Magneto-elasto-resistivity in FeSe

arXiv:2512.16796 · cond-mat.supr-con · Submitted 2025-12-18 · Read on arXiv

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Introduction to the show: ident: Quantum Radio. Generated commentary on the latest quantum physics and condensed matter papers.

Kai: I'm Kai, and with me are Mira and Lev, guest researcher.

Mira: Today's paper: "Magneto-elasto-resistivity in FeSe".

Kai: FeSe stands out among iron-based superconductors due to its extended nematic phase without long-range magnetic order,

Mira: First, who's behind it and why it matters.

Title and authors: Kai: So, we're diving into this paper today on "Magneto-elasto-resistivity in FeSe," which sounds really specific to probing how structure and magnetism interact in these iron-based superconductors. Mira, what stood out to you about the title and who was behind this work?

Mira: Well, the title itself points directly at something that's been a bit of an understudied area: magneto-elasto-resistivity. It suggests they are looking at how applying a magnetic field affects the strain-dependent electrical resistivity, which is really important because it helps us understand the nematic phase without long-range magnetic order. The authors are M. Wissmann, L. Fanfarillo, X.-C. Hong, S. Caprara, S. Aswartham, B¨uchner and C. Hess from various institutions across Germany and France in this paper; it shows a nice collaboration between different groups studying these materials one <ref:2512.16796#pg0>.

Lev: From a quantum error-correction standpoint, the fact that they are using strain to probe nematicity is interesting because strain couples directly to the lattice structure, which we know is sensitive. If we can understand how magnetic fields modify this coupling, it gives us more constraints on how external perturbations affect the underlying electronic states TandemQEC.

Kai: Exactly. So what's the big picture they're trying to show with this investigation into FeSe? What are they actually measuring and what did they find in terms of those key transport properties?

Mira: The paper summarizes that it presents measurements of magneto-elasto-resistivity in FeSe across a range of temperatures and applied magnetic fields. They used a minimal multiband Boltzmann model for transport, which allowed them to derive analytical expressions that successfully capture the magnetic behavior observed experimentally in both the paramagnetic and nematic phases

cond-mat.supr-con#pg0: . Basically, they are using this theoretical framework to describe how the material responds under these combined stimuli.

Lev: That minimal multiband model is key here because it sets up a way to connect microscopic band physics to macroscopic transport measurements, which is exactly what we need when trying to simulate things on hardware Quantum Algorithms for Heterogeneous PDEs. It’s about bridging that gap between the theoretical description and what we might actually see in a system.

Kai: That makes sense. So, if I'm following the summary of "Magneto-elasto-resistivity in FeSe," what are the most important experimental results they highlighted? What did they actually measure with those probes?

Mira: The results highlight two main things derived directly from their analytical expressions: first, there's a field-independent behavior above the structural transition temperature TS when using out-of-plane fields, which is a significant finding

cond-mat.supr-con#pg1: . Second, they found that for in-plane fields—those perpendicular to the c-axis—there is no magnetic field dependence at all, which is quite restrictive.

Title and authors: Lev: That lack of field dependence in one orientation suggests a specific symmetry or coupling mechanism is dominating those transport channels at that level Local decoders for fault-tolerant quantum computation and translation-invariant stabilizer codes. It tells us where we might look for the most stable physical descriptions.

Kai: So, when they talk about the zero-field ER, what's their view on that baseline measurement, and how does it connect to what we already know about FeSe?

Mira: They found that the zero-field elastoresistivity is consistent with existing literature but noted a Curie-Weiss temperature of T* around seventy-one K above TS. Below the transition temperature, they observed that the ER drops and even becomes negative for temperatures below fifty K, which is interesting behavior

cond-mat.supr-con#pg2: .

Lev: A negative resistivity value is a strong signal; it implies some kind of unconventional response in the transport mechanism at those lower temperatures, maybe related to the pairing symmetry or fluctuation effects Stochastic trajectories and excursions in a double quantum dot system. It’s definitely worth checking how that manifests on real hardware.

