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Noise-equivalent power expresses detector noise as an equivalent incident radiant power. In a bandwidth-normalized convention, divide the output amplitude amplitude spectral density by spectral responsivity; the units are $\mathrm{W}\mathrm{H}{\mathrm{z}}^{-1/2}$. It is the incident signal scale giving unit signal-to-noise ratio in a $1\mathrm{Hz}$ noise-equivalent detection bandwidth.^[ref]

For approximately white noise, a bandwidth $B$ gives equivalent rms radiant power $\mathrm{NEP}\sqrt{B}$. Thus $10^{-12}\mathrm{W}\mathrm{H}{\mathrm{z}}^{-1/2}$ over $100\mathrm{Hz}$ corresponds to $10^{-11}\mathrm{W}$. State the wavelength, operating conditions and bandwidth: a bandwidth-normalized specification is not itself a universal minimum detectable energy.

A noise-limited dynamic range is the ratio between an upper usable signal level and a lower level defined by a noise criterion, with the observation conditions specified. The lower bound might require a chosen signal-to-noise ratio; the upper bound can be set by amplifier clipping or detector saturation. The ratio depends on bandwidth, integration time, signal convention and acceptance threshold, not only on displayed digits.

For a linear response $V=Kx$ after offset correction, let the output-noise standard deviation be ${\sigma }_V$, the minimum accepted signal be $k{\sigma }_V$, and the output ceiling be $V_{\max }$. ThenThese equations assume the stated noise and ceiling apply throughout the interval. Changing $K$ alone shifts the input interval without changing $D$ under those assumptions. A real amplifier can change noise and bandwidth with gain; the primary specification reports these dependencies separately.^[ref]

For an original voltage-amplitude example, take a usable RMS signal ceiling of $1\mathrm{V}$, RMS zero-mean noise $100\mu \mathrm{V}$, and $k=5$. The lower accepted signal is $0.5\mathrm{mV}$ and $D=2000$. As a voltage-amplitude ratio at fixed impedance, this is $20{\log }_{10}(2000)\approx 66.02\mathrm{dB}$. If the input quantity instead denotes optical power, its power ratio uses $10{\log }_{10}D$; the physical quantity must accompany a decibel statement.

Noise density and total noise are different. For a flat one-sided output power spectral density $S_V$ over a specified effective noise bandwidth $B$, the model gives ${\sigma }_V^2=S_{V}B$. Increasing $B$ fourfold doubles ${\sigma }_V$ and halves $D$ if the ceiling and threshold factor remain fixed. A spectrum with drift or nonwhite components need not obey that scaling.

A noise-limited detection threshold is consequently an operational choice. Five times RMS noise is not a universal minimum detectable signal, nor by itself a statement of false-alarm probability without a noise distribution and observation rule. To characterize a particular instrument, measure its zero-input fluctuations under the actual filtering and loading conditions, then test a stable source near the proposed lower and upper bounds.

Optical sectioning selects signal from a thin depth range of a specimen without physically cutting it. Repeating the measurement at successive focal depths gives a stack of sections from which three-dimensional organization can be reconstructed.

In a scanning confocal microscope, illumination is focused into the specimen and a detection pinhole rejects much of the fluorescence originating away from focus. A thick fluorescent specimen imaged with a wide-open and then a reduced pinhole demonstrates the rejected background; reducing the pinhole also discards useful photons, so section thickness and signal-to-noise ratio must be considered together.^[ref]

Atomic-resolution cryo-electron microscopy became possible by retaining high-frequency structural information through the whole experiment: specimen preparation, electron optics, detection and computation. The decisive advances improved the information obtained per damaging electron and made it possible to align and average many weak images without averaging away structural differences. A short de Broglie wavelength had always been available; the practical limit was preserving and extracting the information carried by those electrons.

First, vitrification preserves hydrated biological material in a thin noncrystalline layer of water. Rapid freezing avoids the strong periodic scattering and disruption associated with ordinary ice crystals, while cryogenic imaging slows some damage processes. The specimen still suffers radiation damage, and a thicker layer adds background and multiple scattering. Reproducible thin ice, clean grids, stable supports and reduced mechanical drift are therefore prerequisites. The specimen must remain structurally intact and occupy enough orientations for a three-dimensional reconstruction. Adsorption at the air–water interface, preferred orientation and variable thickness can defeat an otherwise excellent microscope. Sample optimization should include independent checks of assembly integrity and activity where feasible.

Second, direct electron detection greatly improved the useful signal relative to earlier indirect cameras. In a counting detector, individual electron events can be localized and recorded without treating the deposited signal merely as a continuous intensity. detective quantum efficiency measures how efficiently the detector preserves the input signal-to-noise ratio as a function of spatial frequency. High efficiency matters particularly because the permissible exposure is limited. At excessive event rates, overlapping events cause coincidence losses, so faster readout permits useful counting at practical collection rates. A nominally smaller camera pixel alone cannot replace a detector that preserves high-frequency information.

Fast detectors also turn an exposure into a sequence of movie frames. Aligning those frames corrects specimen drift and beam-induced movement; local correction handles different movements across the imaged area. Uncorrected movement preferentially smears fine features. dose weighting then combines early and later frames according to the information they retain: later exposure can help low-frequency alignment even after fine structural details have been damaged. ^[ref] exemplifies this computational use of detector movies. Frame alignment cannot restore chemistry already destroyed by radiation damage, and extremely noisy individual frames require constrained motion estimates.

Third, stable and coherent electron optics increase contrast transfer at the finest spacings. A narrow source energy spread reduces chromatic aberration, because electrons with different energies otherwise focus differently. A cold field emission gun provides one route; a monochromator provides another. An energy filter removes many inelastically scattered electrons that otherwise contribute background. This does not remove all damage or every unwanted scattering event. Improved mechanical and electrical stability, reproducible lens settings, accurate coma-free alignment and calibrated magnification make the information more consistent across images.

The 2020 apoferritin reconstructions illustrate the final hardware step. One study combined a cold source, improved energy filtering and a fast direct camera with advanced correction to obtain a map at about $1.22\text{A˚}$. Another used an instrument with monochromation and aberration correction to reach about $1.25\text{A˚}$.^[ref][ref] The two instruments demonstrate complementary ways of preserving coherent high-frequency information. These unusually rigid, symmetric particles are favorable test specimens; their resolutions do not imply that a flexible cellular assembly will reach the same limit.

