Submitted:
01 April 2026
Posted:
02 April 2026
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Abstract
This paper investigates the structure of fuzzy Lie subalgebras, with particular emphasis on isomorphisms and nilpotency. Building on two prior conference contributions, one of which established foundational results on fuzzy bases of Lie algebras, we develop here a more complete and unified treatment of these themes. We introduce a notion of isomorphism between fuzzy Lie subalgebras based on the transfer principle via t-cut sets, and we prove that isomorphic fuzzy Lie subalgebras necessarily share the same nilpotency measure. The central contribution of the paper is a fuzzy measure of nilpotency N(μ)∈[0,1], defined for any non-constant fuzzy Lie subalgebra μ of a Lie algebra g. This invariant equals 1 precisely when μ is fuzzy nilpotent, and decreases as the subalgebra departs from nilpotency. We show that nilpotency of the underlying Lie algebra implies N(μ)=1, but that the converse fails in general, as witnessed by an explicit counterexample.
Keywords:
fuzzy lie algebra
; nilpotent lie algebra
; isomorphisms
MSC: 03E72 (primary); 17B99; 17B30; 17B40
1. Introduction
The interplay between fuzzy set theory and algebraic structures has been a fertile area of research since Zadeh’s foundational work [1]. The idea of endowing classical algebraic objects with a graded membership function — rather than a sharp, crisp boundary — opens up a richer landscape in which structural properties can be studied not just as binary predicates, but as matters of degree. After Zadeh, Rosenfeld started researching how the fuzzy set theory could be used in abstract algebra, and wrote about this in a well-known work [2]. He was inspired by a paper [3], in which appears the first occurrence of fuzzy set theory used in topological spaces. For more about the history of this topic the reader is referred to [4]. Lie algebra is a well-known algebraic structure that is used a lot for its complex bracket operations and its links to geometry and physics. It is a great subject to use in this type of fuzzy enrichment.
The concept of a fuzzy Lie subalgebra, first discussed in [5], has since been extensively investigated, with a particularly detailed analysis being offered in [6]. The majority of the current research concentrates on the definitional and categorical dimensions of fuzzy Lie subalgebras, encompassing their substructures, homomorphisms, and ideals. The question of nilpotency, however, has received comparatively little attention in the fuzzy setting, despite being one of the most central notions in classical Lie theory.
The present paper grows out of two conference contributions [7,8]. The first [7] laid the groundwork by investigating the foundational properties of fuzzy Lie algebras as fuzzy vector spaces, with particular attention to the notion of a fuzzy basis and the conditions under which a classical basis retains its fuzzy character. The second [8] introduced a definition of nilpotency tailored to the fuzzy setting and undertook a comparative analysis with both the classical notion and existing alternatives in the literature. Here, we consolidate and significantly extend those results, providing a more complete and unified treatment.
Specifically, we introduce a definition of nilpotency for fuzzy Lie subalgebras via an ascending central series adapted to the fuzzy context inspired by the one previosly introduced in [9] for fuzzy groups. We also show that while nilpotency of the underlying crisp Lie algebra implies fuzzy nilpotency, the converse fails — a phenomenon that is both natural and, we believe, geometrically meaningful. To capture this asymmetry, we propose a numerical invariant , which we call the fuzzy nilpotency measure of a fuzzy Lie subalgebra . This measure equals 1 precisely when is fuzzy nilpotent, and takes smaller values the further is from nilpotency.
We also study isomorphisms between fuzzy Lie subalgebras, proposing a definition based on the transfer principle through t-cut sets. We compare this with the categorical notion developed in [10], and we prove that isomorphic fuzzy Lie subalgebras necessarily share the same nilpotency measure. Finally, we interpret N as a fuzzy measure in the sense of Sugeno, and establish some of its basic properties, including subadditivity.
The paper is organised as follows. Section 2 recalls the necessary background on Lie algebras and fuzzy Lie subalgebras, including fuzzy bases and t-cut sets. In Section 3, we study isomorphisms of fuzzy Lie subalgebras and their connection with flags of subalgebras. Section 4 introduces nilpotent fuzzy Lie subalgebras and the fuzzy nilpotency measure N, along with its basic properties.
