-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathNote_on_bloch_theorem.nb
6367 lines (6324 loc) · 344 KB
/
Note_on_bloch_theorem.nb
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
(* Content-type: application/vnd.wolfram.mathematica *)
(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)
(* CreatedBy='Mathematica 11.1' *)
(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[ 158, 7]
NotebookDataLength[ 352541, 6359]
NotebookOptionsPosition[ 349439, 6299]
NotebookOutlinePosition[ 349792, 6315]
CellTagsIndexPosition[ 349749, 6312]
WindowFrame->Normal*)
(* Beginning of Notebook Content *)
Notebook[{
Cell[CellGroupData[{
Cell["BT to PP-STM: some ideas", "Title",
CellChangeTimes->{{3.756401106120541*^9,
3.756401150681322*^9}},ExpressionUUID->"ac314331-f3a1-4c61-8d04-\
c74518aa7fb7"],
Cell["\<\
This notebook contains ideas and test for implementation of BT into PPSTM code.
One of the possible simplification can be usage of Rescaled coefficients, \
than the full Bloch Theorem (1st part)
The second is to expand these rescaled coefficients (derived later) rather \
than change the C++ part\
\>", "Text",
CellChangeTimes->{{3.7564011580132523`*^9, 3.756401262223295*^9}, {
3.756401360884273*^9, 3.756401414355287*^9}, {3.7564015976488256`*^9,
3.756401600472625*^9}},ExpressionUUID->"29998dae-35d3-49e3-b37f-\
4b4b86eb1e55"],
Cell[BoxData[{
RowBox[{
RowBox[{"F1", "[",
RowBox[{"k_", ",", "c_", ",", "x_"}], "]"}], ":=",
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "x"}], "]"}], "*",
RowBox[{"(",
RowBox[{
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{"x", "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}], "+",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "1"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}], "+",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "2"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}], "+",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "3"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}], "+",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "4"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}],
")"}]}]}], "\[IndentingNewLine]",
RowBox[{
RowBox[{"F2", "[",
RowBox[{"k_", ",", "c_", ",", "x_"}], "]"}], ":=",
RowBox[{"(",
RowBox[{
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "0"}], "]"}], "*",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{"x", "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}], "+",
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "1"}], "]"}], "*",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "1"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}], "+",
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "2"}], "]"}], "*",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "2"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}], "+",
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "3"}], "]"}], "*",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "3"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}], "+",
RowBox[{
RowBox[{"Cos", "[",
RowBox[{"k", "*", "4"}], "]"}], "*",
RowBox[{"Exp", "[",
RowBox[{
RowBox[{"-",
RowBox[{
RowBox[{"(",
RowBox[{"x", "-", "4"}], ")"}], "^", "2"}]}], "/",
RowBox[{"(",
RowBox[{"2", "*",
RowBox[{"c", "^", "2"}]}], ")"}]}], "]"}]}]}], ")"}]}]}], "Input",
CellChangeTimes->{{3.7504094402425117`*^9, 3.75040970748035*^9}, {
3.7504097635376453`*^9, 3.750409834001115*^9}, {3.750409865427372*^9,
3.750409869936771*^9}, {3.750409964976818*^9,
3.750410019272956*^9}},ExpressionUUID->"fca75b08-dd3b-43de-ab39-\
3f8b2dae59fd"],
Cell[CellGroupData[{
Cell[BoxData[{
RowBox[{
RowBox[{"k", "=", "0"}], ";",
RowBox[{"c", "=", "0.15"}], ";"}], "\[IndentingNewLine]",
RowBox[{"Plot", "[",
RowBox[{
RowBox[{"{",
RowBox[{
RowBox[{"F1", "[",
RowBox[{"k", ",", "c", ",", "x"}], "]"}], ",",
RowBox[{"F2", "[",
RowBox[{"k", ",", "c", ",", "x"}], "]"}]}], "}"}], ",",
RowBox[{"{",
RowBox[{"x", ",", "0", ",", "4"}], "}"}], ",",
RowBox[{"PlotRange", "\[Rule]",
RowBox[{"{",
RowBox[{
RowBox[{"-", "1"}], ",", "1"}], "}"}]}], ",",
RowBox[{"PlotLegends", "\[Rule]",
RowBox[{"{",
RowBox[{
"\"\<Full Bloch Theorem\>\"", ",",
"\"\<Rescalled coefficients only\>\""}], "}"}]}]}], "]"}]}], "Input",
CellChangeTimes->{{3.750409713241844*^9, 3.750409736080233*^9},
3.7504097880461493`*^9, {3.750409846625155*^9, 3.7504099195965977`*^9}, {
3.7504100257612743`*^9, 3.750410127223371*^9}, {3.7504101651897163`*^9,
3.7504102316078053`*^9},
3.750410270610077*^9},ExpressionUUID->"89abaa56-99db-432e-8f0b-\
a7ba67999271"],
Cell[BoxData[
TemplateBox[{GraphicsBox[{{{{}, {},
TagBox[{
Directive[
Opacity[1.],
RGBColor[0.368417, 0.506779, 0.709798],
AbsoluteThickness[1.6]],
LineBox[CompressedData["
1:eJwcWndcze/7rs5JixBSya4+IYSI0PWoqJSEIiQkW0VFkbSXprT3QkVTU0pR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"]]}, Annotation[#, "Charting`Private`Tag$12461#1"]& ],
TagBox[{
Directive[
Opacity[1.],
RGBColor[0.880722, 0.611041, 0.142051],
AbsoluteThickness[1.6]],
LineBox[CompressedData["
1:eJwcWndcze/7rs5JixBSya4+IYSI0PWoqJSEIiQkW0VFkbSXprT3QkVTU0pR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