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The linear-$T$ resistivity is one of the hallmarks of various strange metals regardless of their microscopic details. Towards understanding this universal property, the holographic method or gauge/gravity duality has made much progress.…

High Energy Physics - Theory · Physics 2024-07-01 Yongjun Ahn , Hyun-Sik Jeong , Dujin Ahn , Keun-Young Kim

The linear-$T$ resistivity is one of the characteristic and universal properties of strange metals. There have been many progress in understanding it from holographic perspective (gauge/gravity duality). In most holographic models, the…

High Energy Physics - Theory · Physics 2024-07-01 Hyun-Sik Jeong , Keun-Young Kim , Chao Niu

We give a review on our recent work arXiv:1006.0779 [hep-th] and arXiv:1006.1719 [hep-th], in which properties of holographic strange metals were investigated. The background is chosen to be anisotropic scaling solution in…

High Energy Physics - Theory · Physics 2011-09-07 Bum-Hoon Lee , Da-Wei Pang , Chanyong Park

High $T_c$ cuprate strange metals are noted for a DC-resistivity that scales linearly with $T$ from the onset of superconductivity to the crystal melting temperature, indicative of a Planckian dissipation life time $\tau_{\hbar}\simeq \hbar…

We compute the direct current resistivity of a scale-invariant, $d$-dimensional strange metal with dynamic critical exponent $z$ and hyperscaling-violating exponent $\theta$, weakly perturbed by a scalar operator coupled to random-field…

High Energy Physics - Theory · Physics 2014-04-02 Andrew Lucas , Subir Sachdev , Koenraad Schalm

We present a semi-analytic method for constructing holographic black holes that interpolate from anti-de Sitter space to hyperscaling-violating geometries. These are holographic duals of conformal field theories in the presence of an…

High Energy Physics - Theory · Physics 2015-01-26 Andrew Lucas , Subir Sachdev

A theoretical understanding of the enigmatic linear-in-temperature ($T$) resistivity, ubiquitous in strongly correlated metallic systems, has been a long sought-after goal. Furthermore, the slope of this robust $T$-linear resistivity is…

Strongly Correlated Electrons · Physics 2020-09-23 Peter Cha , Aavishkar A. Patel , Emanuel Gull , Eun-Ah Kim

For strongly interacting systems holographic duality is a powerful framework for computing e.g. dispersion relations to all orders in perturbation theory. Using the standard Reissner-Nordst\"om black hole as a holographic model for a…

High Energy Physics - Theory · Physics 2019-02-20 Ulf Gran , Marcus Tornsö , Tobias Zingg

We consider a short-range deformation potential scattering model of electron-acoustic phonon interaction to calculate the resistivity of an ideal metal as a function of temperature (T) and electron density (n). We consider both 3D metals…

Strongly Correlated Electrons · Physics 2019-02-07 E. H. Hwang , S. Das Sarma

We study the thermo-electric transport coefficients of an extended version of the Gubser-Rocha model. After reviewing the two relaxation time model from holography and studying the effect of the magnetic field on thermo-electric transports…

High Energy Physics - Theory · Physics 2024-03-15 Xian-Hui Ge , Zhaojie Xu

In the last decade, motivated by the concept of Planckian relaxation and the possible existence of a quantum critical point in cuprate materials, holographic techniques have been extensively used to tackle the problem of strange metals and…

Strongly Correlated Electrons · Physics 2024-03-06 Yongjun Ahn , Matteo Baggioli , Hyun-Sik Jeong , Keun-Young Kim

We construct a neural network to learn the RN-AdS black hole metric based on the data of optical conductivity by holography. The linear perturbative equation for the Maxwell field is rewritten in terms of the optical conductivity such that…

High Energy Physics - Theory · Physics 2023-03-28 Kai Li , Yi Ling , Peng Liu , Meng-He Wu

We investigate holographic models of superfluids and superconductors in which the gravitational theory includes a dilatonic field. Dilaton extensions are interesting as they allow us to obtain a better description of low temperature…

High Energy Physics - Theory · Physics 2015-06-05 Alberto Salvio

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between…

Computational Physics · Physics 2021-01-29 Massimiliano Lupo Pasini , Ying Wai Li , Junqi Yin , Jiaxin Zhang , Kipton Barros , Markus Eisenbach

In an attempt to understand the density-density response of the cuprate superconductors, we study plasmons in a layered strange metal using the Gubser-Rocha model. The latter is a well-known bottom-up holographic model for a strange metal…

Strongly Correlated Electrons · Physics 2023-11-10 S. T. Van den Eede , T. J. N. van Stralen , C. F. J. Flipse , H. T. C. Stoof

We analyze a class of bottom-up holographic models for low energy thermo-electric transport. The models we focus on belong to a family of Einstein-Maxwell-dilaton theories parameterized by two scalar functions, characterizing the dilaton…

High Energy Physics - Theory · Physics 2015-12-15 Mukund Rangamani , Moshe Rozali , Darren Smyth

The accurate modeling of the mechanical behavior of rubber-like materials under multi-axial loading constitutes a long-standing challenge in hyperelastic material modeling. This work employs deep symbolic regression as an interpretable…

Computational Engineering, Finance, and Science · Computer Science 2025-04-09 Rasul Abdusalamov , Mikhail Itskov

This paper introduces the physics and philosophy of strange metals, which are characterized by unusual electrical and thermal properties that deviate from conventional metallic behaviour. The anomalous strange-metal behaviour discussed here…

History and Philosophy of Physics · Physics 2025-08-01 Enrico Cinti , Sebastian De Haro , Mark Golden , Umut Gürsoy , Henk T. C. Stoof

We derive new black hole solutions in Einstein-Maxwell-Axion-Dilaton theory with a hyperscaling violation exponent. We then examine the corresponding anomalous transport exhibited by cuprate strange metals in the normal phase of…

High Energy Physics - Theory · Physics 2017-09-06 Xian-Hui Ge , Yu Tian , Shang-Yu Wu , Shao-Feng Wu

Deep Learning (DL), in particular deep neural networks (DNN), by default is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering…

Machine Learning · Statistics 2022-09-26 Hai V. Nguyen , Tan Bui-Thanh
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