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REVIEW 4 major objections 6 minor 56 references

All four gamma-ray-active blazars show millimeter-wave polarization swings; none of the four quiet ones do, and a turbulent-cell model cannot reproduce the swings.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-08-04 00:45 UTC pith:UXWS4JRQ

load-bearing objection Solid first cut at mm-wave EVPA swings from SPT-3G; the 4/4 vs 0/4 dichotomy is intriguing, but the swing sample is cadence- and prior-dependent, and one equation isn't reproducible. the 4 major comments →

arxiv 2608.00302 v1 pith:UXWS4JRQ submitted 2026-07-31 astro-ph.HE astro-ph.GA

Polarization Angle Swings in Blazars Detected in the Millimeter-wave with the South Pole Telescope

A. Simpson , E. Anderes , A. J. Anderson , B. Ansarinejad , M. Archipley , L. Balkenhol , D. R. Barron , P. S. Barry
show 88 more authors
K. Benabed A. N. Bender B. A. Benson F. Bianchini L. E. Bleem S. Bocquet F. R. Bouchet E. Camphuis M. G. Campitiello J. E. Carlstrom J. Carron C. L. Chang P. M. Chichura A. Chokshi T.-L. Chou A. Coerver T. M. Crawford C. Daley T. de Haan K. R. Dibert M. A. Dobbs M. Doohan D. Dutcher C. Feng K. R. Ferguson N. C. Ferree K. Fichman A. Foster S. Galli A. E. Gambrel A. K. Gao F. Ge F. Guidi S. Guns N. W. Halverson A. D. Hincks E. Hivon G. P. Holder W. L. Holzapfel J. C. Hood A. Hryciuk N. Huang E. J\"arvel\"a T. Jhaveri F. K\'eruzor\'e A. R. Khalife L. Knox K. Kornoelje C.-L. Kuo K. Levy Y. Li A. E. Lowitz C. Lu G. P. Lynch X. Ma T. J. Maccarone G. Madejski A. S. Maniyar E. S. Martsen F. Menanteau M. Millea J. Montgomery Y. Nakato T. Natoli A. Ouellette Z. Pan K. A. Phadke A. W. Pollak K. Prabhu W. Quan M. Rahimi A. Rahlin C. L. Reichardt M. Rouble J. E. Ruhl A. C. Silva Oliveira J. A. Sobrin A. A. Stark C. Tandoi C. Trendafilova J. D. Vieira A. G. Vieregg A. Vitrier Y. Wan N. Whitehorn W. L. K. Wu M. R. Young J. A. Zebrowski
This is my paper
classification astro-ph.HE astro-ph.GA
keywords blazarsactive galactic nucleimillimeter astronomypolarimetryradio jetsEVPA swingsgamma-ray flaresstochastic models
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper makes the first systematic search for EVPA swings — large, sustained rotations of the polarization direction — in the millimeter-wave emission of blazars, using five years of nearly daily South Pole Telescope observations at 95 and 150 GHz. It argues that these swings are real at millimeter wavelengths and connected to high-energy activity: all four blazars with continuous gamma-ray detections show swings, none of the four without them do, a split with only a 0.78% chance of occurring by coincidence. It further argues that the simplest stochastic mechanism — a jet of many independent turbulent cells with randomly reoriented polarization — cannot account for the observed swing population: simulations calibrated to each source's polarization degree produce significantly fewer, longer, slower swings than observed. If correct, the result opens millimeter-wave polarization as a slower but comparable window onto the same jet physics seen at optical wavelengths, and it indicts the simplest turbulent-cell picture in favor of more structured or deterministic explanations. The paper also finds that although several individual swings coincide with gamma-ray flares at low chance probability, the full ensemble of swing-flare time lags is consistent with random timing.

