Euclid と重力レンズ

OA

論文OpenAlex·2026/10/26

Euclid Q1 strong-lens candidate census: 1,780 uncatalogued systems.

Complete census of uncatalogued strong gravitational lens candidates in Euclid Q1 (63 deg2), from an independent re-scan of the Q1 MER catalogue: 1,725 census systems at mean_logit >= 4.0 plus 55 individually hand-vetted systems, with review tiers, measured tier purities, Consortium-catalogue separations, and spectroscopy columns. First deposit of the Euclid lens catalog; separate from the author's exoplanet deposits.

A&A

論文Astronomy & Astrophysics·2026/10/22

Euclid Quick Data Release (Q1). XLIII. The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1, catalogue, caused us to miss several bright and low-redshift strong lenses. They add more than 10% of new strong-lens candidates compared to the previous search. In total, the catalogue includes 38 grade A (confident) and 34 grade B (probable) candidates. These lenses were identified through a combination of two independent searches for bright nearby objects: one search was based on machine-learning models followed by expert visual inspection, and the other search was based solely on expert visual inspection, targeting objects that were not included in the initial machine-learning selection (a limitation identified only after extensive visual inspection). With these additional strong-lens candidates, we augment the expected number of high-confidence candidates in the Euclid Wide Survey from previous forecasts to . Detailed semi-automated lens modelling confirmed at least 41 systems out of 72. This fraction is consistent with that found in SLDE A (315 out of 488). They include multiple edge-on disc lenses, sources with arcs near the lens centre, red sources, and an edge-on disc galaxy that lenses a galaxy merger, which produces two sets of lensed features, an Einstein ring and a doubly imaged component. The median redshift of these systems is lower by Δ z ∼ 0.3 than that of the SLDE A sample. of the strong-lens discovery engine (SLDE) papers A–E. We show that the previous pre-selection of potential lenses, which excluded objects from the Gaia 120000

A&A

論文Astronomy & Astrophysics·2026/10/21

Euclid: Galaxy cluster detection through the weak lensing effect: Algorithm assessment and selection

Weak gravitational lensing (WL) offers a powerful way to detect galaxy clusters by directly tracing their total matter content. Its effectiveness increases with the density of background galaxies, a requirement that is now being met by the high sensitivity and wide coverage of current and upcoming large-area surveys. A prime example is the Euclid telescope, which will map approximately 14,000,deg2$ of the sky, measuring the shapes of billions of galaxies and opening a meaningful window for detecting galaxy clusters uniquely through their WL signal. We present the results of nine galaxy cluster detection algorithms in a blind challenge, using 1200,deg^2 of synthetic Euclid-like WL observations from the DEMNUni-Cov simulations. The performance of these methods was assessed by matching their detections to known synthetic clusters with signal-to-noise ratios greater than 2, satisfying the selection cut of $łogten( ) > 13.3 + 1.049,z + 2 , and by adopting two different matching procedures. The purpose of the challenge is to identify and improve strategies for galaxy cluster detection via WL in preparation of the upcoming Euclid data releases. To this end, we pre-selected four methods based on their individual performance and complementary nature. Each pre-selected method adopted a distinct approach: AMICO-WL employing an optimal filtering technique, DoG employing Gaussian filtering, O21 relying on aperture-mass filtering, and W234 applying multi-scale wavelet filtering. Taken together, the results of these methods can be merged to enhance the processing of Euclid data. Individually, these algorithms reach approximately 10% completeness for a mean purity of 90%, while their combination leads to roughly a two-fold improvement in overall performance, exceeding 70% completeness for low-redshift, high-mass clusters. When extrapolating the results of this work to Euclid Data Release 1, we expect to detect approximately 2500 galaxy clusters via weak gravitational lensing.

OA

論文OpenAlex·2026/10/23

Searching for strong gravitational lenses using Zernike polynomials.

Strong gravitational lensing is a direct consequence of general relativity. It refers to the bending of light from a distant source by a massive foreground galaxy, known as the lens. The lensed image of the background source, typically a young star-forming galaxy, appears as a ring or arcs around the lens. Such systems provide a powerful probe of the dark matter content of the lens galaxy. However, strong lenses are rare, so finding them requires surveying vast areas of the sky at high resolution. With its sharp imaging and wide field of view, the Euclid space telescope is expected to find more than 100,000 lenses among roughly 1.5 billion galaxies. Euclid's strong lensing team currently searches for them with computationally expensive deep-learning classifiers. In this thesis, we develop a lightweight alternative based on Zernike polynomials, a complete set of complex orthogonal polynomials on the unit disk, indexed by an order p and a repetition q. We show that the Einstein radius of a lens is inversely proportional to the order, p, of the most strongly excited mode. We decompose 6" x 6" cutouts of Euclid strong lenses and non-lenses into Zernike modes with 0 ≤ p ≤ 40 and q ∈{ 0, 1}, and use the moment amplitudes as features for simple machine-learning methods. Among these, a support vector machine (SVM) with a radial basis function kernel achieves the highest area under the ROC curve (AUC), while positive-unlabelled (PU) learning achieves the highest recall. Neural networks trained with a recall-weighted loss consistently outperform these classical methods. We combine SVM, PU learning, EasyEnsemble and neural networks into an ensemble classifier that reaches an AUC of 0.87 and a recall of 0.77 while requiring about 7000 times fewer operations than the classifiers currently used in the Euclid strong lensing discovery engine. Over the full survey, this would substantially reduce computing time, cost and energy consumption. This work is a step towards efficient and sustainable alternatives to the heavy algorithms used in large astronomical surveys.

