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We propose a streamlined combination scheme of the transcorrelation (TC) and coupled cluster (CC) theory, which not only increases the convergence rate with respect to the basis set, but also extends the applicability of the lowest order CC…

Strongly Correlated Electrons · Physics 2021-07-28 Ke Liao , Thomas Schraivogel , Hongjun Luo , Daniel Kats , Ali Alavi

The problem of the relationship between entanglement and two-qubit systems in which it is embedded is central to the quantum information theory. This paper suggests that the concurrence hierarchy as an entanglement measure provides an…

Quantum Physics · Physics 2009-11-11 Mahmoud Abdel-Aty

Online Conformal Prediction (CP) struggles to balance temporal adaptability and structural stability. Feedback-driven methods (e.g., Adaptive Conformal Inference (ACI)) suffer from systemic marginal under-coverage and high interval variance…

Machine Learning · Computer Science 2026-05-04 Yu-Hsueh Fang , Chia-Yen Lee

In nonperturbative regimes, the superfluid instability in the two-dimensional Hubbard model can be described by an emergent BCS theory with small effective pairing constants. We compute the effective couplings using a controlled bold-line…

Strongly Correlated Electrons · Physics 2021-07-28 Fedor Šimkovic , Youjin Deng , Evgeny Kozik

We study the Heisenberg $S=1/2$ chain with random ferro- and antiferromagnetic couplings using quantum Monte Carlo simulations at ultra-low temperatures, converging to the ground state. Finite-size scaling of correlation functions and…

Strongly Correlated Electrons · Physics 2025-02-26 Sibei Li , Hui Shao , Anders W. Sandvik

We introduce polynomial couplings, a generalization of probabilistic couplings, to develop an algorithm for the computation of equivalence relations which can be interpreted as a lifting of probabilistic bisimulation to polynomial…

Logic in Computer Science · Computer Science 2021-04-28 Giorgio Bacci , Giovanni Bacci , Kim G. Larsen , Mirco Tribastone , Max Tschaikowski , Andrea Vandin

The VertexCover problem is proven to be computationally hard in different ways: It is NP-complete to find an optimal solution and even NP-hard to find an approximation with reasonable factors. In contrast, recent experiments suggest that on…

Data Structures and Algorithms · Computer Science 2020-02-20 Thomas Bläsius , Philipp Fischbeck , Tobias Friedrich , Maximilian Katzmann

The two-dimensional attractive Hubbard model is studied in the weak to intermediate coupling regime by employing a non-perturbative approach. It is first shown that this approach is in quantitative agreement with Monte Carlo calculations…

Strongly Correlated Electrons · Physics 2009-10-31 B. Kyung , S. Allen , A. -M. S. Tremblay

We study the critical behavior (CB) of all period $p$-tuplings $(p \!=\!2,3,4,\dots)$ in $N$ $(N \!=\! 2,3,4,\dots)$ symmetrically coupled one-dimensional maps. We first investigate the CB for the $N=2$ case of two coupled maps, using a…

chao-dyn · Physics 2009-10-28 Sang-Yoon Kim

Correlations derived through single-particle approximations of the many-body problem frequently result in erroneously inflated or diminished physical properties. In the context of transition metals, the impact of correlations can be…

Materials Science · Physics 2025-08-05 Jacques R. Eone

The spectral density of random graphs with topological constraints is analysed using the replica method. We consider graph ensembles featuring generalised degree-degree correlations, as well as those with a community structure. In each case…

Disordered Systems and Neural Networks · Physics 2011-04-08 Tim Rogers , Conrad Pérez Vicente , Koujin Takeda , Isaac Pérez Castillo

We study random constraint satisfaction problems (CSPs) in the unsatisfiable regime. We relate the structure of near-optimal solutions for any Max-CSP to that for an associated spin glass on the hypercube, using the Guerra-Toninelli…

Discrete Mathematics · Computer Science 2023-03-30 Chris Jones , Kunal Marwaha , Juspreet Singh Sandhu , Jonathan Shi

We perform a numerical study of the kinetic Blume-Capel (BC) model to find if it exhibits the metamagnetic anomalies previously observed in the kinetic Ising model for supercritical periods. We employ a heat-bath Monte Carlo (MC) algorithm…

Statistical Mechanics · Physics 2024-10-24 Celeste Mendes , Gloria M. Buendia , Per Arne Rikvold

We consider chains of random constraint satisfaction models that are spatially coupled across a finite window along the chain direction. We investigate their phase diagram at zero temperature using the survey propagation formalism and the…

Computational Complexity · Computer Science 2015-06-03 S. Hamed Hassani , Nicolas Macris , Rudiger Urbanke

We consider the problem of estimating rare event probabilities, focusing on systems whose evolution is governed by differential equations with uncertain input parameters. If the system dynamics is expensive to compute, standard sampling…

Computation · Statistics 2019-11-05 Siddhant Wahal , George Biros

We study the phase transitions of a random copolymer chain with quenched disorder. We apply a replica variational approach based on a Gaussian trial Hamiltonian in terms of the correlation functions of monomer Fourier coordinates. This…

Disordered Systems and Neural Networks · Physics 2009-10-30 A. Moskalenko , Yu. A. Kuznetsov , K. A. Dawson

We consider the matching augmentation problem (MAP), where a matching of a graph needs to be extended into a $2$-edge-connected spanning subgraph by adding the minimum number of edges to it. We present a polynomial-time algorithm with an…

Data Structures and Algorithms · Computer Science 2023-05-29 Mohit Garg , Felix Hommelsheim , Nicole Megow

We determine under which conditions certain natural models of random constraint satisfaction problems have sharp thresholds of satisfiability. These models include graph and hypergraph homomorphism, the $(d,k,t)$-model, and binary…

Combinatorics · Mathematics 2009-03-17 Hamed Hatami , Michael Molloy

We demonstrate for the first time that ill-conditioned, non-smooth, constrained distributions in very high dimension, upwards of 100,000, can be sampled efficiently $\textit{in practice}$. Our algorithm incorporates constraints into the…

Machine Learning · Computer Science 2022-10-18 Yunbum Kook , Yin Tat Lee , Ruoqi Shen , Santosh S. Vempala

We introduce an ensemble Markov chain Monte Carlo approach to sampling from a probability density with known likelihood. This method upgrades an underlying Markov chain by allowing an ensemble of such chains to interact via a process in…

Computation · Statistics 2021-06-08 Michael Lindsey , Jonathan Weare , Anna Zhang
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