Core claim

Using five years of SPT-3G observations of eight bright blazars, the authors identify 14 EVPA swings at 95 and 150 GHz — the first systematic detection of such swings in the millimeter band. All 14 swings occur in the four blazars with continuous gamma-ray detections; none occur in the four without, a separation with 0.78% probability under a no-connection null. The swings are slower and smaller than optical swings (mean amplitude 124°, mean rate 5.6° per day), consistent with a more slowly evolving millimeter emission region downstream in the jet. Random-walk simulations of a multi-cell turbulent jet, calibrated to each source's polarization degree and its spread, generate significantly few

What carries the argument

The EVPA swing identifier assumes the true change between consecutive two-day measurements is the minimum 180°-unwrapped angle, then segments the light curve where the sign of the rotation derivative flips significantly or a gap exceeds seven days; a swing is a segment with ≥3 points, ≥2 significant flips, |Δχ|>90°, and >68% probability that all adjacent pairs were unwrapped correctly. The random-walk multi-cell model pictures the jet as many independent cells with random polarization angles, fixing the number of cells from the ratio of theoretical synchrotron polarization (72%) to observed mean polarization and keeping only simulations that reproduce each source's polarization mean and scat

Load-bearing premise

The entire swing sample rests on the assumption that the true change in polarization angle between consecutive two-day observations is the smallest 180°-unwrapped difference; if real rotations approach 90° between samples, swings are shortened, missed, or split, and the reported counts and distributions shrink with them.

What would settle it

Re-observe the same eight sources with a denser cadence (hourly to one-day sampling at comparable sensitivity). If the minimum-rotation assumption is wrong, the denser data will show inter-sample EVPA changes near 90° that the two-day light curves mis-resolve, and the swing counts will change; if it holds, the same 14 swings reappear with unchanged amplitudes and the gamma-ray split persists. A second decisive check is longer monitoring of the four gamma-ray-quiet blazars: one clear |Δχ|>90° swing in any of them would break the paper's central split.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Millimeter-wave polarization places the swing phenomenon in the jet's slower, downstream emission region, so mm-wave monitors can track the same gamma-ray-linked physics at a less demanding cadence than optical polarimetry.
  • The two-day cadence caps the detectable rotation rate near 90° per sample, so the 14 detected swings are a lower bound on the true population; faster swings would have been truncated or missed entirely.
  • The failure of the multi-cell random walk shifts the burden toward deterministic or more structured mechanisms — ordered-field reorientation, multiple emission components, or jet geometry — for explaining EVPA swings.
  • The PD–rotation-rate anti-correlation, previously seen at optical wavelengths, holds at millimeter wavelengths: the most variable source has the lowest mean polarization and the calmest sources have the highest.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The comparison that rules out the turbulent model is tuned to polarization degree alone; a richer stochastic picture — correlated cells, a persistent ordered component, or time-varying cell counts — might survive, so the paper's negative result specifically indicts the simplest random walk, not turbulence in general.
  • If the same physical events drive optical and millimeter swings, co-sampled optical-plus-millimeter polarization of these same sources should show the millimeter swing lagging and more gradual — a pairing prediction the paper's slower-downstream-region picture implies but does not test.
  • The 0.78% swing–gamma-ray split rests on four sources on each side; extending the same analysis to more of the remaining bright sources, or to future wide-area millimeter surveys, is the direct way to see whether the split holds.
  • A denser-cadence re-observation of the same sources would test the minimum-rotation prior directly: hourly or one-day sampling would reveal whether inter-sample rotations near 90° are being mis-resolved and whether the true swing population is larger than 14.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. This paper reports the first systematic search for electric vector position angle (EVPA) swings in millimeter-wave blazar polarization, using five years of SPT-3G observations at 95 and 150 GHz toward the ~1500 deg^2 Main field. Eight of 168 bright sources pass a polarization signal-to-noise selection, and four of these have continuous Fermi-LAT gamma-ray detections. The authors identify 14 EVPA swings, all in the gamma-ray subsample, and compare their number, amplitude, duration, and rotation rate with a multi-cell random-walk model; the model underproduces swings and yields different amplitude/duration/rate distributions. They also analyze week-timescale rotation-rate variability and gamma-ray flare associations, finding individual low-probability associations but no ensemble correlation. The paper carefully applies bias-corrected polarization degree, non-Gaussian EVPA errors, leakage correction, and a probability-of-correct-measurement filter, but the central swing sample and the random-walk comparison rest on assumptions that are not fully validated in the present text.

