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相关论文: On the breakdown of dimensional reduction and supe…

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We provide a theoretical analysis by means of the nonperturbative functional renormalization group (NP-FRG) of the corrections to scaling in the critical behavior of the random-field Ising model (RFIM) near the dimension $d_{DR}\approx 5.1$…

无序系统与神经网络 · 物理学 2021-01-04 Ivan Balog , Gilles Tarjus , Matthieu Tissier

We apply the nonperturbative functional renormalization group (NP-FRG) in the superfield formalism that we have developed in the preceding paper to study long-standing issues concerning the critical behavior of the random field Ising model.…

统计力学 · 物理学 2013-05-30 Matthieu Tissier , Gilles Tarjus

We provide a resolution of one of the long-standing puzzles in the theory of disordered systems. By reformulating the functional renormalization group (FRG) for the critical behavior of the random field Ising model in a superfield…

统计力学 · 物理学 2015-05-27 Matthieu Tissier , Gilles Tarjus

We revisit perturbative RG analysis in the replicated Landau-Ginzburg description of the Random Field Ising Model near the upper critical dimension 6. Working in a field basis with manifest vicinity to a weakly-coupled Parisi-Sourlas…

统计力学 · 物理学 2022-07-18 Apratim Kaviraj , Slava Rychkov , Emilio Trevisani

By the Parisi-Sourlas conjecture, the critical point of a theory with random field (RF) disorder is described by a supersymmeric (SUSY) conformal field theory (CFT), related to a $d-2$ dimensional CFT without SUSY. Numerical studies…

统计力学 · 物理学 2022-08-31 Apratim Kaviraj , Slava Rychkov , Emilio Trevisani

In a recent letter, Fytas et al. [Phys. Rev. Lett. 122, 240603 (2019)] study the critical point of the equilibrium random-field Ising model (RFIM) in $D=5$ by means of state-of-art zero-temperature lattice simulations. We show that their…

无序系统与神经网络 · 物理学 2019-10-04 Ivan Balog , Gilles Tarjus , Matthieu Tissier

We use the RG framework set up in arXiv:2009.10087 to explore the $\phi^3$ theory with a random field interaction. According to the Parisi-Sourlas conjecture this theory admits a fixed point with emergent supersymmetry which is related to…

高能物理 - 理论 · 物理学 2022-09-14 Apratim Kaviraj , Emilio Trevisani

Numerical evidence suggests that the Random Field Ising Model loses Parisi-Sourlas SUSY and the dimensional reduction property somewhere between 4 and 5 dimensions, while a related model of branched polymers retains these features in any…

统计力学 · 物理学 2023-10-19 Slava Rychkov

We have developed a non-perturbative functional renormalization group approach for the random field O(N) model (RFO(N)M) that allows us to investigate the ordering transition in any dimension and for any value of N including the Ising case.…

无序系统与神经网络 · 物理学 2009-11-10 Gilles Tarjus , Matthieu Tissier

We study the critical behavior and phase diagram of the $d$-dimensional random field O(N) model by means of the nonperturbative functional renormalization group approach presented in the preceding paper. We show that the dimensional…

统计力学 · 物理学 2011-07-20 Matthieu Tissier , Gilles Tarjus

We review the theoretical description of the random field Ising and $O(N)$ models obtained from the functional renormalization group, either in its nonperturbative implementation or, in some limits, in perturbative implementations. The…

无序系统与神经网络 · 物理学 2020-04-22 Gilles Tarjus , Matthieu Tissier

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical…

无序系统与神经网络 · 物理学 2017-04-12 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

Perturbation theory for the random-field Ising model (RFIM) has the infamous attribute that it predicts at all orders a dimensional-reduction property for the critical behavior that turns out to be wrong in low dimension. Guided by our…

无序系统与神经网络 · 物理学 2015-10-07 Gilles Tarjus , Matthieu Tissier

We study the replica field theory which describes the pinning of elastic manifolds of arbitrary internal dimension d in a random potential, with the aim of bridging the gap between mean field and renormalization theory. The full effective…

凝聚态物理 · 物理学 2009-07-10 Pierre Le Doussal , Kay Joerg Wiese

We investigate dimensional reduction, the property that the critical behavior of a system in the presence of quenched disorder in dimension d is the same as that of its pure counterpart in d-2, and its breakdown in the case of the…

无序系统与神经网络 · 物理学 2013-08-09 Maxime Baczyk , Matthieu Tissier , Gilles Tarjus , Yoshinori Sakamoto

The functional RG for the random field and random anisotropy O(N) sigma-models is studied to two loop. The ferromagnetic/disordered (F/D) transition fixed point is found to next order in d=4+epsilon for N > N_c (N_c=2.8347408 for random…

无序系统与神经网络 · 物理学 2009-11-11 Pierre Le Doussal , Kay Joerg Wiese

Hyperuniformity, where the static structure factor obeys $S(q)\sim q^{\varsigma}$ with $\varsigma> 0$, emerges at criticality in systems having multiple, symmetry-unrelated, absorbing states. Important examples arise in periodically sheared…

统计力学 · 物理学 2025-07-11 Xiao Ma , Johannes Pausch , Gunnar Pruessner , Michael E. Cates

We show that it is possible to use dimensional regularization (DR) beyond the usual $\varepsilon$-expansion in the context of renormalization group (RG) calculations in Critical Phenomena. Based on this fact, we propose a new functional RG…

高能物理 - 理论 · 物理学 2026-04-29 P. Beretta , A. Codello

Quenched disorder is very important but notoriously hard. In 1979, Parisi and Sourlas proposed an interesting and powerful conjecture about the infrared fixed points with random field type of disorder: such fixed points should possess an…

高能物理 - 理论 · 物理学 2020-05-20 Apratim Kaviraj , Slava Rychkov , Emilio Trevisani

If collider experiments demonstrate that the Minimal Supersymmetric Standard Model (MSSM) is a good description of nature at the weak scale, the experimental priority will be the precise determination of superpartner masses. These masses…

高能物理 - 唯象学 · 物理学 2014-11-21 Marcela Carena , Patrick Draper , Nausheen R. Shah , Carlos E. M. Wagner
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