Abstract
In this article, we obtain certain bounds for statistical curvatures of submanifolds with any codimension of Kenmotsu-like statistical manifolds. In this context, we construct a class of optimum inequalities for submanifolds in Kenmotsu-like statistical manifolds containing the normalized scalar curvature and the generalized normalized Casorati curvatures. We also define the second fundamental form of those submanifolds that satisfy the equality condition. On Legendrian submanifolds of Kenmotsu-like statistical manifolds, we discuss a conjecture for Wintgen inequality. At the end, some immediate geometric consequences are stated.
1. Introduction
A statistical manifold is an extension of a statistical model that is abstraction. The statistical manifold characterization is based on a statistical model in which the density functions are swapped by any Riemannian manifold , the Riemannian metric substitutes the Fisher information matrix of the manifold , the dual connections and are exchanged by a couple of dual connections and , and the skewness tensor is modified by a three-covariant skewness tensor, which counts the cummulants of the third order. Amari [1] first developed statistical manifolds in 1985. He looked at it from the standpoint of information geometry, and such manifolds include the concept of dual connections, also known as conjugate connections in affine geometry, which is strongly linked to affine differential geometry and has applications in numerous fields of scientific disciplines.
In its most basic form, information geometry is a part of mathematics that uses differential geometry concepts to the topic of probability theory. A model is a statistical manifold, and the amount of the parameters affects the point of statistical manifold and its transformation are well known from thermodynamics. The natural Riemannian manifold for thermodynamics is the statistical manifold. The geometrical representation in the framework of Gibbs’s statistical mechanical representation for reversible and irreversible fluctuations in the value of the critical variable. Entropy mechanics, which can give significant mechanical techniques in the analysis of thermodynamics, remains at the center of Gibbs’ work. Gibbs statistical manifolds frameworks have been extended to represent statistical manifold kinematics. Furthermore, thermodynamic equilibrium exists in the form of statistical groups across independent states, which serve as a link between statistical thermodynamics and information geometry theories. Fisher information matrix, for example, is useful to neural networks and Langevin kinetics. Furthermore, Newtonian dynamics can be recast in the language of Riemannian geometry applied to probability theory, namely, information geometry, where the link is made using the probability distribution’s average. As a result, the dynamics take place on a statistical manifold that is naturally endowed with a metric structure furnished by information geometry and the curvature of the statistical manifolds has a significant influence. For example, an entropy dynamics (ED) statistical model has been constructed on a -dimensional statistical manifold M. The micro-coordinated on the manifolds are represented by the expectation values of micro variables associated with Gaussian distribution.
The normalized square of the length of the second basic form of a submanifold of a Riemannian manifold was defined by Casorati [2] as Casorati curvature. This concept went beyond the primary direction of Riemannian manifold hypersurfaces. Geometry and other domains, such as computer visual information, have examined the Casorati curvature. Some findings were achieved in terms of isotropical Casorati curvature of production surfaces. In Riemannian manifolds, a geometrical explanation of the Casorati curvature of submanifolds was also investigated. Recently, a geometric analysis of the Cauchy–Schwarz inequality in terms of Casorati curvature has been considered. In this reason, the geometric study of Casorati curvatures for submanifolds is new and has many research problems. A couple of optimal Casorati inequalities had been obtained by many distinguished geometers in different ambient space forms (for example, [3,4]). Decu et al. have built certain inequalities for statistical submanifolds of Kenmotsu statistical manifolds with constant -sectional curvature involving normalized -Casorati curvatures and scalar curvature in [5]. Inequalities for statistical warped product submanifolds were explored by Aliya et al. in [6].