Fourth, modern reconstruction treats the noisy images statistically. single-particle analysis estimates how many randomly oriented projections correspond to a common three-dimensional structure. Bayesian inference and maximum likelihood estimation permit uncertainty in image orientations and class membership to be handled rather than committing every weak image to a single exact alignment from the beginning. ^[ref] provides a concrete implementation. Two-dimensional classes reject many damaged or overlapping particles; three-dimensional classification can separate different compositions or conformations. Appropriate symmetry increases the effective information, but an incorrect symmetry assumption can erase a real asymmetric feature.

Refinement increasingly corrects individual particle movements and optical imperfections. Per-particle defocus estimates accommodate height differences in ice. Beam tilt, higher-order aberrations and anisotropic magnification need correction when their accumulated phase errors become important. The contrast transfer function changes the magnitude and sign of Fourier components; combining images recorded with different defocus values recovers information suppressed at particular transfer-function zeros. Near atomic spacings, accounting for Ewald sphere curvature can further improve reconstruction. Such corrections require adequate signal and calibration; simply adding more adjustable parameters to weak data risks fitting noise.

Automation and fast computation make these methods practical. Stable automated acquisition and beam-image-shift strategies collect large image sets; parallel computation permits repeated alignment, classification and refinement. More particles improve the average only if they carry consistent signal. Under an ideal independent-noise model, the amplitude signal-to-noise ratio improves in proportion to $\sqrt{N}$; a systematic alignment error or persistent structural heterogeneity will not disappear by this scaling. For a target spacing $d$ and real-space pixel size $a$, Nyquist–Shannon sampling theorem requires $a\le d/2$. For $d=1.2\text{A˚}$ this gives $a\le 0.6\text{A˚}$ per pixel, a necessary sampling condition rather than a guarantee of such resolution.

Validation is part of the technological achievement. Split particles into independent halves and refine them independently; calculate their Fourier shell correlation, commonly reporting the spacing at the $0.143$ criterion for independently refined half-maps. Shared high-resolution references, poorly handled masks or correlated data can inflate agreement, so independence and mask correction matter. Inspect directional coverage and local resolution, compare models against held-out map information, and check stereochemistry. The global resolution is a summary: flexible loops, bound lipids and minor components may be much worse than the ordered core.

Finally, distinguish an atomistic model from atomically resolved data. At ordinary near-atomic resolution, side chains and backbone features can support building an atomic model while individual neighboring chemical atoms are not all separated. At true atomic resolution, many individual atomic peaks become distinguishable and some hydrogen contributions may be detectable under favorable conditions. cryo-electron microscopy reconstructs scattering electrostatic potential, so interpretation of very fine features is not identical to interpreting X-ray crystallography electron-density maps. The breakthrough was the combined improvement of specimen quality, counting movies, optical coherence and statistical reconstruction, with independent validation showing that the fine detail was supported by the data.

In transit spectroscopy, starlight passes tangentially through the planet's terminator atmosphere during primary transit. Wavelength-dependent opacity changes the effective occulting radius. For a thin atmosphere with an absorption feature spanning $N_H$ atmospheric scale heights,Here $\mu$ is the mean particle mass in units of $m_H$, not a chemical potential. Large planets with warm low-gravity, low-molecular-weight atmospheres against small stars have larger signals. A spherical isothermal atmosphere has tangential column enhancement of order $\sqrt{2\pi R_p/H}$ over a vertical column, explaining sensitivity to tenuous high-altitude gas. Molecular bands, atomic lines, scattering slopes and clouds constrain the terminator, but cloud opacity, reference pressure and abundance-temperature degeneracies limit unique retrievals.^[ref]

Occultation spectroscopy instead subtracts the star-only spectrum during secondary eclipse from the star-plus-planet spectrum immediately outside eclipse. It measures the dayside planet/star flux ratio. In the blackbody approximation the thermal eclipse depth isLonger infrared wavelengths generally improve contrast for a cooler planet; molecular absorption or emission depends on the vertical temperature gradient. At optical wavelengths reflected light can dominate, with full-phase contrast $A_g(\lambda )(R_p/a{)}^2$, where $A_g$ is geometric albedo. Eclipse spectra therefore probe dayside emission or reflection, rather than the transit's slant absorption. Clouds and temperature inversions affect interpretation.^[ref]

For either measurement, the photon-limited signal-to-noise ratio scales as the spectral feature amplitude times $\sqrt{N_{\gamma }}$, with a penalty for subtracting finite in- and out-of-event samples. Finer spectral bins reduce photons per bin; bright hosts, repeated events and stable instruments improve sensitivity. Detector systematics, telluric absorption for ground observations, and variable starspots can limit the practical gain. Space observations remove telluric contamination, not stellar variability or instrumental drift. Neither technique directly measures a unique bulk composition or samples all longitudes of the planet.

The principal feature is the abundance of planets with radii of roughly one to a few Earth radii compared with large gas giants within the stated short-period sample. The smallest few plotted bins are of broadly similar height, followed by a substantial decline at larger sizes. Thus the figure supports a high occurrence of small planets relative to giants, rather than an indefinitely steep rise toward arbitrarily small sizes. The horizontal scale is logarithmic: one should compare counts in the displayed bins with their widths in $\ln R_p$, not mistake a bin count for a density per unit linear radius.

The vertical axis is an average number of planets per target star. This exoplanet occurrence rate need not equal the fraction of stars hosting a planet, because one star can host several. The restriction to periods below $85$ days also matters: the figure is not a census of distant gas giants or of every planet in a system. Neither the detailed reduction procedure nor the raw detection counts are specified in the caption, so they cannot be reconstructed uniquely from the histogram.

Selection effects actually make the small-planet population harder to see. A full, undiluted exoplanet transit depth is approximately $(R_p/R_{\star }{)}^2$. For independent photometric errors of fractional size ${\sigma }_f$ per sample, an idealized detection signal-to-noise ratio iswhere $N_{\mathrm{in}}$ counts in-transit samples. At fixed star and orbital period, halving planet radius reduces this amplitude by four. Fainter hosts, correlated stellar noise, gaps and transit vetting reduce transit survey completeness further. Geometric transit probability also falls with orbital distance, $p_{\mathrm{tr}}\simeq R_{\star }/a\propto P^{-2/3}$ for fixed stellar mass. For a fixed observing baseline and cadence, the small-planet circular duration law gives $N_{\mathrm{in}}\propto P^{-2/3}$ and approximately $\mathrm{SNR}\propto R_p^2{P}^{-1/3}$.