Kai: Moving on to the magnetic field application, what did they find when they applied those fields below the transition temperature? What was the most surprising result there?

Mira: Below TS, applying a magnetic field causes the magneto-elasto-resistivity to strongly increase towards positive values and shows a pronounced upturn as it gets colder

cond-mat.supr-con#pg2: . That upturn is specifically attributed by them to superconducting fluctuations near the superconducting critical temperature TC, which adds another layer of complexity

cond-mat.supr-con#pg2: .

Lev: So they are linking the magnetic field effect directly to fluctuation effects near the superconducting state, which is a very specific kind of physics we need to model carefully for any quantum simulation TandemQEC. It means the model has to account for that thermal and phase transition interplay.

Kai: This paper seems really focused on showing how a simple multiband model can handle these complex magnetic field dependencies. What kind of suggestions or improvements do the authors offer to their analysis or the overall approach?

Mira: The conclusion is quite strong here: they argue that a minimal two-band model is sufficient to reproduce the essential magneto-elasto-transport features in FeSe

cond-mat.supr-con#pg1: . They explicitly state that while orbital effects are important microscopically, they aren't crucial for achieving a consistent description within this framework

cond-mat.supr-con#pg1: .

Title and authors: Lev: That’s an important limitation to note for anyone building simulations; it suggests we can capture the main physics without needing to model every single orbital state explicitly, which simplifies things immensely for error correction simulations Hamiltonian-Level Certificate for Network-Free Distributed Quantum Simulation. It shows a pathway to tractable modeling.

Kai: So, they are essentially saying that this minimal model works well enough to describe Hall resistivity, magnetoresistance, and MER consistently

cond-mat.supr-con#pg1: . What does this mean for the wider field of iron-based superconductor research?

Mira: It means the approach is robust enough to capture how magnetic fields influence strain response in this class of materials

cond-mat.supr-con#pg1: . They also found that in-plane fields yield a MER that is independent of the magnetic field at all temperatures, which is quite a specific constraint

cond-mat.supr-con#pg2: .

Lev: That independence from the in-plane field is something we should use as a benchmark when designing experiments or simulations for related systems; it helps us narrow down the physical variables that actually matter for the response Quantum nonclassicality from causal data fusion.

Kai: It sounds like they've given us a solid analytical tool to predict how strain and magnetic fields interact in FeSe. So, to wrap up this discussion on "Magneto-elasto-resistivity in FeSe," what are the final thoughts on the implications of this study?

Mira: The implication is that we have a better handle on the interplay between nematicity, magnetism, and superconductivity by measuring MER

cond-mat.supr-con#pg2: . It provides a new experimental handle complementary to strain measurements alone

cond-mat.supr-con#pg2: .

Lev: For error correction researchers, having a model that successfully predicts the field dependence of MER in this context is valuable because it gives us concrete parameters to test against when we start designing protocols for fault-tolerant quantum computation TandemQEC. It moves the discussion from abstract theory to something measurable.

Kai: I think that's a big step forward because it shows that focusing on these coupled transport measurements yields consistent, predictable results even when dealing with complex phenomena like nematicity and fluctuations in FeSe

cond-mat.supr-con#pg1: .

Mira: Indeed, and the fact that they successfully used a minimal model suggests that we don't always need the most complicated microscopic details to capture the essential physics of these superconductors

cond-mat.supr-con#pg1: .

Lev: I'm just glad we can get this kind of consistent analytical framework established for these materials; it’s hard to build scalable quantum systems on top of highly complex, poorly understood condensed matter physics Quantum Algorithms for Heterogeneous PDEs.

Kai: It was a really detailed look at how the magnetic field modifies the strain response in FeSe using this magneto-elasto-resistivity measurement

cond-mat.supr-con#pg0: . That’s what we've covered on this paper.

The paper's summary: Kai: So, to recap the core finding of "Magneto-elasto-resistivity in FeSe," they managed to use a minimal two-band model to successfully describe how magnetic fields affect the strain response in this iron-based superconductor across different temperatures and field orientations.

