Abstract
A new FD (Finite Difference) method with zero phase-lag and its derivatives up to order six is proposed for the approximate solution of problems in Chemistry.
1 Introduction
1.1 The problem
We discuss the solution of the following Systems of Differential Equations:
where \(1 \le i \le N\) and \(m \ne i\).
(3) \(\longrightarrow\) BVP (\(=\) Boundary value problem) \(\longrightarrow\) boundary conditions:
where \(j_{l}(x)\) and \(n_{l}(x)\) \(\longrightarrow\) spherical Bessel and Neumann functions respectively (see [62]).
Categories of problems (see [62]):
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Open Channels
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Close Channels
Asymptotic form (4) of (3) for the open channels problem (see [62]) \({\longrightarrow }\):
where:
More details see in [67, 143,144,145,146,147,148,149,150,151] and references therein. Areas of application of the problems of the form (1) can also be found in [152,153,154,155,156,157,158,159,160] and references therein (Neural Networks, impulsive delayed systems, delayed switched systems, Impulsive control method, impulsive functional differential equations with infinite delays, singularly perturbed nonlinear systems, etc)
[62] \(\longrightarrow\):
where (j, l), \((j ^\prime ,l ^\prime )\), \(J=j+l=j ^\prime + l ^\prime\) \(\longrightarrow\) [62].
and
where for E, I and \(\nu\) \(\longrightarrow\) [62] and references therein.
2 Introductiuon of the algorithm
In this section we will present the development of the new proposed scheme.
where \(\{\eta \sigma \}_{n+i} = \{\beta \lambda \}''\left( t_{n+i}, \{\beta \lambda \}_{n+i} \right) , i=-1\left( 1 \right) 1\), \(\overline{\{\eta \sigma \}}_{n-1} = \{\beta \lambda \}''\left( t_{n-1}, \overline{\{\beta \lambda \}}_{n-1} \right)\), \(\overline{\overline{\{\eta \sigma \}}}_{n-1} = \{\beta \lambda \}''\left( t_{n-1}, \overline{\overline{\{\beta \lambda \}}}_{n-1} \right)\), \(\overline{\{\eta \sigma \}}_{n} = \{\beta \lambda \}''\left( t_{n}, \overline{\{\beta \lambda \}}_{n} \right)\) and
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\(b_{{1}} = \frac{1}{12}\),
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\(a_{{j}}, \, j=0 (1) 5\) and \(b_{0}\), to be determined.
Figure 1\(\longrightarrow\) The Production of the of the new proposed algorithm (more information on flowcharts \(\longrightarrow\) [161]).
In Fig. 1:
The general forms of the stability polynomials \(ST_{k}, \, k=0,\,1\) is presented in [40]
Theorem 1\({\mathop {\longrightarrow }\limits ^{using \, ST_{j}, \, \, j=0,1}}\): \(PhL + DPL_{j}\) (with \(PhL = {\text{phase}}{-}{\text{lag}}\) and \(DPL_{j} = {\text{phase-lag's derivative of order}} j\)
Theorem 1
[12] The terms OPL and \(CF_{PL}\) are defined by:
where OPL \(\longrightarrow\) phase–lag’s order and \(CF_{PL}\) \(\longrightarrow\) phase–lag’s constant . OPL and \(CF_{PL}\) \({\mathop {\longrightarrow }\limits ^{(4)- (7)}}\) phase–lag.
(4) \(+\) \(ST_{j}, \, \, j=0,1\) with general form given by [40] \(+\) (8) \(+\) Stage 5 of Fig. 1\(\longrightarrow\):
where
where \(PLM_{j}, \, \, j=0 \left( 1 \right) 7\) are the Polynomials of the Stability Functions of the Finite Difference Method. \(v \rightarrow 0 \, \bigvee \, PLM_{0} (v) \rightarrow 0 \bigvee \, PLM_{3} (v)\bigvee \, PLM_{5} (v) \rightarrow 0\bigvee \, PLM_{7} (v) \rightarrow 0\) \(\Longrightarrow\) expressions in Taylor series are procured:
\(a_{{j}}, \, j=0 (1)5\) and \(b_{{0}}\), for \(v = \phi \, h\) \({\mathop {\longrightarrow }\limits ^{\text{are plotted in}}}\) Fig. 2
LTE \({\mathop {\longrightarrow }\limits ^{for \, the\, Method \, (4), \, which \, is \, declared \, as \, NM142S4SPD6}}\):
3 Theoretical study of the new proposed method
3.1 Theoretical study of the local truncation error of the new proposed method
Local Truncation Error of the Finite Difference Method \({\mathop {\longrightarrow }\limits ^{scalar \, pattern}}\):
with
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POTENT(x) \(\longrightarrow\) the potential.
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\(POTENT_{z}\) \(\longrightarrow\) POTENT(x) on \(x_{z}\).
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\(\hbox {PTN}(x) = POTENT(x) - POTENT_{z}\),
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\(\imath =POTENT_{z}-E\) and
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E \(\longrightarrow\) the energy.
For the contemplation of the Local Truncation Error of the Finite Difference Method, we use:
3.1.1 Classical algorithm, related as method A
3.1.2 Procedure projected in [40], related as method B
3.1.3 Procedure projected in [41], related as method C
3.1.4 Procedure projected in [42], related as Method D
3.1.5 Procedure projected in [43], related as Method E
3.1.6 Procedure projected in in [44], Related as Method F
3.1.7 Procedure projected in Section 2, Related as Method G
The LTE of Method G is given by (11).
