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Antiferromagnetic spin rings represent prototypical realizations of highly correlated, low-dimensional systems. Here we theoretically show how the introduction of magnetic defects by controlled chemical substitutions results in a strong…

Mesoscale and Nanoscale Physics · Physics 2015-06-11 I. Siloi , F. Troiani

Random fields disorder Ising ferromagnets by aligning single spins in the direction of the random field in three space dimensions, or by flipping large ferromagnetic domains at dimensions two and below. While the former requires random…

Disordered Systems and Neural Networks · Physics 2017-12-12 Juan Carlos Andresen , Helmut G. Katzgraber , Moshe Schechter

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is…

Machine Learning · Computer Science 2017-12-25 Pierre Baldi , Peter Sadowski , Zhiqin Lu

We study a fully connected quantum spin model resonantly coupled to a small environment of non-interacting spins, and investigate how initial state properties are remembered at long times. We find memory of initial state properties, in…

Quantum Physics · Physics 2022-10-24 M. R. Lambert , Shan-Wen Tsai , Shane P. Kelly

Many living and artificial systems improve their fitness or performance by adapting to changing environments or diverse training data. However, it remains unclear how such environmental variation influences adaptation, what is learned in…

Computational Physics · Physics 2026-04-09 Mengjie Zu , Carl P. Goodrich

We study spin transport in nonitinerant one-dimensional quantum spin chains. Motivated by possible applications in spintronics, we consider rectification effects in both ferromagnetic and antiferromagnetic systems. We find that the crucial…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 Kevin A. van Hoogdalem , Daniel Loss

Factorization machines (FM) are a popular model class to learn pairwise interactions by a low-rank approximation. Different from existing FM-based approaches which use a fixed rank for all features, this paper proposes a Rank-Aware FM…

Machine Learning · Computer Science 2019-05-21 Xiaoshuang Chen , Yin Zheng , Jiaxing Wang , Wenye Ma , Junzhou Huang

Quantum annealers can provide non-local optimization by tunneling between states in a process that ideally eliminates memory of the initial configuration. We study the crossover between memory loss and retention due to quantum fluctuations,…

Quantum Physics · Physics 2025-09-16 Elijah Pelofske , Cristiano Nisoli

There are several interacting spin systems which have a gap in their spin excitation spectrum. The gap does not occur due to anisotropies present in the system but is quantum mechanical in origin. We give a brief overview on the different…

Materials Science · Physics 2007-05-23 Indrani Bose

We consider the coarsening properties of a kinetic Ising model with a memory field. The probability of a spin-flip depends on the persistence time of the spin in a state. The more a spin has been in a given state, the less the spin-flip…

Statistical Mechanics · Physics 2009-11-13 Fabio Caccioli , Silvio Franz , Matteo Marsili

A variation in the environment of a system, such as the temperature, the concentration of a chemical solution or the appearance of a magnetic field, may lead to a drift in one of the parameters. If the parameter crosses a bifurcation point,…

Adaptation and Self-Organizing Systems · Physics 2023-08-16 Julia Cantisán , Serhiy Yanchuk , Jesús M. Seoane , Miguel A. F. Sanjuán , Jürgen Kurths

The low-energy properties of a system at a critical point may have additional symmetries not present in the microscopic Hamiltonian. This letter presents the theory of a class of multicritical points that provide an interesting example of…

Strongly Correlated Electrons · Physics 2009-11-07 Kedar Damle , David A. Huse

In this paper, we propose and investigate a new neural network architecture called Neural Random Access Machine. It can manipulate and dereference pointers to an external variable-size random-access memory. The model is trained from pure…

Machine Learning · Computer Science 2016-02-11 Karol Kurach , Marcin Andrychowicz , Ilya Sutskever

A focus of recent experimental and theoretical studies on heavy fermion systems close to antiferromagnetic (AFM) quantum critical points (QCP) is directed toward revealing the nature of the fixed point, i.e., whether it is an itinerant…

Strongly Correlated Electrons · Physics 2007-05-23 Hiroaki Kadowaki , Yoshikazu Tabata , Masugu Sato , Naofumi Aso , Stephane Raymond , Shuzo Kawarazaki

The necessity of having an electronic device working in relevant biological time scales with a small footprint boosted the research of a new class of emerging memories. Ag-based volatile resistive switching memories (RRAMs) feature a…

Emerging Technologies · Computer Science 2024-02-08 Saverio Ricci , David Kappel , Christian Tetzlaff , Daniele Ielmini , Erika Covi

A model for single-domain uniaxial ferromagnetic particles with high anisotropy, the Ising model, is studied. Recent experimental observations have been made of the probability that the magnetization has not switched. Here an approach is…

Materials Science · Physics 2009-10-30 M. A. Novotny , M. Kolesik , P. A. Rikvold

The current efforts to fabricate non-volatile magnetic recording media with a high areal density is deteriorated by the increasing temporal instability of the stored information. If the stored energy per magnetic particle competes with the…

Materials Science · Physics 2009-10-31 P. J. Jensen

The speed of writing of state-of-the-art ferromagnetic memories is physically limited by an intrinsic GHz threshold. Recently, an alternative research direction has been initiated by realizing memory devices based on antiferromagnets in…

This work focuses on the training dynamics of one associative memory module storing outer products of token embeddings. We reduce this problem to the study of a system of particles, which interact according to properties of the data…

Machine Learning · Computer Science 2024-03-01 Vivien Cabannes , Berfin Simsek , Alberto Bietti

Spin-polarized antiferromagnets (AFMs), including altermagnets, noncollinear AFMs, and two-dimensional layer-polarized AFMs, have emerged as transformative materials for next-generation spintronic and optoelectronic technologies. These…

Materials Science · Physics 2025-06-23 Zhenzhou Guo , Xiaotian Wang , Wenhong Wang , Gang Zhang , Xiaodong Zhou , Zhenxiang Cheng
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