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Tensor decomposition is a mathematically supported technique for data compression. It consists of applying some kind of a Low Rank Decomposition technique on the tensors or matrices in order to reduce the redundancy of the data. However, it…

Machine Learning · Computer Science 2025-05-27 Habib Hajimolahoseini , Walid Ahmed , Austin Wen , Yang Liu

We outline refined versions of two major quantum algorithms for performing principal component analysis and solving linear equations. Our methods are exponentially faster than their classical counterparts and even previous quantum…

Quantum Physics · Physics 2025-04-02 Nhat A. Nghiem

Any four-dimensional Supersymmetric Quantum Field Theory with eight supercharges can be associated to a certain complex symplectic manifold called the "K-theoretic Coulomb branch" of the theory. The collection of K-theoretic Coulomb…

High Energy Physics - Theory · Physics 2024-06-18 Davide Gaiotto , Jörg Teschner

Many statistical problems involve the estimation of a $\left(d\times d\right)$ orthogonal matrix $\textbf{Q}$. Such an estimation is often challenging due to the orthonormality constraints on $\textbf{Q}$. To cope with this problem, we…

Methodology · Statistics 2019-06-04 Luca Bagnato , Antonio Punzo

In recent years, reduced basis methods (RBMs) have been adapted to the many-body eigenvalue problem and they have been used, largely in nuclear physics, as fast emulators able to bypass expensive direct computations while still providing…

Superconductivity · Physics 2023-04-19 Virgil V. Baran , Denis R. Nichita

In this work we present a low-rank algorithm for computing low-rank approximations of large-scale Lyapunov operator $\varphi$-functions. These computations play a crucial role in implementing of matrix-valued exponential integrators for…

Numerical Analysis · Mathematics 2025-01-07 Dongping Li , Xiuying Zhang , Hongjiong Tian

We present a classically solvable model that leads to optimized low-depth quantum circuits leveraging separable pair approximations. The obtained circuits are well suited as a baseline circuit for emerging quantum hardware and can, in the…

Quantum Physics · Physics 2022-04-07 Jakob S. Kottmann , Alán Aspuru-Guzik

Using a complete basis set we have obtained an analytic expression for the matrix elements of the Coulomb interaction. These matrix elements are written in a closed form. We have used the basis set of the three-dimensional isotropic quantum…

Mathematical Physics · Physics 2007-10-17 Jaime Zaratiegui

We study primary submodules and primary decompositions from a differential and computational point of view. Our main theoretical contribution is a general structure theory and a representation theorem for primary submodules of an arbitrary…

Commutative Algebra · Mathematics 2022-02-15 Justin Chen , Yairon Cid-Ruiz

Efficient methods for the simulation of quantum circuits on classic computers are crucial for their analysis due to the exponential growth of the problem size with the number of qubits. Here we study lumping methods based on bisimulation,…

We introduce a new basis of the non-commutative symmetric functions whose commutative images are Schur functions. Dually, we build a basis of the quasi-symmetric functions which expand positively in the fundamental quasi-symmetric functions…

Combinatorics · Mathematics 2016-11-08 Chris Berg , Nantel Bergeron , Franco Saliola , Luis Serrano , Mike Zabrocki

We consider the problem of constructing a canonical polyadic (CP) decomposition for a tensor network, rather than a single tensor. We illustrate how it is possible to reduce the complexity of constructing an approximate CP representation of…

Chemical Physics · Physics 2024-07-30 Karl Pierce , Edward F Valeev

We develop a higher order generalization of the LQ decomposition and show that this decomposition plays an important role in likelihood-based estimation and testing for separable, or Kronecker structured, covariance models, such as the…

Statistics Theory · Mathematics 2018-06-20 David C. Gerard , Peter D. Hoff

The problem of finding and characterizing minimal sets of dequantizers and quantizers applied in the mapping of operators onto functions is considered, for finite-dimensional quantum systems. The general properties of such sets are…

Quantum Physics · Physics 2018-09-26 P. Adam , V. A. Andreev , A. Isar , M. A. Man'ko , V. I. Man'ko

The mechanism of describing quantum states by standard probability (tomographic one) instead of wave function or density matrix is elucidated. Quantum tomography is formulated in an abstract Hilbert space framework, by means of the identity…

Quantum Physics · Physics 2008-11-26 V. I. Man'ko , G. Marmo , A. Simoni , A. Stern , E. C. G. Sudarshan , F. Ventriglia

Real-space refinement of atomic models in macromolecular crystallography or in cryo electron microscopy fits a model to a map obtained experimentally. This requires generating model maps of a limited resolution which moreover may vary from…

Computational Engineering, Finance, and Science · Computer Science 2022-06-22 Ludmila Urzhumtseva , Vladimir Y. Lunin , Alexandre Urzhumtsev

Electronic structure methods for accurate calculation of molecular properties have a high cost that grows steeply with the problem size, therefore, it is helpful to have the underlying atomic basis functions that are less in number but of…

Chemical Physics · Physics 2019-03-15 Dimitri N. Laikov

The necessity of complex numbers in quantum mechanics has long been debated. This paper develops a real Kahler space formulation of quantum mechanics [19], asserting equivalence to the standard complex Hilbert space framework. By mapping…

Quantum Physics · Physics 2025-06-10 Irina Aref'eva , Igor Volovich

Ab initio methods for electronic structure of molecules have reached a satisfactory accuracy for calculation of static properties, but remain too expensive for quantum dynamical calculations. We propose an efficient semiclassical method for…

Chemical Physics · Physics 2015-05-13 Baiqing Li , Cesare Mollica , Jiri Vanicek

Intuitively, if a density operator has small rank, then it should be easier to estimate from experimental data, since in this case only a few eigenvectors need to be learned. We prove two complementary results that confirm this intuition.…

Quantum Physics · Physics 2012-10-18 Steven T. Flammia , David Gross , Yi-Kai Liu , Jens Eisert