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We revisit the topic of two-state quantum systems using Geometric Algebra (GA) in three dimensions $\mathcal G_3$. In this description, both the quantum states and Hermitian operators are written as elements of $\mathcal G_3$. By writing…

Mathematical Physics · Physics 2021-03-10 Pedro Amao , Hernán Castillo

Networks can describe the structure of a wide variety of complex systems by specifying which pairs of entities in the system are connected. While such pairwise representations are flexible, they are not necessarily appropriate when the…

Social and Information Networks · Computer Science 2022-01-17 Jean-Gabriel Young , Giovanni Petri , Tiago P. Peixoto

The analysis of symmetry in quantum systems is of utmost theoretical importance, useful in a variety of applications and experimental settings, and is difficult to accomplish in general. Symmetries imply conservation laws, which partition…

Quantum Physics · Physics 2023-10-20 Caleb Rotello , Eric B. Jones , Peter Graf , Eliot Kapit

Artificial neural networks have been recently introduced as a general ansatz to compactly represent many- body wave functions. In conjunction with Variational Monte Carlo, this ansatz has been applied to find Hamil- tonian ground states and…

Strongly Correlated Electrons · Physics 2018-10-24 Kenny Choo , Giuseppe Carleo , Nicolas Regnault , Titus Neupert

Long-range effective methods are ubiquitous in physics and in quantum theory, in particular. Furthermore, the reliability of such methods is higher when the nature of short-ranged interactions need not be modeled explicitly. This may be…

Quantum Physics · Physics 2022-06-07 David M. Jacobs

A set of Hamiltonians that are not self-adjoint but have the spectrum of the harmonic oscillator is studied. The eigenvectors of these operators and those of their Hermitian conjugates form a bi-orthogonal system that provides a…

Quantum Physics · Physics 2017-11-23 Oscar Rosas-Ortiz , Kevin Zelaya

We develop randomized quantum algorithms to simulate quantum collision models, also known as repeated interaction schemes, which provide a rich framework to model various open-system dynamics. The underlying technique involves composing…

Quantum Physics · Physics 2025-08-20 Kushagra Garg , Zeeshan Ahmed , Subhadip Mitra , Shantanav Chakraborty

The sparse modeling is an evident manifestation capturing the parsimony principle just described, and sparse models are widespread in statistics, physics, information sciences, neuroscience, computational mathematics, and so on. In…

Machine Learning · Computer Science 2023-08-29 Jianyi Lin

High-dimensional simulation optimization is notoriously challenging. We propose a new sampling algorithm that converges to a global optimal solution and suffers minimally from the curse of dimensionality. The algorithm consists of two…

Machine Learning · Statistics 2021-07-21 Liang Ding , Rui Tuo , Xiaowei Zhang

We describe a method that allows for a practical application of the theory of pseudo-Hermitian operators to PT-symmetric systems defined on a complex contour. We apply this method to study the Hamiltonians $H=p^2+x^2(ix)^\nu$ with…

Quantum Physics · Physics 2007-05-23 Ali Mostafazadeh

We introduce a new diagonalization method called quasi-sparse eigenvector diagonalization which finds the most important basis vectors of the low energy eigenstates of a quantum Hamiltonian. It can operate using any basis, either orthogonal…

High Energy Physics - Theory · Physics 2009-10-31 Dean Lee , Nathan Salwen , Daniel Lee

Quantum sensing utilizing unique quantum properties of non-Hermitian systems to realize ultra-precision measurements has been attracting increasing attention. However, the debate on whether non-Hermitian systems are superior to Hermitian…

Quantum Physics · Physics 2023-12-14 Yan-Yi Wang , Chun-Wang Wu , Wei Wu , Ping-Xing Chen

The unprecedented predictive success of deep generative models in complex many-body systems, such as AlphaFold3, raises an epistemological question: do these networks merely memorize data distributions via high-dimensional interpolation, or…

Disordered Systems and Neural Networks · Physics 2026-05-18 Wenjie Xi , Wei-Qiang Chen

An observer-based Hamiltonian identification algorithm for quantum systems is proposed. For the 2-level case an exponential convergence result based on averaging arguments and some relevant transformations is provided. The convergence for…

Mathematical Physics · Physics 2007-05-23 Mazyar Mirrahimi , Pierre Rouchon

We introduce an alternative way to understand the decomposition of a quantum system into interacting parts and show that it is natural in several physical models. This enables us to define a reduced density operator for a working system…

Quantum Physics · Physics 2022-09-08 Adam Stokes

Learning the structure of the entanglement Hamiltonian (EH) is central to characterizing quantum many-body states in analog quantum simulation. We describe a protocol where spatial deformations of the many-body Hamiltonian, physically…

Recently, we have theoretically proposed and experimentally demonstrated an exact and efficient quantum simulation of photosynthetic light harvesting in nuclear magnetic resonance (NMR), cf. B. X. Wang, \textit{et al.} npj Quantum…

The use of the hyperspherical harmonic (HH) basis in the description of bound states in an $A$-body system composed by identical particles is normally preceded by a symmetrization procedure in which the statistic of the system is taken into…

Nuclear Theory · Physics 2011-02-22 M. Gattobigio , A. Kievsky , M. Viviani

Solving a Poisson equation is generally reduced to solving a linear system with a coefficient matrix $A$ of entries $a_{ij}$, $i,j=1,2,...,n$, from the discretized Poisson equation. Although the variational quantum algorithms are promising…

Quantum Physics · Physics 2023-09-25 Hui-Min Li , Zhi-Xi Wang , Shao-Ming Fei

In this work, we study the maximum matching problem from the perspective of sensitivity. The sensitivity of an algorithm $A$ on a graph $G$ is defined as the maximum Wasserstein distance between the output distributions of $A$ on $G$ and on…

Data Structures and Algorithms · Computer Science 2025-11-24 Yuichi Yoshida , Zihan Zhang
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