Mira: Exactly, it boils down to showing that even with just two bands, you can capture the essential physics of both nematic order and magnetic field effects on transport by focusing on that magneto-elasto-resistivity measurement. This is significant because it means we don't need overly complex microscopic details about orbital composition to get a consistent picture of what's happening when you poke these materials with strain and magnets.

Lev: From my side, the fact that the model works with just two bands gives us a much more tractable starting point for simulation; it suggests that we can build protocols for error correction on this system using fewer degrees of freedom than if we had to map out every single band structure explicitly.

Kai: That tractability is what really interests me from an experimentalist's point of view, because if the theory works so well with a minimal setup, it gives us better targets for what to measure next in the lab. What about those specific results they highlighted regarding the field independence?

Mira: They pointed out two major things: first, they found that when you use out-of-plane magnetic fields, the magneto-elasto-resistivity actually doesn't change above the structural transition temperature TS, which is a pretty clean result to pin down. Second, for in-plane fields—those applied perpendicular to the c-axis—the result remains completely independent of the magnetic field at all temperatures.

Lev: That independence from in-plane fields is something I think would be crucial for quantum hardware design; it tells us that certain physical couplings are totally decoupled from those specific transport channels under those orientations, which simplifies the noise profile we need to model.

Kai: So, they're saying that these clean field dependencies provide a solid benchmark against which we can test other theoretical frameworks or even compare them against what our experimental probes are actually showing us in real-time.

Mira: Precisely; it gives us a way to see if the minimal model holds up when we introduce more complex physics, like those superconducting fluctuations near the critical temperature TC, which they showed contribute to a noticeable upturn below TS.

Lev: That fluctuation contribution is what really ties everything together for me because modeling phase transitions and fluctuations simultaneously is where the real difficulty lies in running simulations that aim for fault tolerance.

Kai: It sounds like this paper gives us a powerful new analytical tool that connects structural strain, magnetic fields, and electronic transport in FeSe in a very predictable way. What does this mean for the broader field of iron-based superconductors?

Mira: It suggests that we can use magneto-elasto-resistivity as a powerful complementary probe alongside traditional strain measurements to better understand the interplay between magnetism and superconductivity in these materials.

Lev: For quantum error correction researchers, having a model that successfully predicts how magnetic fields modify the strain response means we have concrete parameters to test against when we start designing protocols for fault-tolerant quantum computation on these superconducting platforms.

Kai: It’s encouraging because it shows that focusing on this specific transport measurement yields consistent, predictable results even when dealing with complex phenomena like nematicity and fluctuations in FeSe. Where do you think they should go from here?

Mira: I think the next step is to use these derived parameters to generate hypotheses about the origin of nematicity itself, trying to distinguish between structural ordering versus spin-fluctuation driven effects.

Lev: If we can successfully model this response analytically, it provides a blueprint for how we might approach modeling other correlated electron systems where strain and magnetic fields are both key experimental levers.

The paper's improvements: Kai: So, moving on from the findings, what are the suggestions or improvements the authors propose for this work? Mira, can you pin down what they think is missing or where they see room for future development in their approach?

Mira: They suggest that while their minimal two-band model is sufficient to capture these essential features, there's still a lot of room to refine how they handle the temperature dependence phenomenologically. They specifically flag that the treatment of temperature effects isn't fully rigorous, and they think further work should focus on better connecting those fitting parameters directly to microscopic physical mechanisms rather than treating them purely as empirical constants.

Lev: I agree with Mira; from a simulation standpoint, relying on phenomenological fits is risky because it doesn't give you the predictive power you need when scaling up to more complex systems. If we could move toward a model where those coefficients c0, c1, c2 and others are derived directly from first principles rather than being fitted to data, that would be much better for building reliable error correction protocols.

Kai: That's where my experimental experience comes in; if the theory gets even a little closer to connecting the parameters back to lattice dynamics or specific electronic states, it gives us a clearer target for what we should be looking at next when we set up our next set of measurements. What about those limitations they mentioned regarding orbital effects?