Recovering an intrinsic exoplanet occurrence rate therefore requires correcting for geometric alignments, incomplete recovery and false positives. An illustrative estimator for a radius-period bin iswhere $C_j$ is the recovery probability over the relevant target sample and $w_j$ accounts for candidate reliability. Real analyses must average these probabilities over heterogeneous targets and measurement uncertainty; the formula indicates the required weights, not a reconstruction of the unpublished inputs to this figure. A primary Kepler space telescope analysis explicitly models both false positives and incomplete detection to infer occurrence.^[ref]

Thus the apparent preference for small planets cannot be explained by their being photometrically easier to detect. Small transits are harder. A plateau in occurrence below about twice Earth's size was independently reported using synthetic-transit injection and recovery, though that study used a different $5$–$50$-day selection and is not identified here as the source of the exam's plot.^[ref]

The natural physical framework is core accretion in a protoplanetary disk. Most initial disk mass is gas, principally hydrogen and helium; a much smaller fraction is solid material. Protoplanetary dust coagulation first assembles aggregates through low-speed sticking. Settling and differential drag help concentrate solids, but bouncing, the fragmentation barrier to dust growth and radial drift of solids in a gas disk prevent a simple assumption that every collision grows a body smoothly to planetary size. Concentration in dust traps or through streaming instability, followed by gravitational collapse of a dense solid population, provides routes to planetesimals. Subsequent collisions must dissipate sufficient relative energy to bind material rather than disrupt it.

Once sufficiently large planetesimals exist, gravitational focusing enhances their accretion cross-sections:When background random velocities remain small, larger bodies grow disproportionately fast in runaway planetesimal growth. As they become massive enough to stir the surrounding population, oligarchic growth develops: several planetary embryos occupy neighboring feeding zones, while much of the remaining solid material resides in smaller planetesimals. Heating the planetesimal random motions weakens gravitational focusing, and local depletion drives the embryos toward an isolation mass. Collisions among embryos can continue assembly after gas dispersal.

This solid-building pathway naturally produces many modest cores. Producing a large gas giant requires an additional, time-sensitive step: a sufficiently massive core must acquire and cool a gaseous envelope while disk gas remains available. Gas captured by a low-mass core releases gravitational potential energy; the envelope's ability to radiate that energy governs its contraction and further accretion. A characteristic cooling estimate iswhere $E_{\mathrm{tot}}$ includes the envelope’s gravitational and internal energies. This states an energy budget rather than a calibrated accretion timescale. Increasing core mass generally facilitates faster gas growth in the appropriate envelope regime. The critical core mass for gas accretion depends on opacity, solid accretion heating and disk conditions; no one exact threshold follows from the histogram. If envelope cooling becomes rapid enough and gas supply persists, runaway gas accretion can produce a giant. If core growth or cooling is too slow, protoplanetary disk dispersal removes the reservoir first, leaving a rocky core or a smaller planet with a limited envelope.

The snow line changes the supply of condensed solids: where water ice can survive, additional solid material can help cores grow. Its location depends on the evolving disk temperature and pressure, so there is no universal orbital radius at which giants must form. Short-period planets need not have assembled entirely at their present locations. Planetary migration can carry cores and giants inward; scattering and collisions can further reshape their orbits. Pebble accretion is another way to supply solids rapidly to embryos, but its efficiency depends on particle coupling and the available pebble flow. These processes alter the distribution without requiring every core to become a giant.

Radius also is not a linear proxy for mass. A relatively small hydrogen-helium envelope can increase a planet's radius substantially, so some planets with a few Earth radii need not be purely rocky. Contraction as planets cool and irradiation-driven atmospheric escape can subsequently reduce their radii. Hence the final histogram combines solid growth, gas capture, migration and later thermal evolution. In particular, the smallest bins need not all share one composition or one formation location.

Direct fragmentation through gravitational instability of an astrophysical disk is an alternative route to massive gaseous objects. It requires a sufficiently self-gravitating disk, described locally by Toomre's stability criterion, together with sufficiently rapid cooling for bound fragments to survive. It does not naturally explain the dominant population of small close-in cores by itself, although migration or further evolution can change the locations of fragments. The observed abundance of small planets is therefore consistent with solid cores commonly forming while only a minority acquire a massive gas envelope before disk dispersal. It does not uniquely prove a particular prescription for each uncertain growth stage.

The physical explanation is widespread core formation combined with restricted access to runaway gas accretion. The strongest observational conclusion concerns small versus giant planets in the stated period range, after accounting for selection; the figure alone does not determine a universal core threshold, a unique mass distribution, or the population beyond the period cut.

Choose the baseline vector from the first antenna to the second. Apart from a sign convention for receiver delay, the geometric delay is ${\tau }_g=\mathbf{b}\cdot \mathbf{s}/c$, and the phase difference is $\varphi =2\pi \nu {\tau }_g$. For equal received source powers $P_a$, adding the voltages and averaging over many wave periods givesUncorrelated receiver noise adds a mean level but not the source's coherent cross term. For an east-west baseline and one choice of hour-angle sign, ${\tau }_g=(b/c)\cos \delta \sin H(t)$. Earth rotation therefore sweeps the phase; locally the fringe frequency is $(b/\lambda )\cos \delta \cos H\dot{H}$. Tracking the antenna pointing keeps the source in the primary beam. Electronic fringe stopping is a separate operation: it can remove this phase evolution, making a source at the phase centre constant in the corrected complex visibility. The oscillating power above is the geometrical fringe before that correction.

For a small angular displacement $d\theta$ along the projected baseline, $d\varphi =2\pi b_{p}d\theta /\lambda$. One full fringe therefore spans $\Delta \theta \sim \lambda /b_p$. Here $b_p=|\mathbf{b}-(\mathbf{b}\cdot \mathbf{s})\mathbf{s}|$. This is the angular period of the measured Fourier component and the characteristic resolution scale when such long baselines are synthesized; precise beam width and image ambiguity also depend on baseline coverage and weighting. A single pair by itself does not give an unambiguous complete image.

Writing $x=h\nu /(k_{B}T)$, the expansion $e^x-1=x+O(x^2)$ immediately gives the Rayleigh-Jeans law,The factor two counts the two independent modes of polarization of waves. A small brightness-temperature perturbation thus has $\Delta I_{\nu }=2k_B{\nu }^2\Delta T_{\mathrm{RJ}}/c^2$ in this limit.