Wintgen [7], on the other hand, proposed a crucial relationship between the Gauss curvature, normal curvature, and squared mean curvature of any surface N in a four-dimensional Euclidean space , as well as the necessary and sufficient conditions under which the equality case holds. Guadalupe and Rodriguez generalized Wintgen’s inequality to a real-space surface of arbitrary codimension in the form , . After that, Chen extended this inequality to surfaces in a 4-dimensional pseudo-Euclidean space with a neutral metric. In [8], DeSmet, Dillen, Verstraelen, and Vrancken found the DDVV conjecture (called the generalized Wintgen inequality in general) for an isometric immersion of a Riemannian manifold into a real space form. Furthermore, in [8], they conjectured this inequality for a submanifold with codimension 2 in a real space form . The solution of this conjecture was independently proven by Lu [9] and Ge and Tang [10] for general case. Since then, many remarkable articles were published and several inequalities of this type were obtained for other kinds of submanifolds in different ambient spaces (see [11,12,13,14,15]).
The derivation of inequality in terms of Casorati curvatures for various submanifolds in various ambient spaces is focused on an optimization approach that establishes that the polynomial of quadratic type in the components of the second fundamental form is parabolic. However, in the present paper, the proof of the inequality involving Casorati curvatures (of submanifolds in Kenmotsu-like statistical manifolds) in Theorem 3 is emphasised on a constrained extremum problem on the submanifold given in Lemma 1. Equality case is also examined. On the other hand, we extend the classical DDVV inequality to a Legendrian submanifold in Kenmotsu-like statistical manifolds. The main ingredient in proving Theorem 6 is given by Theorem 5, which actually translates the DDVV-conjecture to an algebraic problem involving some traceless symmetric matrices.
2. Preliminaries
A semi-Riemannian manifold and non-degenerate metric , and a torsion-free affine connection by . The triplet is said to be a statistical manifold [16] with symmetric . It is usually denoted by .
In case of a statistical manifold, we have a second connection as:
for any , . The torsion-free affine connection is called dual (or conjugate) of the connection with respect to the and obeys
where is indicates the Levi-Civita connection on .
A semi-Riemannian manifold is said to be an almost contact metric manifold with almost contact structure of certain kind [17] if it admits the almost contact structure which satisfies the following equations:
and also has another tensor field of type which obeys
for any . It is easy to see that
As a tensor field is not symmetric, it shows that everywhere.
Kenmotsu [18] initiated the study of Kenmotsu geometry, which is a crucial class of contact geometry. The almost contact metric manifold of certain class is said to be Kenmotsu-like statistical manifold [19], if the following axioms hold
The curvature tensor with respect to on a Kenmotsu-like statistical manifold is given as:
where .
After, shifting to in (9), we turn up the expression of the curvature tensor for .
Certainly, is a statistical manifold. For example, every semi-Riemannian manifold endowed with a Riemannian connection is a trivial statistical manifold. In this case, one turn up
for any [16].
Let M be a submanifold of on a statistical manifold . Then ( is also said to be a statistical manifold with the induced statistical structure on M from and we say is a statistical submanifold in .
The Gauss and Weingarten equations are used in statistical settings, respectively, defined by [20]:
for any and , where and are the dual connections on . Similarly, on M, we denote them by D and . For and , the bilinear and symmetric imbedding curvature tensor of M in are, respectively, indicated by h and .
The finest relation between h (respectively, ) and A (respectively, ) can be seen as [20]
for any and .
It is also noted that the relations and exist by using (2).
The curvature tensor of and D are given by and R, respectively. Then, for any . Now, the corresponding Gauss formula are [20]
and
The Ricci equations for and are, respectively, given below [20]
and
for any and . Here and are the normal curvature tensors for and on , respectively.
The usual definitions, in general, cannot produce a sectional curvature with regard to dual connections (which, of course, are not metric). In [21,22], Opozda presented a statistical sectional curvature on a statistical manifold. As a result, the statistical curvature tensor fields of and M are defined as:
Additionally, the normal statistical curvature tensor is defined as:
For , we put
where is the tangential and is the normal component of . Likewise, we can write
where is the tangential and is the normal component of .
Similar to the classical definition of C-totally real and Legendrian submanifolds of a Kenmotsu manifold (see [23]), we provide the following definition:
Definition 1.