Significance. If the results hold, this would be the first systematic detection of millimeter-wave EVPA swings, extending the optical/γ-ray connection to longer wavelengths and providing a direct constraint on stochastic jet models. The analysis has notable strengths: bias-corrected polarization degree, non-Gaussian EVPA error propagation, explicit I-to-Q/U leakage correction, a quantitative probability-of-correct-measurement gate, and a simulation acceptance threshold. These are appropriate and carefully executed. However, the central claims—the 4/4 vs 0/4 gamma-ray dichotomy and the failure of the random-walk model—depend on the swing identification pipeline, whose completeness and false-positive rate are not characterized with recovery simulations, and one key formula contains an undefined quantity. These issues are fixable within the manuscript's scope and do not invalidate the overall approach, but they currently leave the main conclusions more fragile than necessary.

major comments (4)
  1. [Sec. 3.4, Eq. (11)] The term m(n) in Eq. (11) is never defined. The probability of correct measurement Pswing, computed from Eq. (13), is used as a gate for swing selection in Sec. 3.5, so the swing sample cannot be reproduced from the text as written. Please define m(n) (or rewrite the summation in Eq. 10-11) and specify the domains of x, n, and the summation limits.
  2. [Sec. 3.3–3.5 and Sec. 4.1] The 14-swings sample and the resulting 4/4 vs 0/4 dichotomy rest on the minimum-distance 180° unwrapping assumption. The authors acknowledge in Sec. 4.1 that the maximum detectable rotation rate is limited by this assumption, and Sec. 2.3 shows that a 4-day cadence fails to recover a swing seen by SPT at 2-day cadence. However, no recovery test on simulated light curves with known true EVPA evolution is provided. Please add such simulations to quantify the completeness and false-positive rate of the swing identifier as a function of cadence, swing amplitude, and rotation rate. Without this, it is unclear whether the claimed dichotomy and the random-walk comparison are driven by selection effects.
  3. [Sec. 4.2, Fig. 3] The text says the observed number of EVPA swings per blazar (combining 95 and 150 GHz) is compared to the number per simulated light curve (a single band). If this is the case, the comparison is not apple-to-apple: a blazar with two observed bands should be compared to the sum of two independently simulated light curves. Please clarify the construction of the simulated distribution. If the comparison is truly per-blazar vs per-light-curve, the reported A-D p-value <0.001 for the swing count is not interpretable as evidence against the stochastic model.
  4. [Sec. 3.4] The log-normal parameters (μ, σ) are fit to the observed |Δχ| distributions of the same eight sources that are later used to identify swings. This makes Pswing a data-driven probability rather than an independent model. Please state whether the fit excludes the identified swing segments, and test the sensitivity of the swing sample to the choice of log-normal model or to small changes in the fitted parameters.
minor comments (6)
  1. [Sec. 3.4, Eqs. (10)–(12)] Please specify the units of x in the log-normal model (degrees?) and interpret the fitted values (μ, σ) = (1.98, 0.99), etc. The limit notation in Eq. (10) is also unusual; consider a finite sum or a clearer definition.
  2. [Sec. 4.1] The reported probability of 0.78% for all 14 swings occurring exclusively in gamma-ray sources needs derivation. Under a simple binomial null with 14 independent assignments to 4 gamma-ray and 4 non-gamma-ray sources, P = 0.5^14 ≈ 0.006%, so the quoted value must come from a different null hypothesis. Please explain the calculation or correct the number.
  3. [Sec. 3.2] The sentence 'All sources with ⟨SNR_Π,95⟩<3 or ⟨SNR_Π,150⟩<3 are cut' is ambiguous: it could mean that a source is cut if either band fails, or that each band is treated separately. Please clarify the selection criterion.
  4. [Sec. 2.3] The ACT data are described as obtained through private communication with reduction details in a forthcoming paper. For reproducibility, please provide more details in an appendix or state that the data will be publicly released.
  5. [Sec. 3.6] The acceptance threshold of 20% for simulated PD mean and variance is arbitrary. The fraction of accepted simulations (47.2%) is quoted, but please also report the sensitivity of the main conclusions to this threshold.
  6. [Sec. 4.2] The Anderson-Darling tests for amplitude, duration, and rate are computed on 14 observed events against a much larger simulation sample. With such a small observed sample, the asymptotic null distribution may be unreliable. Please report the effective sample sizes and consider permutation-based p-values.