arXiv

プレプリントarXiv·2026/10/14

Cosmology with strong gravitational lenses

Three of the most pressing open questions in cosmology -- the nature of dark energy and dark matter, and the growing tension in the value of the Hubble constant H$_0$ -- call for cosmological probes that are independent of, and complementary to, traditional methods. Strong gravitational lensing offers exactly that: a purely gravitational probe of the universe's expansion history and matter distribution, sensitive to dark matter's presence regardless of whether it interacts with light. Time-delay lenses and multiplane lenses can measure H$_0$ and the dark energy equation of state directly, while the distortion of lensed images can reveal the abundance and internal structure of dark matter subhalos. After a brief theoretical and historical introduction, I review recent breakthroughs enabled by JWST and by advances in lens modeling and stellar dynamics. Examples include the recent measurement of H$_0$ with 3\% precision in flat $Λ$ cold dark matter cosmology, and a tentative detection of dark matter self-interaction. Strong lensing is entering a pivotal era: wide-field surveys with Euclid, Rubin, and Roman, and radio surveys with the Square Kilometer Array, are poised to increase the number of known strong lenses by orders of magnitude, positioning strong lensing to play a central role in answering these open questions in the decade ahead.

arXiv

プレプリントarXiv·2026/10/14

Strong gravitational lensing with Euclid

Euclid data is going to lead to the discovery of approximately 10^5 new strong gravitational lenses, thereby increasing the number of known lenses by a factor of 30. Such an impressive jump has the potential to revolutionise the field of strong lensing, by covering an ever-increasing range in the parameter space occupied by the lenses and lensed sources, and by uncovering rare and precious strong lens systems. The first quick data release of Euclid has already revealed hundreds of lenses, giving us a taste of what the final Euclid strong lens sample might look like. These lenses include a variety of objects acting as deflectors, from isolated galaxies to clusters, from early-type galaxies to edge-on disks. As many as four double-source plane lenses, in which one foreground object lenses two galaxies at two different redshifts, have already been discovered. As more data are acquired, it might become possible to detect the strong lensing signature of dwarf galaxy satellites, and to find lenses with an unusually large number of images. In this paper, we try to anticipate the kind of discoveries that these data will bring along.

OA

プレプリントOpenAlex·2026/10/20

The Chronos Equation: Computational Unification of the Standard Model, the Emergent Dark Sector, and Quantum Gravity in 53 Qubits, Out-of-Time Retrodiction (2020-2026), and 2027 Blind Forecasts

Every revolution in fundamental physics has been crystallized into a single mathematical statement capable of uniting previously disparate realms of nature. Across five foundational monographs encompassing 8,388 net empirical and quantum-computational degrees of freedom, we established the non-perturbative solutions to the five grand challenges of contemporary physics using the proprietary Chronos-Quantum Engine (2^28 = 268,435,456 complex states in 2.147 GB VRAM coupled to 53-qubit positive Grassmannian submanifolds Gr+(4,53) in 3.58 GB VRAM). Here we distill those 8,388 degrees of freedom into a single operator equation acting on the universal statevector: The Chronos Equation. To subject this unification to a strict out-of-sample test across time, we freeze all invariants of the Chronos Equation at the epistemic cutoff of January 1, 2020. We confront its zero-parameter retrodictions against 20 flagship discoveries unlocked between 2021 and 2026, including the JWST early massive galaxies (z=14.32), DESI DR1/DR2 dynamical dark energy, and the CMS W-boson mass, achieving a global goodness-of-fit of χ2/NDF = 0.1786 (refuting the 2020 standard consensus at p = 3.1 x 10^-41). Finally, we seal our zero-parameter prospective forecasts for the two flagship cosmological releases of 2027: ESA Euclid DR1 (predicting a 3.81x weak-lensing excess over ΛCDM at R=3.0 Mpc) and JWST Cycle 4-5 (predicting 51,296x more stellar mass than ΛCDM at z=20.0), establishing a strict Popperian falsification protocol. This milestone marks the transition from passive observational cosmology to the era of Metric Engineering.

OA

論文OpenAlex·2026/10/12

Dynamic-Strategy Cosmology: Frozen Causal-Coherence Test Matrix, Version 1.0 - 12 October 2026

This document freezes the Dynamic-Strategy Cosmology (DSC) Causal-Coherence Test Matrix, Version 1.0, as of 12 October 2026. It records twelve pre-specified empirical tests linking the DSC exhaustion-repulsion mechanism to cosmic expansion, causal chronology, effective equation-of-state evolution, structure growth, CMB-growth coherence, gravitational response, nonlinear structure, second-order mode coupling, weak lensing, high-redshift continuity, predictive freezing, and cross-observable causal coherence. The document is a pre-data audit rather than a new fit. Future observations may change only the status assigned to each test; the frozen prediction content is not to be retrospectively altered in response to later datasets unless a separately dated theoretical revision is explicitly issued. The purpose of the deposit is to provide a permanent, timestamped benchmark against which forthcoming DESI, DES, Euclid, CMB, lensing, clustering, and other late-time cosmological observations can be assessed.