Manuscript En01-B@2 · En01-B-v2.tex · f226d1eb
Calibrated Obstructions and Nuisance-Cancelling Controls for Gravity-Related Decoherence A Superconducting-Microsphere Interferometer: Regularized Dynamics, Preparation Records, and Detector Certificates
Proves an exact complete-record overlap when a shared quadratic force shift stays inside an independent calibration width, and a nonquadratic homogeneous-sphere contrast whose unsmeared coefficient is -5041/81920. Gaussian regularization keeps that contrast strictly negative at every finite width, with a uniform bound for r_c at most R/100. Log-visibility intervals and a bounded attempted-run statistic are separate certificates. En01-A is a conceptual predecessor and is not a premise. This is not an experimental exclusion, not a derivation of a metric, and not a gravity-generated entanglement test. Radiation bounds are not transferred by replacing a microscopic cutoff with a sphere radius. Continuous apparatus inputs remain unresolved. No quantum coefficient is admitted. No compilation is asserted. No execution record is claimed.
Front matter
abstractAbstractFront matter · lines 725–758
Open as its own pageWe develop a paired negative and constructive identifiability analysis for the superconducting-microsphere interferometer proposed by Pino and collaborators. For a shared residual force-diffusion amplitude independently restricted to an interval, proportional quadratic environmental and gravitational responses produce an exact complete-record match whenever the gravitational coefficient shift does not exceed the calibration width. This establishes family overlap, not containment of the entire alternative family. We distinguish calibration of the environmental source from calibration of total centre-of-mass heating, and derive a regularized-model near-obstruction bound with explicit domain and implementation errors.
A complementary three-separation contrast cancels a common preparation offset and quadratic environmental attenuation. For a continuous homogeneous sphere at separations , its unsmeared gravitational coefficient is , in units . We prove that the contrast remains strictly negative for every finite Gaussian regularization length, obtain a uniform quantitative lower bound for , and give validated spectral quadrature and large-smearing bounds. A robust signed contrast margin survives only when setting-dependent preparation, environmental-shape, trajectory, and sensing errors are sufficiently small.
Log-visibility inference is connected to complete attempted-run records through confidence intervals; it is not treated as a bounded per-run statistic. A separate bounded-statistic route provides uniform sample certificates. The analytical results and embedded regressions do not claim reproduced apparatus performance or an experimental exclusion.
- figureA signed contrast is not an experimental exclusionFront matter · En01-B@2#fig:scope-En01-B · lines 760–773Quadratic calibration overlap→Nonquadratic sphere contrast→Experimental exclusionA signed contrast is not an experimental exclusion.
A signed contrast is not an experimental exclusion. The three boxes name objects this manuscript keeps separate. The dashed box is the stated stop. Not a proof, and not an admission of a quantum coefficient.
- figureA signed contrast is not an experimental exclusionFront matter · En01-B@2#fig:split-En01-B · lines 775–786Quadratic calibration overlapExperimental exclusionA signed contrast is not an experimental exclusion.
A signed contrast is not an experimental exclusion. Reading downward is not a transfer. Not a proof, and not an admission of a quantum coefficient.
- figureReading downward is not a transferFront matter · En01-B@2#fig:chain-En01-B · lines 788–799Quadratic calibration overlap↓Nonquadratic sphere contrast↓Experimental exclusionA signed contrast is not an experimental exclusion.
Reading downward is not a transfer. Not a proof, and not an admission of a quantum coefficient.
- figureQuadratic calibration overlap is not Experimental exclusionFront matter · En01-B@2#fig:pair-En01-B · lines 801–810Quadratic calibration overlapnot the same objectExperimental exclusionNonquadratic sphere contrast. A signed contrast is not an experimental exclusion.
Quadratic calibration overlap is not Experimental exclusion. Not a proof, and not an admission of a quantum coefficient.
- figureThree statuses stay separateFront matter · En01-B@2#fig:gate-En01-B · lines 812–822Named: Quadratic calibration overlap→Used here: Nonquadratic sphere contrast→Not claimed: Experimental exclusionA signed contrast is not an experimental exclusion.
Three statuses stay separate. Not a proof, and not an admission of a quantum coefficient.
sectionFront matterFront matter · lines 822–825
Open as its own pageFigure fig:scope-En01-B, Figure fig:split-En01-B, Figure fig:chain-En01-B, Figure fig:pair-En01-B, and Figure fig:gate-En01-B name the stop. Not a proof, and not an admission of a quantum coefficient.
Question, contribution, and scope
sectionQuestion, contribution, and scopeQuestion, contribution, and scope · lines 827–874
Open as its own pageA reduced fringe contrast does not identify the source of decoherence. The relevant question is whether a calibrated environmental family can reproduce the same recorded outcomes as a specified additional gravity-related dynamical model.
We use the staged superconducting-microsphere proposal of Pino and collaborators Pino2018 as the experimental reference. Its long-wavelength localization model motivates a residual force-diffusion nuisance, while its preparation and sensing stages require explicit accounting of squared-position outcomes and failures. The reference is a proposal, not a completed gravitational-decoherence experiment.
The contribution has two linked parts:
Calibrated obstruction. A shared uncertain residual amplitude can leave an exact non-identifiable region even after an environmental calibration interval is supplied. The matching condition is imposed across all stages and settings.
Nuisance-cancelling control. A specified separation contrast eliminates selected constant and quadratic attenuation terms, but retains a nonquadratic gravitational response with a proved regularization-dependent margin.
These conclusions concern different models and must not be conflated. The obstruction is exact in the declared quadratic dynamical model. The positive contrast is a controlled attenuation diagnostic whose application to the full apparatus requires a residual ledger. Coefficient separation alone is not detector separation.