Circularity Check

1 steps flagged

Mild circularity in the P_swing calibration; the central gamma-ray and random-walk comparisons retain independent content.

specific steps
  1. self definitional [Sec. 3.3–3.5 (Eqs. 8–13)]
    "we assume the minimum distance between consecutive data points, and χ0 is adjusted in 180° intervals ... χ=χ0−k·180° (8) where k=round((χ0,i−χ_{i−1})/180) (9). ... To assess the probability that the change between two adjacent EVPA data points is measured correctly ... This model is then fit to the distribution of |∆χi,j| ... The probability that any given ∆χi,j is measured correctly is: P(∆χi,j,∆t)=LN(...)/LN_model(...). ... an EVPA swing is defined as any segment with Pswing >68%."

    Eqs. 8–9 force every adjacent pair onto the minimum-distance branch before |Δχ| is measured. Sec. 3.4 fits its log-normal (μ,σ) to those already-unwrapped |Δχi,j| values, then feeds them back through Eq. 13 to define P_swing, which Sec. 3.5 thresholds at 68% to declare swings. Thus the 'probability of correct measurement' is conditioned on the very minimum-distance prior it is meant to validate: rotations approaching 90°/bin are pre-emptively wrapped to <90°, making the probability computation self-consistent rather than falsifiable. The swing list, amplitudes, durations, and rates—and hence the gamma-ray dichotomy and random-walk comparison built on that list—inherit this prior. The circularity is mild because the (μ,σ) fit is not explicitly fit to the swing indicator itself, and the gamm

full rationale

The paper's central claims are not built on a self-citation chain or on a fitted parameter being renamed as a prediction in the strongest sense. The random-walk simulations calibrate Ncells and Nvar to observed PD mean and variance (Eqs. 15–16) but then compare simulated swing counts, amplitudes, durations, and rates—quantities not used in the calibration—so that comparison is not forced by construction. The gamma-ray-active versus inactive dichotomy is based on an external Fermi-LAT selection and on the swing counts, not on a parameter fitted to those counts. The ACT cross-check provides independent, if qualitative, support for the SPT measurements. The one genuine circular element is the Sec. 3.4 probability-of-correct-measurement computation: the log-normal model is fit to the same minimum-distance-unwrapped EVPA data that it is then used to score, and the resulting P_swing threshold determines which segments become the reported 14 swings. This makes the swing sample partly self-consistent with the unwrapping prior, and the paper itself concedes that the prior sets the maximum detectable rotation rate (Sec. 4.1). Because this affects the swing sample that underlies the abstract's dichotomy and the random-walk rejection, the overall score is a mild 2 rather than 0, but the central astrophysical associations and simulation comparison retain substantial independent content.

Axiom & Free-Parameter Ledger

6 free parameters · 6 axioms · 0 invented entities

The central claims rest on several fitted calibration parameters (leakage coefficients, random-walk cell counts, log-normal variability parameters), hand-chosen swing thresholds, and domain assumptions about the 180-degree unwrapping and the multi-cell jet model. No new physical entities are introduced. The most consequential fitted elements are the leakage coefficients, which set the EVPA zero-point, and the (mu,sigma) variability parameters, which calibrate the swing identifier to the same data being searched.