Mira: They are quite clear: they acknowledge that orbital effects are important microscopically, but their current framework effectively absorbs them into the band conductivities used for fitting. The improvement suggested is to create a system where you can explicitly test whether adding those orbital details actually changes the essential magneto-elasto-transport features, instead of just ignoring them in the fit.

Lev: That’s a good direction; testing model robustness is key for any serious theoretical framework we use for quantum simulations. If we can define criteria to tell when a minimal model is truly sufficient versus when we absolutely need that extra layer of complexity, it helps us manage computational resources better.

Kai: So, the focus shifts from just getting a good fit to building a system that can validate the underlying physics by testing those limits. It sounds like they are advocating for a more principled way to build these transport models rather than just fitting curves.

Mira: Exactly; it’s about moving away from treating things as black boxes and toward creating a framework where we can see how the microscopic assumptions dictate the macroscopic behavior, which is vital for understanding complex correlated systems like FeSe.

Conclusion: Kai: So, to wrap up this discussion on "Magneto-elasto-resistivity in FeSe," we've seen how this work uses a minimal two-band model to successfully map out the magnetic field effects on strain response in iron-based superconductors.

Mira: That’s right; the core of the paper is showing that even a simple theoretical framework can capture these complex transport features by focusing on magneto-elasto-resistivity measurements across different temperature regimes and magnetic orientations.

Lev: For me, this is really significant because it provides us with a concrete analytical tool to test against when we start designing protocols for error correction on these superconducting platforms.

Kai: It’s exciting to see how the experimental setup—using strain and magnets in FeSe single crystals—yielded results that fit so neatly into this theoretical structure.

Mira: Precisely, and the fact that they managed to show consistency across different field orientations really strengthens the underlying assumptions of their minimal model.

Lev: If we can establish this kind of predictive power, it gives us a blueprint for modeling other correlated electron systems where strain and magnetic fields are both key experimental levers.

Kai: It sounds like we have a solid foundation now to look at how these physical constraints might translate into quantum simulation requirements. What's next on our list?

Mira: We should probably keep an eye on their suggestion to rigorously test the model against more complex microscopic details, especially regarding those orbital effects they mentioned.

Lev: I agree; that validation step is what separates a good paper from one that truly helps push the field forward for scalable quantum systems.

Kai: It was really a detailed look at how the magnetic field modifies the strain response in FeSe using this magneto-elasto-resistivity measurement.

Mira: Indeed, and it shows that focusing on these coupled transport measurements yields consistent results even when dealing with complex phenomena like nematicity and fluctuations in FeSe.

Lev: Moving forward, having a model that successfully predicts the field dependence of MER in this context means we have concrete parameters to test against when we start designing protocols for fault-tolerant quantum computation.

IFW Dresden Institut f¨ur Festk¨orper- und Materialphysik Technische Universitat Dresden University Grenoble Alpes CNRS CEA Grenoble-INP Spintec Istituto dei Sistemi Complessi CNR Sapienza Universit`a di Roma Institut f¨ur Physik Brandenburg Technical University

cond-mat.supr-con

Submitted: 2025-12-18

Updated: 2025-12-19

DOI: 10.1103/qq37-26x6

License: http://creativecommons.org/licenses/by-nc-nd/4.0/

Importance score: 73/100

The gist: FeSe stands out among iron-based superconductors due to its extended nematic phase without long-range magnetic order, and this work presents measurements of magneto-elasto-resistivity in FeSe as a

Key concepts

Nematic Phase
FeSe exhibits a nematic phase below TS, which is a state of electronic order without long-range magnetic ordering. This paper studies how this nematic state affects electrical resistance and strain response under magnetic fields.
Magneto-Elasto-Resistivity (MER)
MER measures how the electrical resistivity changes when both temperature and applied strain are varied in the presence of a magnetic field. It is used here to probe the magnetic behavior within FeSe, particularly below its structural transition temperature.
Minimal Multiband Boltzmann Model
This theoretical framework describes electron transport in FeSe by treating it as a system with multiple electronic bands. It incorporates nematic order by introducing an anisotropy in band conductivities, allowing the model to predict how magnetic fields influence resistivity and strain.
Out-of-Plane vs. In-Plane Fields
The study distinguishes between magnetic fields applied parallel (out-of-plane) and perpendicular (in-plane) to the crystal's c-axis. The results show that out-of-plane fields are field independent above TS, whereas in-plane fields result in a MER that is completely independent of the magnetic field at all temperatures.