All analytical results are proved here. External inputs are the reference architecture, the motivation for regularized mass-density models, and the radiation constraints cited in Section sec:radiation. Neither a manuscript registry nor an unverified companion result is a mathematical premise.
En01-A En01A provides conceptual background on accessible state differences. Here the difference is between dynamically constructed outputs, not a state and its record pinching. Its copy-screening and Möbius results are not imported.
Reference protocol and observation boundary
sectionReference protocol and observation boundaryReference protocol and observation boundary · En01-B@2#tab:protocol, En01-B@2#eq:record · lines 876–955
Open as its own pageInput Reference benchmark Application status Sphere Niobium, Geometry and material must be measured Mass Approximately amu Independent mass characterization Nominal separation nm Preparation-outcome dependent Cooling ms Initial preparation retained Boost ms Stage retained Free expansion ms Stage retained Split sensing ms Finite squared-position instrument Rotation ms Stage retained Inflation ms Stage retained Final sensing ms Finite squared-position readout Post-cooling duration Approximately ms Not an attempt repetition period {Proposed reference values from Pino2018 (Sec. V and Appendix). The listed rounded post-cooling durations sum to ms. They are not demonstrated capabilities.}
The order is
The three control separations introduced below are proposed settings; their feasibility is not established by the single reference separation.
An attempted run includes its preparation record, its accept/reject flag, sensing failures, and detector bins. A quantum instrument is a countably additive family of completely positive maps whose total map is trace preserving. For a continuous outcome, instrument integrals, rather than individual density elements, are trace nonincreasing.
Let be propagation maps and the finite sensing instruments. The successful record law is schematically
Rejection and failure outcomes complete its mass to one. Later maps may depend on earlier accessible outcomes.
The -dependence of a sensing instrument includes dynamics during its finite interaction time. It is not a choice of different electronics for the two hypotheses. A common terminal detector channel is applied only after completing the hypothesis-dependent sphere–sensor evolution.
For an impulsive diagnostic, a normalized squared-position instrument has Kraus density
In a resolved positive-outcome regime its packet-centre separation is approximately . Replacing finite split sensing by this impulsive map requires a separate approximation bound.
Declared regularized model and its dynamics
sectionConvention and rigid-body specificationDeclared regularized model and its dynamics › Convention and rigid-body specification · En01-B@2#eq:DP · lines 959–1000
Open as its own pageLet be a positive finite intrinsic mass measure on , with total mass , and let
The width is the standard deviation in each Cartesian direction. A fixed-orientation rigid body moves along a unit vector , with centre-of-mass position operator on :
We declare the generator
The alternative adds , with . Unit strength means this normalization, not every convention called Díosi–Penrose in the literature. Regularization and normalization are physical model specifications Bahrami2014,TilloyDiosi2017.
Our Fourier convention is
Thus .
theoremTheorem: Bounded regularized kick generatorDeclared regularized model and its dynamics › Convention and rigid-body specification · En01-B@2#thm:kick, En01-B@2#eq:kick, En01-B@2#eq:rate · proof attached · lines 1001–1057
Open as its own pagePut , , and
Then is a finite positive even measure and
Writing ,
Its exponential is a CPTP semigroup on trace-class operators. The position coherence rate is
Proof. Since ,
Fourier transforming gives . On smooth finite-rank position kernels, substitution in (eq:DP) gives multiplication by . Evenness removes the sine part in (eq:kick). The bounded integral extends the identity to trace-class operators.
For , define
Then
is a norm-convergent CPTP mixture. The zero-rate case is the identity. The norm bound follows from the norm-one unitary conjugations.
assumptionAssumption: Admitted baseline and sensing dynamicsDeclared regularized model and its dynamics › Convention and rigid-body specification · En01-B@2#ass:baseline · lines 1059–1067
Open as its own pageFor every tested setting and nuisance value, the common Hamiltonian, environmental evolution, and apparatus couplings define a strongly continuous CPTP propagator with the composition property. Its instruments are well defined. Unbounded diffusion terms, when used, have admitted realizations and the same operation domains in matched comparisons.
propositionProposition: Bounded addition to an admitted baselineDeclared regularized model and its dynamics › Convention and rigid-body specification · En01-B@2#prop:addition · proof attached · lines 1069–1083
Open as its own pageUnder Assumption ass:baseline, adding gives a unique strongly continuous CPTP bounded-perturbation propagator.
Proof. Interleave the baseline propagator with Poisson-distributed jumps of rate , applying at each jump. The sum over ordered jump times converges in trace norm, with factorial bounds, and is CPTP. It solves the bounded variation-of-constants equation. Picard iteration with bound proves uniqueness.
sectionConvention and rigid-body specificationDeclared regularized model and its dynamics › Convention and rigid-body specification · lines 1083–1089
Open as its own pageThe gravitational contribution is included during cooling, pre-split evolution, and finite sensing. Boundedness of does not make the kinetic Hamiltonian or the position operator bounded.
sectionDifferent mass and packet prescriptionsDeclared regularized model and its dynamics › Different mass and packet prescriptions · En01-B@2#eq:spectral · lines 1090–1146
Open as its own pageFor two displaced intrinsic profiles,
and Fourier substitution gives .
A continuous homogeneous sphere has
so
A microscopic constituent specification instead has
Its cross terms cannot be discarded without an approximation argument. Writing
its rate is
This follows by convolving two Gaussian mass profiles and using their Newtonian potential.