free parameters (6)
  • EVPA swing definition thresholds = P_swing>68%, N>=3, Nsig>=2, |Delta_chi|>90 deg
    Chosen by hand following Blinov et al. (2015); affects which segments count as swings and therefore the central swing count.
  • log-normal variability parameters (mu,sigma) per Delta_t bin = (1.98,0.99), (2.05,1.04), (2.16,1.04) for 1.5, 4.5, 7.5-day bins
    Fit to the observed |Delta_chi| distributions in Sec. 3.4 and used to compute P(Delta_chi) and P_swing; this calibrates the swing identifier to the same data being tested.
  • random walk cell count Ncells per source/band = Ncells=(Pi_exp/<Pi_obs>)^2 (Eq. 15), values not tabulated
    Chosen so simulations reproduce observed mean PD; a fitted parameter, though the swing statistics tested are not used in the fit.
  • random walk cells changed per step Nvar per source/band = Nvar=(sigma(Pi_obs)/<Pi_obs>) Ncells (Eq. 16)
    Chosen to reproduce observed PD variance; fit to data, not to swing properties.
  • I-to-Q/U leakage coefficients = 95 GHz: -0.237%, -0.466% (delta>-56); -0.285%, -0.168% (delta<-56). 150 GHz: -0.285%, -1.34% (delta>-56); -0.128%, -0.65
    Computed by forcing average Q/I and U/I to zero across sources, assuming uniform random EVPA; affects the zero-point of all EVPA measurements.
  • gamma-ray flare profile parameters (Fc, Fp,i, Tr,i, Td,i, Nflare) = per source, AIC-selected; not tabulated
    Exponential rise/decay fit (Eq. 17) with boundary constraints; used to define flare start times for swing-flare time lags.
axioms (6)
  • domain assumption Minimum-distance unwrapping of the 180-degree EVPA ambiguity
    Sec. 3.3, Eq. 8-9: assumes true change between consecutive EVPA points is the smallest one; if true inter-point rotation approaches 90 degrees, swing identification and P_swing are biased.
  • domain assumption Uniform random EVPA across sources for leakage correction
    Sec. 2.1: average Q/I and U/I set to zero under the assumption that source EVPAs are uniformly distributed; a violation shifts EVPA zero-points.
  • domain assumption Selected sources with <SNR_Pi>>3 in both bands are blazars
    Sec. 3.2: identification by PKS, Roma-BZCAT, high redshift, and bright mm flux; used to define the Main Sample.
  • domain assumption Multi-cell random-walk model: independent cells with identical PD and uncorrelated angles
    Sec. 3.6: model used for the null test; derived from Smith (2012) and Kiehlmann et al. (2016). If the true jet turbulence has correlations, the null is too simple.
  • domain assumption Synchrotron expected PD Pi_exp=(p+1)/(p+7/3) approximately 72%
    Sec. 3.6, standard synchrotron result from Longair (2011); used to set Ncells.
  • ad hoc to paper EVPA swing and gamma-ray flare definitions are reasonable proxies
    Sec. 3.5 and 3.7: thresholds (P_swing>68%, N>=3, Nsig>=2, |Delta_chi|>90 deg; flare separation >3 days, amplitude <=2x max) are arbitrary; authors acknowledge definitions are 'somewhat arbitrary' in Sec. 5.

pith-pipeline@v1.3.0-alltime-deepseek · 23759 in / 13524 out tokens · 120670 ms · 2026-08-04T00:45:20.058274+00:00 · methodology

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read the original abstract

We present the first systematic search for electric vector position angle (EVPA) swings in the millimeter-wave (mm-wave) emission of blazars, using five years of observations from the South Pole Telescope SPT-3G camera at 95 and 150 GHz, and investigate their connection to gamma-ray flares. Of the 168 bright sources in the ~1500 square degrees SPT-3G Main Field, eight have sufficient polarization signal-to-noise for reliable EVPA measurement, four of which have continuous Fermi LAT gamma-ray detections. We detect EVPA swings in all four gamma-ray-active blazars and in none of the remaining four, consistent with the established connection between EVPA swings and high-energy emission seen at optical wavelengths. The observed swing amplitudes and rotation rates are smaller than those found in optical studies, consistent with mm-wave EVPA variability being slower than at shorter wavelengths. Random walk simulations of the polarization angle using a multi-cell model fail to reproduce both the number, amplitude, and duration of the observed swings, suggesting that this mechanism is insufficient to explain the observed swing population. Analysis of EVPA variability on one-week timescales is consistent with the anti-correlation between polarization degree and EVPA rotation rate previously observed at optical wavelengths. Of the 14 detected swings, eight are within 30 days of a gamma-ray flare. While many individual swing-flare associations are found to have a very low probability of happening by chance, the full ensembles of 95 and 150 GHz swing time lags with respect to gamma-ray flares are found to be consistent with random coincidence.

