Ultraviolet/infrared mixing-driven suppression of Kondo screening in the antiferromagnetic quantum critical metal
Bibliographic record
Abstract
We study a magnetic impurity placed in the two-dimensional antiferromagnetic quantum critical metal (AFQCM), using the field-theoretic functional renormalization group. Critical spin fluctuations represented by a bosonic field compete with itinerant electrons to couple with the impurity through the spin-spin interaction. At long distances, the antiferromagnetic electron-impurity (Kondo) coupling dominates over the boson-impurity coupling. However, the Kondo screening is weakened by the boson with increasing severity as the hot spots connected by the magnetic ordering wave vector are better nested. For ${v}_{0,i}\ensuremath{\ll}1$, where ${v}_{0,i}$ is the bare nesting angle at the hot spots, the temperature ${T}_{K}^{\mathrm{AFQCM}}$ below which Kondo coupling becomes $O(1)$ is suppressed as $\frac{log\mathrm{\ensuremath{\Lambda}}/{T}_{K}^{\mathrm{AFQCM}}}{log\mathrm{\ensuremath{\Lambda}}/{T}_{K}^{\mathrm{FL}}}\ensuremath{\sim}\frac{{g}_{f,i}}{{v}_{0,i}log1/{v}_{0,i}}$, where ${T}_{K}^{\mathrm{FL}}$ is the Kondo temperature of the Fermi liquid with the same electronic density of states, and ${g}_{f,i}$ is the boson-impurity coupling defined at UV cutoff energy $\mathrm{\ensuremath{\Lambda}}$. The remarkable efficiency of the single collective field in hampering the screening of the impurity spin by the Fermi surface originates from ultraviolet/infrared (UV/IR) mixing: bosons with momenta up to a UV cutoff actively suppress Kondo screening at low energies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".