Let M be an n-dimensional submanifold of an -dimensional Kenmotsu-like statistical manifold . If , then M is called C-totally real. However, if , then a C-totally real submanifold turns to a Legendrian submanifold. Thus, it is easy to say that Legendrian submanifold is a C-totally real submanifold with the smallest possible codimension.
In the following sections, we prove several sharp inequalities on statistical submanifold immersed into a Kenmotsu-like statistical manifold with a curvature tensor of the kind (9).
3. Bounds for Normalized Scalar Curvature
In this section, we derive an inequality on the normalized scalar curvature of a statistical submanifold immersed into a Kenmotsu-like statistical manifold with a curvature tensor of the kind (9).
Let a statistical submanifold M of dimension m in a Kenmotsu-like statistical manifold . We assume a local orthonormal tangent (respectively, normal) frame (respectively, ) of (respectively, ), . Then, is the scalar curvature of M and hence the normalized scalar curvature of M are express as:
The mean curvature vectors are given by:
We set
for and .
We show the following.
Theorem 1.
Let a statistical submanifold in a Kenmotsu-like statistical manifold with curvature tensor is of the form (9). Then
Proof.
The characterization of equality cases in Theorem 1.
4. Optimizations on a Statistical Submanifold with Casorati Curvatures
In this section, first we study Casorati curvatures (in short ) for a statistical submanifold, with respect to D and , in a Kenmotsu-like statistical manifold.
Let a statistical submanifold M of dimension m in a Kenmotsu-like statistical manifold . We assume a local orthonormal tangent (respectively, normal) frame (respectively, ) of (respectively, ), . Then, the squared norm of second fundamental forms h and ( and ) are, respectively, indicated by and , known by the Casorati curvatures () of M in . Therefore, we have:
here
Next, we define an orthonormal basis of a t-dimensional subspace L of , . Then, the scalar curvature of the d-plane section L and the of subspace L are, respectively, given below:
and
The normalized and are, respectively, defined as:
and
Further, we, respectively, define the generalized normalized and as follows:
- (1)
- For
- (2)
- For
where
In a similar way, the normalized and and the generalized normalized and can be defined. We also notice that
To derive the section’s optimum inequalities, we require the following key lemma.
Lemma 1
([24]). If be a hyperplane of and is a quadratic form, then
The restricted extremum problem therefore gives f the following global solution:
provided that
Let and be orthonormal frames of and , , respectively. From Equations (9) and (13), we arrive at
We now define a quadratic polynomial in terms of the components of the second fundamental form Q as
We suppose that L is spanned by (without loss of generality), combining (20), it follows that:
where
Let us assume the quadratic form , for , defined by
and the problem as follows:
On Comparing the functions (18) and (22), we find that
which verify the relation the relation (19). Thus, by Lemma 1, entails that the critical point is given by:
and a result, it is the global lowest point.
Next, plugging (23) into (22), we arrive at
From (21) and (24), we get and hence we have the following:
Further, we find that:
Hence, we get the following inequality.
Theorem 3.
Let a statistical submanifold in a Kenmotsu-like statistical manifold with curvature tensor is of the form (9). Then, the generalized normalized and holds
Remark 1.
In a similar way ones can obtain inequality for the generalized normalized and , that is,
The characterization of equality cases in Theorem 3.
Theorem 4.
5. Bounds for the Normalized Normal Scalar Curvature
In this segment, we use the most important ingredient, derived by Lu for the symmetric and trace-free operators in [9], in the proof of our desired DDVV inequality. This is as follows.
Theorem 5.
Let a Riemannian submanifold of dimension n immersed into -dimensional Riemannian manifold. For every set of symmetric -matrices with trace zero the following inequality holds:
Let an m-dimensional Legendrian submanifold M of a Kenmotsu-like statistical manifold with curvature tensor is of the form (9) and and be orthonormal frames of and , , respectively. From Equations (9) and (13), we arrive at:
Then, the normalized scalar curvature of of M is
However, if we fix , and , the traceless part of the second fundamental forms, then, respectively, we get:
Thus, the expression (28) becomes:
Now, we compute our main extrinsic curvature and the normalized normal scalar curvature of M as below.
which refers to the following:
On simplifying (29) and applying the Cauchy-Schwarz inequality, , for , we introduce an inequality in (29) for as follows:
Now, by following the same steps done in [13], the sets , and of symmetric with trace zero operators on are defined as:
Clearly, we have the relations
and
for any .
