UVCT_diagrams']:
1246 UVCTdiag.calculate_orders(self['process']['model'])
1247
1248
1249
1250
1251
1252 if not self['process']['has_born']:
1253 return UVCTsuccessful
1254
1255
1256
1257 for bornDiag in self['born_diagrams']:
1258
1259
1260
1261
1262
1263
1264
1265 LoopUVCTDiagramsAdded={}
1266 for leg in self['process']['legs']:
1267 counterterm=self['process']['model'].get_particle(abs(leg['id'])).\
1268 get('counterterm')
1269 for key, value in counterterm.items():
1270 if key[0] in self['process']['perturbation_couplings']:
1271 for laurentOrder, CTCoupling in value.items():
1272
1273 orderKey=[(key[0],2),]
1274 orderKey.sort()
1275 orderKey.append(('EpsilonOrder',-laurentOrder))
1276 CTCouplings=[CTCoupling for loop_parts in key[1] if
1277 set(loop_parts).intersection(set(self['process']\
1278 ['forbidden_particles']))==set([])]
1279 if CTCouplings!=[]:
1280 try:
1281 LoopUVCTDiagramsAdded[tuple(orderKey)].get(\
1282 'UVCT_couplings').extend(CTCouplings)
1283 except KeyError:
1284 LoopUVCTDiagramsAdded[tuple(orderKey)]=\
1285 loop_base_objects.LoopUVCTDiagram({\
1286 'vertices':copy.deepcopy(bornDiag['vertices']),
1287 'type':'UV'+('' if laurentOrder==0 else
1288 str(-laurentOrder)+'eps'),
1289 'UVCT_orders':{key[0]:2},
1290 'UVCT_couplings':CTCouplings})
1291
1292 for LoopUVCTDiagram in LoopUVCTDiagramsAdded.values():
1293 LoopUVCTDiagram.calculate_orders(self['process']['model'])
1294 self['loop_UVCT_diagrams'].append(LoopUVCTDiagram)
1295
1296 return UVCTsuccessful
1297
1299 """ Scan each loop diagram and recognizes what are the R2/UVmass
1300 CounterTerms associated to them """
1301
1302
1303
1304
1305
1306
1307
1308
1309 CT_interactions = {}
1310 for inter in self['process']['model']['interactions']:
1311 if inter.is_UVmass() or inter.is_UVloop() or inter.is_R2() and \
1312 len(inter['particles'])>1 and inter.is_perturbating(\
1313 self['process']['perturbation_couplings']):
1314
1315
1316
1317 for i, lparts in enumerate(inter['loop_particles']):
1318 keya=copy.copy(lparts)
1319 keya.sort()
1320 if inter.is_UVloop():
1321
1322
1323
1324
1325 if (set(self['process']['forbidden_particles']) & \
1326 set(lparts)) != set([]):
1327 continue
1328 else:
1329 keya=[]
1330 keyb=[part.get_pdg_code() for part in inter['particles']]
1331 keyb.sort()
1332 key=(tuple(keyb),tuple(keya))
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353 try:
1354 CT_interactions[key].append((inter['id'],i))
1355 except KeyError:
1356 CT_interactions[key]=[(inter['id'],i),]
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376 CT_added = {}
1377
1378 for diag in self['loop_diagrams']:
1379
1380
1381 searchingKeyA=[]
1382
1383 searchingKeyB=[]
1384 trackingKeyA=[]
1385 for tagElement in diag['canonical_tag']:
1386 for structID in tagElement[1]:
1387 trackingKeyA.append(structID)
1388 searchingKeyA.append(self['process']['model'].get_particle(\
1389 self['structure_repository'][structID]['binding_leg']['id']).\
1390 get_pdg_code())
1391 searchingKeyB.append(self['process']['model'].get_particle(\
1392 tagElement[0]).get('pdg_code'))
1393 searchingKeyA.sort()
1394
1395 searchingKeyB=list(set(searchingKeyB))
1396 searchingKeyB.sort()
1397 trackingKeyA.sort()
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417 searchingKeySimple=(tuple(searchingKeyA),())
1418 searchingKeyLoopPart=(tuple(searchingKeyA),tuple(searchingKeyB))
1419 trackingKeySimple=(tuple(trackingKeyA),())
1420 trackingKeyLoopPart=(tuple(trackingKeyA),tuple(searchingKeyB))
1421