2. Preliminaries
A vector space over a field is a Lie algebra if it is equipped with a bilinear map , the Lie bracket, satisfying the following properties:
for every .
This study focuses on finite-dimensional Lie algebras, meaning those with a finite basis as vector spaces. As illustrated by Equation (1), this bilinear map is alternating, and it is crucial to recognise that this implies the map is skew-symmetric. Indeed, we have
Thus, since the Lie bracket is bilinear, the previous equation and Equation (1) imply that
and then
If the field has a characteristic that is not 2, then the last condition on the Lie bracket is equivalent to requiring that it is alternating, since
Given the assumptions on the underlying field, equation (3) can replace the initial formulation. Throughout this work, we consider Lie brackets defined over real vector spaces, that is, over the field . Unless stated otherwise, the Lie bracket is assumed to be skew-symmetric by definition.
The identity in Equation (2), known as the Jacobi identity, plays a central role in Lie algebra theory. It ensures the coherent behaviour of the Lie bracket operation. A detailed treatment of this identity is beyond the scope of this paper; for further reading, see [11,12].
As is common in abstract algebra, once a structure is defined, its substructures are also introduced. These are subsets that themselves satisfy the axioms of the original structure (e.g., subgroups, subrings, linear subspaces). Lie subalgebras follow this pattern: they are vector subspaces of a Lie algebra that also form Lie algebras under the same bracket operation.
The notion of a fuzzy Lie subalgebra was first introduced by Yehia in [5]. The reader will find the majority of the definitions of fuzzy Lie algebra that are to be recalled in the same paper. For our purposes, we adopt the formalism and notation from [6] Definitions 1.16–1.17.
Definition 1.
Let be a Lie algebra over a field . A fuzzy set is called a fuzzy Lie subalgebra of over if
- 1.
- ,
- 2.
- ,
- 3.
- ,
for all and .
As a consequence of the second condition, we obtain and for all .
The first two conditions in Definition 1 characterise the fuzzy closure of vector addition and scalar multiplication, respectively. Together, they define a fuzzy subspace. The third condition is particularly significant, ensuring the fuzzy closure under the Lie bracket. From now on, we write to indicate that is a fuzzy Lie subalgebra of . Here, we recall some basic properties about fuzzy Lie subalgebras that will be utilised in our subsequent investigations.
Proposition 1.
Let μ be a fuzzy subspace of a vector space V. Then, for all , we have
- 1.
- .
- 2.
- If , then .
- 3.
- If , then .
We now recall that, if is a fuzzy subset of a Lie algebra over a field , the (crisp) set
is the t-cut set of for every .
The final part of this section introduces definitions and results that are essential for our study. We begin with a key concept from [13].
Definition 2.
Let V be a fuzzy vector space over a field . A set of vectors is said to be fuzzy linearly independent if
- 1.
- is linearly independent,
- 2.
- ,
for all , .
Definition 3
([13] Definition 4.1). A fuzzy basis of a fuzzy vector space V is a fuzzy linearly independent set that spans V.
In the classical setting, a basis of a vector space is a maximal set of linearly independent vectors that spans the space. Analogously, a fuzzy basis is a spanning set of fuzzy linearly independent vectors.
Any finite basis of a vector space V is trivially a fuzzy basis of V. Indeed, if is a crisp basis, then for any scalars , we have and . Therefore, and , satisfying condition (2) in Definition 2.
We now recall some properties of fuzzy Lie algebras from [7].
Proposition 2
([7] Proposition 2). Let be a real Lie algebra and let . Then
- 1.
- .
- 2.
- , for all and .
- 3.
- If for , then
We now extend the concept of fuzzy bases to Lie algebras. In classical Lie theory, the basis of a Lie algebra is simply a basis of the underlying vector space. The same idea applies in the fuzzy context.