Finite-width centre-of-mass packets are states of , not intrinsic mass profiles. Their coherence kernel experiences at every position pair. Packet width is not interchangeable with .
propositionProposition: Quadratic coefficient and remainderDeclared regularized model and its dynamics › Different mass and packet prescriptions · En01-B@2#prop:quadratic · proof attached · lines 1147–1181
Open as its own pageDefine
For , these are finite and
The quadratic generator is
For isotropic profiles,
Proof. Integrate . Angular means of and are and . Gaussian decay controls all moments.
Residual force noise under independent calibration
sectionOne shared amplitude, not a free amplitude per settingResidual force noise under independent calibration › One shared amplitude, not a free amplitude per setting · En01-B@2#eq:scalar0, En01-B@2#eq:scalar1 · lines 1186–1214
Open as its own pageLet . The narrow residual model is
Here are declared functions of stage, time, and accessible history. The same amplitude is used across settings. Independent environmental characterization supplies
The reference's vibrational localization has a potential-dependent transfer function and can vanish during free motion Pino2018 (Sec. II). Thus proportionality to a persistent gravitational contribution is not inferred from the words “force noise”. It is an explicit model condition.
theoremTheorem: Calibrated quadratic obstructionResidual force noise under independent calibration › One shared amplitude, not a free amplitude per setting · En01-B@2#thm:width, En01-B@2#eq:obstruction · proof attached · lines 1215–1266
Open as its own pageSuppose the two hypotheses use the same interval , all known dynamics and apparatus specifications match, and
at every relevant stage, setting, and history, with one constant . Put .
The coefficient intervals and overlap exactly when
Whenever (eq:obstruction) holds, at least one null–alternative pair has identical complete attempted-run laws, including preparation, heralding, finite sensing, and failures. For that pair, every test satisfies
Consequently no test has both errors uniformly below over the entire two families.
This is family overlap, not containment of every alternative member in the null. When , the coefficient intervals are disjoint, but observable separation does not follow without a detector argument.
Proof. Matching requires . Such values in exist precisely when , which for is (eq:obstruction). One explicit pair is , .
For this pair the total generators in (eq:scalar0)–(eq:scalar1) agree. Uniqueness gives identical propagation. The same apparatus coupling and instrument give identical unnormalized outcome states. Induct over stages and accessible histories to obtain identical complete laws.
For a randomized test declaring alternative,
The remaining qualifications follow from interval overlap alone.
sectionOne shared amplitude, not a free amplitude per settingResidual force noise under independent calibration › One shared amplitude, not a free amplitude per setting · lines 1266–1273
Open as its own pageIf , or all vanish on the effective observation domain, there is no gravitational shift in this quadratic comparison. Otherwise nonproportional cannot be matched by this scalar shift at the generator level. That failure is not, by itself, an identifiability theorem.
- figureFigureResidual force noise under independent calibration › One shared amplitude, not a free amplitude per setting · En01-B@2#fig:width · lines 1274–1298
Quadratic-model obstruction for any chosen positive unit . Regularization enters through . Above the boundary only coefficient overlap is excluded; detector separation still needs proof. The optional artifact plots the corresponding homogeneous-sphere surface as a function of .
sectionCalibration records versus a calibrated intervalResidual force noise under independent calibration › Calibration records versus a calibrated interval · lines 1300–1303
Open as its own pageLet denote calibration data and the interferometer record.
propositionProposition: Joint-calibration distinctionResidual force noise under independent calibration › Calibration records versus a calibrated interval · En01-B@2#prop:joint · proof attached · lines 1304–1325
Open as its own pageWrite the joint laws as
They are equal if and only if their calibration marginals are equal and their conditional interferometer laws agree almost everywhere under the common marginal.
A match of interferometer laws after fixing an interval does not imply a match of the joint laws when an external calibration distinguishes the corresponding environmental amplitudes.
Proof. Equality of joint laws implies equality of marginals. Uniqueness of conditional probabilities up to marginal null sets gives the conditional equality. Conversely, integrate the common conditional law against the common marginal.
sectionCalibration records versus a calibrated intervalResidual force noise under independent calibration › Calibration records versus a calibrated interval · lines 1325–1333
Open as its own pageTheorem thm:width is therefore an obstruction for inference using the declared interval and interferometer records. If raw external calibration data are also used, their laws belong in the comparison. Coverage of an interval alone does not establish equality of those laws.
propositionProposition: Heating is not source identificationResidual force noise under independent calibration › Calibration records versus a calibrated interval · En01-B@2#prop:heating · proof attached · lines 1334–1361
Open as its own pageFor a pure force-diffusion term , its contribution to momentum heating is
If two models have identical centre-of-mass generators throughout a heating calibration and the interferometer, all admitted centre-of-mass calibration instruments have identical laws. Total heating alone does not identify the environmental part of .
Proof. On a common moment domain,
Move the double commutator to the observable. This is the diffusion contribution; Hamiltonian or damping terms may also change .
Identical generators give identical states before each heating instrument and hence identical recorded distributions, as in Theorem thm:width.
sectionCalibration records versus a calibrated intervalResidual force noise under independent calibration › Calibration records versus a calibrated interval · lines 1361–1367
Open as its own pageAn external force sensor, gas characterization, or bath-resolved measurement can be an independent source calibration. A measurement of total centre-of-mass diffusion is not automatically such a calibration.
Near-obstruction in the full regularized model
propositionProposition: Bounded-aperture generator remainderNear-obstruction in the full regularized model · En01-B@2#prop:aperture · proof attached · lines 1371–1389
Open as its own pageIn a model with bounded self-adjoint position operator ,
Proof. Evenness writes the generator as . The cosine family is the average of two unitary-conjugation trace-norm isometries. Taylor's integral remainder after the quadratic term is bounded by . Since , integration proves the result.
theoremTheorem: Full-model near-obstruction certificateNear-obstruction in the full regularized model · En01-B@2#thm:near, En01-B@2#eq:zeta · proof attached · lines 1391–1443
Open as its own pageChoose in the calibration interval. Replace the gravitational quadratic term by . Suppose bounded-aperture comparison models have , and the actual complete laws are within total variation of those comparison laws.
