.. Nightingale Mist the second, played by Winona Horowitz Emmanuelle Hyacinth Ryder: ..".. Who is this stunningly genius level intellect young handsome man.. He is the true, authentic genius, Davy Kirkpatrick.. and this article is copy and pasted from the website for the 'Daily Galaxy'.. and this article is written by Arezki Amiri.."..

Sponsored Daily Galaxy 64.2K Followers “I mapped the invisible”: American high-school student stuns astronomers by discovering 1.5 million hidden cosmic objects Story by Arezki Amiri • 8h • 4 min read From Classroom To Cosmos A Teen Mapped 1.5 Million Hidden Space Objects. Credit: Fox 11 Los Angeles | The Daily Galaxy --Great Discoveries Channel From Classroom To Cosmos A Teen Mapped 1.5 Million Hidden Space Objects. Credit: Fox 11 Los Angeles | The Daily Galaxy --Great Discoveries Channel © Daily Galaxy CA The numbers arrived with the dispassion of a telemetry readout: 10.5 years of observations, 200 billion individual detections, a complete infrared survey of the entire sky. For more than a decade after the NEOWISE telescope began its reactivated mission, the data sat in institutional archives, processed for its primary purpose of asteroid tracking but otherwise unread. The variable objects, quasars that flickered, stars that pulsed, binaries that dimmed as they eclipsed, remained invisible, buried in the noise of their own abundance. If You Receive CPP In Ontario, You Should See This If You Receive CPP In Ontario, You Should See This Canadian Final Expense · Sponsored call to action icon more A Caltech senior research scientist named Davy Kirkpatrick had spent years looking at that dataset and wondering what it contained. He had mentored high school students for five summers, but he also wanted to extract something from the NEOWISE archive that no one had yet extracted: a complete catalog of every infrared source that changed brightness over time. This mosaic is composed of images covering the entire sky, taken by the Wide-field Infrared Survey Explorer (WISE) This mosaic is composed of images covering the entire sky, taken by the Wide-field Infrared Survey Explorer (WISE) © Daily Galaxy CA The problem, as he later put it, was that the data had grown too large for conventional methods. “At that point, we were creeping up towards 200 billion rows in the table of every single detection that we had made over the course of over a decade,” Kirkpatrick said. His idea for a summer project was modest: take a small patch of sky, find some variable stars by hand, and publish them as a proof of concept. Then a 17-year-old from Pasadena High School walked into his laboratory and proposed doing something else entirely. Related video: Not an asteroid, not a comet - this object didn’t look like anything we know (TED) TED Not an asteroid, not a comet - this object didn’t look like anything we know Current Time 0:00 / Duration 13:24 0 View on Watch View on Watch The Model That Runs at 53 Microseconds Per Star Matteo Paz had attended Caltech’s public stargazing lectures with his mother since elementary school. By the summer of 2023, when he joined Kirkpatrick’s lab through the university’s Summer Research Connection program, he had completed AP Calculus in eighth grade through Pasadena Unified’s accelerated Math Academy and was studying undergraduate level mathematics. An elective course integrating coding and theoretical computer science had introduced him to machine learning. The Caltech feature on exploring space with AI traces the origins of their collaboration through these outreach programs. Paz told Kirkpatrick on their first day that he wanted to publish a paper. Kirkpatrick did not discourage him. “He has allowed an unbridled learning experience,” Paz said. “I think that’s why I’ve grown so much as a scientist.” The model Paz developed, named VARnet, processes astronomical time series data through three integrated stages. Wavelet decomposition reduces the impact of spurious measurements. A modified discrete Fourier transform extracts periodic features from irregularly sampled light curves. The Anomaly Extraction Pipeline The Anomaly Extraction Pipeline © Daily Galaxy CA The Astronomical Journal published the complete technical specifications, available in the peer reviewed paper on the VARnet architecture, describing how convolutional neural networks classify each source into one of four categories: non variable, transient events such as supernovae, intrinsic pulsators, or eclipsing binary systems. Meet 11 of the hottest Olympians at the 2026 Winter Games in Milano-Cortina Meet 11 of the hottest Olympians at the 2026 Winter Games in Milano-Cortina Postmedia · Sponsored call to action icon more The performance metrics show processing times of less than 53 microseconds per source on a GPU with 22 gigabytes of VRAM, with an F1 score of 0.91 on a validation set of known variable objects. The model scales to the full NEOWISE dataset. A Mentorship Forged in Tennessee Kirkpatrick grew up in a farming community in Tennessee. His ninth grade chemistry and physics teacher, Marilyn Morrison, told him and his mother that he had scientific potential and outlined the courses he would need for college. She was, Kirkpatrick said, the reason he became an astronomer. His professional background is detailed on his staff page at IPAC, the Infrared Processing and Analysis Center at Caltech where the NEOWISE data is archived. “I wanted to pass on that same sort of mentoring to someone else and hopefully many someone eleses,” Kirkpatrick said. “If I see their potential, I want to make sure that they are reaching it. I’ll do whatever I can to help them out.” Matteo Paz With Caltech President Thomas F. Rosenbaum Matteo Paz With Caltech President Thomas F. Rosenbaum © Daily Galaxy CA That philosophy shaped the summer project’s direction. When Paz proposed building anAI model to analyze the entire NEOWISE database rather than a single patch of sky, Kirkpatrick connected him with Caltech researchers Shoubaneh Hemmati, Daniel Masters, Ashish Mahabal, and Matthew Graham, who provided expertise in machine learning techniques for astronomy and in the analysis of objects that vary on different timescales. The CPAP Store - Lowest Priced CPAP Products - CPAP Supplies Canada The CPAP Store - Lowest Priced CPAP Products - CPAP Supplies Canada thecpapstore.ca · Sponsored call to action icon more The collaboration revealed a constraint in the NEOWISE data. The telescope’s observational rhythm, scanning in great circles centered on the Sun, meant it could not systematically detect objects that flashed once and faded, or those that changed gradually over years. Some classes of variable phenomena would remain invisible to any automated survey based on NEOWISE data alone. The 1.5 Million Candidates VARnet flagged 1.5 million potential variable objects in the NEOWISE archive. The figure does not represent 1.5 million confirmed discoveries in the traditional sense. Each flagged source is a candidate requiring follow up observation and classification by astronomers. Some will prove to be known objects now characterized in infrared wavelengths for the first time. Some will be false positives. Some fraction will be genuinely new detections of quasars, variable stars, and transient events. The full catalog is scheduled for publication in 2025. When released, it will provide the astronomical community with a dataset large enough to support statistical studies of infrared variability across the entire sky, rather than the piecemeal analyses that have characterized the field to date. This illustration shows the Wide-field Infrared Survey Explorer (WISE) spacecraft in Earth orbit. This illustration shows the Wide-field Infrared Survey Explorer (WISE) spacecraft in Earth orbit. © Daily Galaxy CA Paz, now a Caltech employee working at IPAC while finishing high school, described the model’s potential applications beyond astronomy. “The model I implemented can be used for other time domain studies in astronomy, and potentially anything else that comes in a temporal format,” he said. “I could see some relevance to chart analysis, where the information similarly comes in a time series and periodic components can be critical. You could also study atmospheric effects such as pollution, where the periodic seasons and day night cycles play huge roles.” Enjoyed this article? Subscribe to our free newsletter for engaging stories, exclusive content, and the latest news. 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