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The astronomical magnitude convention is $m_1-m_2=-2.5{\log }_{10}(F_1/F_2)$, with both fluxes measured through the same photometric passband. A five-unit magnitude difference therefore corresponds toThe brighter endpoint has one hundred times the visual flux of the fainter endpoint. Absolute fluxes require a magnitude zero point, which is not given.

Phase folding of a light curve maps timestamps onto a trial cycle of duration $P>0$. Given a reference time $t_0$, define the phase in cycles bywhere $\mathrm{frac}(x)=x-\lfloor x\rfloor$ is the fractional part, using the floor function also for negative $x$. Plot brightness against ${\varphi }_i$ rather than $t_i$; measurements separated by an integer multiple of $P$ occupy the same phase. For a periodic function $F(t+P)=F(t)$, this reveals the shared shape of many cycles. Folding changes coordinates; it neither averages samples nor chooses the correct $P$ by itself. Welsh et al.'s folded Kepler plot separates the exoplanet transit and orbital brightness modulation. ^[ref].

The second figure uses a completely synthetic trapezoidal dip: $P=3$ days, $t_0=1$ day, and the same $1\%$ depth and four-hour duration as the first figure. Different colours identify four successive cycles. Correct folding superimposes the dips; a wrong trial orbital period spreads them out. If $P^{\prime }=P+ϵ$, the centre of the $n$th repeated event shifts by approximately $-nϵ/P$ cycles when folded on $P^{\prime }$, for $|ϵ|\ll P$. With $P^{\prime }=3.03$ days, the fourth plotted event is displaced by $-3(0.03)/3.03\simeq -0.0297$ cycles. Transit-timing variations can also smear a constant-period fold, so retain the original timestamps and inspect individual events.

One may combine nearby phases with a weighted mean, but the uncertainty reduction requires assumptions. For $N$ independent measurements with common standard deviation $\sigma$ and effectively the same expected brightness within the bin, their arithmetic mean has standard deviation $\sigma /\sqrt{N}$. Thus sixteen independent $0.0006$-precision samples give $0.00015$ precision on that phase-bin mean. Shared calibration errors, changing starspots, and bins wide enough to mix ingress with out-of-transit brightness violate these assumptions. A folded plot can conceal changes between cycles. Gaussian process models can represent correlated variability and interpolate irregular samples, but their predictions and uncertainties depend on their assumed covariance function.

The bottom panels show the same model as relative brightness $f=F/F_0$ and as magnitude difference in one fixed photometric passband with a fixed magnitude zero point:A dip to $f=0.99$ gives $\Delta m\simeq +0.010912$ magnitudes: fainter means a larger apparent magnitude. The figure places larger magnitude differences lower on the page so the two dip shapes are easy to compare; reversing that plotting convention does not change the formula. For $f=1-\delta$ and small $\delta$, expansion of the logarithm gives $\Delta m\simeq (2.5/\ln 10)\delta \simeq 1.085736\delta$. The exact transform is nonlinear: transforming an exposure's mean brightness is generally different from averaging its instantaneous apparent magnitudes. The ordinary logarithm cannot be applied to a nonpositive background-subtracted measurement; keep such measurements and their uncertainties in brightness units for an appropriate statistical model.

A photometric system specifies photometric passbands and magnitude zero points, allowing calibrated brightness comparisons.

Spectral flux density is radiant power received per unit area and per unit wavelength or frequency. The two conventions satisfy $F_{\lambda }d\lambda =-F_{\nu }d\nu$ under $\nu =c/\lambda$, hence $F_{\lambda }=(c/{\lambda }^2)F_{\nu }$ when the arguments refer to the same photons. Integrating over a photometric passband gives its measured flux.

The stretch method rescales the light curve's time axis by $s(1+z)$ and corrects peak apparent magnitude by $\alpha (s-1)$, fitting $\alpha$ jointly with cosmology.^[ref]

Here is a deliberately stipulated local model that exposes the signs. Let $t_{\mathrm{obs}}$ be observer time in days, $t_{\max }$ the observed peak time and $T(u)$ a dimensionless template with $T(0)=1$. In a single photometric passband, writeHere $u$ is rest-frame time in days; the template's argument carries those units. For illustration, assign the intrinsic relation $M_B(s)=M_{B,0}-\alpha (s-1)$ with $\alpha >0$: broader events are intrinsically brighter. Define the sign of the K correction by $m_{\mathrm{obs}}=M_B(s)+\mu +A_B+K$, where $A_B$ is interstellar extinction in magnitudes. ThenRemoving attenuation makes the magnitude smaller; standardizing a broad, intrinsically bright event makes it larger. The fitted cosmological time dilation must be removed before comparing intrinsic durations. This schematic factorization explains the bookkeeping; an actual multicolour fit must also model changing intrinsic colours and correlated uncertainties.

For two equally standardized sources, cancellation of their common absolute magnitude gives an especially clean result:A stipulated residual of $+0.20$ mag therefore means a distance ratio $10^{0.04}=1.09648$ and a radiative flux ratio $10^{-0.08}=0.83176$ relative to the comparison prediction, provided luminosity and attenuation have been correctly standardized. This is a conversion of a hypothetical residual, not a measured survey value.

The High-Z Supernova Search Team analysis fitted multicolour light curves and interstellar extinction, and compared a second decline-rate method. Similar local and distant spectroscopy supported, but did not establish, population stability. Nearly colourless attenuation remained a qualified alternative.^[ref]

The Supernova Cosmology Project compared low- and high-redshift colours, removed red outliers in its primary fit, and tested Malmquist bias with artificial-source recovery.^[ref]

The inference can be organized as a chain of independently testable failure modes. A magnitude zero point offset between nearby and distant observations imitates a distance modulus offset; a common offset instead changes the intercept. An erroneous photometric passband response changes a K correction in a redshift-dependent way because different emitted wavelengths cross the detector band. Residual host-galaxy light changes the recovered radiative flux. Color excess constrains wavelength-dependent interstellar extinction only after intrinsic colour is modeled; grey attenuation is not bounded by colour alone. Changes in stellar population or metallicity could shift standardized absolute magnitude without large changes in the chosen shape parameter. These are logical degeneracies, so increasing the sample size alone cannot remove them.

A useful control strategy therefore compares subsets with different host environments, fits consistent rest-frame photometric passbands, and checks artificial-source recovery through the same image processing and selection. A Malmquist bias tends to select brighter detectable sources, but the relative bias between the nearby and distant samples is what matters. Peculiar velocity mainly perturbs the nearby redshift anchor; weak gravitational lensing changes individual brightnesses and the selection distribution. Neither can be replaced by an arbitrary extra scatter term when its mean or selection dependence is uncertain.