Figures

Figures reproduced from arXiv: 2608.00302 by A. A. Stark, A. Chokshi, A. Coerver, A. C. Silva Oliveira, A. D. Hincks, A. E. Gambrel, A. E. Lowitz, A. Foster, A. G. Vieregg, A. Hryciuk, A. J. Anderson, A. K. Gao, A. N. Bender, A. Ouellette, A. Rahlin, A. R. Khalife, A. Simpson, A. S. Maniyar, A. Vitrier, A. W. Pollak, B. A. Benson, B. Ansarinejad, C. Daley, C. Feng, C. L. Chang, C.-L. Kuo, C. L. Reichardt, C. Lu, C. Tandoi, C. Trendafilova, D. Dutcher, D. R. Barron, E. Anderes, E. Camphuis, E. Hivon, E. J\"arvel\"a, E. S. Martsen, F. Bianchini, F. Ge, F. Guidi, F. K\'eruzor\'e, F. Menanteau, F. R. Bouchet, G. Madejski, G. P. Holder, G. P. Lynch, J. A. Sobrin, J. A. Zebrowski, J. Carron, J. C. Hood, J. D. Vieira, J. E. Carlstrom, J. E. Ruhl, J. Montgomery, K. A. Phadke, K. Benabed, K. Fichman, K. Kornoelje, K. Levy, K. Prabhu, K. R. Dibert, K. R. Ferguson, L. Balkenhol, L. E. Bleem, L. Knox, M. A. Dobbs, M. Archipley, M. Doohan, M. G. Campitiello, M. Millea, M. Rahimi, M. Rouble, M. R. Young, N. C. Ferree, N. Huang, N. W. Halverson, N. Whitehorn, P. M. Chichura, P. S. Barry, S. Bocquet, S. Galli, S. Guns, T. de Haan, T. Jhaveri, T. J. Maccarone, T.-L. Chou, T. M. Crawford, T. Natoli, W. L. Holzapfel, W. L. K. Wu, W. Quan, X. Ma, Y. Li, Y. Nakato, Y. Wan, Z. Pan.