With uniform history-wise bounds when feedback is used,
where
The sums denote the stages of an attempted run, not an unweighted sum over alternative experimental designs. A bound exceeding one is replaced by the trivial bound one.
For independent attempted runs,
Thus uniformly small errors require .
Proof. After matching the scalar shift, the generator difference is
The first norm is bounded by Proposition prop:aperture. The second is at most . Variation of constants and CPTP contractivity bound the state trace distance by half the integrated generator norms. Complete instruments and terminal processing contract the same norm. Add the two law-approximation errors.
For product laws, by telescoping. Every test has error sum at least one minus product-law total variation.
sectionNear-obstruction in the full regularized modelNear-obstruction in the full regularized model · lines 1443–1450
Open as its own pageA scalar rate remainder is not a full-protocol trace-distance estimate. The terms must cover aperture replacement, boundary dynamics, preparation, sensing, and any other approximation. Spatial tail probabilities alone need not control the change of the Hamiltonian at a truncation boundary.
propositionProposition: State-specific residual certificateNear-obstruction in the full regularized model · En01-B@2#prop:residual · proof attached · lines 1451–1473
Open as its own pageLet be an admitted exact evolution and a Hermitian normalized absolutely continuous approximation on a common variation-of-constants domain. If
is integrable in trace norm, then
The statement also applies to direct sums of unnormalized instrument blocks.
Proof. Propagate the initial difference and the residual integral. The admitted propagator contracts Hermitian trace norm.
Beyond quadratic localization: an explicit control
sectionDiagnostic attenuation modelBeyond quadratic localization: an explicit control › Diagnostic attenuation model · En01-B@2#eq:Y · lines 1478–1517
Open as its own pageFor a setting with fixed effective separation , suppose
The common offset and quadratic coefficient can differ between fitted hypotheses, but each is shared across the settings of its hypothesis.
The constant and quadratic forms are motivated by saturated short-wavelength and long-wavelength localization, respectively Pino2018 (Sec. II). Actual gas-scattering localization and setting-dependent preparation are not assumed to obey them exactly; their departures enter .
Equation (eq:Y) is a controlled diagnostic, not the complete seven-stage prediction.
Choose
Then
Define
theoremTheorem: Nuisance cancellation and robust marginBeyond quadratic localization: an explicit control › Diagnostic attenuation model · En01-B@2#thm:contrast · proof attached · lines 1518–1562
Open as its own pageUnder (eq:Y),
If , put . The contrast intervals are
For a fixed alternative they are disjoint exactly when
with remaining gap
For an alternative family, a common oriented certificate instead requires one sign and
An infimum of absolute values does not establish a common oriented threshold when the sign varies.
Proof. Multiply (eq:Y) by the weights and sum. The two nuisance terms vanish. The residual magnitude is bounded by the weighted sum of its component bounds. Two centred closed intervals with radii and centre distance are disjoint precisely under the displayed strict inequality. The family statement applies the same orientation to every alternative.
propositionProposition: Unsmeared continuous-sphere rateBeyond quadratic localization: an explicit control › Exact homogeneous-sphere calculation · En01-B@2#prop:sphere · proof attached · lines 1571–1611
Open as its own pageFor a continuous homogeneous sphere,
where
In particular .
Proof. The intrinsic density autocorrelation is
It is the overlap volume of two spheres times the squared density. Its Newtonian pairing at displacement is
Integrating the polynomial separately below and above gives
for , and otherwise. The rate is . Its quadratic coefficient follows at .
corollaryCorollary: Exact three-separation signatureBeyond quadratic localization: an explicit control › Exact homogeneous-sphere calculation · En01-B@2#cor:exactcontrast, En01-B@2#eq:exactcontrast · proof attached · lines 1613–1637
Open as its own pageWith ,
Proof. The quadratic contribution cancels. The remaining moments are
Therefore
sectionExact homogeneous-sphere calculationBeyond quadratic localization: an explicit control › Exact homogeneous-sphere calculation · lines 1637–1642
Open as its own pageReplacing gravity by a purely quadratic kernel makes the contrast zero. Allowing an independently free preparation offset at each setting also destroys the cancellation premise.
Gaussian regularization: sign, margin, and validated integration
sectionGaussian regularization: sign, margin, and validated integrationGaussian regularization: sign, margin, and validated integration · En01-B@2#eq:b · lines 1644–1662
Open as its own pageSet
Equation (eq:spectral) gives
The constant term vanishes, and at the origin. Its pointwise oscillations do not determine the sign of the complete integral.
lemmaLemma: Radial autocorrelation after Gaussian smearingGaussian regularization: sign, margin, and validated integration › A sign theorem for every finite Gaussian width · En01-B@2#lem:radial · proof attached · lines 1665–1698
Open as its own pageFor a homogeneous sphere and , its smeared autocorrelation
is positive, smooth, radial, and strictly decreasing at every radius .
Proof. The unsmeared is nonnegative, radial, and decreasing on , and vanishes outside that ball. Its layer-cake representation is a positive mixture of indicators of balls of nonzero radii.
