Cross-calibration of atomic pressure sensors and deviation from quantum diffractive collision universality for light particles
Bibliographic record
Abstract
Abstract The room-temperature, velocity-averaged, total cross section for atom–atom and atom–molecule collisions can be approximated using a universal function depending only on the magnitude of the leading order dispersion coefficient, C 6 . This feature of the total cross section together with the universal function for the energy distribution transferred by glancing angle collisions ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mi>p</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>QDU6</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:math> (Booth et al 2019 New J. Phys. 21 102001)) can be used to empirically determine the total collision cross section and realize a self-calibrating, vacuum pressure standard. This was previously validated for Rb+N 2 and Rb+Rb collisions. However, the post-collision energy distribution is expected to deviate from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mi>p</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>QDU6</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:math> in the limit of small C 6 and small reduced mass. Here we observe this deviation experimentally by performing a direct cross-species loss rate comparison for Rb+H 2 and Li+H 2 collisions. We measure a velocity averaged total collision cross section ratio of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>R</mml:mi> <mml:mo>=</mml:mo> <mml:mo fence="false" stretchy="false">⟨</mml:mo> <mml:msub> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>tot</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> <mml:mi>v</mml:mi> <mml:mrow> <mml:msub> <mml:mo fence="false" stretchy="false">⟩</mml:mo> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mtext>Li+H</mml:mtext> </mml:mrow> </mml:mrow> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> <mml:mo>:</mml:mo> <mml:mo fence="false" stretchy="false">⟨</mml:mo> <mml:msub> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>tot</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> <mml:mi>v</mml:mi> <mml:mrow> <mml:msub> <mml:mo fence="false" stretchy="false">⟩</mml:mo> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mtext>Rb+H</mml:mtext> </mml:mrow> </mml:mrow> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> <mml:mo>=</mml:mo> <mml:mn>0.83</mml:mn> <mml:mo stretchy="false">(</mml:mo> <mml:mn>5</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:math> . Based on an ab initio computation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo fence="false" stretchy="false">⟨</mml:mo> <mml:msub> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>tot</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> <mml:mi>v</mml:mi> <mml:mrow> <mml:msub> <mml:mo fence="false" stretchy="false">⟩</mml:mo> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mtext>Li+H</mml:mtext> </mml:mrow> </mml:mrow> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> <mml:mo>=</mml:mo> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>3.104</mml:mn> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>15</mml:mn> </mml:mrow> </mml:msup> </mml:math> m 3 s −1 , we deduce <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo fence="false" stretchy="false">⟨</mml:mo> <mml:msub> <mml:mi>σ</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>tot</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> <mml:mi>v</mml:mi> <mml:mrow> <mml:msub> <mml:mo fence="false" stretchy="false">⟩</mml:mo> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mtext>Rb+H</mml:mtext> </mml:mrow> </mml:mrow> <mml:mn>2</mml:mn> </mml:msub> </mml:mrow> </mml:msub> </mml:mrow> <mml:mo>=</mml:mo> <mml:mn>3.6</mml:mn> <mml:mo stretchy="false">(</mml:mo> <mml:mn>2</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mo>×</mml:mo> <mml:msup> <mml:mn>10</mml:m
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".