Figure 3\(\longrightarrow\) flowchart for Local Truncation Error of the Finite Difference Method.
Stage 4.1 \(\longrightarrow\):
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\(\imath \approx 0 \, \equiv \, E \approx V\): \(POTENT_{z} \approx E \Rightarrow \imath =POTENT_{z} - E \approx 0 \Rightarrow \imath ^{i} \approx 0, \, i=1,2, \ldots \Rightarrow h^{\rho } \, \sum \limits _{i=0}^{\zeta }{\ell _{i}\, \imath ^{i}} \approx h^{\rho } \, \ell _{0}\).
Physical Causality:
\(\ell _{0}\) \(\longrightarrow\) Supplement Material A.
Conclusion 1
\(\imath \approx 0\) \(\longrightarrow\) \(LTE_{CL}=LTE_{NM142S4SPD1}=LTE_{NM142S4SPD2}=LTE_{NM142S4SPD3} =LTE_{NM142S4SPD4}=LTE_{NM142S4SPD5}\).
Stage 4.2 \(\longrightarrow\):
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\(\left| \imath \right|>>0\) \(\equiv\) \(\left| V \right|>> \bigvee<< \left| E \right|\): \(E<<POTENT_{z} \vee E>>POTENT_{z} \Rightarrow \imath =POTENT_{z} - E>>0 \vee \imath =POTENT_{z} - E<<0\).
Conclusion 2
\(\left| \imath \right|>>0\) \(\longrightarrow\) \(\min {LTE}=\sum \limits _{i=0}^{\daleth }{\ell _{i}\, \imath ^{i}}\) and \(\daleth \longrightarrow \min {}\).
Physical Causality: Asymptotic forms of LTEs:
3.1.8 Method A
3.1.9 Method B
3.1.10 Method C
3.1.11 Method D
3.1.12 Method E
3.1.13 Method F
3.1.14 Method G
The above theoretical results give:
Theorem 2
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Method A: \(LTE=O\left( \imath ^8 \right)\).
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Method B: \(LTE=ADSX\,\, \, O\left( \imath ^6 \right)\).
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Method C: \(LTE=BYSP\,\, \, O\left( \imath ^6 \right)\).
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Method D: \(LTE=TNSI\,\, \, O\left( \imath ^5 \right)\).
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Method E: \(LTE=VCSM\,\, \, O\left( \imath ^5 \right)\).
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Method F: \(LTE=STVY\,\, \, O\left( \imath ^4 \right)\).
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Method F: \(LTE=AZCC\,\, \, O\left( \imath ^4 \right)\).
with \({\text{BYSP}}<< {\text{ADSX}}\), \({\text{VCSM}}<< {\text{TNSI}}\) and \({\text{AZCC}}<< {\text{STVY}}\). Theorem 2\(\longrightarrow\) Method G is the most effectual one on accuracy.
3.2 Theoretical study of the stability (stability analysis of the new introduced method
Stability Analysis of the Finite Difference Method \({\mathop {\longrightarrow }\limits ^{{\text{for}} \, {\text{the}} \, {\text{newly}} \, {\text{Produced}} \, {\text{Scheme}}}}\) scholar’s paragon:
Conclusion 3
(5), (28) \(\longrightarrow\) \(\chi \ne \phi\).
Figure 4\(\longrightarrow\) Stability Analysis of the New Introduced Finite Difference Method.
Stage 1 \(+\) Stage 2 \(\longrightarrow\):
and
where \(ST_{j} \left( s,v\right) , \, j=0,1\) are given in [40]
Stage 3 \(\longrightarrow\): \(s = \chi \, h\) \(\wedge\) \(v = \phi \, h\).
Stage 4 \(\longrightarrow\):
where
where \(PLM_{j}\left( s,v \right) , \, \, j=8,9,10\) are the Polynomials of the general Stability Functions of the New Introduced Scheme.
Stability District of the New Introduced Scheme \(\, \equiv \,\) \(s-v\). Figure 5\(\longrightarrow\) \(s-v\) range of Stability District of the New Introduced Scheme.
Conclusion 4
Figure 6 for \(s-v\) \(\longrightarrow\):
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Colored district of \(s-v\) \(\longrightarrow\) Stabilized district.
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White district of \(s-v\) \(\longrightarrow\) Unstabilized district.
Conclusion 5
Report on the new nominated Method \(\longrightarrow\):
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\(s \ne v\) \(\longrightarrow\) stabilized for \(s, \, v\) \(\in\) \(s-v\) \(\backslash\) \(\{\) around first diagonal \(\}\).
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\(s = v\) \(\longrightarrow\) stabilized for \(s, \, v\) \(\in\) \(\{\) around first diagonal \(\}\).
Conclusion 6
Figure 6. \(\longrightarrow\) the new deployed procedure is P-stable\(\, \equiv \, \langle s-v \rangle \equiv \left( 0, \infty \right)\).
The Table 1\(\longrightarrow\) intervals of periodicity of Methods of (4).
(4) \(+\) (11) \(+\) Theorem 2\(+\) Stage 5 of Fig. 1\(+\) Table 1\(\Longrightarrow\)
Theorem 3
The new deployed Method:
-
has 4 levels,
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Algebraic Order \(\longrightarrow\) 14,
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\(PhL = 0\),
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\(DPL_{1}=DPL_{2}=DPL_{3}=DPL_{4}=DPL_{3}=DPL_{5}=DPL_{6}=0\),
-
is P-stable.
where \(PhL = {\text{phase}}{-}{\text{lag}}\) and \(DPL_{j} = {\text{derivative of the phase--lag of order j}}\)
4 Numerical tests
Figure 7\(\longrightarrow\) Valuing the newly deployed Algorithm.
