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Since Grover's seminal work, quantum search has been studied in great detail. In the usual search problem, we have a collection of n items and we would like to find a marked item. We consider a new variant of this problem in which…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

Rank-d Tensorial Group Field Theories are quantum field theories defined on a group manifold $G^{\times d}$, which represent a non-local generalization of standard QFT, and a candidate formalism for quantum gravity, since, when endowed with…

High Energy Physics - Theory · Physics 2016-07-13 Joseph Ben Geloun , Riccardo Martini , Daniele Oriti

Using continuous wavelet transform it is possible to construct a regularization procedure for scale-dependent quantum field theory models, which is complementary to functional renormalization group method in the sense that it sums up the…

High Energy Physics - Theory · Physics 2019-03-27 M. V. Altaisky

The source code of successful projects is evolving all the time, resulting in hundreds of thousands of code changes stored in source code repositories. This wealth of data can be useful, e.g., to find changes similar to a planned code…

Software Engineering · Computer Science 2022-11-01 Luca Di Grazia , Paul Bredl , Michael Pradel

We show how the synergy of scaling and non-overlapping global symmetries can lead to Renormalisation Group Invariants (RGIs) among the parameters of potentials with multiple scalars. The instrumental role of scale-invariant field directions…

High Energy Physics - Theory · Physics 2026-05-25 Apostolos Pilaftsis

The computation of the normaliser of a permutation group in the full symmetric group is an important and hard problem in computational group theory. This article reports on an algorithm that builds a descending chain of overgroups to…

Group Theory · Mathematics 2023-03-27 Andreas-Stephan Elsenhans

Renormalization Group Equations (RGEs) are indispensable tool to know the behavior of physical parameters at different energy scales. They are also extremely crucial if we want to extend our known Standard Model gauge group by some extra…

High Energy Physics - Phenomenology · Physics 2019-07-25 Joydeep Roy

The Residual Quantization (RQ) framework is revisited where the quantization distortion is being successively reduced in multi-layers. Inspired by the reverse-water-filling paradigm in rate-distortion theory, an efficient regularization on…

Machine Learning · Computer Science 2017-05-02 Sohrab Ferdowsi , Slava Voloshynovskiy , Dimche Kostadinov

A simple backreaction problem in quantum mechanics, the full quantum anharmonic oscillator, and quantum parametric resonance are studied using Renormalization Group techniques for global asymptotic analysis. In this short note this…

High Energy Physics - Theory · Physics 2017-02-16 I. L. Egusquiza , M. A. Valle-Basagoiti

The renormalization group is a tool that allows one to obtain a reduced description of systems with many degrees of freedom while preserving the relevant features. In the case of quantum systems, in particular, one-dimensional systems…

Quantum Physics · Physics 2009-11-13 Jose Gaite

Fine-grained 3D shape retrieval aims to retrieve 3D shapes similar to a query shape in a repository with models belonging to the same class, which requires shape descriptors to be capable of representing detailed geometric information to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-05 Rao Fu , Jie Yang , Jiawei Sun , Fang-Lue Zhang , Yu-Kun Lai , Lin Gao

Query reformulation is the process by which a input search query is refined by the user to match documents outside the original top-n results. On average, roughly 50% of text search queries involve some form of reformulation, and term…

Computer Vision and Pattern Recognition · Computer Science 2019-10-29 Kyle Xiao , Houdong Hu , Yan Wang

Variational Quantum Algorithms (VQAs) are a promising approach to leverage Noisy Intermediate-Scale Quantum (NISQ) computers. However, choosing optimal quantum circuits that efficiently solve a given VQA problem is a non-trivial task.…

Quantum Physics · Physics 2025-10-07 Swagat Kumar , Jan-Nico Zaech , Colin Michael Wilmott , Luc Van Gool

Quantization methods have been introduced to perform large scale approximate nearest search tasks. Residual Vector Quantization (RVQ) is one of the effective quantization methods. RVQ uses a multi-stage codebook learning scheme to lower the…

Computer Vision and Pattern Recognition · Computer Science 2015-09-18 Shicong Liu , Hongtao Lu , Junru Shao

We apply real-space RG methods to study two quantum group invariant Hamiltonians, that of the XXZ model and the Ising model in a transverse field defined in an open chain with appropiate boundary terms. The quantum group symmetry is…

Condensed Matter · Physics 2008-11-26 Miguel A. Martin-Delgado , German Sierra

Quantum computing leverages quantum mechanics to address computational problems in ways that differ fundamentally from classical approaches. While current quantum hardware remains error-prone and limited in scale, Variational Quantum…

Quantum Physics · Physics 2025-09-16 Michael Kölle , Simon Salfer , Tobias Rohe , Philipp Altmann , Claudia Linnhoff-Popien

We describe glsim, a C++ library designed to provide routines to perform basic housekeeping tasks common to a very wide range of simulation programs, such as reading simulation parameters or reading and writing self-describing binary files…

Computational Physics · Physics 2011-07-29 Tomas S. Grigera

Verification of C++ programs has seen considerable progress in several areas, but not for programs that use these languages' mathematical libraries. The reason is that all libraries in widespread use come with no guarantees about the…

Programming Languages · Computer Science 2022-06-23 Roberto Bagnara , Michele Chiari , Roberta Gori , Abramo Bagnara

Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While…

Machine Learning · Statistics 2021-08-30 Santtu Tikka , Antti Hyttinen , Juha Karvanen

As applied to quantum theories, the program of renormalization is successful for `renormalizable models' but fails for `nonrenormalizable models'. After some conceptual discussion and analysis, an enhanced program of renormalization is…

High Energy Physics - Theory · Physics 2009-05-01 John R. Klauder