Fit of experimental data using an Euler Hamiltonian. In the case of parameters starting with identifiers 90 or 92, the parameter names are those of a traditional Watson Hamiltonian. Parameters 90ij00 correspond to X_ij Parameters 92ij00 correspond to Y_ij See also the paper. HD2+, I^r, A Tue Jul 12 16:25:17 2016 LINES REQUESTED= 39 NUMBER OF PARAMETERS= 16 NUMBER OF ITERATIONS= 9 EXP.FREQ. - CALC.FREQ. - DIFF. - EXP.ERR.- EST.ERR.-AVG. CALC.FREQ. - DIFF. - WT. 1: 1 1 1 0 0 0 1476605.70800 1476605.71209 -0.00409 0.01500 0.00000 2: 1 1 1 0 0 0 1476605.71250 1476605.71209 0.00041 0.00470 0.00000 3: 1 1 0 1 0 1 691660.44000 691660.44328 -0.00328 0.02000 0.00000 4: 1 1 0 1 0 1 691660.44340 691660.44328 0.00012 0.00400 0.00000 5: 2 0 2 0 0 0 3049429.49000 3049429.43401 0.05599 0.76000 0.00000 6: 2 0 2 1 1 1 1572823.71800 1572823.72192 -0.00392 0.10000 0.00000 7: 2 1 2 1 1 0 1567027.80000 1567027.99160 -0.19160 0.80000 0.00000 8: 2 1 1 2 0 2 1038663.15400 1038663.14312 0.01088 0.10000 0.00000 9: 2 1 1 2 0 2 1038663.14300 1038663.14312 -0.00012 0.01000 0.00000 10: 2 2 0 2 1 1 1370051.60000 1370051.60196 -0.00196 0.30000 0.00000 11: 3 1 2 3 0 3 1654895.92400 1654895.92387 0.00013 0.10000 0.00000 12: 3 2 1 3 1 2 1341265.34200 1341265.34231 -0.00031 0.10000 0.00000 13: 2 0 2 0 0 0 101.7190000 101.7180170 0.0009830 -0.0014000 0.0000000 14: 3 0 3 1 0 1 161.1830000 161.1811315 0.0018685 -0.0020000 0.0000000 15: 2 2 1 1 0 1 144.2450000 144.2455025 -0.0005025 -0.0020000 0.0000000 16: 2 2 1 1 0 1 144.2470000 144.2455025 0.0014975 -0.0020000 0.0000000 17: 2 1 1 1 1 1 87.1110000 87.1098253 0.0011747 -0.0012000 0.0000000 18: 2 1 1 1 1 1 87.1120000 87.1098253 0.0021747 -0.0014000 0.0000000 19: 2 1 1 1 1 1 87.1100000 87.1098253 0.0001747 -0.0020000 0.0000000 20: 2 1 2 1 1 0 52.2710000 52.2704274 0.0005726 -0.0009000 0.0000000 21: 2 2 0 2 0 2 80.3460000 80.3460755 -0.0000755 -0.0014000 0.0000000 22: 2 2 0 2 0 2 80.3470000 80.3460755 0.0009245 -0.0020000 0.0000000 23: 3 2 2 2 0 2 181.5980000 181.5957771 0.0022229 -0.0014000 0.0000000 24: 3 1 2 2 1 2 141.0430000 141.0407812 0.0022188 -0.0014000 0.0000000 25: 3 1 2 2 1 2 141.0420000 141.0407812 0.0012188 -0.0014000 0.0000000 26: 3 1 3 2 1 1 63.6650000 63.6653766 -0.0003766 -0.0011000 0.0000000 27: 3 1 3 2 1 1 63.6640000 63.6653766 -0.0013766 -0.0014000 0.0000000 28: 3 1 3 2 1 1 63.6630000 63.6653766 -0.0023766 -0.0020000 0.0000000 29: 4 1 3 2 1 1 262.6850000 262.6847492 0.0002508 -0.0020000 0.0000000 30: 3 0 3 2 2 1 16.9350000 16.9356290 -0.0006290 -0.0020000 0.0000000 31: 3 0 3 2 2 1 16.9360000 16.9356290 