4.1 Local error control procedure
Local Error Control Procedure \(\longrightarrow\) Local Truncation Error’s Control Procedure.
Local Error Control Procedure \({\mathop {\longrightarrow }\limits ^{includes}}\): variable–step process (see in [75, 143] and references therein).
Table 2\(\longrightarrow\) Papers on the Subject (see [1]–[143]).
Note 1 Local Error Control Procedure \(\longrightarrow\) Procedure for the Control of the Local Truncation Error \({\mathop {\longrightarrow }\limits ^{is \, defined\, as}}\):
Definition 1
where \(\{\beta \lambda \}^{L}_{n+1}\) \(\longrightarrow\) [86], L \(\longrightarrow\) low algebraic order , \(\{\beta \lambda \}^{H}_{n+1}\) \(\longrightarrow\) Sect. 2, H \(\longrightarrow\) high algebraic order .
In [75], the flowchart for Local Error Control Procedure is displayed.
4.2 Description of the problem
and
and \(Potent_{ij} \rightarrow 0\) as \(x \rightarrow \infty\).
Boundary conditions\({\mathop {\longrightarrow }\limits ^{open \, channels}}\)
where
-
\(j_{l}(x)\) \(\longrightarrow\) spherical Bessel functions and
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\(n_{l}(x)\) \(\longrightarrow\) spherical Neumann functions.
[62] \(\longrightarrow\):
Figure 8\(\longrightarrow\) Flowchart for the problem’s (33) - (35) solution.
We use the following schemes:
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Method 1: Allison’s Algorithm [62],
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Method 2: See [61],
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Method 3: See [54],
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Method 4: See [65],
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Method 5: See [67],
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Method 6: See [73],
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Method 7: See [49],
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Method 8: See [71],
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Method 9: See [74],
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Method 10: See [37],
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Method 11: See [85],
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Method 12: See [40],
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Method 13: See [41],
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Method 14: See [42],
-
Method 15: See [43],
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Method 16: See [44],
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Method 17: Sect. 2.
Table 3\(\longrightarrow\) CT (in seconds) and MBAST for the 16 Methods.
All computations were carried out on a x86-64 compatible PC using double-precision arithmetic data type (64 bits) according to IEEE© Standard 754 for double precision.
5 General conclusion
A new FD method with phase–lag and its derivatives up to order 6 equal to zero is protduced. The theoretical evaluation which is presented in Sect. 3, proves the theoretical superiority of the new introduced scheme. The computational evaluation of the new method, which is based on (33), proves the efficiency of the new scheme.
References
M.M. Chawla, S.R. Sharma, Families of 5th order Nyström methods for Y”=F(X, Y) and intervals of periodicity. Computing 26(3), 247–256 (1981)
J.M. Franco, M. Palacios, High-order P-stable multistep methods. J. Comput. Appl. Math. 30, 1–10 (1990)
J.D. Lambert, Numerical Methods for Ordinary Differential Systems, The Initial Value Problem (Wiley, New York, 1991), pp., Pages 104–107
E. Stiefel, D.G. Bettis, Stabilization of Cowell’s Method. Numer. Math. 13, 154–175 (1969)
M.M. Chawla, S.R. Sharma, Intervals of periodicity and absolute stability of explicit Nyström Methods for Y”=F(X, Y). Bit 21(4), 455–464 (1981)
M.M. Chawla, Unconditionally stable Noumerov-type methods for 2nd order differential-equations. Bit 23(4), 541–542 (1983)
M.M. Chawla, P.S. Rao, A Noumerov-type method with minimal phase-lag for the integration of 2nd order periodic initial-value problems. J. Comput. Appl. Math. 11(3), 277–281 (1984)
M.M. Chawla, Numerov made explicit has better stability. Bit 24(1), 117–118 (1984)
M.M. Chawla and P.S. Rao, High-Accuracy P-stable Methods for Y” = F(T,Y), IMA J. Numer. Anal. 5(2) 215–220 (1985) and M.M. Chawla, Correction, IMA J. Numer. Anal. 6(2) 252–252 (1986)
T. Lyche, Chebyshevian multistep methods for ordinary differential eqations. Numer. Math. 19, 65–75 (1972)
T.E. Simos, P.S. Williams, A Finite Difference Method for the numerical solution of the Schrödinger equation. J. Comput. Appl. Math. 79, 189–205 (1997)
R.M. Thomas, Phase properties of high order almost P-stable formulae. BIT 24, 225–238 (1984)
J.D. Lambert, I.A. Watson, Symmetric multistep Methods for periodic initial values problems. J. Inst. Math. Appl. 18, 189–202 (1976)