Terminology

Summary

FeSe stands out among iron-based superconductors due to its extended nematic phase without long-range magnetic order, and this work presents measurements of magneto-elasto-resistivity in FeSe as a function of temperature and applied magnetic field, deriving analytical expressions that capture the magnetic behavior of the whole set of experimental data both in the paramagnetic and in the nematic phase.

Experimental Setup and Measurements

The researchers synthesized FeSe single crystals and performed magneto-transport measurements using home-made probes inserted into an Oxford Instruments cryostat equipped with a 15/17 T magnet. The transport characterization utilized a standard 4-wire configuration with 50 µm-thick silver wires. Uniaxial strain was applied along the 110 crystalline direction, activating the B2g mode associated with nematic fluctuations. Magnetic fields were oriented both out of plane (parallel to the crystallographic c-axis) and in plane (perpendicular to the crystallographic c-axis). The results are presented in figures showing temperature dependence of resistivity, magnetoresistivity (MR), and magneto-elasto-resistivity (MER).

Theoretical Framework and Model

The analysis employs a minimal multiband Boltzmann model for transport, extending it to account for the multiband nature of FeSe. This framework incorporates nematic order below the structural transition temperature TS by introducing an x/y anisotropy in the band conductivities. The authors explicitly state that they do not make any assumptions about the microscopic origin of nematicity and that effects like electronic correlations and bands’ orbital composition are effectively incorporated at the microscopic level in the x/y band conductivities, used in defining the fitting parameters.

Key Findings from Magneto-Elasto-Resistivity (MER)

The analysis reveals two key features emerging directly from the analytical expressions:

  1. The field-independent behavior above TS for out-of-plane fields (parallel to the crystallographic c-axis).

  2. The absence of magnetic-field dependence for in-plane fields (perpendicular to the crystallographic c-axis).

The zero-field ER is consistent with existing literature, exhibiting a Curie-Weiss temperature of T∗ ≈ 71 K above TS. Below TS, the ER drops and becomes negative for T < 50 K. The application of a magnetic field has almost no effect above TS, and the Curie-Weiss fit returns a value consistent with the zero-field measurement. Below TS, the MER strongly increases towards positive values and shows a pronounced upturn with decreasing T.

Analytical Derivations for Magnetic Field Dependence

The theoretical derivation for out-of-plane magnetic fields (Bz) leads to an analytical expression for the resistivity tensor in Eq. (1), which is then generalized to a multiband system in Eq. (A3). The resulting magnetoresistance is given by Eq. (3):

∆ρ(B) / ρ(0) = 1 + b0B2z / 1 + b1B2z - 1, where b0 and b1 are functions of the band resistivity tensors. In the isotropic case, the MER becomes independent of the magnetic field above TS, consistent with experimental observations.

Conclusion on Model Sufficiency

The study concludes that a minimal two-band model is sufficient to reproduce the essential magneto-elasto-transport features in FeSe. While orbital effects are important microscopically, they are not crucial for achieving a consistent description within this framework. The model successfully captures the magnetic field dependence of three different measured quantities: Hall resistivity, magnetoresistance, and MER. The authors emphasize that the model focuses on describing the magnetic-field dependence of MER, treating temperature dependence phenomenologically. Furthermore, in-plane fields yield a MER that is independent of the magnetic field at all temperatures. The inclusion of superconducting fluctuations near TC contributes to a pronounced upturn in MER.