Therefore, we have:
Then, by applying Theorem 5, we can easily arrive at:
Substituting (28) in the last relation, we get:
However, the normalized scalar curvature of M for Levi–Civita connection is:
Putting (34) into (35), we give the main result of this segment.
Theorem 6.
Let a Legendrian submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). Then we have:
6. Some Geometric Applications
In this part, we study some immediate applications of the results (Theorems 1 and 3) proved in the previous section.
In light of Lemma 1 and taking in (respectively, ), we find that:
at any point .
Thus, we turn up the following corollaries on Theorem 3.
Corollary 1.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). Then, the normalized and holds
Remark 2.
In a similar way, ones can obtain inequality for the normalized and .
Now, from
and together with , we have the relation
Hence, the following corollary follows directly from inequalities (25) and (26).
Corollary 2.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). If M is minimal, that is, . Then, we have:
Corollary 3.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). If M is minimal, that is, . Then, we have:
Some consequences of Theorem 1 are the following.
Corollary 4.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). If , then
Corollary 5.
Let a statistical submanifoldof a Kenmotsu-like statistical manifoldwith curvature tensor is of the kind (9). Suppose that
- 1.
- and;
- 2.
- and;
- 3.
- .
Then.
Remark 3.
In the above Corollary 5, we have , , which gives . Similarly, implies . Hence, an inequality (17) reduces to .
Corollary 6.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). If the following holds
Then neither nor .
Let us take a minimal submanifold M for the Levi-Civita connection, which gives because of and thus, we have the relation . Then Theorem 6 gives
Corollary 7.
Let a statistical submanifold of a Kenmotsu-like statistical manifold with curvature tensor is of the kind (9). Then we have
7. Related Examples
Example 1.
Let be a Euclidean space with local coordinate system , which admits the following almost complex structure J
the metric and the flat affine connection is a Kähler-like statistical manifold (see [17]). If is a trivial statistical manifold, it is known from [13] that the product manifold is a Kenmotsu-like statistical manifold, where .
We define and η by
and We also find
Next, we give examples of submanifolds in as follows:
Example 2.
Example 3.
Let us take a 3-dimensional submanifold of defined by an isometric immersion as Then the vector fields at each point of are given as , and . By direct calculations, we have and hence by Koszula formula, we calculate the Levi-Civita connection as for . This tells us that is a totally geodesic submanifold of with respect to . Thus, Theorem 4 is satisfied.
Example 4.
Let ω be an isometric immersion from to defined by , . The vector fields at each point of are given by , , and . By direct calculations, we find that , , and . It is easy to see that is a non-totally geodesic submanifold of with respect to Levi-Civita connection . In this case, the inequalities (25) and (26) are precisely satisfied at all points and the case of equality cannot be attained.
Author Contributions
Conceptualization, A.N.S. and M.D.S.; formal analysis, A.N.S. and M.D.S.; investigation, A.N.S. and M.D.S.; methodology, A.H.A.; project administration, A.N.S. and A.H.A.; validation, A.N.S. and M.D.S.; writing—original draft. All authors have read and agreed to the published version of the manuscript.
Funding
The present work is supported by the Deanship of Scientific research, King Khalid University, Saudi Arabia.
Institutional Review Board Statement
Not Applicable.
Informed Consent Statement
Not Applicable.
Data Availability Statement
Not Applicable.
Acknowledgments
The authors are grateful to the referees for the valuable suggestions and comments towards the improvement of this paper. The third author extends their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under grant number R.G.P.2/74/42.
Conflicts of Interest
The authors declare that they have no competing interest.
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