How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Frame change of a declared protocol: how the prediction map and an additive error transform between two inertial frames
A worked conditional computation of the frame behaviour of one declared protocol: a protocol whose readout is the position of one label at one observation time is described in a second inertial frame, and the prediction map and the additive error are transformed by the displayed affine law. The item asserts no measured position, no measured error and no frame-independent reading; it records that the prediction map and the error model are frame-relative data of a protocol.
Example
Fix one particle label (), the force branch and a model as in Operational observable model of the force branch: parameters, preparations, observation times, readout, units and additive error, and fix two inertial frames , of the model with adapted coordinates and . By Galilean transformation of worldlines: velocity and acceleration laws, frame-independence of zero coordinate acceleration, and the group of frame changes there are , and with
The protocol in . Take a protocol of Operational observable model of the force branch: parameters, preparations, observation times, readout, units and additive error with a single observation time and the position readout of dimension , read in metres (Dimensions and SI unit conventions of the non-relativistic classical mechanics framework); the observation is for an error random element on a probability space .
Domains under the coordinate change. The transformed configuration set at time is , so the transformed time-configuration domain is open (it is the image of under the invertible affine frame change). It need not be a product with one fixed configuration set, for example when a boost translates bounded . The following formulas always describe the coordinates of the same worldline and recorded events. They define a force-branch protocol in only when the transformed model has an admissible fixed-domain presentation, in particular when ; no fixed-domain model is asserted in the general moving-domain case.
The coordinate readout in . The same event at which the readout is taken has -time ; reading the same label position in at that time defines the transformed prediction map on the same parameter/preparation labels, and the -coordinates of the recorded point are so the additive-error form is preserved with the rotated error and the transformed open error domain , which contains and contains every value of .
Transform of the error law. Suppose is square-integrable with mean and covariance matrix in the sense of Mean vector and covariance matrix of a square-integrable random vector. Then has mean and covariance and in the Euclidean norm because is orthogonal. In particular an additive error declared in one frame need not have the same law in another: its law is the pushforward under , which equals the original law precisely when that law is invariant under this rotation, and the prediction map acquires the known affine term . A protocol must declare the frame of its readout and of its error model.
Facts & Assumptions
Given: Two inertial frames , with the transformation of Galilean transformation of worldlines: velocity and acceleration laws, frame-independence of zero coordinate acceleration, and the group of frame changes, a protocol with the single position readout , and a square-integrable error with mean and covariance .
The transformation law between the two frames is and for every event , with , and ; the parameters have dimensions , , and is dimensionless (Galilean transformation of worldlines: velocity and acceleration laws, frame-independence of zero coordinate acceleration, and the group of frame changes, Inertial frames, stationary observers and the adopted Galilean transformations between frames, Dimensions and SI unit conventions of the non-relativistic classical mechanics framework).
A continuous map preimage of a Borel set is Borel, and composing a random element with a Borel map gives a random element: for the continuous affine map one has Borel for Borel , and (A measurable function between measurable spaces, A continuous map has Borel preimages of Borel sets, Random elements and real random variables).
For a square-integrable random vector with mean and covariance and a linear map , the affine map applied to has covariance (The covariance of the linearization is , Mean vector and covariance matrix of a square-integrable random vector); expectations of integrable components are linear and the components of a linear image are finite linear combinations of integrable components (Linearity, monotonicity, and the modulus bound for expectation).
Verification
The worldline of the label described in satisfies for by [L1] applied to the events of the worldline; the readout event in has -time , hence -time , and evaluating at gives .
Square-integrability of and the hypothesis give for every , and the components of are finite linear combinations of the integrable components , so by linearity of expectation of the components [L3]; for the covariance, [L3] applied to , and the affine map (whose derivative is at every point) gives , and orthogonality of gives for every , hence equality of the norms of and pointwise.
The recorded point has -coordinates by the same transformation law applied to the observed event, and substituting together with step 1.1 gives ; the rotated error is a random element of by [L2], since is linear and continuous and addition of the constant vector is a translation.
The computation is a transformation of declared protocol data; it asserts nothing about which frame an apparatus realizes, no measured position and no measured error, and it shows that the prediction map and the error model of Operational observable model of the force branch: parameters, preparations, observation times, readout, units and additive error are frame-relative and that a change of frame applies to both, with the affine shift and the rotation of the error.
Depends on
Operational observable model of the force branch: parameters, preparations, observation times, readout, units and additive error
Galilean transformation of worldlines: velocity and acceleration laws, frame-independence of zero coordinate acceleration, and the group of frame changes
Inertial frames, stationary observers and the adopted Galilean transformations between frames
Mean vector and covariance matrix of a square-integrable random vector
The covariance of the linearization is
Dimensions and SI unit conventions of the non-relativistic classical mechanics framework
Random elements and real random variables
A measurable function between measurable spaces
A continuous map has Borel preimages of Borel sets
Linearity, monotonicity, and the modulus bound for expectation
Dependency tree · 2 levels
Sources
- D. Tong, Dynamics and Relativity (Cambridge lecture notes, Lent 2013), Section 1.2.1, printed page 5 (PDF page 11): the Galilean transformations t' = t + b, x' = Rx + vt + a between inertial frames
- K. K. Likharev, Essential Graduate Physics, Part CM: Classical Mechanics (title page last edited September 1, 2026), Section 1.1 point (v), chapter pages 2-3 (PDF pages 6-7): the transfer of the radius vector and of velocity and acceleration between frames, with the warning that rotating frames require more care
- JCGM 100:2008, Evaluation of measurement data - Guide to the expression of uncertainty in measurement (BIPM, 2008 corrected version), clauses 5.1.2 and 5.2.2, equations (10) and (13): propagation of covariance through a linear relation, used here for the rotating error