1422
1423
1424
1425 try:
1426 CTIDs=copy.copy(CT_interactions[searchingKeySimple])
1427 except KeyError:
1428 CTIDs=[]
1429 try:
1430 CTIDs.extend(copy.copy(CT_interactions[searchingKeyLoopPart]))
1431 except KeyError:
1432 pass
1433 if not CTIDs:
1434 continue
1435
1436
1437 try:
1438 usedIDs=copy.copy(CT_added[trackingKeySimple])
1439 except KeyError:
1440 usedIDs=[]
1441 try:
1442 usedIDs.extend(copy.copy(CT_added[trackingKeyLoopPart]))
1443 except KeyError:
1444 pass
1445
1446 for CTID in CTIDs:
1447
1448
1449 if CTID not in usedIDs and diag.get_loop_orders(\
1450 self['process']['model'])==\
1451 self['process']['model']['interaction_dict'][CTID[0]]['orders']:
1452
1453
1454 CTleglist = base_objects.LegList()
1455 for tagElement in diag['canonical_tag']:
1456 for structID in tagElement[1]:
1457 CTleglist.append(\
1458 self['structure_repository'][structID]['binding_leg'])
1459 CTVertex = base_objects.Vertex({'id':CTID[0], \
1460 'legs':CTleglist})
1461 diag['CT_vertices'].append(CTVertex)
1462
1463
1464 if self['process']['model']['interaction_dict'][CTID[0]]\
1465 ['loop_particles'][CTID[1]]==[] or \
1466 self['process']['model']['interaction_dict'][CTID[0]].\
1467 is_UVloop():
1468 try:
1469 CT_added[trackingKeySimple].append(CTID)
1470 except KeyError:
1471 CT_added[trackingKeySimple] = [CTID, ]
1472 else:
1473 try:
1474 CT_added[trackingKeyLoopPart].append(CTID)
1475 except KeyError:
1476 CT_added[trackingKeyLoopPart] = [CTID, ]
1477
1481
1483 """ Returns a DGLoopLeg list instead of the default copy_leglist
1484 defined in base_objects.Amplitude """
1485
1486 dgloopleglist=base_objects.LegList()
1487 for leg in leglist:
1488 dgloopleglist.append(loop_base_objects.DGLoopLeg(leg))
1489
1490 return dgloopleglist
1491
1493 """ Overloaded here to convert back all DGLoopLegs into Legs. """
1494 for vertexlist in vertexdoublelist:
1495 for vertex in vertexlist:
1496 if not isinstance(vertex['legs'][0],loop_base_objects.DGLoopLeg):
1497 continue
1498 vertex['legs'][:]=[leg.convert_to_leg() for leg in \
1499 vertex['legs']]
1500 return True
1501
1503 """Create a set of new legs from the info given."""
1504
1505 looplegs=[leg for leg in legs if leg['loop_line']]
1506
1507
1508
1509 model=self['process']['model']
1510 exlegs=[leg for leg in looplegs if leg['depth']==0]
1511 if(len(exlegs)==2):
1512 if(any([part['mass'].lower()=='zero' for pdg,part in model.get('particle_dict').items() if pdg==abs(exlegs[0]['id'])])):
1513 return []
1514
1515
1516 loopline=(len(looplegs)==1)
1517 mylegs = []
1518 for i, (leg_id, vert_id) in enumerate(leg_vert_ids):
1519
1520
1521
1522
1523 if not loopline or not (leg_id in self.lcutpartemployed):
1524
1525
1526
1527
1528 if len(legs)==2 and len(looplegs)==2:
1529
1530 depths=(looplegs[0]['depth'],looplegs[1]['depth'])
1531 if (0 in depths) and (-1 not in depths) and depths!=(0,0):
1532
1533
1534
1535 continue
1536
1537
1538
1539
1540
1541 depth=-1
1542
1543
1544 if len(legs)==2 and loopline and (legs[0]['depth'],\
1545 legs[1]['depth'])==(0,0):
1546 if not legs[0]['loop_line']:
1547 depth=legs[0]['id']
1548 else:
1549 depth=legs[1]['id']
1550
1551
1552 if len(legs)==1 and legs[0]['id']==leg_id:
1553 depth=legs[0]['depth']
1554
1555
1556
1557
1558 mylegs.append((loop_base_objects.DGLoopLeg({'id':leg_id,
1559 'number':number,
1560 'state':state,
1561 'from_group':True,
1562 'depth': depth,
1563 'loop_line': loopline}),
1564 vert_id))
1565 return mylegs
1566
1568 """Allow for selection of vertex ids."""