Figure 1
Figure 1. Figure 1: Six-month light curves of SPT-S J021045-5101.0 from SPT data binned in two-day intervals (left) and ACT data with typical separation of four days during this time interval (right). In each panel, from top to bottom, the rows are as follows: (1) Stokes I flux density in Jy for the 95 (red circle), 150 (blue square), and 220 (orange diamond) GHz frequency bands, (2) PD (Π), (3) adjusted EVPA (χ) and identifi… view at source ↗
Figure 2
Figure 2. Figure 2: Distributions of Main Sample EVPA swing amplitudes (left), durations (middle), and rates (right), in the 95 GHz (red), 150 GHz (blue), and combined 95 and 150 GHz random walk simulations (hatched black). 0 1 2 3 4 5 6 7 8 Nswing per blazar 0.0 0.2 0.4 0.6 0.8 Fraction of Total 95 & 150 GHz Main Sample 95 & 150 GHz Random walk simulations [PITH_FULL_IMAGE:figures/full_fig_p011_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Distribution of the number of EVPA swings ob￾served (in both 95 and 150 GHz) per blazar in the Main Sample (black) and in the random walk simulations (hatched black). The random walk simulations are unable to replicate the distribution of EVPA amplitudes, durations, and rota￾tion rate, and the number of EVPA swings produced by each simulation is significantly lower (A-D p-value < 0.001) than the sources in… view at source ↗
Figure 4
Figure 4. Figure 4: CDFs of the EVPA rotation rates for the eight blazars in the Main Sample at 95 GHz (left) and 150 GHz (right), computed from pairs with time differences of 4 < ∆ti,j < 10 days on ∼7-day binned light curves. A distribution further to the left indicates lower variability while a distribution further to the right indicates higher variability. SPT-S J205616-4714.8 (dark red) is a clear outlier, with its CDF si… view at source ↗
Figure 5
Figure 5. Figure 5: Distribution of time lags between EVPA swings and gamma-ray flares (left) and relative height of associated gamma-ray flares (right) for EVPA swings with |τobs| < 30 days for 95 GHz (red), 150 GHz (blue), 95 GHz simulations (hatched red), and 150 GHz simulations (hatched blue). Within this plot the dotted lines mark the bin edges of the histogram, all bins within these lines represent the same bin for the … view at source ↗
Figure 6
Figure 6. Figure 6: CDF of the probability of accidental association between gamma-ray flares and all EVPA swings in 95 GHz (solid, red), 150 GHz (solid, blue), and the simulated random EVPA swings (dashed, gray). While some EVPA swings in￾dividually have low probability of coincidental association, the time lag distributions of 95 and 150 GHz EVPA swing associated with gamma-ray flares are not significantly dif￾ferent from t… view at source ↗
Figure 7
Figure 7. Figure 7: Five-year light curves for the gamma-ray subsample of blazars. In each panel, from top to bottom, the rows are as follows: (1) Flux density in mJy for the 95 (red circle), 150 (blue square), and 220 (orange diamond) GHz frequency bands, (2) PD (Π), (3) adjusted EVPA (χ), (4) Fermi gamma-ray 3σ detection flux (black), upper limits (red triangle), and flare fit (blue), identified swings in the 95 (red highli… view at source ↗
Figure 7
Figure 7. Figure 7: continued. 500 1000 1500 2000 I [mJy] 95 GHz 150 GHz 220 GHz 0 2 4 6 8 [ % ] 100 50 0 50 [ ° ] 150 GHz swing 58700 58900 59100 59300 59500 59700 59900 60100 MJD [days] 0.0 0.2 0.4 F [ p h 1 0 6 c m 2 s ] Flare Fit Fermi Upper Limit Fermi Detection SPT-S J030956-6058.6 | 4FGL J0309.9-6058 | PMN J0309-6058 [PITH_FULL_IMAGE:figures/full_fig_p018_7.png] view at source ↗
Figure 7
Figure 7. Figure 7: continued. 500 1000 1500 2000 I [mJy] 95 GHz 150 GHz 220 GHz 0 2 4 6 8 [ % ] 58700 58900 59100 59300 59500 59700 59900 60100 MJD [days] 50 0 [ ° ] SPT-S J232918-4730.3 | PMN J2329-4730 [PITH_FULL_IMAGE:figures/full_fig_p019_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Five-year light curves for the non-gamma-ray subsample of blazars. In each plot, from top to bottom, the rows are as follows: (1) Flux density in mJy for the 95 (red circle), 150 (blue square), and 220 (orange diamond) GHz frequency bands, (2) PD (Π), (3) adjusted EVPA (χ), identified swings in the 95 (red highlight) and 150 GHz bands (blue highlight) [PITH_FULL_IMAGE:figures/full_fig_p019_8.png] view at source ↗
Figure 8
Figure 8. Figure 8: continued. 500 1000 1500 I [mJy] 95 GHz 150 GHz 220 GHz 0 5 10 15 [ % ] 58700 58900 59100 59300 59500 59700 59900 60100 MJD [days] 100 75 50 25 [ ° ] SPT-S J025329-5441.8 | 4FGL J0253.2-5441 | PMN J0253-5441 [PITH_FULL_IMAGE:figures/full_fig_p020_8.png] view at source ↗
Figure 8
Figure 8. Figure 8: continued [PITH_FULL_IMAGE:figures/full_fig_p021_8.png] view at source ↗

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