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With manual searching processes, the rate at which scientists and astronomers discover exoplanets is slow because of inefficiencies that require an extensive time of laborious inspections. In fact, as of now there have been about only 5,000…

Machine Learning · Computer Science 2025-07-29 Ethan Lo , Dan C. Lo

Despite the continuous proposal of new anomaly detection algorithms and extensive benchmarking efforts, progress seems to stagnate, with only minor performance differences between established baselines and new algorithms. In this position…

Machine Learning · Computer Science 2025-07-22 Philipp Röchner , Simon Klüttermann , Franz Rothlauf , Daniel Schlör

With the increasingly complex and changeable electromagnetic environment, wireless communication systems are facing jamming and abnormal signal injection, which significantly affects the normal operation of a communication system. In…

Signal Processing · Electrical Eng. & Systems 2022-05-31 Tingyan Kuang , Huichao Chen , Lu Han , Rong He , Wei Wang , Guoru Ding

The application of machine learning techniques for anomaly detection in particle accelerators has gained popularity in recent years. These efforts have ranged from the analysis of quenches in radio frequency cavities and superconducting…

Accelerator Physics · Physics 2021-12-16 Jonathan P. Edelen , Nathan M. Cook

Exoplanet characterization missions planned for the future will soon enable searches for life beyond our solar system. Critical to the search will be the development of life detection strategies that can search for biosignatures while…

Earth and Planetary Astrophysics · Physics 2024-01-23 Amber V. Young , Jaime Crouse , Giada Arney , Shawn Domagal-Goldman , Tyler D. Robinson , Sandra T. Bastelberger

As two neutron stars merge, they emit gravitational waves that can potentially be detected by earth bound detectors. Matched-filtering based algorithms have traditionally been used to extract quiet signals embedded in noise. We introduce a…

High Energy Astrophysical Phenomena · Physics 2020-09-29 Marlin B. Schäfer , Frank Ohme , Alexander H. Nitz

Exoplanet hunting efforts have revealed the prevalence of exotic worlds with diverse properties, including Earth-sized bodies, which has fueled our endeavor to search for life beyond the Solar System. Accumulating experiences in…

Anomalies are strange data points; they usually represent an unusual occurrence. Anomaly detection is presented from the perspective of Wireless sensor networks. Different approaches have been taken in the past, as we will see, not only to…

Machine Learning · Computer Science 2017-08-30 Pelumi Oluwasanya

Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to…

Earth and Planetary Astrophysics · Physics 2021-07-26 Kai Hou Yip , Quentin Changeat , Nikolaos Nikolaou , Mario Morvan , Billy Edwards , Ingo P. Waldmann , Giovanna Tinetti

The Search for Extraterrestrial intelligence (SETI) is a scientific and cultural effort seeking evidence of intelligent life beyond earth. Radio SETI observes the radio spectrum for ''technosignatures" that could be produced by an advanced…

Instrumentation and Methods for Astrophysics · Physics 2021-09-29 Kenneth M. Houston , Andrew P. V. Siemion , Steve Croft

Anomaly detection has the potential to discover new physics in unexplored regions of the data. However, choosing the best anomaly detector for a given data set in a model-agnostic way is an important challenge which has hitherto largely…

High Energy Physics - Phenomenology · Physics 2026-01-27 Marie Hein , Gregor Kasieczka , Michael Krämer , Louis Moureaux , Alexander Mück , David Shih

We describe a new metric that uses machine learning to determine if a periodic signal found in a photometric time series appears to be shaped like the signature of a transiting exoplanet. This metric uses dimensionality reduction and…

Large area astronomical surveys will almost certainly contain new objects of a type that have never been seen before. The detection of 'unknown unknowns' by an algorithm is a difficult problem to solve, as unusual things are often easier…

Instrumentation and Methods for Astrophysics · Physics 2025-08-06 David Parkinson , Gary Segal

Fault detection is a key challenge in the management of complex systems. In the context of SparkCognition's efforts towards predictive maintenance in large scale industrial systems, this problem is often framed in terms of anomaly detection…

Machine Learning · Computer Science 2024-05-29 Elad Liebman

We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the Global Positioning System (GPS),…

Instrumentation and Methods for Astrophysics · Physics 2018-04-25 B. M. Roberts , G. Blewitt , C. Dailey , A. Derevianko

In the upcoming decade large astronomical surveys will discover millions of transients raising unprecedented data challenges in the process. Only the use of the machine learning algorithms can process such large data volumes. Most of the…

A stable-frequency transmitter with relative radial acceleration to a receiver will show a change in received frequency over time, known as a "drift rate''. For a transmission from an exoplanet, we must account for multiple components of…

Earth and Planetary Astrophysics · Physics 2023-11-03 Megan G. Li , Sofia Z. Sheikh , Christian Gilbertson , Matthias Y. He , Howard Isaacson , Steve Croft , Evan L. Sneed

A pair of resonant laser fields can drive a three-level system into a dark state where it seizes to absorb and emit radiation due to destructive interference. We propose a scheme to search for this resonance by randomly changing the…

Quantum Physics · Physics 2017-02-14 Alexander Holm Kiilerich , Klaus Mølmer

Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions. However, the predictive performance of purely unsupervised anomaly detection often fails…

Machine Learning · Computer Science 2014-01-27 Nico Goernitz , Marius Micha Kloft , Konrad Rieck , Ulf Brefeld

The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously unknown classes of objects. To maximise the scientific value…

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