In this fuzzy setting, the notion of ideal of a Lie algebra, i.e. a subalgebra I of such that , has a fuzzy counterpart.
Definition 4.
A fuzzy set is called a fuzzy Lie ideal of if
- 1.
- 2.
- 3.
for alll ,
After this definition, we have to remember this important tool in the theory of fuzzy Lie algebra.
Theorem 1.
A fuzzy set μ of a Lie algebra is a fuzzy Lie subalgebra of if and only if each nonempty set is a Lie subalgebra of
More precisely, this result extends to a broad class of algebras. Statements of the form “a subset A has property P” are classified by Kondo and Dudek [14] as type 0. They established a transfer principle that allows one to lift such properties from classical algebraic structures to their fuzzy counterparts, and vice versa. As they observed, this principle also suggests that genuinely new results in fuzzy algebra should go beyond what can be directly inferred from it. For further details, we refer the reader to the paper cited above and the references therein.
We conclude this section with a result from [7] that provides a practical criterion for deciding when, under a particular choice of the membership function, a basis of a Lie algebra is also a fuzzy basis. Here we recall that a set is a fuzzy basis for a real vector space V if the elements of are fuzzy linearly independent elements, i.e.
for all .
Theorem 2.
Let and a basis of L with and , with and . The set is a fuzzy basis of μ if and only if
for every .
3. Isomorphisms of Fuzzy Lie Subalgebras
In this section, we propose a definition of isomorphism between fuzzy Lie subalgebras based on the transfer principle via t-cut sets, and we compare it with the categorical notion introduced in [10].
For our purposes, we only need the notion of a filtration on an object in a category and, more importantly, that of a morphism of filtered objects, which will serve as the foundation for our definition of isomorphism between fuzzy Lie subalgebras. These concepts were originally introduced by Deligne [15] in the setting of abelian categories, but since we do not require any of the additional structure that such categories provide, the definitions make sense in any category, and in particular in the category of Lie algebras.
Let be a category and let A be an object of . A filtration on A is a family of subobjects such that
The pair is called a filtered object, and the filtration is said to be finite if there exist integers such that and . A morphism of filtered objects is a morphism in such that
Let now be a Lie algebra and let be a fuzzy Lie subalgebra of . Clearly, if , then . Hence, given a partition of the interval , the corresponding family of t-cut sets defines an increasing filtration of (for more results on t-cuts set and partitions, we refer the reader to [7]). Under these assumptions, and in view of the definitions above, we introduce the notion of isomorphism of fuzzy Lie subalgebras as follows.
Definition 5.
Let be two fuzzy Lie subalgebras of and , respectively. We say that μ is isomorphic to ν, denoted by , if for every there exists an isomorphism of Lie algebras .
In the previous definition, it follows straightforwardly that the Lie algebras and are isomorphic via .
Corollary 1.
If , then .
Thanks to the previous result, from now on we may, without loss of generality, restrict our attention to isomorphisms of fuzzy Lie subalgebras of the same Lie algebra.
Example 1.
Regarding Definition 5, one might expect that it is sufficient to consider an automorphism f of and define for every . However, this is not the case.
Indeed, let be the 4-dimensional Lie algebra generated by the matrices
The only nontrivial bracket between the generators is . Consider the ideal . This ideal is not characteristic (see [16]), meaning that there exists an automorphism f of such that . For instance, define f by and for . Then . Now let μ be a fuzzy Lie subalgebra of defined by , , and , and let . Then, for , we have , but .
Proposition 3.
Let be two fuzzy Lie subalgebras of and let f be an automorphism of such that . Then, μ is isomorphic to
Proof.
We have for every Indeed, suppose that Then and hence
Moreover, let Then , indeed
and □
We recall now the notion of isomorphism between fuzzy Lie subalgebras of a Lie algebra presented in [10]. Let be the category whose objects are the pairs , where is a Lie algebra and is a fuzzy subalgebra of , and whose morphisms are homomorphisms of Lie algebras such that We observe that an isomorphism in is an isomorphism of Lie algebras such that and for any and
Proposition 4.
