Hidden orders in spin–orbit-entangled correlated insulators
Bibliographic record
Abstract
In many materials, ordered phases and their order parameters are easily characterized by standard experimental methods. ‘Hidden order’ refers to a phase transition in which an ordered state emerges without such an easily detectable order parameter, despite clear thermodynamic evidence of the transition. The underlying mechanisms for these unconventional states of matter stem from spin–orbit coupling, which intertwines intersite exchange, classical electron–magnetic interactions and electron–lattice effects. This physics is elusive to experimental probes and beyond traditional theories of insulating magnetism, requiring sophisticated methodologies for its exploration. In this Review, we survey exotic hidden-order phases in correlated insulators, particularly focusing on the latest progress in material-specific theories and numerical approaches. The relevant degrees of freedom in these phases are local high-rank multipole moments of magnetic and charge density that emerge from spin–orbit-entangled correlated shells of heavy d and f electron ions and interact on the lattice via various mechanisms. We discuss approaches to modelling hidden orders in realistic systems via direct ab initio calculations or by constructing low-energy many-body effective Hamiltonian. We also describe how these new theoretical tools have helped to uncover driving mechanisms for recently discovered multipolar phases in double perovskites of heavy transition metals and how they have proved instrumental in disentangling the role of various interactions in ‘traditional’ f-electron multipolar materials such as actinide dioxides. In both cases, material-specific theories have played a key part in interpreting and predicting experimental signatures of hidden orders. Hidden orders involve phase transitions without obvious order parameters, challenging experimental detection and conventional theories. This Review summarizes recent advances in modelling hidden-order phases in correlated insulators, highlighting the role of material-specific theories in the interpretation and prediction of the experimental signatures of hidden orders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".