M.M. Chawla, A new class of explicit 2-step 4th order methods for Y” = F(T, Y) with extended intervals of periodicity. J. Comput. Appl. Math. 14(3), 467–470 (1986)
M.M. Chawla, B. Neta, Families of 2-step 4th-order P-stable methods for 2nd-order differential-equations. J. Comput. Appl. Math. 15(2), 213–223 (1986)
M.M. Chawla, P.S. Rao, A Noumerov-type method with minimal phase-lag for the integration of 2nd-order periodic initial-value problems. 2. Explicit method. J. Comput. Appl. Math. 15(3), 329–337 (1986)
M.M. Chawla, P.S. Rao, B. Neta, 2-step 4th-order P-stable methods with phase-lag of order 6 for Y”=F(T, Y). J. Comput. Appl. Math. 16(2), 233–236 (1986)
M.M. Chawla, P.S. Rao, An explicit 6th-order method with phase-lag of order 8 for Y”=F(T, Y). J. Comput. Appl. Math. 17(3), 365–368 (1987)
M.M. Chawla, M.A. Al-Zanaidi, Non-dissipative extended one-step methods for oscillatory problems. Int. J. Comput. Math. 69(1–2), 85–100 (1998)
M.M. Chawla, M.A. Al-Zanaidi, A two-stage fourth-order “Almost” P-stable method for oscillatory problems. J. Comput. Appl. Math. 89(1), 115–118 (1998)
M.M. Chawla, M.A. Al-Zanaidi, S.S. Al-Ghonaim, Singly-implicit stabilized extended one-step methods for second-order initial-value problems with oscillating solutions. Math. Comput. Model. 29(2), 63–72 (1999)
J.P. Coleman, Numerical-methods for Y”=F(X, Y) via rational-approximations for the cosine. IMA J. Numer. Anal. 9(2), 145–165 (1989)
J.P. Coleman, A.S. Booth, Analysis of a family of Chebyshev methods for Y” = F(X, Y). J. Comput. Appl. Math. 44(1), 95–114 (1992)
J.P. Coleman, L. Gr, P-stability and exponential-fitting methods for Y”=F(X, Y). IMA J. Numer. Anal. 16(2), 179–199 (1996)
J.P. Coleman, S.C. Duxbury, Mixed collocation methods for Y ” = F(X, Y). J. Comput. Appl. Math. 126(1–2), 47–75 (2000)
L. Gr, Ixaru, S. Berceanu, Coleman method maximally adapted to the Schrödinger-equation. Comput. Phys. Commun. 44(1–2), 11–20 (1987)
L. Gr, Ixaru, The Numerov method and singular potentials. J. Comput. Phys. 72(1), 270–274 (1987)
L.G. Ixaru, M. Rizea, Numerov method maximally adapted to the Schrödinger-equation. J. Comput. Phys. 73(2), 306–324 (1987)
L.G. Ixaru, H. De Meyer, G. Vanden Berghe, M. Van Daele, Expfit4—a fortran program for the numerical solution of systems of nonlinear second-order initial-value problems. Comput. Phys. Commun. 100(1–2), 71–80 (1997)
L.G. Ixaru, G. Vanden Berghe, H. De Meyer, M. Van Daele, Four-step exponential-fitted methods for nonlinear physical problems. Comput. Phys. Commun. 100(1–2), 56–70 (1997)
L.G. Ixaru, M. Rizea, Four step methods for Y”=F(X, Y). J. Comput. Appl. Math. 79(1), 87–99 (1997)
M. Daele, G. Vanden Berghe, H. De Meyer, L.G. Ixaru, Exponential-fitted four-step methods for Y ”=F(X, Y). Int. J. Comput. Math. 66(3–4), 299–309 (1998)
L.G. Ixaru, B. Paternoster, A conditionally P-stable fourth-order exponential-fitting method for Y ” = F(X, Y). J. Comput. Appl. Math. 106(1), 87–98 (1999)
L.G. Ixaru, Numerical operations on oscillatory functions. Comput. Chem. 25(1), 39–53 (2001)
L.G. Ixaru, G. Vanden Berghe, H. De Meyer, Exponentially fitted variable two-step BDF algorithm for first order odes. Comput. Phys. Commun. 150(2), 116–128 (2003)
Z. Chen, C. Liu, T.E. Simos, New three-stages symmetric two step method with improved properties for second order initial/boundary value problems. J. Math. Chem. 56(9), 2591–2616 (2018)
M.A. Medvedeva, T.E. Simos, An accomplished phase FD process for DEs in chemistry. J. Math. Chem. 57(10), 2208–2228 (2019)
S. Hao, T.E. Simos, A phase fitted FinDiff process for DifEquns in quantum chemistry. J. Math. Chem. 58(2), 353–381 (2020)
I. Alolyan, T.E. Simos, A four-stages multistep fraught in phase method for quantum chemistry problems. J. Math. Chem. 57, 1627–1651 (2019)
M.A. Medvedeva and T.E. Simos, Phase fitted algorithm for problems in quantum chemistry. J. Math. Chem. (to appear)
Z. Wang, T.E. Simos, A finite difference method with zero phase-lag and its derivatives for quantum chemistry problems. J. Math. Chem. (in press)
M.A. Medvedev, T.E. Simos, A finite difference method with phase-lag and its derivatives equal to zero for problems in chemistry. J. Math. Chem. (in press)
Z. Wang, T.E. Simos, A new algorithm with eliminated phase–lag and its derivatives up to order five for problems in quantum chemistry. J. Math. Chem. (to appear)
X. Mingfei, T.E. Simos, A multistage two-Step fraught in phase scheme for problems in mathematical Chemistry. J. Math. Chem. 57(7), 1710–1731 (2019)
J. Lv, T.E. Simos, A Runge-Kutta type crowded in phase algorithm for Quantum Chemistry problems. J. Math. Chem. 57(8), 1983–2006 (2019)
X. Zhang, T.E. Simos, A multiple stage absolute in phase scheme for Chemistry problems. J. Math. Chem. 57(9), 2049–2074 (2019)