Let be an isomorphism of Lie algebras and let μ be a fuzzy Lie subalgebra of . Then there exists a fuzzy Lie subalgebra ν of such that and are isomorphic in .
Proof.
Since every is given by , with , hence the statement is proven by defining . □
Let be a Lie algebra and let be a basis of . Now, consider another basis of . Thus, by Theorem 2 and Proposition 4, it follows that is a fuzzy basis of as in Theorem 2.
Definition 6.
Let be a Lie algebra. We say that has a flag of subalgebras if there is a chain
where is a -dimensional subalgebra of for
In other words, a flag of subalgebras is a finite filtered object in the category of Lie algebras. A huge class of Lie algebras that admit a flag of subalgebras is the class of solvable Lie algebras [17] Theorem 2.7. The following result shows that, given a flag of subalgebras, it is always possible to construct a fuzzy Lie subalgebra whose associated family of t-cut sets recovers exactly the original flag.
Proposition 5.
Let be a Lie algebra that has a flag of subalgebras
Then there exists a fuzzy subalgebras of such that there exists such that
Proof.
Let be the fuzzy subset defined as
for every and For every , let be such that Then
Moreover, if , we have As a consequence, for every , is a subalgebra of and hence is a fuzzy subalgebra of . □
Remark 1.
Let μ be a fuzzy subalgebra of a Lie algebra and let be a subalgebra of . Then the fuzzy subset given by the restriction of μ to is a fuzzy subalgebra of . Indeed, for every ,
and
Moreover, the inclusion of in is such that
Consequently, given a Lie algebra that has a flag of subalgebras , there exists, for every , a fuzzy subalgebra of . Moreover, the inclusion is such that , for every
Then, for every , the map given by the inclusion of in is a morphism in .
Proposition 6.
If a Lie algebra has a flag of subalgebras, then every epimorphic image of also has a flag of subalgebras.
In particular, if is a Lie algebra with flag of subalgebras
and is a surjective homomorphism of Lie algebras, then the chain
is a flag of subalgebras of , where . Now, let the fuzzy subalgebra associated with by Proposition 5 and let be the fuzzy subset of defined as
for every Then, is the fuzzy subalgebra associated with the flag (5) by Proposition 5. Indeed, let Then
4. Nilpotent Fuzzy Lie Subalgebras
In this section, we address the following question: can nilpotency be formulated in the context of fuzzy algebra? We focus on nilpotency as a first step toward introducing a suitable measure of the degree to which a given property is satisfied by a class of fuzzy algebraic structures (for instance, nilpotency in the case of fuzzy Lie subalgebras). We provide two answers to this question. The first is more classical: we introduce a central series associated with a fuzzy subalgebra of a Lie algebra and define nilpotency by requiring that this series eventually stabilizes. This approach is inspired by the work of [9] and [18], where nilpotent subgroups were extended to the fuzzy setting; we propose here a similar generalisation for Lie algebras by introducing the notion of nilpotent fuzzy Lie subalgebras. The second approach takes into account the intrinsic vagueness of the fuzzy framework and proposes a way to measure the degree of nilpotency of a fuzzy Lie subalgebra. We note that a substantial part of this section is based on [8], which is here extended and complemented by the study of isomorphisms introduced in Section 3.
For any , we denote by
the iterated Lie bracket. Recall that a Lie algebra is said to be nilpotent if there exists such that
This condition is equivalent to the vanishing of the lower central series of , and hence it characterizes the nilpotency of . Let be a fuzzy Lie subalgebra. We define the lower central series associated to inductively as follows: we put
and, inductively, for every ,
It is straightforward to verify that the sequence is increasing, i.e. , for all .
Definition 7.
A fuzzy Lie subalgebra μ of a Lie algebra over a field is called nilpotent fuzzy Lie subalgebra of if there exists such that The smallest k such that is called fuzzy nil-index of μ.
As one would expect, for a nilpotent Lie algebra, fuzzy nilpotency is trivially necessary, as the following result demonstrates.