Hot intracluster electrons inverse-Compton scatter the microwave-background photons. The scattering optical depth is $d\tau =n_e{\sigma }_{T}dl$ and the characteristic thermal fractional energy transfer is of order $k_B{T}_e/(m_e{c}^2)$. The integrated distortion is therefore controlled byScattering conserves photon number while shifting photons toward higher frequencies, giving a low-frequency decrement and a high-frequency increment. Thus the printed estimate correctly gives a negative change of order $y{T}_{\mathrm{CMB}}$. Its numerical coefficient, however, is not the standard Rayleigh-Jeans coefficient. For nonrelativistic electrons and small $y$, the Kompaneets equation gives $\Delta n=y{x}^{-2}{\partial }_x(x^4{\partial }_x{n}_0)$. At small $x$, $n_0\simeq 1/x$, so $\Delta n\simeq -2y/x$ andEquivalently the thermodynamic-temperature spectral factor is $x\coth (x/2)-4\to -2$. The original PDF really prints the estimate with $-y$, not $-2y$; both numerical conventions are retained below. Relativistic corrections at the supplied $T_e$ are small compared with this factor-of-two difference.^[ref]

The uniform cube has a constant line-of-sight depth $L=6\times 10^{22}\mathrm{m}$. Using the supplied cross-section rather than replacing it with a more precise value givesAdopt $T_{\mathrm{CMB}}=2.72548\mathrm{K}$, explicitly an external measured constant, not a temperature supplied in the question. The values $k_B=1.380649\times 10^{-23}\mathrm{J}{\mathrm{K}}^{-1}$, $c=299792458\mathrm{m}{\mathrm{s}}^{-1}$ and $m_e\simeq 9.10938\times 10^{-31}\mathrm{kg}$ set the physical units. Hence the printed relation gives $\Delta T\simeq -22\mu \mathrm{K}$; the standard Rayleigh-Jeans result gives $\Delta T\simeq -44\mu \mathrm{K}$. Keeping the answer as $-8.14\times 10^{-6}{T}_{\mathrm{CMB}}$, or twice that, avoids needing a numerical background temperature.^[ref]

The face is a square, so its solid angle is $\Omega =(6\pi /10800{)}^2=3.046\times 10^{-6}\mathrm{sr}$, not the area of a circular six-arcminute aperture. At $15\mathrm{GHz}$,Thus $\Delta S_{\nu }\simeq -4.67\times 10^{-4}\mathrm{Jy}=-0.47\mathrm{mJy}$ using the printed estimate, or $-0.93\mathrm{mJy}$ using the standard factor two. The sign denotes missing brightness relative to the surrounding microwave background. At this frequency $h\nu /(k_B{T}_{\mathrm{CMB}})\simeq 0.264$; the exact nonrelativistic spectral intensity differs from the strict Rayleigh-Jeans approximation by about one percent. This precision does not affect the estimates.

For the array noise, the system temperature sets the receiver noise scale; let $A_e={\eta }_A\pi d^2/4$ be the effective area of each dish, and let ${\eta }_c$ describe correlation losses. No efficiencies or polarization of waves count are supplied, so first take ${\eta }_A={\eta }_c=1$ and a single independent polarization of waves. An unpolarized point source produces antenna temperature $T_a=S_{\nu }{A}_e/(2k_B)$, and the system-equivalent flux density is $\mathrm{SEFD}=2k_B{T}_{\mathrm{sys}}/A_e$. The interferometric radiometer equation gives one baseline an rms flux error $\mathrm{SEFD}/\sqrt{2\Delta \nu t}$. There are $N(N-1)/2=45$ cross-correlation baselines; averaging their independent thermal noise for a point source givesThe ideal single-dish effective area is $4\pi {\mathrm{m}}^2$, giving $\mathrm{SEFD}=6.59\times 10^3\mathrm{Jy}$ andCombining two independent parallel-hand polarization of waves measurements gives $6.3\mu \mathrm{Jy}$. Nonunit efficiencies increase these estimates by $1/({\eta }_A{\eta }_c)$. Here signal equal to noise means a weak-source signal-to-noise ratio of one after integration; it does not mean equating the source to the entire unaveraged receiver-noise power.^[ref]

At the band centre, $\lambda =0.01999\mathrm{m}$. Taking a representative maximum projected baseline of $20\mathrm{m}$ gives ${\theta }_{\mathrm{res}}\sim 3.4$ arcminutes. A corner-to-corner baseline of $20\sqrt{2}\mathrm{m}$ would give about $2.4$ arcminutes before projection and weighting. The exact antenna locations and source declination are not supplied, so neither a unique synthesized beam shape nor an exact FWHM is determined. The individual-dish primary-beam scale, roughly $\lambda /4\mathrm{m}\sim 17$ arcminutes, is the field of view, not the synthesized resolution.

To extract the cluster signal, retain frequency-resolved complex visibilities and fit an extended SZ template together with contaminating compact sources. For the ideal uniform square centred at the phase centre and with a nearly constant primary beam across it, the Fourier transform isThis is why the integrated decrement must not be treated as a point-source flux on every baseline. The first axial visibility null occurs at $b=\lambda /\Theta \simeq 11.5\mathrm{m}$. Short baselines carry most of the large-scale decrement; the longest baselines are useful for separating unresolved positive radio sources. natural visibility weighting or a suitable taper gives a clearer extended-source image than emphasizing the longest baselines, while a visibility-domain matched filter uses all samples with weights proportional to template amplitude divided by noise variance. Its amplitude estimate is $\hat{a}=\mathrm{Re}(T^{†}{C}^{-1}d)/(T^{†}{C}^{-1}T)$ for a real template amplitude. A joint fit propagates radio-source uncertainty instead of subtracting exact, noise-free source models.

Earth-rotation and multifrequency synthesis improve Fourier coverage, but each channel must use its own baseline in wavelengths, primary beam and SZ spectrum. Use the longer baselines and spectra to identify variable point sources, flag bad data, and test the decrement with time, antenna and frequency splits. Primary-beam and absolute-flux calibration must be included. Large-scale microwave-background fluctuations and residual ground or atmospheric signals can remain even below the thermal-noise estimate. The narrow low-frequency band alone gives limited separation of SZ and primary microwave-background temperature structure. There is no zero-spacing interferometric datum: integrated flux is model dependent unless sufficiently short baselines or additional total-power information are available. Exact cluster detection significance cannot be obtained from the point-source noise alone without the actual projected baseline distribution and weighting.

