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We extend the usual process-theoretic view on locality and causality in subsystems (based on the tensor product case) to general quantum systems (i.e.\ possibly non-factor, finite-dimensional von Neumann algebras). To do so, we introduce a…

Quantum Physics · Physics 2026-02-03 Octave Mestoudjian , Matt Wilson , Augustin Vanrietvelde , Pablo Arrighi

This is the third part in a series of papers in which we introduce and develop a natural, general tensor category theory for suitable module categories for a vertex (operator) algebra. In this paper (Part III), we introduce and study…

Quantum Algebra · Mathematics 2012-05-14 Yi-Zhi Huang , James Lepowsky , Lin Zhang

We construct natural maps (the Klein and Wirtinger maps) from moduli spaces of vector bundles on an algebraic curve $X$ to affine spaces, as quotients of the nonabelian theta linear series. We prove a finiteness result for these maps over…

Algebraic Geometry · Mathematics 2007-05-23 David Ben-Zvi , Indranil Biswas

The universal C*-algebras of discrete product systems generalize the Toeplitz- Cuntz algebras and the Toeplitz algebras of discrete semigroups. We consider a semigroup P which is quasi-lattice ordered in the sense of Nica, and, for a…

Operator Algebras · Mathematics 2007-05-23 Neal J. Fowler

We define $\Delta$-equivalence for operator systems and show that it is identical to stable isomorphism. We define $\Delta$-contexts and bihomomorphism contexts and show that two operator systems are $\Delta$-equivalent if and only if they…

Operator Algebras · Mathematics 2026-02-27 George K. Eleftherakis , Evgenios T. A. Kakariadis , Ivan G. Todorov

We investigate quantum algorithms derived from tensor networks to simulate the static and dynamic properties of quantum many-body systems. Using a sequentially prepared quantum circuit representation of a matrix product state (MPS) that we…

Quantum Physics · Physics 2024-12-04 Michael L. Wall , Aidan Reilly , John S. Van Dyke , Collin Broholm , Paraj Titum

We demonstrate that the matrix quantum group $SL_q(2)$ gives rise to nontrivial matrix product operator representations of the Lie group $SL(2)$, providing an explicit characterization of the nontrivial global $SU(2)$ symmetry of the XXZ…

Statistical Mechanics · Physics 2022-02-15 Romain Couvreur , Laurens Lootens , Frank Verstraete

We review the construction of braided tensor categories and modular tensor categories from representations of vertex operator algebras, which correspond to chiral algebras in physics. The extensive and general theory underlying this…

High Energy Physics - Theory · Physics 2015-06-15 Yi-Zhi Huang , James Lepowsky

The generalized state space of a commutative C*-algebra, denoted S_H(C(X)), is the set of positive unital maps from C(X) to the algebra B(H) of bounded linear operators on a Hilbert space H. C*-convexity is one of several non-commutative…

Operator Algebras · Mathematics 2009-02-12 M. C. Gregg

Let $(G, P)$ be an abelian, lattice ordered group and let $X$ be a compactly aligned product system over $P$. We show that the C*-envelope of the Nica tensor algebra $\mathcal{N}\mathcal{T}^+_X$ coincides with both Sehnem's covariance…

Operator Algebras · Mathematics 2019-11-27 Adam Dor-On , Elias Katsoulis

We use product systems of $C^*$-correspondences to introduce twisted $C^*$-algebras of topological higher-rank graphs. We define the notion of a continuous $\mathbb{T}$-valued $2$-cocycle on a topological higher-rank graph, and present…

Operator Algebras · Mathematics 2021-07-30 Becky Armstrong , Nathan Brownlowe

We construct commutative algebra spectra that represent the operator $K$-theory of $C^*$-algebras, which are algebras over the commutative ring spectra that represent topological $K$-theory. The spectral multiplicative structure introduces…

Operator Algebras · Mathematics 2022-03-08 R. Vasconcellos , L. C. P. A. M. Müssnich , N. J. B. Aza

We propose an index of non-invertible symmetry operators in 1+1 dimensions and discuss its relation to the realizability of non-invertible symmetries on the tensor product of finite dimensional on-site Hilbert spaces on the lattice. Our…

Strongly Correlated Electrons · Physics 2026-02-17 Kansei Inamura

Let $X$ be a reflexive Hardy space or weighted Bergman space on the unit disk in the complex plane. For a bounded linear operator $S$ on $X$, let $\textrm{wem}(S):= \sup_{(f_n)} \limsup_n \|Sf_n\|$, that is, the supremum of cluster points…

Functional Analysis · Mathematics 2025-09-08 David Norrbo

We consider an algebra of even-order square tensors and introduce a stretching map which allows us to represent tensors as matrices. The stretching map could be understood as a generalized matricization. It conserves algebraic properties of…

Representation Theory · Mathematics 2023-02-08 Vyacheslav Futorny , Mikhail Neklyudov , Kaiming Zhao

We characterize classes of linear maps between operator spaces $E$, $F$ which factorize through maps arising in a natural manner via the Pisier vector-valued non-commutative $L^p$ spaces $S_p[E^*]$ based on the Schatten classes on the…

funct-an · Mathematics 2008-02-03 Francesco Fidaleo

Let $X^{(2)}$ denote the second symmetric product space of a partially ordered vector space $X$, endowed with the projective cone. A characterization of linear maps $T\colon X^{(2)}\to X^{(2)}$ which preserve the set of all positive…

Functional Analysis · Mathematics 2026-05-19 Pavankumar Raickwade , K. C. Sivakumar

Two successive generalizations of the usual tensor products are given. One can be constructed for arbitrary binary operations, and not only for semigroups, groups or vector spaces. The second one, still more general, is constructed for…

General Mathematics · Mathematics 2008-10-31 Elemer E Rosinger

Given a real inner product space V and a group G of linear isometries, max filtering offers a rich class of G-invariant maps. In this paper, we identify nearly sharp conditions under which these maps injectively embed the orbit space V/G…

Functional Analysis · Mathematics 2025-04-25 Dustin G. Mixon , Yousef Qaddura

Modern approaches to generative modeling of continuous data using tensor networks incorporate compression layers to capture the most meaningful features of high-dimensional inputs. These methods, however, rely on traditional Matrix Product…

Machine Learning · Computer Science 2024-12-11 Danylo Kolesnyk , Yelyzaveta Vodovozova
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