Proposition 7.
If μ is a fuzzy Lie subalgebra of a nilpotent Lie algebra , then μ is a fuzzy nilpotent Lie subalgebra. Moreover, they have the same nil-index.
Proof.
Since is nilpotent, then there exists an integer such that , with . Hence, for every , . Then, for every , . This implies that , and statement is proved beacause . □
We show that the converse is not true with the following example.
Example 2.
Let be the unique 2-dimensional non-abelian Lie algebra over the filed , with basis the set , and brackets given by . It is known in the literature that is not nilpotent, but with this example we want to show that it is possible to define a fuzzy nilpotent fuzzy subalgebra μ on a non-nilpotent Lie algebra . Let us define a fuzzy subalgebra with the following membership function:
We want to check whether μ is fuzzy nilpotent and, if it is the case, to compute the fuzzy nil-index of μ. In order to do this, we need to find the ascending central series associated with μ, and see if and when . Of course, by deifnition, . The first non-trivial set of the series is the subset
Let and two generic elements of . Let us compute . We have that
Hence, for every , we have that . This means that , thus μ is fuzzy nilpotent with fuzzy nil-index equal to 1.
We now want to introduce a sort of fuzzy measure for the nilpotency of a fuzzy Lie algebra. In particular, we are looking for a function , where , such that when is a nilpotent fuzzy Lie subalgebra of , and otherwise.
To this end, we set and . By definition, the following inequality holds for every
In the next term of the series, this inequality extends as follows:
More generally, for each for , we define recursively . Then, for any we have
To emphasize this, we consider the minimum of the possible membership degrees for a k-tuple of elements, that is . If is nilpotent, then there exists , called nil-index of such that and . We observe that if is nilpotent with nil-index k, then every fuzzy Lie subalgebra of is nilpotent with nil-index k. To quantify the extent to which a fuzzy Lie subalgebra approaches nilpotency, we define a fuzzy measure of nilpotency. This measure reflects how the membership values of higher-order commutators behave in the fuzzy setting. Formally, we put
It is clear that, since for every , then and, in particular, if is nilpotent then for every fuzzy Lie subalgebra of . In this formula, the numerator takes the minimum membership degree over all iterated Lie brackets of length k for two reasons. First, since for all , taking the maximum would trivially yield , which would defeat the purpose. Second, we want to capture the worst-case behaviour of iterated brackets, that is, how far they can be from the zero vector in terms of membership degree. This is then normalised by , the membership degree of the zero vector, which serves as a natural reference value. The only reason for considering the limit in Equation (7) as is to theoretically extend this measure to infinite-dimensional Lie algebras, and moreover because the lower central series does not necessarily terminate a priori.
Remark 2.
We briefly explain why, at least in the present manuscript, we have not introduced an analogue of the measure N for fuzzy subgroups. In the Lie algebra setting, nilpotency admits two equivalent characterisations: via the lower central series terminating at the trivial subalgebra, and via the condition expressed in Equation (6). The same equivalence does not hold in the group-theoretic setting. Indeed, for groups, the condition in Equation (6), where the bracket denotes the commutator , characterises the class of k-Engel groups, which coincides with the class of nilpotent groups only in the finite case. As soon as one moves to finitely generated groups, this equivalence breaks down. Since our measure N is built precisely on the condition in Equation (6), extending it to the group setting would capture Engel-type behaviour rather than nilpotency proper, making the analogy less meaningful. For a thorough treatment of nilpotent groups and Engel groups, we refer the reader to [19,20,21].
Conversely, even if is not nilpotent, a fuzzy Lie subalgebra may still satisfy In particular, we require that every has to be not constant since if for every , then . Moreover, if is a nilpotent fuzzy Lie subalgebra of , then
Example 3.
This example is the Example 1.3 in [6]. Let the 3–dimensional real vector space with lie bracket , where , that is the classical cross product. Then is a real Lie algebra. We define a fuzzy set μ on by
One can easily check that μ is a fuzzy Lie algebra. With the values above, we have and , then , for every . Moreover, using Theorem 2, it is straightforward to see that is a fuzzy basis of μ.