Spatial geometry. An embedding of the three-sphere isTaking differentials and collecting terms gives the induced metric tensorPut $\bar{r}=A\sin \chi$. Then $d\bar{r}=A\cos \chi d\chi$, soThe areal radius $\bar{r}$ is not a global radial coordinate on the entire three-sphere: its maximum occurs at the equator and two hemispheres share each smaller value. Use separate charts there; the coordinate singularity at $\bar{r}=A$ is not a physical singularity.

For Euclidean space and hyperbolic space of curvature $-1/A^2$, respectively,For the latter, $\bar{r}=A\sinh \chi$ gives $d{\ell }_{-}^2=A^2[d{\chi }^2+{\sinh }^2\chi d{\Omega }^2]$. In all three cases the induced two-metric at fixed $\bar{r}=\bar{R}$ is ${\bar{R}}^{2}d{\Omega }^2$. Its surface area is thereforeThis equality compares the same areal radius, not the same proper radial distance. For a proper radial distance $\ell$, the corresponding areas are $4\pi A^2{\sin }^2(\ell /A)$, $4\pi {\ell }^2$, and $4\pi A^2{\sinh }^2(\ell /A)$.

Homogeneity, isotropy and redshift. The FRW metric has constant-time spatial slices of constant curvature $k/a^2(t)$, with $k=+1,0,-1$ selecting the three geometries above. Their isometries act transitively on points and isotropically about every point, implementing the cosmological principle. Multiplication by one common time-dependent scale factor preserves these properties. With the source's $k=\pm 1$ normalization, $r$ is dimensionless and $a$ has units of length; using a dimensionless scale factor instead rescales the spatial curvature parameter. The origin of the spherical coordinates is arbitrary; it does not identify a physical centre. Cosmic time is the proper time of the comoving observers, and the absence of time-space cross terms makes their worldlines orthogonal to the homogeneous slices.

For a radial null geodesic between comoving endpoints,The next wave crest travels between the same endpoints. Subtracting the two path integrals, for wave periods short compared with the expansion time, gives $\delta t_0/a_0=\delta t_E/a_E$. Thus the cosmological redshift isBoth observers' clocks are cosmic proper-time clocks. Peculiar velocities and local gravitational-potential shifts have been left out of this homogeneous calculation.

Angular size and brightness. For a galaxy small compared with its distance, the angular diameter distance is $D_A=a_{E}R$ and its angular diameter isHere the emitted proper diameter is measured transverse to the line of sight; radial proper distance is a different integral when $k\ne 0$. Ignoring absorption, lensing caustics and intrinsic evolution, photon-number conservation spreads an isotropic-equivalent luminosity across the sphere $4\pi a_0^2{R}^2$. Each photon loses energy by $1+z$, and its arrival interval is stretched by the same factor. The received bolometric flux isThe disc's proper projected area is ${\mathcal{A}}_d=\pi d^2/4$, and its observed solid angle is ${\Omega }_d\simeq {\mathcal{A}}_d/D_A^2$. Therefore its surface brightness isThis is cosmological surface-brightness dimming. The normalization uses $L$ as isotropic-equivalent luminosity along the viewing direction; another disc emission law changes that normalization but not the redshift power. This is a bolometric result. In a specified observed frequency band the emitted spectrum is sampled at a shifted frequency and requires a spectral correction.

The distinction in telescope aperture and resolved surface brightness matters here. A larger telescope collects more photons and improves angular resolution, but cannot restore the incoming radiance lost by cosmological dimming. For aperture diameter $D$ and a diffraction resolution element of solid angle ${\Omega }_{\mathrm{res}}\sim (\lambda /D{)}^2$, the collected power from uniform resolved brightness scales asindependent of $D$. This is consistent with conservation of etendue. It explains why increasing aperture while keeping every gain in resolution does not increase counts per native resolution element from a smooth extended source. It does not make larger telescopes useless: at a fixed angular bin the counts grow as $D^2$, so a photon-noise-limited or uniform-sky-noise-limited signal-to-noise ratio grows roughly as $D\sqrt{t_{\exp }}$. They also resolve smaller structures and improve point-source sensitivity. Aperture, exposure and angular binning help measure a dim galaxy, without changing its intrinsic $(1+z{)}^{-4}$ brightness penalty.

The image annotation gives probe electric current $I=43\mathrm{pA}=4.3\times 10^{-11}\mathrm{A}$ and working distance $L=2.4\mathrm{mm}$. Interpret $d_o$ as the probe diameter and $\alpha$ as its convergence semiangle, in radians. To estimate that angle from the available dimensions, approximate the effective aperture plane as a distance $L$ from the specimen. With aperture radius $r_a=25\mu \mathrm{m}$,The electron beam brightness $\beta$ measures electric current per probe area per solid angle; the supplied convention corresponds to a circular probe and a paraxial cone of solid angle approximately $\pi {\alpha }^2$. The aperture diameter must be halved, and the annotated current is in picoamperes. Treating the full aperture angle as $\alpha$ would introduce a factor-of-two error in $d_o$.

This is a conditional optical estimate: the working distance is not necessarily the actual electron-optical distance from the effective aperture to the focused probe. The answer assumes that approximation, the quoted electron beam brightness at the operating voltage, and negligible optical aberrations. The 30 kV annotation gives a much shorter de Broglie wavelength than 4 nm, so a nanometre-scale probe is plausible. Actual electron microscope resolution also depends on diffraction, scattering in the specimen, signal generation and collection, signal-to-noise ratio, drift and specimen charging. A 4 nm probe does not establish that every measured edge width is 4 nm.

A $1.5\mathrm{mm}$ beam illuminates only $N=300$ slits, giving $mN=900$ and $\delta {\lambda }_R\simeq 0.511\mathrm{nm}$. The two main lobes broaden by $1000/300$ compared with the wider beam. Their $0.5\mathrm{nm}$ separation is slightly below the stated Rayleigh threshold: marginally unresolved by that criterion. This is not an assertion that the profile has only one maximum: the ideal equal-line sum still has two maxima and a modest central dip, as plotted. Inference from real data also requires adequate signal-to-noise ratio and a known instrumental profile.

Electrical noise reduction starts by identifying what is unwanted in the measured signal and where it enters. Increasing gain amplifies both signal and input noise; it does not by itself improve the input signal-to-noise ratio. Separate intrinsic component fluctuations, amplifier noise and external pickup before choosing a remedy.