For a ball of radius , let
By the divergence theorem,
Pair a point with with its reflection across the plane orthogonal to . For , the Gaussian value at the nearer point is strictly larger. The paired integral before the minus sign is positive. Thus . Integrate this strict inequality against the positive layer-cake mixture. Smoothness and positivity follow from Gaussian convolution.
theoremTheorem: Strictly negative regularized control responseGaussian regularization: sign, margin, and validated integration › A sign theorem for every finite Gaussian width · En01-B@2#thm:sign · proof attached · lines 1700–1747
Open as its own pageFor every finite , the function
is strictly concave on . Consequently
for the three separations used here. On every compact interval of finite positive regularization lengths, its negative magnitude has a strictly positive minimum.
Proof. Let . The shell theorem gives
Writing , differentiation gives
Strict decrease of implies , so .
For , strict concavity gives
Since and , their slope difference equals . This proves the sign.
Continuity in follows by dominated convergence in the spectral integral on compact positive intervals. A continuous strictly positive has a positive minimum on such an interval.
sectionA sign theorem for every finite Gaussian widthGaussian regularization: sign, margin, and validated integration › A sign theorem for every finite Gaussian width · lines 1747–1751
Open as its own pageThe last assertion is an existence result. The next theorem supplies an explicit usable lower bound.
theoremTheorem: Uniform small-smearing certificateGaussian regularization: sign, margin, and validated integration › A sign theorem for every finite Gaussian width · En01-B@2#thm:small, En01-B@2#eq:small · proof attached · lines 1752–1791
Open as its own pageFor all ,
Hence, on ,
More generally,
Proof. Because , . Parseval's identity for the uniform unit-ball density gives
Indeed, ; applying the stated Fourier normalization proves the identity.
Use
in (eq:b). The bound is . Set and apply Corollary cor:exactcontrast. The final rational inequality is direct.
corollaryCorollary: A uniform constructive marginGaussian regularization: sign, margin, and validated integration › A sign theorem for every finite Gaussian width · En01-B@2#cor:uniformmargin · proof attached · lines 1793–1810
Open as its own pageFor alternatives with , , and , the oriented contrast has a common deterministic gap at least
A positive value certifies separation within the declared attenuation model and residual bounds.
Proof. Use the fixed negative sign and (eq:small) in Theorem thm:contrast.
propositionProposition: Large-smearing upper boundGaussian regularization: sign, margin, and validated integration › Large smearing reduces the available margin · En01-B@2#prop:large · proof attached · lines 1814–1839
Open as its own pageFor the homogeneous sphere,
Thus its constructive margin tends to zero as , despite remaining strictly signed for every finite .
Proof. The quadratic terms cancel and
Using ,
The weighted fourth moment is . Substitute and express the result in units .
- figureFigureGaussian regularization: sign, margin, and validated integration › Large smearing reduces the available margin · En01-B@2#fig:small · lines 1841–1864
A proved lower certificate, not an approximation to the full response curve. The certificate becoming zero does not mean the response changes sign; Theorem thm:sign proves otherwise.
propositionProposition: Explicit spectral integration enclosureGaussian regularization: sign, margin, and validated integration › Validated spectral quadrature · En01-B@2#prop:quadrature · proof attached · lines 1868–1930
Open as its own pageLet , , and use composite Simpson quadrature with an even number of equal intervals on . For , define
Let and
If , put
Then the finite-interval quadrature error for is at most
The omitted tail is bounded by
Validated nodal intervals and an interval for , combined with these errors, give a rigorous enclosure for .
An enclosure at extends to a whole regularization cell by adding .
Proof. The normalized sphere form factor is an average of with , so . Leibniz's rule gives . Since , . The Gaussian derivative is , bounded by . The product derivative bound is therefore . The standard Simpson remainder, obtained by integrating the fourth-order interpolation remainder panel by panel, gives the stated finite-interval error.
For the first tail bound, use , , and
For , . Integrating gives the second bound after multiplying by . The cell extension is Theorem thm:small.
sectionValidated spectral quadratureGaussian regularization: sign, margin, and validated integration › Validated spectral quadrature · lines 1930–1937
Open as its own pageThe embedded optional validated calculation uses exact rational interval Taylor evaluations, including a Machin-identity enclosure for . It does not assume floating-point trigonometric evaluations are rigorous. Ordinary floating central values are separately labelled diagnostic.
Preparation and detector conditions for the control
sectionResidual ledgerPreparation and detector conditions for the control › Residual ledger · En01-B@2#tab:residual · lines 1941–1976
Open as its own pageDeparture from (eq:Y) Required bound or modification Setting-dependent preparation visibility Bound its log-visibility departure from one shared offset Finite packet width and shape change State-specific packet or full-protocol error certificate Unsaturated gas localization Bound departure from the constant template Nonquadratic environmental attenuation Bound it or include an additional nuisance template Setting-dependent sensing response Joint response calibration, including efficiencies and failures Separation uncertainty Derivative or interval propagation with calibrated separation windows Moving branch separation Trajectory-integrated templates, validated before use Different pre-split dynamics Full protocol comparison, not a post-split attenuation insertion Outcome-dependent preparation Retain records; bound windowing and heralding effects constructive theorem requires every relevant departure to enter its residual budget. An independently free offset at each setting invalidates the cancellation rather than merely increasing precision requirements.
propositionProposition: Separation-error propagationPreparation and detector conditions for the control › Residual ledger · En01-B@2#prop:separation · proof attached · lines 1977–2007
Open as its own pageIf and on the corresponding windows, then
For the homogeneous sphere, Gaussian smearing gives , and
For nominal weights cancelling , the quadratic nuisance leakage is at most
Proof. Apply the mean-value theorem termwise. Differentiate (eq:rate) and use . Smearing multiplies the positive moment integral by a factor at most one. The last bound expands .
sectionResidual ledgerPreparation and detector conditions for the control › Residual ledger · lines 2007–2011
Open as its own pageA separation error is therefore not harmless when the cancelled nuisance coefficient is arbitrarily large.
