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We develop a general theory for thermal transport in anharmonic systems under the weak system-bath coupling approximation similar to the quantum master equation formalism. A current operator is derived, which is valid not only in the steady…

Mesoscale and Nanoscale Physics · Physics 2012-05-28 Juzar Thingna , J. L. García-Palacios , Jian-Sheng Wang

Recently, a universal relation between the thermal expansion coefficient of glasses $\alpha_g$, their glass-transition temperature Tg, and the so-called fragility index m of the corresponding supercooled liquid state was found to be valid…

Soft Condensed Matter · Physics 2024-10-29 P. Lunkenheimer , K. Samwer , A. Loidl

Computing-in-Memory (CiM) is a promising paradigm to address the memory bottleneck constraining traditional systems. Most power-efficient CiM variants can directly perform Boolean operations in non-volatile memory arrays. Higher…

Emerging Technologies · Computer Science 2026-04-09 Patrick Miller , Hüsrev Cilasun , Sachin S. Sapatnekar , Ulya R. Karpuzcu

Strand displacement and tile assembly systems are designed to follow prescribed kinetic rules (i.e., exhibit a specific time-evolution). However, the expected behavior in the limit of infinite time--known as thermodynamic equilibrium--is…

Emerging Technologies · Computer Science 2017-09-26 David Doty , Trent A. Rogers , David Soloveichik , Chris Thachuk , Damien Woods

We study the effects of time-dependent substrate/film temperature in the deposition of a mesoscopically thick film using a statistical model that accounts for diffusion of adatoms without lateral neighbors whose coefficients depend on an…

Statistical Mechanics · Physics 2013-10-30 T. A. de Assis , F. D. A. A. Reis

Anomalous temperature dependence of heat capacity of glassy systems during a cooling-heating cycle has remained an ill-understood problem for a long time. Most of the features observed in the experimental measurement of the heat capacity of…

Soft Condensed Matter · Physics 2007-05-23 Dwaipayan Chakrabarti , Biman Bagchi

Thermal energy agitates all matter and its competition with ordering tendencies is one of the most fundamental organizing principles in the physical world. Thus, it is natural to enquire if an effective temperature could result when…

Statistical Mechanics · Physics 2018-09-10 Ming Han , Jing Yan , Steve Granick , Erik Luijten

A model glass with fast and slow processes is studied. The statics is simple and the facilitated slow dynamics is exactly solvable. The main features of a fragile glass take place: Kauzmann transition, Vogel-Fulcher law, Adam-Gibbs relation…

Statistical Mechanics · Physics 2009-11-07 L. Leuzzi , Th. M Nieuwenhuizen

Materials with low thermal conductivity usually have complex crystal structures. Herein we experimentally find that a simple crystal structure material AgTlI2 (I4/mcm) owns an extremely low thermal conductivity of 0.25 W/mK at room…

Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing (AM), as various aspects of the AM process require continuous monitoring and regulation, with temperature being a particularly significant factor.…

Optimization and Control · Mathematics 2023-07-17 Eleni Zavrakli , Andrew Parnell , Andrew Dickson , Subhrakanti Dey

After a brief introduction to the dynamics of supercooled liquids, we discuss some of the advantages and drawbacks of computer simulations of such systems. Subsequently we present the results of computer simulations in which the dynamics of…

Statistical Mechanics · Physics 2009-10-31 Walter Kob

Industrial anomaly detection is an important task within computer vision with a wide range of practical use cases. The small size of anomalous regions in many real-world datasets necessitates processing the images at a high resolution. This…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Blaž Rolih , Dick Ameln , Ashwin Vaidya , Samet Akcay

Collective spins in thermal gases are at the core of a multitude of science and technology applications. In most of them, the random thermal motion of the particles is considered detrimental as it is responsible for decoherence and noise.…

Quantum Physics · Physics 2024-02-27 P. Bevington , J. Nicholson , J. D. Zipfel , W. Chalupczak , C. Mishra , V. Guarrera

We present a first principle scheme to compute the rigidity, i. e. the shear-modulus of structural glasses at finite temperatures using the cloned liquid theory, which combines the replica theory and the liquid theory. With the aid of the…

Soft Condensed Matter · Physics 2012-06-08 Hajime Yoshino

Model interaction potentials for real materials are generally optimized with respect to only those experimental properties that are easily evaluated as mechanical averages (e.g., elastic constants (at T=0 K), static lattice energies and…

Materials Science · Physics 2009-10-31 Jess B. Sturgeon , Brian. B. Laird

Over the ages, efforts have been made to use composite design to reinforce metals and alloys in order to increase their strength and modulus. On the other hand, nature herself improves the strength, ductility, stiffness and toughness of…

We consider a dual model of decision making, in which an individual forms its opinion based on contrasting mechanisms of imitation and rational calculation. The decision making model (DMM) implements imitating behavior by means of a network…

Adaptation and Self-Organizing Systems · Physics 2015-06-22 Malgorzata Turalska , Bruce J. West

We use molecular dynamics simulations to study the dynamics of an ensemble of interacting self-propelled semi-flexible polymers in contact with a thermal bath. Our intention is to model complex systems of biological interest. We find that…

Soft Condensed Matter · Physics 2011-05-06 Davide Loi , Stefano Mossa , Leticia F. Cugliandolo

Knowledge Distillation (KD) aims at transferring the knowledge of a well-performed neural network (the {\it teacher}) to a weaker one (the {\it student}). A peculiar phenomenon is that a more accurate model doesn't necessarily teach better,…

Machine Learning · Computer Science 2022-10-14 Xin-Chun Li , Wen-Shu Fan , Shaoming Song , Yinchuan Li , Bingshuai Li , Yunfeng Shao , De-Chuan Zhan

Recent years have witnessed the great successes of embedding-based methods in recommender systems. Despite their decent performance, we argue one potential limitation of these methods -- the embedding magnitude has not been explicitly…

Information Retrieval · Computer Science 2023-06-07 Jiawei Chen , Junkang Wu , Jiancan Wu , Sheng Zhou , Xuezhi Cao , Xiangnan He