Physical sources. A resistor at temperature $T$ has classical one-sided open-circuit thermal electrical noise density $S_V=4k_{B}TR$ per hertz. In a flat measurement bandwidth $B$, its rms voltage is $\sqrt{4k_{B}TRB}$. Lowering an appropriate resistance, reducing temperature or narrowing the useful bandwidth can reduce this noise, with loading and signal-gain tradeoffs considered. These are power spectral densities; an amplitude spectral density is their square root.

Discrete independent charge transfers give shot noise, with one-sided current density $S_I=2eI$ in the simple Poisson process model. Reducing leakage or unwanted bias current can help, but reducing a photocurrent may also reduce the desired signal. Charge correlations can change the simple shot-noise law. At low frequency, flicker noise and drift often dominate and are not described by a white spectrum.

Amplifier and impedance choice. An operational amplifier has equivalent input voltage and current noise. In a simplified uncorrelated model, a resistive source contributes the input-referred voltage densityHere $e_n,i_n$ are the voltage and current amplitude spectral densities and $Z_s$ is the source electrical impedance; feedback components add further terms in a full circuit. Low current noise matters particularly for a high-impedance source, while voltage noise can dominate for a low-impedance source. Minimize needless source impedance, leakage and long sensitive connections without sacrificing the required transduction gain or bandwidth. Bias-current offsets and thermal drift also require calibration; they are not removed simply by quoting a random-noise density.

Pickup and bandwidth. Shield sensitive circuits against electric-field coupling, minimize loop area to reduce changing magnetic-flux pickup, and use twisted signal/return pairs or suitable coaxial connections. Differential readout rejects common-mode interference when impedances and amplifier responses are adequately matched. Plan the signal returns to avoid unwanted circulating ground currents, and decouple supply rails locally so supply fluctuations do not enter the signal path. Mechanical vibration, cable motion and temperature changes may be converted into electrical noise as well.

A low-pass filter removes out-of-band noise before digitization; an anti-aliasing filter is needed because digital filtering cannot undo already aliased content. Avoid a narrower passband than the physical signal requires. For a known periodic signal, modulation and a lock-in amplifier select a narrow frequency interval, often moving the measurement above a strong flicker noise region. A notch can reject a narrow interference line if that does not remove essential signal information.

Independent noise contributions add in variance, not directly in rms amplitude. Averaging $N$ independent equal-variance readings reduces the standard error by $N^{-1/2}$, but slow correlated drift and systematic errors need separate controls. Good noise reduction preserves the information-bearing signal while reducing unwanted coupling, intrinsic fluctuations or the admitted noise bandwidth.

The optical telescope supplies collecting area and spatial selection, the spectral selector supplies a passband, and the photodetector converts received radiant flux into a measured signal. For an extended source, a useful schematic photon count iswhere $A\Omega$ is the etendue, $\tau$ the integration time, $\eta$ the net transmission and quantum efficiency, and $L_{\lambda }$ the spectral radiance. An illustrative independent-noise model givesHere $N_b$ and $N_d$ denote background and dark counts, and ${\sigma }_{\mathrm{read}}$ is readout standard deviation. This makes the roles of the three components explicit.

A larger optical telescope collects more photons at fixed angular pixel size and improves the diffraction-limited resolution. Its limits include optical aberrations, alignment, launch size, stray light and pointing. Conservation of etendue constrains simultaneous collecting area and angular acceptance. Increasing spatial resolution by narrowing a pixel's solid angle reduces its photons.

A narrower spectral passband or higher spectral resolving power separates diagnostic features and rejects unwanted background, but usually reduces photons per channel and hence signal-to-noise ratio. Selector transmission, leakage, slit width, detector format and the required time cadence limit the trade. A wider band helps only insofar as it adds useful signal rather than mostly background.

The photodetector's quantum efficiency, dark current, read noise, dynamic range and response time determine conversion losses and added noise. Cooling can suppress thermal background and dark current, but cannot remove photon shot noise. Longer integration improves a stationary signal's signal-to-noise ratio until motion, saturation, drift or required cadence becomes limiting.

Interpret the stated detector width $d=20\mu \mathrm{m}$ as one square spatial sample. At the point directly below the spacecraft, the small-angle approximation gives pixel angular width $d/f\simeq \Delta x/h$. ThusThere is a definition error in the source: the usual focal ratio, or f-number, divides focal length by the entrance-aperture diameter $D$, whereas the printed parenthesis divides by detector width $d$. Reporting both avoids silently changing the question:The actual optical design is therefore approximately f/1.36, a fast optical telescope, not an optically slow f/34000 instrument. Such a focal ratio is demanding but possible in principle: optical aberrations, obscuration, field coverage, stray light and alignment need careful design. The single-sample angular width is $2.94\times 10^{-5}\mathrm{rad}$. Spatial sampling alone does not guarantee true resolving power; diffraction, pointing and signal-to-noise ratio also matter. At large viewing angles, the same angular pixel covers a larger, distorted surface footprint. If the detector is literally one element, scanning is additionally needed to form a map.

Use one spectral resolution element, $\Delta \nu =0.5{\mathrm{cm}}^{-1}$, and assume comparable angular resolution horizontally and vertically, so the pixel solid angle is $\Omega \simeq {\theta }^2=6.67\times 10^{-6}\mathrm{sr}$. The question specifies only the vertical angle; without an assumption about horizontal field of view the diameter is not unique. Interpret throughput $\eta =0.5$ as dimensionless transmission. With primary collecting area $A_p=\pi d^2/4$, the power in that element iswhen $A_p$ is in square metres. There is no extra factor of $\pi$ multiplying the supplied spectral radiance.

For an integration time $t=1$ s, the order-of-magnitude effective noise bandwidth is $\Delta f\simeq 1/t=1$ Hz. The root-mean-square noise-equivalent power is then $P_n=\mathrm{NEP}\sqrt{\Delta f}=5\times 10^{-11}$ W.^[ref] A signal-to-noise ratio of 10 requires $P_s=5\times 10^{-10}$ W, and thereforeAn ideal rectangular average of a one-sided white noise spectral density has $\Delta f=1/(2t)$, giving $d\simeq 5.9$ cm instead. A circular field with diameter $\theta$ changes the diameter by another order-unity factor. These convention choices all require an aperture substantially larger than the $9.5$ mm diffraction estimate, so signal collection is the stronger constraint. The estimate treats the quoted NEP as applicable to the reconstructed channel; a detailed Fourier transform spectroscopy design would also specify scan weighting, background and how interferogram noise propagates into that channel.

