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Related papers: Information Storage in the Stochastic Ising Model

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The ability to store quantum information without recourse to constant feedback processes would yield a significant advantage for future implementations of quantum information processing. In this paper, limitations of the prototypical model,…

Quantum Physics · Physics 2009-02-23 Alastair Kay

We study a mechanism whereby quantum information present in the initial state of a quantum many-body system can be protected for arbitrary times due to a combination of symmetry and spatial locality. Remarkably, the mechanism is…

Quantum Physics · Physics 2022-06-16 Julia Wildeboer , Thomas Iadecola , Dominic J. Williamson

This paper deals with the stochastic Ising model with a temperature shrinking to zero as time goes to infinity. A generalization of the Glauber dynamics is considered, on the basis of the existence of simultaneous flips of some spins. Such…

Probability · Mathematics 2017-01-20 Roy Cerqueti , Emilio De Santis

Cells store information in DNA and in stable programs of gene expression, which thereby implement forms of long-term cellular memory. Cells must also possess short-term forms of information storage, implemented post-translationally, to…

Molecular Networks · Quantitative Biology 2007-06-27 Matthew Thomson , Jeremy Gunawardena

In this paper, we address the question of information preservation in ill-posed, non-linear inverse problems, assuming that the measured data is close to a low-dimensional model set. We provide necessary and sufficient conditions for the…

Information Theory · Computer Science 2018-12-05 Nicolas Keriven , Rémi Gribonval

It is well known that Glauber dynamics on spin systems typically suffer exponential slowdowns at low temperatures. This is due to the emergence of multiple metastable phases in the state space, separated by narrow bottlenecks that are hard…

Probability · Mathematics 2024-12-24 Reza Gheissari , Alistair Sinclair

We study zero-temperature Glauber dynamics for Ising-like spin variable models in quenched random networks with random zero-magnetization initial conditions. In particular, we focus on the absorbing states of finite systems. While it has…

Statistical Mechanics · Physics 2012-03-21 Yongjoo Baek , Meesoon Ha , Hawoong Jeong

Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existing methods, such as regularization, replay, and frozen subnetworks, add external…

Machine Learning · Computer Science 2026-04-09 Radu Negulescu

Configurational entropy (CE) and configurational complexity (CC) are recently popularized information theoretic measures used to study the stability of solitons. This paper examines their behavior for 2D and 3D lattice Ising Models, where…

Statistical Mechanics · Physics 2025-03-06 Damian R Sowinski , Sean Kelty , Gourab Ghoshal

Ising models, and the physical systems described by them, play a central role in generating entangled states for use in quantum metrology and quantum information. In particular, ultracold atomic gases, trapped ion systems, and Rydberg atoms…

As the penetration level of transmission-scale time-intermittent renewable generation resources increases, control of flexible resources will become important to mitigating the fluctuations due to these new renewable resources. Flexible…

Optimization and Control · Mathematics 2011-07-11 Krishnamurthy Dvijotham , Scott Backhaus , Misha Chertkov

We study the statistical properties of the sum $S_t=\int_{0}^{t}dt' \sigma_{t'}$, that is the difference of time spent positive or negative by the spin $\sigma_{t}$, located at a given site of a $D$-dimensional Ising model evolving under…

Statistical Mechanics · Physics 2009-10-31 J. -M. Drouffe , C. Godreche

The foraging problem asks how a collective of particles with limited computational, communication and movement capabilities can autonomously compress around a food source and disperse when the food is depleted or shifted, which may occur at…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-24 Shunhao Oh , Dana Randall , Andréa W. Richa

Learning Gibbs distributions using only sufficient statistics has long been recognized as a computationally hard problem. On the other hand, computationally efficient algorithms for learning Gibbs distributions rely on access to full sample…

Machine Learning · Computer Science 2026-02-16 Abhijith Jayakumar , Shreya Shukla , Marc Vuffray , Andrey Y. Lokhov , Sidhant Misra

Motivated by the recent proposed models of the information engine [D. Mandal and C. Jarzynski, Proc. Natl. Acad. Sci. 109, 11641 (2012)] and the information refrigerator [D. Mandal, H. T. Quan, and C. Jarzynski, Phys. Rev. Lett. 111, 030602…

Statistical Mechanics · Physics 2015-06-30 Yuansheng Cao , Zongping Gong , H. T. Quan

Information must take up space, must weigh, and its flux must be limited. Quantum limits on communication and information storage leading to these conclusions are here described. Quantum channel capacity theory is reviewed for both steady…

Quantum Physics · Physics 2015-06-26 Jacob D. Bekenstein , Marcelo Schiffer

The non-equilibrium dynamics of the model 3d-Ising spin glass - Fe$_{0.55}$Mn$_{0.45}$TiO$_3$ - has been investigated from the temperature and time dependence of the zero field cooled magnetization recorded under certain thermal protocols.…

Materials Science · Physics 2016-08-31 R. Mathieu , P. E. Jönsson , P. Nordblad , H. Aruga Katori , A. Ito

The characterisation of information processing is an important task in complex systems science. Information dynamics is a quantitative methodology for modelling the intrinsic information processing conducted by a process represented as a…

Information Theory · Computer Science 2018-08-01 Richard E. Spinney , Joseph T. Lizier

The application of the Shannon entropy to study the relationship between information and structures has yielded insights into molecular and material systems. However, the difficulty in directly observing and manipulating atoms and molecules…

In the study of social networks, a fundamental problem is that of influence maximization (IM): How can we maximize the collective opinion of individuals in a network given constrained marketing resources? Traditionally, the IM problem has…

Disordered Systems and Neural Networks · Physics 2016-09-30 Christopher Lynn , Daniel D. Lee