Critical Evaluation of Studies Alleging Evidence for Technosignatures in the POSS1-E Photographic Plates

TL;DR

This paper critically evaluates recent claims of technosignatures in POSS1-E SPFs by reanalyzing three public SPF datasets and highlighting inconsistencies in definitions and a lack of validation. It shows that when background variations and plate artifacts are properly modeled, there is no demonstrable deficit in Earth's shadow, and correlations with nuclear tests dissipate after normalizing for the true observation window. The analysis attributes many reported alignments and temporal associations to artifact-related patterns and scheduling biases rather than real transients. Overall, the work argues for rigorous data validation and background characterization before asserting optical transients or technosignatures in archival plate data, guiding future, more robust approaches to technosignature searches near Earth.

Abstract

Recent studies by B. Villarroel and colleagues have assembled and analyzed datasets of unidentified features measured from digital scans of photographic plates captured by the first-epoch Palomar Observatory Sky Survey (POSS1) in the pre-Sputnik era. These studies have called attention to (i) a purported deficit of features within Earth's shadow; (ii) the sporadic presence of linear clusters; and (iii) a positive correlation between the timing of feature observations and nuclear tests as well as Unidentified Aerial Phenomena (UAP) sighting reports. These observations were cited as evidence that some fraction of the unidentified features represent glinting artificial objects near Earth. We have examined these claims using two related, previously published datasets. When analyzing the most vetted of these, we do not observe the reported deficit in the terrestrial shadow. We determine that a third of the features in the reported linear clusters were not confidently distinguished from catalog stars. We find that the reported correlation between the timing of feature observations and nuclear tests becomes insignificant after properly normalizing by the number of observation days, and is almost completely determined by the observation schedule of the Palomar telescope. We uncover important inconsistencies in the definitions of the datasets used in these studies, as well as the use of unvalidated datasets containing catalog stars, scan artifacts, and plate defects. It has not been shown that any of the features in these datasets represent optical transients. We examine the spatial distribution of the plate-derived features, finding an overall gradual increase in number density toward the corners and edges of plates, as well as examples of (i) empty north-south strips that span multiple plates; (ii) clusters and voids having geometric shapes; and (iii) amorphous clusters.

Figures (12)

• Figure 1: Diagram illustrating the relative sizes and overlap relationships of the SPF datasets defined in Table \ref{['tab_data_sets']}. The dashed line and "?" here represent our uncertainty about the degree of overlap between $V$ (the main focus of calculations in villarroel2025aligned and bruehl2025transients) and $R$ (the vetted "remainder" of unidentified objects, defined in solano2022discovering). The shaded subsets $R$ and $W$ are publicly available.
• Figure 2: Examples of Selected POSS1-E Features (SPFs) in $R$ ($N=5,399$), the most vetted subset of $S$ ($N=298,165$) published by solano2022discovering. The red crosses at the center are $\sim 10^{\prime\prime}$ in diameter. We have identified these features as follows: (i) clear artifacts or defects that do not resemble objects visible in a Pan-STARRS image of the same field (A (object 1092), B (object 1179), C (object 1223), D (object 1248)); and (ii) clear examples of an object that was incorrectly identified as having vanished (object 1043 in E vs. F, and object 1051 in G vs. H, where E and G are POSS1-E images and F and H are Pan-STARRS images), probably on account of displacement from high proper motion. Based on 540 objects examined, cases of this sort comprise 4--5% of $R$ ($N = 5,399$). The images are available online from http://svocats.cab.inta-csic.es/vanish-possi/.
• Figure 3: Cumulative distribution function of SPF counts as a function of the total fraction of plates, ranked in order of decreasing counts from left to right, for $W$, $R$, and $M$. In the case of $W$, roughly 20% of the most crowded plates contain over 60% of all SPFs. $M$ is more uniform in terms of how SPFs are distributed across plates; this is partly because all SPFs in $M$ are likely celestial objects, and because the Galactic plane was occluded when this dataset was sampled. The curve still represents a significant departure from a uniform-random distribution (dotted line), possibly associated with variations in astronomical viewing conditions. The discussions of spatial variability in Sections \ref{['sec_boundary_dist']} and \ref{['sec_templating']} suggest there may be multiple factors contributing to the spatial variation in SPF counts shown in $R$ and $W$, arising from (i) how plates are manufactured, stored, scanned, and handled, or (ii) how datasets were constructed in solano2022discovering.
• Figure 4: Scatter plots of SPFs from $W$ on nine plates that exhibit distinctive patterns. Red dots signify SPFs that could not be unambiguously assigned to the plate in question because of overlap with the neighboring plate's field of view (and hence confined to the edges). These patterns are not visible in the dataset $M$ of SPFs that appear in both E and O plates (i.e., likely celestial objects), suggesting that they are unrelated to nonuniform sensitivity of the instrumentation or photographic medium. The geometric patterns and relationship to plate boundaries strongly suggest (i) a physical process that has templated the spatial distribution of SPFs, such as a surface that has come into contact with the plate, or a region that has been preferentially exposed to processes that tend to degrade the medium over time; or (ii) a spatial filter applied when processing the data. We have plotted SPFs from $W$ because (i) it is publicly accessible; (ii) it is large enough for these patterns to be visible, and (iii) because it is a dense, uniform-random sample and majority subset of $S$, the parent set of set $V$ analyzed by bruehl2025transients and villarroel2025aligned. Each plate is labeled with the plate ID, the number of SPFs on the plate, and the value of the Evans-Clark ratio $\rho$, which is smallest for the most overdispersed (clustered) distributions.
• Figure 5: Histograms of the Evans-Clark ratio $\rho$ calculated for each plate, for SPFs in sets $M$ and $W$. As expected for a uniform-random distribution of points on a finite domain, $\rho$ is typically slightly above 1 for set $M$, comprising SPFs of likely celestial origin because they appear in both the POSS1-E (red band) and POSS1-O plates (blue band). The distribution of SPFs in $W$ is dominantly overdispersed (clustered), with $\rho < 1$ for most plates. See Figure \ref{['fig_unusual_patterns']} for scatter plots of SPFs on individual plates with significant overdispersion, labeled with the estimated $\rho$.