Sensitivity adjustments occur at several stages and over several timescales. They reveal adaptive gain control and flexible reference points, but no single aftereffect uniquely identifies one anatomical site. Changes in threshold, apparent hue, an achromatic setting and a receptor current must be distinguished before explaining them with one adaptation mechanism.

At the receptor level, a finite photocurrent range has to represent environments with very different mean light levels. Julie L. Schnapf and colleagues measured membrane currents from individual macaque cone outer segments. Responses to a maintained light step had an initial component followed by a smaller steady response, and a steady background reduced sensitivity to an added weak flash. This desensitization was distinguishable from loss of pigment through bleaching.^[ref] Direct recording establishes that some gain adjustment occurs before any color name, decision or cortical object representation. The preparation is macaque tissue, and a measured cone current is not identical to a human appearance judgment.

An idealized normalization model illustrates the benefit. If a mechanism's incremental gain is proportional to $1/(I+I_0)$, maintaining a fixed response increment requires $\Delta I\propto I+I_0$. At high backgrounds this gives approximately constant fractional contrast $\Delta I/I$, a Weber-like regime. It should not be confused with a universal law across all intensities. Under a known-background Poisson counting model with mean $N$, the noise standard deviation is $\sqrt{N}$; a small increment has signal-to-noise ratio approximately $\Delta N/\sqrt{N}$. A fixed signal-to-noise criterion then gives fractional threshold proportional to $N^{-1/2}$ instead. The two predictions derive from different assumptions about what limits performance.

Mean adaptation and contrast adaptation also differ. A diagonal cone-gain model replaces $Q_j$ by $g_j{Q}_j$, with gains related to recent stimulation. It can reduce the effect of a persistent chromatic shift in the illuminant. If the signal changes approximately as $Q_j^{\prime }=k_j{Q}_j$, choosing $g_j^{\prime }=g_j/k_j$ cancels that change. This is exact only for the assumed channelwise scaling; real spectral illuminant changes need not transform every surface's catches by the same three factors.

To test adjustments beyond mean cone excitation, experiments can modulate color around an unchanged time average. John Krauskopf and colleagues found direction-selective threshold elevation after temporal chromatic or luminance modulation, supporting separable adaptable mechanisms for particular directions near threshold.^[ref] Michael A. Webster and colleagues then measured appearance after adaptation to modulation along different color-space directions. A color monitor, a modulated adapting field and asymmetric appearance matches allowed testing effects beyond detection thresholds. Appearance shifted away from the adapting direction, including directions intermediate to the simplest cardinal color directions.^[ref] Thus a three-independent-channel account sufficient for some threshold results was not sufficient for all suprathreshold appearance changes. Constant mean catches constrain a simple mean-receptor explanation, but do not prove that all receptor nonlinearities have been removed.

Longer experience changes reference points too. Jay Neitz and colleagues altered chromatic experience with colored filters over days and measured unique yellow settings. Shifts persisted for one to two weeks after filter use ended.^[ref] Persistence after removing the immediate adapting stimulus demonstrates more than an instantaneous receptor response. It supports experience-dependent normalization without showing that a color category or verbal label has been rewritten. Any interocular transfer must also be measured explicitly; duration alone does not identify cortex.

A natural perturbation extends the range to months. Peter B. Delahunt and colleagues followed achromatic settings before and after removal of cataractous lenses. Removal greatly changed short-wavelength input; settings continued to readjust over roughly three months, whereas chromatic discrimination recovered much faster.^[ref] An achromatic setting compensates for a perceived tint, so its physical shift should not be mistaken for a same-direction tint in appearance. The findings indicate distinct adjustment timescales. They are observational evidence with a changing optical input, not a randomized isolation of one neural site or a general treatment recommendation.

These studies support a multilevel experimental strategy. Measure receptor responses, detection thresholds and appearance separately; manipulate mean and contrast independently; test spatial specificity, interocular transfer and recovery. Control exposure, eye position, stimulus calibration, response criterion and learning. A loss of sensitivity can reflect adaptation that preserves dynamic range rather than damage, and stable appearance can coexist with changed receptor inputs. Conversely, perfect compensation is not guaranteed.

Start with the biological quantity to measure: compartment location, molecular colocalization, fast cell dynamics, deep-tissue activity or nanometre-scale organization. Specify the required field, depth, lateral and axial resolution, temporal sampling and acceptable perturbation before choosing the instrument.

For a thin fixed specimen or a shallow live preparation, confocal microscopy provides flexible multicolour imaging and effective optical sectioning with widely available labels. Adjust the pinhole and dwell time against signal-to-noise ratio, bleaching and speed. Repeatedly scanning a large volume can become too slow, and out-of-focus excitation can damage regions that contribute little useful signal.

For a living scattering specimen, two-photon excitation microscopy often offers better access to depth and confinement of excitation. Longer excitation wavelengths scatter less strongly in many tissues, and broad collection can recover scattered emission without a detection pinhole. These benefits do not eliminate depth-dependent optical aberrations, absorption, heating or focal phototoxicity. Pulsed excitation can also make instrumentation and suitable multicolour excitation more demanding.

If the priority is rapid, gentle volumetric observation of a suitable specimen, consider light-sheet fluorescence microscopy rather than forcing either point-scanning method to cover every use case. If subdiffraction molecular organization is required, consider a suitable super-resolution method and assess its labeling, speed and dose costs.

Finally, calibrate the point spread function in a sample-relevant medium, sample finely enough in all three dimensions, and check registration between colour channels. Match photon collection and exposure to the question, with controls for label-induced changes and photobleaching. The best method meets the biological resolution and timing requirements with sufficient signal and acceptable perturbation; the smallest nominal resolution number alone does not decide.

First measure the generator’s spectrum, timing and propagation pattern on quiet records. If practicable, coordinate shutdowns or quiet acquisition windows; otherwise place source/receiver lines to reduce coupling to the noise source and use good ground coupling and adequate instrument dynamic range. Saturated channels cannot be repaired by a later filter.

Separate noise using its measured frequency and moveout: a band-pass/high-pass filter can reject frequencies below the useful seismic band, and an appropriate narrow notch can reject a narrow coherent component. Avoid deleting wanted low-frequency arrivals along with the generator noise. Dense spatial sampling enables frequency–wavenumber filtering or array methods to separate low-apparent-velocity surface noise from target arrivals. A reference sensor near the generator can support coherent-noise subtraction when the transfer is stable.