J. Qiu, T.E. Junjie Huang, Simos, A perfect in phase FD algorithm for problems in Quantum Chemistry. J. Math. Chem. 57(9), 2019–2048 (2019)
F. Hui, T.E. Simos, A new family of two stage symmetric two-Step Methods with vanished phase-lag and its derivatives for the numerical integration of the Schrödinger equation. J. Math. Chem. 53(10), 2191–2213 (2015)
L.G. Ixaru, M. Rizea, Comparison of some four-Step Methods for the numerical solution of the Schrödinger equation. Comput. Phys. Commun. 38(3), 329–337 (1985)
L.G. Ixaru, M. Micu, Topics in Theoretical Physics, Central Institute of Physics, Bucharest (1978)
L.G. Ixaru, M. Rizea, A Numerov-like scheme for the numerical solution of the Schrödinger equation in the deep continuum spectrum of energies. Comput. Phys. Commun. 19, 23–27 (1980)
J.R. Dormand, M.E.A. El-Mikkawy, P.J. Prince, Families of Runge–Kutta-Nyström formulae. IMA J. Numer. Anal. 7, 235–250 (1987)
J.R. Dormand, P.J. Prince, A family of embedded Runge–Kutta formulae. J. Comput. Appl. Math. 6, 19–26 (1980)
G.D. Quinlan, S. Tremaine, Symmetric multistep methods for the numerical integration of planetary orbits. Astronom. J. 100, 1694–1700 (1990)
A.D. Raptis, A.C. Allison, Exponential-fitting methods for the numerical solution of the Schrödinger equation. Comput. Phys. Commun. 14, 1–5 (1978)
M.M. Chawla, P.S. Rao, An Noumerov-type method with minimal phase-lag for the integration of second order periodic initial-value problems II. Explicit Method. J. Comput. Appl. Math. 15, 329–337 (1986)
M.M. Chawla, P.S. Rao, An explicit sixth-order Method with phase-lag of order eight for \(y^{\prime \prime }=f(t, y)\). J. Comput. Appl. Math. 17, 363–368 (1987)
M. Rizea, Exponential fitting method for the time-dependent Schrödinger equation. J. Math. Chem. 48(1), 55–65 (2010)
A. Konguetsof, Two-step high order hybrid explicit Method for the numerical solution of the Schrödinger equation. J. Math. Chem. 48, 224–252 (2010)
A.D. Raptis, J.R. Cash, A variable Step Method for the numerical integration of the one-dimensional Schrödinger equation. Comput. Phys. Commun. 36, 113–119 (1985)
A.C. Allison, The numerical solution of coupled differential equations arising from the Schrödinger equation. J. Comput. Phys. 6, 378–391 (1970)
R.B. Bernstein, A. Dalgarno, H. Massey, I.C. Percival, Thermal scattering of atoms by homonuclear diatomic molecules. Proc. R. Soc. Ser. A 274, 427–442 (1963)
R.B. Bernstein, Quantum mechanical (phase shift) analysis of differential elastic scattering of molecular beams. J. Chem. Phys. 33, 795–804 (1960)
M. Rizea, V. Ledoux, M. Van Daele, G. Vanden Berghe, N. Carjan, Finite Difference approach for the two-dimensional Schrödinger equation with application to scission-neutron emission. Comput. Phys. Commun. 179(7), 466–478 (2008)
J.R. Dormand, P.J. Prince, A family of embedded Runge–Kutta formula. J. Comput. Appl. Math. 6, 19–26 (1980)
M. Kenan, T.E. Simos, A Runge–Kutta type implicit high algebraic order two-Step Method with vanished phase-lag and its first, second, third and fourth derivatives for the numerical solution of coupled differential equations arising from the Schrödinger equation. J. Math. Chem. 53, 1239–1256 (2015)
L.G. Ixaru, M. Rizea, G. Vanden Berghe, H. De Meyer, Weights of the exponential fitting multistep algorithms for first-order odes. J. Comput. Appl. Math. 132(1), 83–93 (2001)
A.D. Raptis, J.R. Cash, Exponential and bessel fitting methods for the numerical-solution of the Schrödinger-equation. Comput. Phys. Commun. 44(1–2), 95–103 (1987)
C.D. Papageorgiou, A.D. Raptis, A method for the solution of the Schrödinger-Equation. Comput. Phys. Commun. 43(3), 325–328 (1987)
Z. Zhou, T.E. Simos, A new two stage symmetric two-step method with vanished phase-lag and its first, second, third and fourth derivatives for the numerical solution of the radial Schrödinger equation. J. Math. Chem. 54, 442–465 (2016)
A.D. Raptis, Exponential multistep methods for ordinary differential equations. Bull. Greek Math. Soc. 25, 113–126 (1984)
H. Ning, T.E. Simos, A low computational cost eight algebraic order hybrid Method with vanished phase-lag and its first, second, third and fourth derivatives for the approximate solution of the Schrödinger equation. J. Math. Chem. 53(6), 1295–1312 (2015)
Z. Wang, T.E. Simos, An economical eighth-order Method for the approximation of the solution of the Schrödinger equation. J. Math. Chem. 55, 717–733 (2017)
K. Yan, T.E. Simos, A finite difference pair with improved phase and stability properties. J. Math. Chem. (in press)
J.R. Cash, A.D. Raptis, A high-order method for the numerical-integration of the one-dimensional Schrödinger-equation. Comput. Phys. Commun. 33(4), 299–304 (1984)
