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Deep neural networks demonstrate strong performance under aligned training-test distributions. However, real-world test data often exhibit domain shifts. Test-Time Adaptation (TTA) addresses this challenge by adapting the model to test data…

Artificial Intelligence · Computer Science 2025-08-27 Byung-Joon Lee , Jin-Seop Lee , Jee-Hyong Lee

We study the effect of localized modes in lattices of size N with parity-time (PT) symmetry. Such modes are arranged in pairs of quasi-degenerate levels with splitting delta exp{-N/xi}, where \xi is their localization length. The level…

Other Condensed Matter · Physics 2009-09-02 Oliver Bendix , Ragnar Fleischmann , Tsampikos Kottos , Boris Shapiro

Zero-free based algorithm is a major technique for deterministic approximate counting. In Barvinok's original framework[Bar17], by calculating truncated Taylor expansions, a quasi-polynomial time algorithm was given for estimating zero-free…

Data Structures and Algorithms · Computer Science 2022-02-01 Penghui Yao , Yitong Yin , Xinyuan Zhang

Variational hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been…

Quantum Physics · Physics 2021-06-30 Sukin Sim , Jonathan Romero , Jerome F. Gonthier , Alexander A. Kunitsa

A polynomial transform is the multiplication of an input vector $x\in\C^n$ by a matrix $\PT_{b,\alpha}\in\C^{n\times n},$ whose $(k,\ell)$-th element is defined as $p_\ell(\alpha_k)$ for polynomials $p_\ell(x)\in\C[x]$ from a list…

Information Theory · Computer Science 2011-07-14 Aliaksei Sandryhaila , Jelena Kovacevic , Markus Pueschel

The area of parameterized approximation seeks to combine approximation and parameterized algorithms to obtain, e.g., (1+eps)-approximations in f(k,eps)n^{O(1)} time where k is some parameter of the input. We obtain the following results on…

Data Structures and Algorithms · Computer Science 2019-06-27 Fabrizio Grandoni , Stefan Kratsch , Andreas Wiese

The subject of this paper is the phase transition between symmetry protected topological states (SPTs). We consider spatial dimension $d$ and symmetry group $G$ so that the cohomology group, $H^{d+1}(G,U(1))$, contains at least one $Z_{2n}$…

Strongly Correlated Electrons · Physics 2015-07-30 Lokman Tsui , Hong-Chen Jiang , Yuan-Ming Lu , Dung-Hai Lee

We present adapted Zhang Neural Networks (AZNN) in which the parameter settings for the exponential decay constant $\eta$ and the length of the start-up phase of basic ZNN are adapted to the problem at hand. Specifically we study…

Numerical Analysis · Mathematics 2023-03-08 Frank Uhlig

First, we study geometric variants of the standard set cover motivated by assignment of directional antenna and shipping with deadlines, providing the first known polynomial-time exact solutions. Next, we consider the following general…

Computational Complexity · Computer Science 2009-09-30 Piotr Berman , Marek Karpinski , Andrzej Lingas

Replicability is a lynchpin for credible discoveries. The partial conjunction (PC) p-value, which combines individual base p-values from multiple similar studies, can gauge whether a feature of interest exhibits replicated signals across…

Methodology · Statistics 2025-07-29 Ninh Tran , Dennis Leung

Quantum Signal Processing (QSP) is a technique that can be used to implement a polynomial transformation $P(x)$ applied to the eigenvalues of a unitary $U$, essentially implementing the operation $P(U)$, provided that $P$ satisfies some…

Quantum Physics · Physics 2023-03-21 Lorenzo Laneve

We present an efficient numerical technique to evaluate the matrix of the (quasiparticle)-random-phase approximation, using the finite amplitude method (FAM). The method is tested in calculation of monopole excitations in 120Sn, compared…

Nuclear Theory · Physics 2013-02-11 Paolo Avogadro , Takashi Nakatsukasa

The verification of systems combining hard timing constraints with concurrency is challenging. This challenge becomes even harder when some timing constants are missing or unknown. Parametric timed formalisms, such as parametric timed…

Formal Languages and Automata Theory · Computer Science 2019-08-20 Étienne André , Didier Lime , Mathias Ramparison

We consider reinforcement learning in parameterized Markov Decision Processes (MDPs), where the parameterization may induce correlation across transition probabilities or rewards. Consequently, observing a particular state transition might…

Machine Learning · Statistics 2015-04-01 Aditya Gopalan , Shie Mannor

In this paper we revisit the classical Edge Disjoint Paths (EDP) problem, where one is given an undirected graph G and a set of terminal pairs P and asks whether G contains a set of pairwise edge-disjoint paths connecting every terminal…

Data Structures and Algorithms · Computer Science 2017-11-07 Robert Ganian , Sebastian Ordyniak , M. S. Ramanujan

For a Coupled Map Lattice with a specific strong coupling emulating Stavskaya's probabilistic cellular automata, we prove the existence of a phase transition using a Peierls argument, and exponential convergence to the invariant measures…

Dynamical Systems · Mathematics 2010-05-19 Augustin de Maere

The broken and unbroken phases of PT and supersymmetry in optical systems are explored for a complex refractive index profile in the form of a Scarf potential, under the framework of supersymmetric quantum mechanics. The transition from…

Quantum Physics · Physics 2021-07-05 Adipta Pal , Subhrajit Modak , Aradhya Shukla , Prasanta K. Panigrahi

We experimentally demonstrate PT-symmetric optical lattices with periodical gain and loss profiles in a coherently-prepared four-level N-type atomic system. By appropriately tuning the pertinent atomic parameters, the onset of PT-symmetry…

In this paper, we show bounds on Peak-to-Average Power Ratio (PAPR) and propose a method to reduce PAPR. These bounds are written in terms of moments of transmitted symbols. Further, we show some bounds in special cases and these special…

Information Theory · Computer Science 2019-09-17 Hirofumi Tsuda

Large-scale atomistic simulations can produce extreme volumes of information in the form of long trajectories. Reliably and automatically extracting key information from such datasets remains a formidable challenge, especially as it…

Computational Physics · Physics 2026-03-31 Rostyslav Hnatyshyn , Danny Perez