0.0003710 -0.0020000 0.0000000 32: 3 2 2 2 2 0 101.2510000 101.2497017 0.0012983 -0.0020000 0.0000000 33: 3 2 2 2 2 0 101.2520000 101.2497017 0.0022983 -0.0020000 0.0000000 34: 4 2 3 3 0 3 223.3660000 223.3665888 -0.0005888 -0.0020000 0.0000000 35: 4 1 3 3 1 3 199.0210000 199.0193726 0.0016274 -0.0020000 0.0000000 36: 4 3 1 3 1 3 323.3580000 323.3578471 0.0001529 -0.0020000 0.0000000 37: 4 1 4 3 1 2 65.9520000 65.9460331 0.0059669 -0.0020000 0.0000000 38: 5 1 4 3 1 2 323.4920000 323.4936261 -0.0016261 -0.0020000 0.0000000 39: 5 1 4 4 1 4 257.5470000 257.5475930 -0.0005930 -0.0020000 0.0000000 NORMALIZED DIAGONAL: 1 1.00000E+000 2 1.00000E+000 3 1.00000E+000 4 1.00000E+000 5 1.00000E+000 6 9.81023E-001 7 2.79893E-003 8 2.45434E-003 9 1.81409E-001 10 4.35315E-001 11 8.70295E-001 12 1.42349E-002 13 3.49420E-002 14 1.09859E-001 15 4.53074E-004 16 9.15760E-001 MARQUARDT PARAMETER = 0, TRUST EXPANSION = 1.00 NEW PARAMETER (EST. ERROR) -- CHANGE THIS ITERATION 1 911000 a 2.500000000( 0)E-03 0.000000000E-03 2 910100 b 0.480000000( 0)E-03 0.000000000E-03 3 931000 a_off 7.300000000( 0)E-03 0.000000000E-03 4 930100 b_off 1.000000000( 0)E-03 0.000000000E-03 5 901000 A 1085204.63(195) 0.00 6 900100 (B+C)/2 523759.68( 61) -0.00 7 902000 -DelK 1890.83(133) -0.00 8 901100 -DelJK 1407.02(104) -0.00 9 900200 -DelJ 78.910(170) 0.000 10 903000 PhiK 5.004(285) 0.000 11 902100 PhiKJ 0.343(177) -0.000 12 901200 PhiJK 2.288(129) 0.000 13 900300 PhiJ 0.0653( 47) 0.0000 14 920000 (B-C)/4 65982.83(169) -0.00 15 921000 -delK 31.56(170) 0.00 16 920100 -delJ 0.530( 62) 0.000 MICROWAVE AVG = -0.011480 MHz, IR AVG = 0.00070 MICROWAVE RMS = 0.057742 MHz, IR RMS = 0.00175 END OF ITERATION 1 OLD, NEW RMS ERROR= 0.82832 0.82832 1 2 0.000000 1 3 0.000000 1 4 0.000000 1 5 0.000000 1 6 0.000000 1 7 0.000000 1 8 0.000000 1 9 0.000000 1 10 0.000000 1 11 0.000000 1 12 0.000000 1 13 0.000000 1 14 0.000000 1 15 0.000000 1 16 0.000000 2 1 0.000000 2 3 0.000000 2 4 0.000000 2 5 0.000000 2 6 0.000000 2 7 0.000000 2 8 0.000000 2 9 0.000000 2 10 0.000000 2 11 0.000000 2 12 0.000000 2 13 0.000000 2 14 0.000000 2 15 0.000000 2 16 0.000000 3 1 0.000000 3 2 0.000000 3 4 0.000000 3 5 0.000000 3 6 0.000000 3 7 0.000000 3 8 0.000000 3 9 0.000000 3 10 0.000000 3 11 0.000000 3 12 0.000000 3 13 0.000000 3 14 0.000000 3 15 0.000000 3 16 0.000000 4 1 0.000000 4 2 0.000000 4 3 0.000000 4 5 0.000000 4 6 0.000000 4 7 0.000000 4 8 0.000000 4 9 0.000000 4 10 0.000000 4 11 0.000000 4 12 0.000000 4 13 0.000000 4 14 0.000000 4 15 0.000000 4 16 0.000000 5 1 0.000000 5 2 0.000000 5 3 0.000000 5 4 0.000000 5 6 -0.179250 5 7 -0.871665 5 8 -0.818704 5 9 0.679479 5 10 0.938326 5 11 -0.814201 5 12 0.454113 5 13 0.367695 5 14 -0.839399 5 15 0.889965 5 16 -0.311947 6 1 0.000000 6 2 0.000000 6 3 0.000000 6 4 0.000000 6 5 -0.179250 6 7 0.297174 6 8 -0.215033 6 9 -0.809940 6 10 -0.147790 6 11 -0.089085 6 12 0.674102 6 13 -0.707827 6 14 0.591974 6 15 -0.465575 6 16 -0.828595 7 1 0.000000 7 2 0.000000 7 3 0.000000 7 4 0.000000 7 5 -0.871665 7 6 0.297174 7 8 0.454459 7 9 -0.597016 7 10 -0.973239 7 11 0.454563 7 12 -0.106635 7 13 -0.320172 7 14 0.653991 7 15 -0.665070 7 16 0.064028 8 1 0.000000 8 2 0.000000 8 3 0.000000 8 4 0.000000 8 5 -0.818704 8 6 -0.215033 8 7 0.454459 8 9 -0.387602 8 10 -0.627589 8 11 0.963887 8 12 -0.825709 8 13 -0.153372 8 14 0.655366 8 15 -0.759858 8 16 0.662573 9 1 0.000000 9 2 0.000000 9 3 0.000000 9 4 0.000000 9 5 0.679479 9 6 -0.809940 9 7 -0.597016 9 8 -0.387602 9 10 0.556141 9 11 -0.489348 9 12 -0.149959 9 13 0.698804 9 14 -0.944284 9 15 0.888821 9 16 0.376069 10 1 0.000000 10 2 0.000000 10 3 0.000000 10 4 0.000000 10 5 0.938326 10 6 -0.147790 10 7 -0.973239 10 8 -0.627589 10 9 0.556141 10 11 -0.626355 10 12 0.328264 10 13 0.235482 10 14 -0.673372 10 15 0.714757 10 16 -0.271521 11 1 0.000000 11 2 0.000000 11 3 0.000000 11 4 0.000000 11 5 -0.814201 11 6 -0.089085 11 7 0.454563 11 8 0.963887 11 9 -0.489348 11 10 -0.626355 11 12 -0.787536 11 13 -0.129821 11 14 0.708879 11 15 -0.798605 11 16 0.609352 12 1 0.000000 12 2 0.000000 12 3 0.000000 12 4 0.000000 12 5 0.454113 12 6 0.674102 12 7 -0.106635 12 8 -0.825709 12 9 -0.149959 12 10 0.328264 12 11 -0.787536 12 13 -0.329125 12 14 -0.142438 12 15 0.283785 12 16 -0.956209 13 1 0.000000 13 2 0.000000 13 3 0.000000 13 4 0.000000 13 5 0.367695 13 6 -0.707827 13 7 -0.320172 13 8 -0.153372 13 9 0.698804 13 10 0.235482 13 11 -0.129821 13 12 -0.329125 13 14 -0.684997 13 15 0.612831 13 16 0.548300 14 1 0.000000 14 2 0.000000 14 3 0.000000 14 4 0.000000 14 5 -0.839399 14 6 0.591974 14 7 0.653991 14 8 0.655366 14 9 -0.944284 14 10 -0.673372 14 11 0.708879 14 12 -0.142438 14 13 -0.684997 14 15 -0.988779 14 16 -0.101825 15 1 0.000000 15 2 0.000000 15 3 0.000000 15 4 0.000000 15 5 0.889965 15 6 -0.465575 15 7 -0.665070 15 8 -0.759858 15 9 0.888821 15 10 0.714757 15 11 -0.798605 15 12 0.283785 15 13 0.612831 15 14 -0.988779 15 16 -0.044928 16 1 0.000000 16 2 0.000000 16 3 0.000000 16 4 0.000000 16 5 -0.311947 16 6 -0.828595 16 7 0.064028 16 8 0.662573 16 9 0.376069 16 10 -0.271521 16 11 0.609352 16 12 -0.956209 16 13 0.548300 16 14 -0.101825 16 15 -0.044928 HD2+, I^r, A Tue Jul 12 16:25:17 2016