A.D. Raptis, Exponentially-fitted solutions of the eigenvalue Shrödinger equation with automatic error control. Comput. Phys. Commun. 28(4), 427–431 (1983)
A.D. Raptis, 2-step methods for the numerical-solution of the Schrödinger-equation. Comput. Phys. Commun. 28(4), 373–378 (1982)
A.D. Raptis, On the numerical-solution of the Schrödinger-equation. Comput. Phys. Commun. 24(1), 1–4 (1981)
A.D. Raptis, Exponential-fitting methods for the numerical-integration of the 4th-order differential-equation Y\(^{iv}\)+F.Y=G. Computing 24(2–3), 241–250 (1980)
H. Van De Vyver, A symplectic exponentially fitted modified Runge–Kutta–Nyström method for the numerical integration of orbital problems. New Astron. 10(4), 261–269 (2005)
H. Van De Vyver, On the generation of P-stable exponentially fitted Runge–Kutta–Nyström methods by exponentially fitted Runge–Kutta methods. J. Comput. Appl. Math. 188(2), 309–318 (2006)
M. Van Daele, G. Vanden Berghe, P-stable Obrechkoff methods of arbitrary order for second-order differential equations. Numer. Algorithms 44(2), 115–131 (2007)
M. Van DAELE, G. Vanden Berghe, P-stable exponentially-fitted Obrechkoff Methods of arbitrary order for second-order differential equations. Numer. Algorithms 46(4), 333–350 (2007)
G. Wang, T.E. Simos, New multiple stages two-step complete in phase algorithm with improved characteristics for second order initial/boundary value problems. J. Math. Chem. 57(2), 494–515 (2019)
C.-W. Hsu, C. Lin, C. Liu, T.E. Simos, A new four-stages two-step phase fitted scheme for problems in quantum chemistry. J. Math. Chem. 57, 1201–1229 (2019). https://doi.org/10.1007/s10910-019-01018-z10.1007/s10910-019-01018-z10.1007/s10910-019-01018-z10.1007/s10910-019-01018-z
G. Vanden Berghe, M. Van Daele, Exponentially-fitted Obrechkoff Methods for second-order differential equations. Appl. Numer. Math. 59(3–4), 815–829 (2009)
D. Hollevoet, M. Van Daele, G. Vanden Berghe, The optimal exponentially-fitted Numerov method for solving two-point boundary value problems. J. Comput. Appl. Math. 230(1), 260–269 (2009)
J.M. Franco, L. Rández, Explicit exponentially fitted two-Step hybrid Methods of high order for second-order oscillatory IVPs. Appl. Math. Comput. 273, 493–505 (2016)
J.M. Franco, Y. Khiar, L. Rández, Two new embedded pairs of explicit Runge-Kutta Methods adapted to the numerical solution of oscillatory problems. Appl. Math. Comput. 252, 45–57 (2015)
J.M. Franco, I. Gomez, L. Rández, Optimization of explicit two-Step hybrid Methods for solving orbital and oscillatory problems. Comput. Phys. Commun. 185(10), 2527–2537 (2014)
J.M. Franco, I. Gomez, Trigonometrically fitted nonlinear two-Step Methods for solving second order oscillatory IVPs. Appl. Math. Comput. 232, 643–657 (2014)
J.M. Franco, I. Gomez, Symplectic explicit methods of Runge–Kutta-Nyström type for solving perturbed oscillators. J. Comput. Appl. Math. 260, 482–493 (2014)
J.M. Franco, I. Gomez, Some procedures for the construction of high-order exponentially fitted Runge–Kutta–Nyström methods of explicit type. Comput. Phys. Commun. 184(4), 1310–1321 (2013)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, On some new low storage implementations of time advancing Runge–Kutta Methods. J. Comput. Appl. Math. 236(15), 3665–3675 (2012)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, Symmetric and symplectic exponentially fitted Runge–Kutta methods of high order. Comput. Phys. Commun. 181(12), 2044–2056 (2010)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, On high order symmetric and symplectic trigonometrically fitted Runge–Kutta Methods with an even number of stages. BIT Numer. Math. 50(1), 3–21 (2010)
J.M. Franco, I. Gomez, Accuracy and linear stability of RKN methods for solving second-order stiff problems. Appl. Numer. Math. 59(5), 959–975 (2009)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, Sixth-order symmetric and symplectic exponentially fitted Runge–Kutta Methods of the Gauss type. J. Comput. Appl. Math. 223(1), 387–398 (2009)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, Structure preservation of exponentially fitted Runge–Kutta Methods. J. Comput. Appl. Math. 218(2), 421–434 (2008)
M. Calvo, J.M. Franco, J.I. Montijano, L. Rández, Sixth-order symmetric and symplectic exponentially fitted modified Runge–Kutta Methods of Gauss type. Comput. Phys. Commun. 178(10), 732–744 (2008)
J.M. Franco, Exponentially fitted symplectic integrators of RKN type for solving oscillatory problems. Comput. Phys. Commun. 177(6), 479–492 (2007)
J.M. Franco, New Methods for oscillatory systems based on ARKN Methods. Appl. Numer. Math. 56(8), 1040–1053 (2006)
J.M. Franco, Runge–Kutta–Nyström Methods adapted to the numerical integration of perturbed oscillators. Comput. Phys. Commun. 147, 770–787 (2002)
