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The phase reduction method is a dimension reduction method for weakly driven limit-cycle oscillators, which has played an important role in the theoretical analysis of synchro- nization phenomena. Recently, we proposed a generalization of…

Adaptation and Self-Organizing Systems · Physics 2015-09-08 Wataru Kurebayashi , Sho Shirasaka , Hiroya Nakao

We have considered the model of the phase transition of the second order for the Coulomb frustrated 2D charged system. The coupling of the order parameter with the charge was considered as the local temperature. We have found that in such…

Strongly Correlated Electrons · Physics 2018-04-04 R. F. Mamin , T. S. Shaposhnikova , V. V. Kabanov

We describe a scheme for producing conditional nonlinear phase shifts on two-photon optical fields using an interaction with one or more ancilla two-level atomic systems. The conditional field state transformations are induced by using high…

Quantum Physics · Physics 2007-05-23 A. Gilchrist , G. J. Milburn

This paper proposes a method for modeling event sequences with ambiguous timestamps, a time-discounting convolution. Unlike in ordinary time series, time intervals are not constant, small time-shifts have no significant effect, and…

Machine Learning · Computer Science 2018-12-07 Takayuki Katsuki , Takayuki Osogami , Akira Koseki , Masaki Ono , Michiharu Kudo , Masaki Makino , Atsushi Suzuki

In this paper we show quantum fluctuation effect of fully frustrated Ising spin systems. Quantum annealing has been expected to be an efficient method to find ground state of optimization problems. However it is not clear when to use the…

Disordered Systems and Neural Networks · Physics 2011-06-06 Shu Tanaka

Spectral methods of moments provide a powerful tool for learning the parameters of latent variable models. Despite their theoretical appeal, the applicability of these methods to real data is still limited due to a lack of robustness to…

Machine Learning · Statistics 2018-10-18 Matteo Ruffini , Guillaume Rabusseau , Borja Balle

We investigate a hybrid quantum-classical solution method to the mean-variance portfolio optimization problems. Starting from real financial data statistics and following the principles of the Modern Portfolio Theory, we generate…

Quantum Physics · Physics 2019-07-01 Davide Venturelli , Alexei Kondratyev

We propose a method of classifying the operation of a system into finitely many modes. Each mode has its own objectives for the system's behaviour and its own mathematical models and algorithms designed to accomplish its objectives. A…

Logic in Computer Science · Computer Science 2021-07-14 Edwin Beggs , John V. Tucker

Quantum annealing is a method developed to solve combinatorial optimization problems by utilizing quantum bits. Solving such problems corresponds to minimizing a cost function defined over binary variables. However, in many practical cases,…

Quantum Physics · Physics 2025-06-26 Seiya Endo , Shohei Kawakatsu , Hiromichi Matsuyama , Kohei Suzuki , Yuichiro Matsuzaki

The second moment method has always been an effective tool to lower bound the satisfiability threshold of many random constraint satisfaction problems. However, the calculation is usually hard to carry out and as a result, only some loose…

Combinatorics · Mathematics 2020-11-06 Jun Liu , Ke Xu , Guangyan Zhou

One-dimensional model of a system where first-order phase transition occurs is examined in the present paper. It is shown that basic properties of the phenomenon, such as a well defined temperature of transition, are caused both by…

Statistical Mechanics · Physics 2009-07-29 Marcin Ostrowski

Numerous recent techniques for text style transfer characterize their approaches as variants of reinforcement learning and preference optimization. In this work, we consider the relationship between these approaches and a class of…

Computation and Language · Computer Science 2024-07-30 Shuai Liu , Jonathan May

Process variant analysis aims at identifying and addressing the differences existing in a set of process executions enacted by the same process model. A process model can be executed differently in different situations for various reasons,…

Other Computer Science · Computer Science 2019-12-24 Farbod Taymouri , Marcello La Rosa , Marlon Dumas , Fabrizio Maria Maggi

Recently, it has been recognized that phase transitions play an important role in the probabilistic analysis of combinatorial optimization problems. However, there are in fact many other relations that lead to close ties between computer…

Statistical Mechanics · Physics 2007-05-23 O. C. Martin , R. Monasson , R. Zecchina

We propose a systematic methodology to identify the topological phase transition through a self-supervised machine learning model, which is trained to correlate system parameters to the non-local observables in time-of-flight experiments of…

Quantum Gases · Physics 2021-09-01 Chi-Ting Ho , Daw-Wei Wang

The nature of the Abelian Higgs Model phase transition is investigated. A variational approximation is used in the evaluation of the relevant finite temperature effective potential. Some of the results presented are valid not only in the…

High Energy Physics - Phenomenology · Physics 2007-05-23 G. Amelino-Camelia

Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinatorial optimization problems. In recent years, advances in quantum technologies have enabled the development of small- and intermediate-scale…

Quantum Physics · Physics 2022-10-05 Sheir Yarkoni , Elena Raponi , Thomas Bäck , Sebastian Schmitt

This paper proposes a tuning methodology for proportional resonant (PR) controllers by using the design philosophy of the Ziegler-Nichols forced oscillation method. Unlike such related methods that are usual for PID design, and those that…

Signal Processing · Electrical Eng. & Systems 2018-07-18 Charles Lorenzini , Luís Fernando Alves Pereira , Alexandre Sanfelice Bazanella

We propose an algorithm for taming Normalizing Flow models - changing the probability that the model will produce a specific image or image category. We focus on Normalizing Flows because they can calculate the exact generation probability…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Shimon Malnick , Shai Avidan , Ohad Fried

We consider the time evolution of simple quantum systems under the influence of random fluctuations of the control parameters. We show that when the parameters fluctuate sufficiently fast, there is a cancellation effect of the noise. We…

Quantum Physics · Physics 2007-05-23 Paolo Solinas , Nino Zanghi
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