Now, is not a nilpotent Lie algebra. Indeed, the non-zero brackets are
Hence, the k-th term of lower central series is , for every . Then , for every , and this implies that .
The fuzzy nilpotent measure N induces an order relation on the set of fuzzy Lie subalgebras of a fixed fuzzy Lie algebra . Specifically, for any we define
Then, if holds, we say that is less nilpotent than . More precisely, we have the following.
Theorem 3.
is a total order on .
In particular, since is a total order, it induces a lattice structure on .
4.1. Properties of N
Let and be two fuzzy subalgebras of a Lie algebra . We define
and
Proposition 8
([6] Theorem 1.2). The fuzzy sets and are fuzzy ideals of .
Proposition 9.
Let be fuzzy ideals of , with μ less nilpotent than ν (i.e. . Then
Proof.
We have
If , then
since As a consequence,
If , then
□
Proposition 10.
Let be fuzzy ideals of . Then
where we set
In particular, if μ is less nilpotent then ν, hence .
Proof.
We have
Moreover, if is less nilpotent that , then and hence
□
Let be a fuzzy subalgebra of a Lie algebra and let be a fuzzy subalgebra of a Lie algebra . Moreover, let be an isomorphism in Then Moreover, let be such that . Then
Indeed, if , then there exists such that and hence , which is a contradiction. By these arguments, one can deduce the following result.
Theorem 4.
Let such that and finite dimensional. Let an isomorphism in . Hence, .
5. Conclusions and Future Work
In this paper, we have developed a framework for the study of fuzzy Lie subalgebras with particular emphasis on isomorphisms and nilpotency. By adopting the transfer principle via t-cut sets, we introduced a natural notion of isomorphism that is well aligned with the underlying crisp structure while preserving the graded nature of fuzziness. Within this framework, we established that if two fuzzy Lie subalgebras are isomorphic in the categorical sense, then they share the same nilpotency measure, thereby confirming the robustness of the invariant under structural equivalence.
5.1. Future Work
The results obtained in this paper open several promising directions for further investigation. First, it would be natural to extend the approach developed here to other structural properties of Lie algebras. In particular, one may ask whether analogous fuzzy measures can be defined for properties such as commutativity, solvability or semisimplicity. Such measures could provide a unified quantitative framework for comparing different algebraic behaviours in the fuzzy setting. Second, the theory could be generalized beyond Lie algebras to other algebraic structures. A particularly interesting candidate is given by Leibniz algebras. Third, from a categorical perspective, it would be worthwhile to investigate whether other classes of maps admit a meaningful fuzzy extension compatible with the t-cut approach. In this direction, derivations constitute a natural object of study. Developing a theory of fuzzy derivations could provide deeper insight into the internal symmetries of fuzzy algebraic structures.
We believe that the perspective adopted in this work contributes to bridging the gap between classical Lie theory and fuzzy logic, and that the tools introduced here will prove useful in the continued development of the field.