propositionProposition: Finite-width packet diagnosticPreparation and detector conditions for the control › Residual ledger · En01-B@2#prop:packet · proof attached · lines 2012–2033
Open as its own pageLet an isometry embed two orthonormal packets with disjoint supports, each within distance of its centre . For a static dephasing interval , comparison with the two-centre kick model gives trace-distance error at most
Proof. Disjoint supports give
The conjugated state difference is bounded by twice this norm. Integrate the generator residual, propagate it contractively, and divide by two.
sectionResidual ledgerPreparation and detector conditions for the control › Residual ledger · lines 2033–2040
Open as its own pageThe disjoint-support condition is essential to this stated operator norm estimate. Gaussian packets require a tail/truncation certificate. Moving and deforming packets require a propagation certificate, not repeated informal use of the static result.
sectionMoving trajectories and additional nuisance templatesPreparation and detector conditions for the control › Moving trajectories and additional nuisance templates · lines 2041–2070
Open as its own pageSuppose a validated branch description gives
where
Choose weights with
Then Theorem thm:contrast applies with replaced by .
More generally, for a matrix of declared nuisance templates, a nuisance-cancelling linear contrast exists precisely when
One choice is , giving . This is linear algebra on a validated attenuation model, not proof that a branch-trajectory model describes the entire interferometer.
From detector records to log-visibility confidence
sectionThe common terminal detectorFrom detector records to log-visibility confidence › The common terminal detector · lines 2074–2086
Open as its own pageLet be normalized completed sphere–sensor outputs and their common finite-outcome detector channel. For a static squared-position approximation,
where is sub-Markov and principally depends on . Add the no-detection effect to normalize the measurement.
propositionProposition: Accessible distinguishability and heraldingFrom detector records to log-visibility confidence › The common terminal detector · En01-B@2#prop:detector · proof attached · lines 2087–2114
Open as its own pageFor ,
Every fixed event bias is at most this detector total variation. For specified distributions, the positive-difference bins attain it.
If an attempted law is
with the normalized successful detector law, then equal success gives
For unequal success, .
Proof. The measurement output is diagonal, giving the first identity. Positivity and trace preservation contract Hermitian trace norm. The positive signed entries sum to half the absolute sum. For heralding, compare the explicit rejection and success entries.
sectionThe common terminal detectorFrom detector records to log-visibility confidence › The common terminal detector · lines 2114–2124
Open as its own pageThis is the trace-distance measurement principle Helstrom1976, not a license to compare unbounded generators in diamond norm.
Ideal readout preserves position total variation for even densities: folding sends to . An odd density difference is lost. Finite response, binning, and jitter can lose more information.
sectionRoute A: invert calibrated event lawsFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · lines 2125–2130
Open as its own pageThe log contrast is not a bounded single-run statistic. It must not be inserted directly into a per-run Hoeffding bound.
assumptionAssumption: Calibrated visibility responseFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · En01-B@2#ass:visibility · lines 2131–2148
Open as its own pageAt setting , a fixed attempted-run histogram event satisfies
with independently or jointly validated ranges
Preparation acceptance and detection efficiencies are included in the response ranges or estimated jointly from retained flags.
theoremTheorem: Visibility and log-contrast confidence intervalsFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · En01-B@2#thm:logCI · proof attached · lines 2150–2200
Open as its own pageAt settings, use independent attempted runs and empirical event frequencies . Let
With probability at least , all event probabilities lie in these intervals.
On the calibration coverage event, valid visibility enclosures are
If an enclosure is empty, the response model and data are inconsistent at the declared confidence level. Otherwise
The interval for is obtained by selecting lower or upper endpoints according to the sign of each weight. It has simultaneous coverage at least if the calibration event has probability at least .
Proof. Apply two-sided Hoeffding to each event and a union bound. For positive , the response equation implies
Rearrange using the observed probability bounds. The logarithm is monotone, and a signed linear combination of intervals has the stated endpoint rule. Combine the two coverage events by a union bound.
sectionRoute A: invert calibrated event lawsFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · lines 2200–2205
Open as its own pageA lower visibility bound is an application condition, not a numerical convenience. Without it, logarithmic errors can become arbitrarily large.
corollaryCorollary: A transparent sufficient log-contrast budgetFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · En01-B@2#cor:logbudget · proof attached · lines 2206–2236
Open as its own pageSuppose are known, with , and all systematic errors have already been included in the deterministic contrast gap . Estimate by inverting the event law and clipping to . With equal per setting, the empirical contrast error is at most
with probability at least . For the three-setting weights, . Thus
is sufficient to keep this error at most . The total attempted-run count is .
Proof. Clipping is nonexpansive when the true visibility belongs to the clipped interval. The inverse response has Lipschitz constant . On , the log has Lipschitz constant . Sum the three errors and solve the resulting inequality.
sectionRoute A: invert calibrated event lawsFrom detector records to log-visibility confidence › Route A: invert calibrated event laws · lines 2236–2243
Open as its own pageThe midpoint decision orientation must use the corresponding deterministic contrast intervals. Detector calibration uncertainty should use Theorem thm:logCI, rather than silently treating fitted response parameters as exact.
Bounded complete-record certificates
sectionBounded complete-record certificatesBounded complete-record certificates · lines 2245–2259
Open as its own pageFor randomized settings with known probabilities , define
The outcomes include setting labels, preparation records, rejections, and sensing failures. Nuisance parameters are jointly constrained across settings.