J.M. Franco, Stability of explicit ARKN Methods for perturbed oscillators. J. Comput. Appl. Math. 173, 389–396 (2005)
X.Y. Wu, X. You, J.Y. Li, Note on derivation of order conditions for ARKN Methods for perturbed oscillators. Comput. Phys. Commun. 180, 1545–1549 (2009)
A. Tocino, J. Vigo-Aguiar, Symplectic conditions for exponential fitting Runge–Kutta–Nyström Methods. Math. Comput. Model. 42, 873–876 (2005)
L. Brugnano, F. Iavernaro, D. Trigiante, Hamiltonian boundary value Methods (energy preserving discrete line integral Methods). JNAIAM J. Numer. Anal. Ind. Appl. Math. 5, 17–37 (2010)
F. Iavernaro, D. Trigiante, High-order symmetric schemes for the energy conservation of polynomial Hamiltonian problems. JNAIAM J. Numer. Anal. Ind. Appl. Math. 4, 87–101 (2009)
A. Konguetsof, A generator of families of two-Step numerical Methods with free parameters and minimal phase-lag. J. Math. Chem. 55(9), 1808–1832 (2017)
A. Konguetsof, A hybrid Method with phase-lag and derivatives equal to zero for the numerical integration of the Schrödinger equation. J. Math. Chem. 49(7), 1330–1356 (2011)
H. Van de Vyver, A phase-fitted and amplification-fitted explicit two-Step hybrid Method for second-order periodic initial value problems. Int. J. Modern Phys. C 17(5), 663–675 (2006)
H. Van de Vyver, An explicit Numerov-type Method for second-order differential equations with oscillating solutions. Comput. Math. Appl. 53(9), 1339–1348 (2007)
Y. Fang, W. Xinyuan, A trigonometrically fitted explicit hybrid Method for the numerical integration of orbital problems. Appl. Math. Comput. 189(1), 178–185 (2007)
B. Neta, P-stable high-order super-implicit and Obrechkoff Methods for periodic initial value problems. Comput. Math. Appl. 54(1), 117–126 (2007)
H. Van de Vyver, Phase-fitted and amplification-fitted two-Step hybrid Methods for y ” = f (x, y). J. Comput. Appl. Math. 209(1), 33–53 (2007)
H. Van de Vyver, Efficient one-step methods for the Schrödinger equation. MATCH Commun. Math. Comput. Chem. 60(3), 711–732 (2008)
J. Martín-Vaquero, J. Vigo-Aguiar, Exponential fitted Gauss, Radau and Lobatto Methods of low order. Numer. Algorithms 48(4), 327–346 (2008)
A. Konguetsof, A new two-Step hybrid Method for the numerical solution of the Schrödinger equation. J. Math. Chem. 47(2), 871–890 (2010)
Fatheah A. Hendi, P-stable higher derivative methods with minimal phase-lag for solving second order differential equations. J. Appl. Math. 2011 Article ID 407151 (2011)
H. Van de Vyver, Comparison of some special optimized fourth-order Runge–Kutta Methods for the numerical solution of the Schrödinger equation. Comput. Phys. Commun. 166(2), 109–122 (2005)
Z. Wang, D. Zhao, Y. Dai, W. Dongmei, An improved trigonometrically fitted P-stable Obrechkoff Method for periodic initial-value problems. Proc. R. Soc. A Math. Phys. Eng. Sci. 461(2058), 1639–1658 (2005)
M. Daele, G. Vanden Berghe, H. De Meyer, Properties and implementation of R-Adams methods based on mixed-type interpolation. Comput. Math. Appl. 30(10), 37–54 (1995)
J. Vigo-Aguiar, L.M. Quintales, A parallel ODE solver adapted to oscillatory problems. J. Supercomput. 19(2), 163–171 (2001)
Z. Wang, Trigonometrically-fitted method with the Fourier frequency spectrum for undamped duffing equation. Comput. Phys. Commun. 174(2), 109–118 (2006)
Z. Wang, Trigonometrically-fitted Method for a periodic initial value problem with two frequencies. Comput. Phys. Commun. 175(4), 241–249 (2006)
J. Vigo-Aguiar, J.M. Ferrandiz, A general procedure for the adaptation of multistep algorithms to the integration of oscillatory problems. SIAM J. Numer. Anal. 35(4), 1684–1708 (1998)
J. Vigo-Aguiar, H. Ramos, Dissipative Chebyshev exponential-fitted Methods for numerical solution of second-order differential equations. J. Comput. Appl. Math. 158(1), 187–211 (2003)
J. Vigo-Aguiar, S. Natesan, A parallel boundary value technique for singularly perturbed two-point boundary value problems. J. Supercomput. 27(2), 195–206 (2004)
C. Tang, H. Yan, H. Zhang, W.R. Li, The various order explicit multistep exponential fitting for systems of ordinary differential equations. J. Comput. Appl. Math. 169(1), 171–182 (2004)
C. Tang, H. Yan, H. Zhang, Z. Chen, M. Liu, G. Zhang, The arbitrary order implicit multistep schemes of exponential fitting and their applications. J. Comput. Appl. Math. 173(1), 155–168 (2005)
H. Van de Vyver, Frequency evaluation for exponentially fitted Runge–Kutta Methods. J. Comput. Appl. Math. 184(2), 442–463 (2005)
J.P. Coleman, L. Gr, Truncation errors in exponential fitting for oscillatory problems. SIAM J. Numer. Anal. 44(4), 1441–1465 (2006)
J. Martín-Vaquero, J. Vigo-Aguiar, Adapted BDF algorithms: higher-order methods and their stability. J. Sci. Comput. 32(2), 287–313 (2007)