Funding
Giuseppe Filippone, Gianmarco La Rosa, and Marco Elio Tabacchi acknowledge financial support from the Sustainability Decision Framework (SDF) Research Project – CUP B79J23000540005 – Grant Assignment Decree No. 5486 adopted on 2023-08-04 by the Italian Ministry of University and Research (MUR). Gianmarco La Rosa also acknowledges support from the Gruppo Nazionale per le Strutture Algebriche, Geometriche e le loro Applicazioni (GNSAGA) of the Istituto Nazionale di Alta Matematica (INdAM) “Francesco Severi”
Informed Consent Statement
Not applicable.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Zadeh, L. Fuzzy sets. Information and Control 1965, 8, 338–353. [Google Scholar] [CrossRef]
- Rosenfeld, A. Fuzzy groups. Journal of Mathematical Analysis and Applications 1971, 35, 512–517. [Google Scholar] [CrossRef]
- Chang, C.L. Fuzzy topological spaces. Journal of Mathematical Analysis and Applications 1968, 24, 182–190. [Google Scholar] [CrossRef]
- Filippone, G.; La Rosa, G.; Mancini, M.; Tabacchi, M.E. Fuzziness and Lie Algebras. In Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems; Lesot, M.J., Vieira, S., Reformat, M.Z., Carvalho, J.P., Batista, F., Bouchon-Meunier, B., Yager, R.R., Eds.; Cham, 2025; pp. 113–123. [Google Scholar] [CrossRef]
- Yehia, S.E. Fuzzy ideals and fuzzy subalgebras of Lie algebras. Fuzzy Sets and Systems 1996, 80, 237–244. [Google Scholar] [CrossRef]
- Akram, M. Fuzzy Lie Algebras, 1 ed.; Infosys Science Foundation Series, Springer Singapore, 2018; pp. XIX, 302. [Google Scholar] [CrossRef]
- Filippone, G.; Galici, M.; La Rosa, G.; Tabacchi, M.E. Some Results on Fuzzy Basis of Fuzzy Lie Algebras. In Proceedings of the Advances in Fuzzy Logic and Technology; Baczyński, M., De Baets, B., Holčapek, M., Kreinovich, V., Medina, J., Eds.; Cham, 2025; pp. 98–109. [Google Scholar] [CrossRef]
- Filippone, G.; Galici, M.; La Rosa, G.; Piazza, F.; Tabacchi, M.E. A new definition of fuzzy nilpotent Lie algebras. In Proceedings of the 2025 IEEE International Conference on Fuzzy Systems (FUZZ), 2025; pp. 1–5. [Google Scholar] [CrossRef]
- Gupta, K.C.; Sarma, B.K. Nilpotent fuzzy groups. Fuzzy Sets and Systems 1999, 101, 167–176. [Google Scholar] [CrossRef]
- La Rosa, G.; Piazza, F. Functors between Fuzzy Varieties. In Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2026. to appear. [Google Scholar]
- Hawkins, T. Jacobi and the Birth of Lie’s Theory of Groups. Archive for History of Exact Sciences 1991, 42, 187–278. [Google Scholar] [CrossRef]
- Sattinger, D.H.; Weaver, O.L. Lie Groups and Algebras with Applications to Physics, Geometry, and Mechanics, 1 ed.; Applied Mathematical Sciences; Springer: New York, NY, 1986; pp. X, 218. [Google Scholar] [CrossRef]
- Lubczonok, P. Fuzzy vector spaces. Fuzzy Sets and Systems 1990, 38, 329–343. [Google Scholar] [CrossRef]
- Kondo, M.; Dudek, W.A. On the transfer principle in fuzzy theory. Mathware & Soft Computing 2005, 12, 41–55. [Google Scholar]
- Deligne, P. Théorie de Hodge. II. (Hodge theory. II). Publications Mathématiques 40, 5–57. [CrossRef]
- Biggs, R.; Remsing, C.C. Subspaces of real four-dimensional Lie algebras: a classification of subalgebras, ideals, and full-rank subspaces. Extr. Math. 2015, 30, 41–93. [Google Scholar]
- Bowman, K.; Towers, D.A.; Varea, V.R. On flags and maximal chains of lower modular subalgebras of Lie algebras. Journal of Lie Theory 2007, 17, 605–616. [Google Scholar] [CrossRef]
- M., E.; Borzooei, R.A. Nilpotent Fuzzy Subgroups. Mathematics 2018, 6. [Google Scholar] [CrossRef]
- Golod, E.S. On some problems of Burnside type. Translations. Series 2. American Mathematical Society 84, 83–88. [CrossRef]
- Robinson, D.J.S. A course in the theory of groups. In Graduate Texts in Mathematics, 2nd ed.; Springer-Verlag: New York, NY; Vol. 80, pp. xvii + 499.
- Zorn, M. Nilpotency of finite groups. Bulletin of the American Mathematical Society 42, 485–486.
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