For a predeclared , set .
theoremTheorem: Route B: robust bounded-statistic certificateBounded complete-record certificates · En01-B@2#thm:bounded · proof attached · lines 2260–2293
Open as its own pageSuppose
If actual laws are within total variation of the corresponding specified family members, put
For , the midpoint threshold between the two enlarged expectation ranges, applied to independent attempted runs, has each error at most
Consequently
is sufficient for each error to be at most . The reversed orientation is equally valid.
Proof. For , total variation bounds the expectation difference. This follows by integrating the events , . The enlarged ranges are separated by . The threshold is at least from either range. Hoeffding's one-sided bound gives Hoeffding1963.
propositionProposition: Common-statistic feasibilityBounded complete-record certificates · En01-B@2#prop:LP · proof attached · lines 2295–2324
Open as its own pageFor finite recorded alphabets and compact closed convex hulls , a positive common bounded-statistic gap exists if and only if .
For finite lists of family vertices, its optimal gap is the linear program
A finite nuisance grid represents a continuous family only after a uniform interpolation or optimization error is supplied.
Proof. A positive gap survives convexification and excludes an intersection. Disjoint compact convex sets admit a strict separating linear functional. Adding a constant to every coordinate and rescaling puts its coefficients in , since all law vectors sum to one. The displayed program is exactly the finite common-gap optimization.
sectionBounded complete-record certificatesBounded complete-record certificates · lines 2324–2361
Open as its own pageA positive log-contrast margin does not automatically imply a positive single-copy linear-program gap. The logarithm is nonlinear; convexification can introduce intersections not present in the original law families. Route A remains a valid separate inferential construction under its assumptions. Route B is the preferred apparatus-facing certificate when its positive gap has actually been established.
For specified laws, the full-record likelihood ratio is
and their classical Chernoff information is
Endpoint terms use support conventions. This is an asymptotic simple-hypothesis exponent Chernoff1952, not a uniform composite-family certificate.
Local nuisance-rank diagnostics can guide settings. With all probability coordinates retained, define , , and for positive . The nuisance-orthogonal information is
It vanishes precisely when . The normalization constraints are retained in the derivative columns; one must not drop a probability coordinate and then use an unmodified diagonal Fisher weight. This tangent-space condition is not a global exclusion theorem.
Calibration–control trade-offs
sectionCalibration–control trade-offsCalibration–control trade-offs · En01-B@2#tab:tradeoff · lines 2363–2419
Open as its own pageRegime Established result Required next certificate Proportional quadratic responses, Exact interferometer-family overlap Joint external calibration may remove the match Full response close to matched quadratic dynamics Near-obstruction with bound Domain, aperture, sensing and residual errors Nonquadratic response survives nuisance cancellation Signed contrast margin Visibility-response confidence or complete-histogram gap Broad residual spectral nuisance Exact absorption if its spectrum admits the gravity addition Independent constraints excluding that spectrum negative and constructive results have compatible but different hypotheses. No row is an apparatus-specific experimental verdict.
The calibration width can be large while an ideal log contrast still cancels the quadratic nuisance. Nevertheless, larger attenuation lowers and increases the required sample count. Cancellation of a nuisance coefficient is not cancellation of its cost to visibility.
Additional settings help only when their validated response is transverse to the admitted nuisance templates. A time-only scan of
has proportional derivatives and cannot distinguish the two coefficients. A separation scan likewise fails in a purely quadratic model. The three-setting construction exploits the exact sphere's nonquadratic response, not the number of settings alone.
If each setting admits a free offset , choose . This matches all diagnostic visibilities and eliminates the proposed positive identification. Likewise a flat response eliminates visibility information at the detector even when the underlying contrast is nonzero.
Existing radiation constraints and interpretation
sectionExisting radiation constraints and interpretationExisting radiation constraints and interpretation · lines 2421–2448
Open as its own pageRadiation limits apply to a universal microscopic collapse model with the corresponding charge dynamics, noise spectrum, mass smearing, and normalization. They are not automatically limits on a continuous macroscopic rigid-body prescription.
Donadi and collaborators excluded the natural prescription considered in their underground radiation study Donadi2021. Their displayed coefficient is times (eq:DP)'s coefficient. The XENONnT analysis reports a source-native
95\%lower bound m for its Markovian DP model and includes charge-cancellation effects XENON2026. These limits cannot be transferred by replacing a macroscopic sphere radius or packet width with the microscopic cutoff.A source template proportional to permits a cubic-strength rescaling only when that template remains valid throughout the scan. When the spectral shape changes, the full external likelihood must be used. A prospective study should show separately the applicable external exclusion set, the certified interferometer sensitivity set, and their difference. This article produces no physical numerical exclusion contour.
Conclusion and submission boundary
sectionConclusion and submission boundaryConclusion and submission boundary · lines 2450–2484
Open as its own pageThe paired contribution is precise. A calibrated common force-noise amplitude leaves an exact quadratic family-overlap region under a declared proportionality condition. Centre-of-mass heating of matched total generators cannot identify the source. Beyond the quadratic approximation, a full-protocol near-obstruction requires operator-level and implementation error bounds.
Conversely, three proposed separations cancel a shared constant and quadratic attenuation while retaining a nonquadratic continuous-sphere response. Its coefficient is evaluated exactly. Gaussian regularization preserves its sign at every finite width, and an explicit uniform magnitude certificate is available for . The positive conclusion survives only below the stated residual margin.
The constructive attenuation theorem is not yet a validation of the reference apparatus's three-setting operation. Actual sensitivity requires calibrated preparation laws, transfer functions, detector response, and uniform propagation errors. The paper supplies the mathematical certificates and a reproducible test artifact; it does not invent those empirical inputs.
No result is imported from characteristic-product, free-shell, retarded-graph, or field-theory admission programmes. A positive detector certificate would not resolve their separate analytic obligations. No Born-rule uniqueness result, ultraviolet completion, or experimental gravity measurement is claimed.