1569
1570 looplegs=[leg for leg in legs if leg['loop_line']]
1571 nonlooplegs=[leg for leg in legs if not leg['loop_line']]
1572
1573
1574 model=self['process']['model']
1575 exlegs=[leg for leg in looplegs if leg['depth']==0]
1576 if(len(exlegs)==2):
1577 if(any([part['mass'].lower()=='zero' for pdg,part in \
1578 model.get('particle_dict').items() if pdg==abs(exlegs[0]['id'])])):
1579 return []
1580
1581
1582
1583
1584 if(len(legs)==3 and len(looplegs)==2):
1585 depths=(looplegs[0]['depth'],looplegs[1]['depth'])
1586 if (0 in depths) and (-1 not in depths) and depths!=(0,0):
1587 return []
1588
1589 return vert_ids
1590
1591
1592
1594 """ Filters the diagrams according to the constraints on the squared
1595 orders in argument and wether the process has a born or not. """
1596
1597 diagRef=base_objects.DiagramList()
1598 AllLoopDiagrams=base_objects.DiagramList(self['loop_diagrams']+\
1599 self['loop_UVCT_diagrams'])
1600
1601 AllBornDiagrams=base_objects.DiagramList(self['born_diagrams'])
1602 if self['process']['has_born']:
1603 diagRef=AllBornDiagrams
1604 else:
1605 diagRef=AllLoopDiagrams
1606
1607 sqorders_types=copy.copy(self['process'].get('sqorders_types'))
1608
1609
1610
1611 if 'WEIGHTED' not in sqorders_types:
1612 sqorders_types['WEIGHTED']='<='
1613
1614 if len(diagRef)==0:
1615
1616
1617
1618
1619
1620 AllLoopDiagrams = base_objects.DiagramList()
1621
1622
1623
1624 AllLoopDiagrams = AllLoopDiagrams.apply_positive_sq_orders(diagRef,
1625 sq_order_constrains, sqorders_types)
1626
1627 if self['process']['has_born']:
1628
1629 AllBornDiagrams = AllBornDiagrams.apply_positive_sq_orders(
1630 AllLoopDiagrams+AllBornDiagrams, sq_order_constrains, sqorders_types)
1631
1632
1633 neg_orders = [(order, value) for order, value in \
1634 sq_order_constrains.items() if value<0]
1635 if len(neg_orders)==1:
1636 neg_order, neg_value = neg_orders[0]
1637
1638
1639 if self['process']['has_born']:
1640 AllBornDiagrams, target_order =\
1641 AllBornDiagrams.apply_negative_sq_order(
1642 base_objects.DiagramList(AllLoopDiagrams+AllBornDiagrams),
1643 neg_order,neg_value,sqorders_types[neg_order])
1644
1645
1646 AllLoopDiagrams = AllLoopDiagrams.apply_positive_sq_orders(
1647 diagRef,{neg_order:target_order},
1648 {neg_order:sqorders_types[neg_order]})
1649
1650
1651
1652 else:
1653 AllLoopDiagrams, target_order = \
1654 AllLoopDiagrams.apply_negative_sq_order(
1655 diagRef,neg_order,neg_value,sqorders_types[neg_order])
1656
1657
1658
1659
1660
1661 self['process']['squared_orders'][neg_order]=target_order
1662 user_squared_orders[neg_order]=target_order
1663
1664 elif len(neg_orders)>1:
1665 raise MadGraph5Error('At most one negative squared order constraint'+\
1666 ' can be specified, not %s.'%str(neg_orders))
1667
1668 if self['process']['has_born']:
1669 self['born_diagrams'] = AllBornDiagrams
1670 self['loop_diagrams']=[diag for diag in AllLoopDiagrams if not \
1671 isinstance(diag,loop_base_objects.LoopUVCTDiagram)]
1672 self['loop_UVCT_diagrams']=[diag for diag in AllLoopDiagrams if \
1673 isinstance(diag,loop_base_objects.LoopUVCTDiagram)]
1674
1676 """ This is a helper function for order_diagrams_according_to_split_orders
1677 and intended to be used from LoopHelasAmplitude only"""
1678
1679
1680
1681 diag_by_so = {}
1682
1683 for diag in diag_set:
1684 so_key = tuple([diag.get_order(order) for order in split_orders])
1685 try:
1686 diag_by_so[so_key].append(diag)
1687 except KeyError:
1688 diag_by_so[so_key]=base_objects.DiagramList([diag,])
1689
1690 so_keys = diag_by_so.keys()
1691
1692
1693 order_hierarchy = self.get('process').get('model').get('order_hierarchy')
1694 order_weights = copy.copy(order_hierarchy)
1695 for so in split_orders:
1696 if so not in order_hierarchy.keys():
1697 order_weights[so]=0
1698
1699
1700
1701
1702 so_keys = sorted(so_keys, key = lambda elem: (sum([power*order_weights[\
1703 split_orders[i]] for i,power in enumerate(elem)])))
1704
1705
1706 diag_set[:] = []
1707 for so_key in so_keys:
1708 diag_set.extend(diag_by_so[so_key])
1709
1710
1712 """ Reorder the loop and Born diagrams (if any) in group of diagrams
1713 sharing the same coupling orders are put together and these groups are
1714 order in decreasing WEIGHTED orders.
1715 Notice that this function is only called for now by the
1716 LoopHelasMatrixElement instances at the output stage.
1717 """
1718
1719
1720
1721 if len(split_orders)==0:
1722 return
1723
1724 self.order_diagram_set(self['born_diagrams'], split_orders)
1725 self.order_diagram_set(self['loop_diagrams'], split_orders)
1726 self.order_diagram_set(self['loop_UVCT_diagrams'], split_orders)
1727
1732 """LoopMultiProcess: MultiProcess with loop features.
1733 """
1734
1735 @classmethod
1737 """ Return the correct amplitude type according to the characteristics
1738 of the process proc """
1739 return LoopAmplitude({"process": proc},**opts)
1740
1745 """Special mode for the LoopInduced."""
1746
1747 @classmethod
1749 """ Return the correct amplitude type according to the characteristics of
1750 the process proc """
1751 return LoopAmplitude({"process": proc, 'has_born':False},**opts)
1752