J. Vigo-Aguiar, J. Martín-Vaquero, H. Ramos, Exponential fitting BDF-Runge–Kutta algorithms. Comput. Phys. Commun. 178(1), 15–34 (2008)
B. Paternoster, Present state-of-the-art in exponential fitting. A contribution dedicated to Liviu Ixaru on his 70th birthday. Comput. Phys. Commun. 183(12), 2499–2512 (2012)
Z. Wang, Obrechkoff one-step method fitted with Fourier spectrum for undamped duffing equation. Comput. Phys. Commun. 175(11–12), 692–699 (2006)
C. Wang, Z. Wang, A P-stable eighteenth-order six-step method for periodic initial value problems. Int. J. Modern Phys. C 18(3), 419–431 (2007)
J. Chen, Z. Wang, H. Shao, H. Hao, Highly-accurate ground state energies of the He atom and the He-like ions by Hartree SCF calculation with Obrechkoff Method. Comput. Phys. Commun. 179(7), 486–491 (2008)
H. Shao, Z. Wang, Arbitrarily precise numerical solutions of the one-dimensional Schrödinger equation. Comput. Phys. Commun. 180(1), 1–7 (2009)
Hezhu Shao and Zhongcheng Wang, Numerical solutions of the time-dependent Schrödinger equation: Reduction of the Error due to space discretization. Phys. Rev. E 79(5) Article Number: 056705 (2009)
Z. Wang, H. Shao, A new kind of discretization scheme for solving a two-dimensional time-independent Schrödinger equation. Comput. Phys. Commun. 180(6), 842–849 (2009)
T.E. Simos, Exponentially fitted Runge–Kutta Methods for the numerical solution of the Schrödinger equation and related problems. Comput. Mater. Sci. 18, 315–332 (2000)
C.J. Cramer, Essentials of Computational Chemistry (Wiley, Chichester, 2004)
F. Jensen, Introduction to Computational Chemistry (Wiley, Chichester, 2007)
A.R. Leach, Molecular Modelling—Principles and Applications (Pearson, Essex, 2001)
P. Atkins, R. Friedman, Molecular Quantum Mechanics (Oxford University Press, Oxford, 2011)
V.N. Kovalnogov, R.V. Fedorov, D.A. Generalov, Y.A. Khakhalev, A.N. Zolotov, Numerical research of turbulent boundary layer based on the fractal dimension of pressure fluctuations. AIP Conf. Proc. 738, 480004 (2016)
V.N. Kovalnogov, R.V. Fedorov, T.V. Karpukhina, E.V. Tsvetova, Numerical analysis of the temperature stratification of the disperse flow. AIP Conf. Proc. 1648, 850033 (2015)
N. Kovalnogov, E. Nadyseva, O. Shakhov, V. Kovalnogov, Control of turbulent transfer in the boundary layer through applied periodic effects. Izvestiya Vysshikh Uchebnykh Zavedenii Aviatsionaya Tekhnika 1, 49–53 (1998)
V.N. Kovalnogov, R.V. Fedorov, D.A. Generalov, Modeling and development of cooling technology of turbine engine blades. Int. Rev. Mech. Eng. 9(4), 331–335 (2015)
D. Yang, X. Li, J. Qiu, Output tracking control of delayed switched systems via state-dependent switching and dynamic output feedback. Nonlinear Anal. Hybrid Syst. 32, 294–305 (2019)
X. Yang, X. Li, Q. Xi, P. Duan, Review of stability and stabilization for impulsive delayed systems. Math. Biosci. Eng. 15(6), 1495–1515 (2018)
X. Li, X. Yang, T. Huang, Persistence of delayed cooperative models: impulsive control method. Appl. Math. Comput. 342, 130–146 (2019)
X. Li, R. Jianhua Shen, Rakkiyappan, Persistent impulsive effects on stability of functional differential equations with finite or infinite delay. Appl. Math. Comput. 329, 14–22 (2018)
D. Yang, X. Li, J. Shen, Z. Zhou, State-dependent switching control of delayed switched systems with stable and unstable modes. Math. Methods Appl. Sci. 41(16), 6968–6983 (2018)
H. Jingting, G. Sui, X. Lv, X. Li, Fixed-time control of delayed neural networks with impulsive perturbations. Nonlinear Anal. Model. Control 23(6), 904–920 (2018)
X. Li, D. O’Regan, H. Akca, Global exponential stabilization of impulsive neural networks with unbounded continuously distributed delays. IMA J. Appl. Math. 80(1), 85–99 (2015)
T. Xiaodi Li, Caraballo, R. Rakkiyappan, X. Han, On the stability of impulsive functional differential equations with infinite delays. Math. Methods Appl. Sci. 38(14), 3130–3140 (2015)
X. Li, J. Shen, R. Haydar Akca, Rakkiyappan, LMI-based stability for singularly perturbed nonlinear impulsive differential systems with delays of small parameter. Appl. Math. Comput. 250, 798–804 (2015)
S. Kottwitz, LaTeX Cookbook, pp. 231–236, Packt Publishing Ltd., Birmingham B3 2PB, UK (2015)
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Medvedev, M.A., Simos, T.E. New FD scheme with vanished phase-lag and its derivatives up to order six for problems in chemistry. J Math Chem 58, 2324–2360 (2020). https://doi.org/10.1007/s10910-020-01168-5
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DOI: https://doi.org/10.1007/s10910-020-01168-5
Keywords
- Phase-lag
- Derivative of the phase-lag
- Initial value problems
- Oscillating solution
- Symmetric
- Hybrid
- Multistep
- Schrödinger equation