Repeated shots/sweeps and stacking improve the signal-to-noise ratio for uncorrelated noise; persistent coherent generator noise does not necessarily average down. Known-sweep Vibroseis correlation also helps reject unrelated noise. Verify the final processing against test gathers to ensure that real arrivals have not been mistaken for noise.

Use a high-resolution multichannel seismic reflection survey, with closely spaced crossing lines or a suitable small three-dimensional survey over the turbine locations. It should map the seabed, the sediment–sandstone boundary, local faults, buried channels, and lateral changes relevant to foundations. Seismic reflection responds to acoustic impedance contrasts and can image an irregular boundary without requiring it to be a first-arrival refractor. Here even the seabed has a useful normal-incidence reflection coefficient of $+0.20$ despite its zero P-velocity contrast.

A seismic refraction survey can provide complementary seismic velocities and geotechnical information, particularly using seabed multicomponent receivers for S waves. Its limitations as the principal imaging method here include the missing water–sediment P refractor, required offsets of hundreds of metres to obtain useful basement first arrivals, and weaker constraints on thin layers or velocity inversions. Variable bathymetry and sediment thickness further complicate simple refraction interpretations.

A shallow-towed boomer seismic source or small sparker seismic source is a sensible initial seismic source for penetrating about 20 m of sediment beneath a 50 m water column. A chirp sub-bottom profiler can add finer imaging of the upper cover where penetration permits; penetration depends on grain size, consolidation, gas, and seismic attenuation. A pilot line should establish the minimum useful source energy and bandwidth. Large low-frequency air-gun arrays are unnecessary for this shallow target. Small coastal vessels, sea state, tow stability and acoustic background constrain usable frequencies and operations. Marine mammals and other local receptors motivate a low-energy effective source, monitoring and appropriate operational mitigation.^[ref]

The expected normal-incidence two-way travel times are $2(50)/1500\simeq 0.0667\mathrm{s}$ for the seabed and $2(50+20)/1500\simeq 0.0933\mathrm{s}$ for basement, separated by $26.7\mathrm{ms}$. Source duration, recording sample interval and bandwidth must distinguish them. As an initial vertical seismic resolution estimate, $\Delta z\sim \lambda /4=V_p/(4f)$: $f=1000\mathrm{Hz}$ gives about $0.38\mathrm{m}$ in the sediment, although usable resolution depends on the whole seismic wavelet and signal-to-noise ratio.

Choose shot and receiver spacing from the shortest useful wavelength, target size, maximum reflector dip, seismic migration needs and achievable navigation accuracy. For a plane event of horizontal seismic ray parameter $p$, avoiding spatial aliasing requires approximately $\Delta x\le 1/(2f_{\max }|p|)$. Source spacing and receiver spacing also set midpoint coverage and seismic acquisition fold; adequate offsets enable moveout correction and velocity estimation. For nearly horizontal shallow reflectors a few-metre shot interval can be practical, whereas steep events at high frequency require denser spatial sampling. These values must be designed together rather than imposing one spacing for every target. Cross-line spacing must resolve lateral features between turbine sites, not merely along each track.

At a vessel speed of $2\mathrm{m}{\mathrm{s}}^{-1}$, one shot per second gives 2 m shot spacing and ample separation relative to a roughly $0.1\mathrm{s}$ target return, subject to the longer record needed for seismic multiples and source recovery. Shallow towing limits seismic source ghosts and receiver ghosts, but requires stable tow depth. Accurate positioning, tides, measured water sound speed, bathymetry and checks for seabed seismic multiples are essential for correct target depths.

Thorlabs' silicon FDS100 experiment sends a collimated, fibre-coupled laser beam through a beam splitter to the photodiode and a reference optical power meter. Varying reverse bias and electrical load tests linearity. The measured readout approaches saturation when its electric potential difference consumes the bias.^[ref] A separate low-signal setup uses a $637\mathrm{nm}$ laser, polarizers, an optical chopper, optical attenuators and a lock-in amplifier inside a light-tight enclosure. These are actual apparatus choices, not the parameters of the constructed example above.^[ref]

For an independent dark current check, Thorlabs enclosed a photodiode in nested metal boxes to exclude light and suppress interference, used a Keithley 6487 ammeter supplying reverse bias, and monitored temperature. Only one specimen per type was tested; the nearby temperature sensor did not directly contact the semiconductor. Such a dark control measures the baseline but cannot certify spectral responsivity.^[ref]

To infer spectral responsivity at a selected wavelength, measure the radiant flux actually reaching the test photodiode, rather than just the reference arm. A reference-arm measurement calibration must include the beam splitter ratio and path losses. With signed readouts in one fixed orientation, subtract a beam-blocked baseline and usefor direct electric current readout or a calibrated linear transimpedance amplifier, respectively. Repeating at several incident powers tests whether this ratio is constant. Blocking only the source estimates ambient light plus electronic baseline; covering the detector excludes ambient light too. Their difference distinguishes optical background from dark current and readout offset. For a broad optical spectrum, the ratio is a spectrum-weighted response, not generally $R$ at one wavelength.

For independent Poisson distribution collection, the root mean square shot noise in a one-sided rectangular frequency band of signal bandwidth $B>0$ isHere $I_d$ is reverse dark current; thermal electrical noise and amplifier noise also contribute.^[ref]

Subtracting a mean dark current removes its offset, not its fluctuations: subtracting a constant leaves the variance unchanged. Consequently $I_{\mathrm{ph}}\gg I_d$ makes dark current shot noise small relative to signal shot noise; it does not by itself establish high signal-to-noise ratio. With an independently measured baseline, the variance of that estimate must also be propagated. Increasing the measurement signal bandwidth raises the admitted noise. Calibration of wavelength, reference radiant flux, readout gain and collection geometry, together with drift and linearity, determines what measurement uncertainty can be claimed.

For a known-background Poisson measurement with mean $N$, the standard deviation is $\sqrt{N}$. A small added mean $\Delta N$ has approximate signal-to-noise ratio $\Delta N/\sqrt{N}$ when background counting noise dominates. A fixed criterion $z$ therefore gives $\Delta N\approx z\sqrt{N}$ and fractional contrast $z/\sqrt{N}$. This is a stated observation model, not a universal human threshold or a two-alternative comparison formula.