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We demonstrate how measuring orbital period derivatives can lead to more accurate distance estimates and transverse velocities for some nearby binary pulsars. In many cases this method will estimate distances more accurately than is…

Astrophysics · Physics 2009-10-28 J. F. Bell , M. Bailes

Optimization is an important module of modern machine learning applications. Tremendous efforts have been made to accelerate optimization algorithms. A common formulation is achieving a lower loss at a given time. This enables a…

Machine Learning · Computer Science 2025-05-29 Zhonglin Xie , Yiman Fong , Haoran Yuan , Zaiwen Wen

The nature of eclipsing time variations (ETVs) in post-common-envelope binaries (PCEBs) is still unknown. Circumbinary planets routinely fail the test of time and the Applegate mechanism has energetic constraints and problems in reproducing…

Solar and Stellar Astrophysics · Physics 2026-05-01 Felipe H. Navarrete , Dominik R. G. Schleicher , Petri J. Käpylä , Marcel Völschow

Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundamental level. Producing thousands of such models requires hundreds of CPU hours, but…

Given two strings of length $n$ over alphabet $\Sigma$, and an upper bound $k$ on their edit distance, the algorithm of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88) computes the unweighted string edit distance in…

Data Structures and Algorithms · Computer Science 2023-02-09 Debarati Das , Jacob Gilbert , MohammadTaghi Hajiaghayi , Tomasz Kociumaka , Barna Saha

The nearest neighbor method together with the dynamic time warping (DTW) distance is one of the most popular approaches in time series classification. This method suffers from high storage and computation requirements for large training…

Machine Learning · Computer Science 2017-03-27 Brijnesh Jain , David Schultz

We propose a new multi-dimensional discrete-time quantum walk (DTQW), whose continuum limit is an extended multi-dimensional Dirac equation, which can be further mapped to the Schr\"{o}dinger equation. We show in two ways that our DTQW is…

Quantum Physics · Physics 2023-04-19 Manami Yamagishi , Naomichi Hatano , Ken-Ichiro Imura , Hideaki Obuse

In this article, we generalize the recent Discrete Time Random Walk (DTRW) algorithm, which was introduced for the computation of probability densities of fractional diffusion. Although it has the same computational complexity and shares…

Computational Physics · Physics 2018-08-20 Gurtek Gill , Peter Straka

Optimal Transport (OT) has established itself as a robust framework for quantifying differences between distributions, with applications that span fields such as machine learning, data science, and computer vision. This paper offers a…

Data Structures and Algorithms · Computer Science 2025-01-14 Sina Moradi

Short-period Galactic double white dwarf (DWD) systems will be observable both in visible light through photometric monitoring and in mHz-range gravitational waves (GWs) with forthcoming space-based laser interferometry such as LISA. When…

Solar and Stellar Astrophysics · Physics 2025-08-06 Nathaniel Leslie , Liang Dai , Kevin Burdge

Recently used in various machine learning contexts, the Gromov-Wasserstein distance (GW) allows for comparing distributions whose supports do not necessarily lie in the same metric space. However, this Optimal Transport (OT) distance…

Machine Learning · Statistics 2022-10-21 Titouan Vayer , Rémi Flamary , Romain Tavenard , Laetitia Chapel , Nicolas Courty

We propose a method based on the discrete truncated Wigner approximation (DTWA) for computing out-of-time-order correlators. This method is applied to long-range interacting quantum spin systems where the interactions decay as a power law…

Statistical Mechanics · Physics 2025-07-21 Tatsuhiko Shirai , Takashi Mori

Computing the quadratic transportation metric (also called the $2$-Wasserstein distance or root mean square distance) between two point clouds, or, more generally, two discrete distributions, is a fundamental problem in machine learning,…

Data Structures and Algorithms · Computer Science 2018-12-18 Jason Altschuler , Francis Bach , Alessandro Rudi , Jonathan Weed

Time Series Analysis (TSA) is a critical workload to extract valuable information from collections of sequential data, e.g., detecting anomalies in electrocardiograms. Subsequence Dynamic Time Warping (sDTW) is the state-of-the-art…

We show that for a weakly dense subset of the domain of attraction of a positive stable random variable of index $0<\alpha<1$($DOA\left(\alpha\right))$ the functional stable convergence is a time-changed renewal convergence of distribution…

Probability · Mathematics 2017-09-12 Ofer Busani

Change point detection plays a fundamental role in many real-world applications, where the goal is to analyze and monitor the behaviour of a data stream. In this paper, we study change detection in binary streams. To this end, we use a…

Machine Learning · Computer Science 2023-01-24 Nikolaj Tatti

The edit distance of two strings is the minimum number of insertions, deletions, and substitutions needed to transform one string into the other. The textbook algorithm determines the edit distance of length-$n$ strings in $O(n^2)$ time,…

Data Structures and Algorithms · Computer Science 2025-02-04 Egor Gorbachev , Tomasz Kociumaka

Temporal graphs are commonly used to represent time-resolved relations between entities in many natural and artificial systems. Many techniques were devised to investigate the evolution of temporal graphs by comparing their state at…

Social and Information Networks · Computer Science 2024-11-20 Lorenzo Dall'Amico , Alain Barrat , Ciro Cattuto

Two-Way Ranging enables the distance estimation between two active parties and allows time of flight measurements despite relative clock offset and drift. Limited by the number of messages, scalable solutions build on Time Difference of…

Signal Processing · Electrical Eng. & Systems 2024-01-04 Patrick Rathje , Olaf Landsiedel