Regression artifact, evidence, and execution status
sectionRegression artifact, evidence, and execution statusRegression artifact, evidence, and execution status · lines 2486–2529
Open as its own pageThe embedded program checks:
exact interval-overlap boundaries;
independently assembled matched quadratic generators in a synthetic seven-label protocol;
the matched total heating coefficient;
constant and quadratic nuisance cancellation;
the rational sphere contrast;
the exact-rational uniform small-smearing lower certificate;
separation-error and visibility-to-log interval propagation;
a bounded common event gap for complete synthetic histograms;
negative controls: quadratic gravity, free preparation offsets, and a flat detector.
The default spectral integrations are floating-point diagnostics. They are not labelled validated continuum computations. The optional
–validatedcalculation encloses using exact rational nodal intervals and Proposition prop:quadrature. Its printed decimal endpoints are presentations of the enclosing rational numbers recorded in the manifest.The staged matrix model is synthetic. Its Hamiltonians, units, packet, instruments, and efficiencies are not the reference apparatus. The survival of exact matching in this regression illustrates the written theorem but is not its proof.
Optional Matplotlib output includes:
regularized contrast diagnostics with the analytic certified small-width region;
the quadratic overlap surface versus strength and regularization;
complete synthetic histograms;
a hypothetical log-contrast sample budget versus calibration width.
A successful local invocation writes the SHA-256, environment, execution time, and results in
En01-B-run.json. No invocation or compilation is claimed here.listingListing: ListingRegression artifact, evidence, and execution status · lines 2530–2535
Open as its own pagepdflatex En01-B.tex pdflatex En01-B.tex python En01-B-check.py python En01-B-check.py --validatedsectionRegression artifact, evidence, and execution statusRegression artifact, evidence, and execution status · lines 2535–2543
Open as its own pageThe build-computed generated-script MD5 identifier is:
fileEn01-B-check.pyThis fingerprints generated bytes; it is not a proof or security certificate.
Corrections and assumption audit
sectionCorrections and assumption auditCorrections and assumption audit · lines 2549–2586
Open as its own pageUndefined state-label notation is replaced by explicit or named quantities.
Continuous instruments are defined through their integrated maps; an outcome density is not incorrectly required to be trace nonincreasing pointwise.
The scalar calibrated obstruction establishes overlap, not whole-family containment.
Matching is required across stages, controls, and histories; proportionality is not inferred from a generic force-noise label.
Raw external calibration and interval-constrained inference are different experiments.
Heating denotes the diffusion contribution unless other dynamical contributions have been subtracted.
The homogeneous-sphere nonquadratic coefficient is exactly .
Regularized sign is proved for the complete integral, not inferred from selected spectral nodes.
Numerical sign certificates retain quadrature, tail, nodal, and parameter-cell errors.
Packet operator-norm estimates explicitly require disjoint supports and an isometric embedding.
Nominal separation cancellation does not remove uncertainty in the actual squared-separation template.
Positive log contrast is not automatically a positive single-copy bounded-statistic gap.
Log-confidence propagation requires a positive visibility floor and positive calibrated detector sensitivity.
Fisher weighting uses complete constrained probability coordinates, or an appropriately transformed reduced metric.
All statistical sample counts refer to attempted runs; calibration coverage, success probabilities, reset time, and correlations require separate accounting.
No numerical or compiler execution record is fabricated.
bibliographyReferencesCorrections and assumption audit · lines 2587–2653
Open as its own pagePino2018
H. Pino, J. Prat-Camps, K. Sinha, B. P. Venkatesh, and O. Romero-Isart, On-chip quantum interference of a superconducting microsphere, Quantum Science and Technology 3, 025001 (2018). doi:10.1088/2058-9565/aa9d15. Reference version: arXiv:1603.01553v3.
En01A
N. Cheung, Accessible Interference in Recorded Quantum Circuits: Exact Interfaces, Record Architecture, and Collapse-Model Hierarchies, author-supplied manuscript
En01-A.tex. Conceptual predecessor; no tower-specific result is assumed here.Bahrami2014
M. Bahrami, A. Smirne, and A. Bassi, Role of gravity in the collapse of a wave function: A probe into the Diósi–Penrose model, Physical Review A 90, 062105 (2014). doi:10.1103/PhysRevA.90.062105. arXiv:1408.6460.
TilloyDiosi2017
A. Tilloy and L. Diósi, Principle of least decoherence for Newtonian semiclassical gravity, Physical Review D 96, 104045 (2017). doi:10.1103/PhysRevD.96.104045. arXiv:1706.01856.
Donadi2021
S. Donadi, K. Piscicchia, C. Curceanu, L. Diósi, M. Laubenstein, and A. Bassi, Underground test of gravity-related wave function collapse, Nature Physics 17, 74–78 (2021). Published online 7 September 2020. doi:10.1038/s41567-020-1008-4. arXiv:2111.13490.
XENON2026
E. Aprile et al. (XENON Collaboration), Challenging Spontaneous Quantum Collapse with XENONnT, Physical Review Letters 136, 120201 (2026). doi:10.1103/2jm3-4976. Reference version: arXiv:2506.05507v2.
Helstrom1976
C. W. Helstrom, Quantum Detection and Estimation Theory, Academic Press, New York (1976).
Hoeffding1963
W. Hoeffding, Probability inequalities for sums of bounded random variables, Journal of the American Statistical Association 58, 13–30 (1963). doi:10.1080/01621459.1963.10500830.
Chernoff1952
H. Chernoff, A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations, Annals of Mathematical Statistics 23, 493–507 (1952).