Tuning a magnetic energy scale with pressure and field in UTe2
Bibliographic record
Abstract
When a fragile ordered state is suppressed to zero temperature, a quantum phase transition occurs, which is often marked by the appearance of unconventional superconductivity. While the quantum critical point can be hidden, the influence of the quantum criticality extends to fairly high temperatures, manifesting non-Fermi liquid behavior in a wide range of the field-temperature-pressure phase space. Here, we report the tuning of a magnetic energy scale in the heavy-fermion superconductor UTe2, previously identified with a peak in the c-axis electrical transport temperature dependence, using applied hydrostatic pressures and a-axis-oriented magnetic fields as complementary (and opposing) tuning parameters: the characteristic peak in c-axis resistivity decreases in temperature with applied pressure before vanishing near the critical pressure of 15 kbar (1.5 GPa), while the application of field shifts the peak to a higher temperature and broadens it under all studied pressures. At the critical pressure, the transport behavior deviates from Fermi liquid behavior, exhibiting a nearly linear temperature dependence of resistivity with an enhanced pre-factor. Our results shed light on the microscopic origin of the c-axis resistivity peak and provide a clear picture of magnetic energy scale evolution relevant to quantum criticality in UTe2. The heavy-fermion superconductor UTe2 has attracted recent interest for its novel superconducting phases, tunable by pressure and magnetic field. Here, a systematic study of anisotropic resistivity indicates an influence of quantum criticality that may be important to unconventional superconductivity in this compound.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".