Summary of Fitting Results

The fitting procedure for the MER data using Eq. (A30) yields parameters c0, c1, c2, and c3/c4. Under the approximation N0n ≈ 0 (which is true in the isotropic case), the magnetic field dependence simplifies to Eq. (A31): ∂N/∂ϵ = c01 + c1B2z / 1 + c2B2z. This leads to fitting parameters that are consistent with those derived from the MR analysis, confirming the internal consistency of the minimal two-band model. The resulting coefficients are provided in Table IV and Table V, showing how the magnetic field dependence is captured by these fitted parameters. The discrepancy between unconstrained and constrained fits points toward limitations in the standard perturbative treatment of the Boltzmann equation at low temperatures.

Improvements for AI systems

Based on this scientific paper, here are specific improvements for AI systems, categorized by capability:

)Specific Improvements for AI Systems:

  1. [Multiband Model Integration & Parameter Extraction]: Implement a minimal two-band Boltzmann model (as derived in Appendix A) into materials informatics pipelines.

  2. [Magnetic Field Dependence Prediction]: Improve predictive models for magneto-transport properties by incorporating the analytical expressions (Eqs. 3, 4, and especially Eq. 27/A29) derived from the two-band framework to predict how Magneto-Elasto-Resistivity (MER) changes with applied magnetic field strength and crystallographic orientation.

  3. [Nematic Phase Characterization]: Enhance AI's ability to identify and quantify the onset of nematic order in iron-based superconductors by correlating experimental signatures (like the temperature dependence of resistivity anisotropy, Eq. 4) with theoretical predictions derived from the model parameters (e.g., identifying characteristic temperatures like TS).

  4. [Orbital vs. Structural Origin Discrimination]: Develop a classification system that can robustly distinguish between nematicity driven by structural/orbital ordering versus that driven by spin fluctuations, based on the fitted parameters (specifically comparing results where orbital effects are explicitly included versus those where they are absorbed into fitting parameters).

  5. [Model Robustness Assessment]: Create a framework to assess the robustness of transport models in complex materials by testing if key physical features (like field independence of MER above TS, as seen in Fig. 3(a)) emerge naturally from minimal models without requiring fine-tuning of numerous fitting parameters.

  6. [Fluctuation Contribution Modeling]: Integrate a mechanism to account for superconducting fluctuations (related to the upturn near TC) into transport models, allowing the AI to predict how these fluctuations modify the magnetic field dependence of resistivity and MER in different temperature regimes.

)What the Improved AI System Can Do:

The improved AI system will be capable of performing highly sophisticated materials discovery and characterization tasks in condensed matter physics, specifically tailored for iron-based superconductors (Fe-SCs):

  1. [Automated Property Prediction]: The system can accurately predict the magnetic field dependence of transport properties (Hall resistivity and MER) in FeSe or similar compounds by inputting structural parameters and material compositions, leveraging the derived analytical formulas (A30).

  2. [Phase Identification]: It will be able to reliably identify whether a material is in its nematic phase or not by analyzing measured transport anisotropy data, using the model's predictions regarding resistivity anisotropy versus strain.

  3. [Model Validation and Refinement]: The system can autonomously test the validity of different theoretical frameworks (e.g., two-band vs. three-band) against experimental MER data, flagging when a simpler minimal model is sufficient and when more complex physics (like orbital effects) is strictly necessary for accurate description.

  4. [Hypothesis Generation]: It can generate testable hypotheses about the origin of nematicity (e.g., The observed field independence of MER above TS suggests a weak coupling between the nematic order parameter and the magnetic field) by comparing model outputs to experimental observations, guiding further physical investigation.

  5. [Feature Extraction]: The system can automatically extract key physical scales from complex datasets—such as characteristic transition temperatures (TS, TC) and critical magnetic fields where transport behavior changes dramatically—directly from the fitted parameters of the derived equations.

Abstract

FeSe stands out among iron-based superconductors due to its extended nematic phase without the onset of long-range magnetic order. While strain-dependent electrical resistivity has been extensively explored to probe nematicity, its influence on magneto-transport properties remains less understood. In this work, we present measurements of the magneto-elasto-resistivity in FeSe as a function of temperature and applied magnetic field. Using a minimal multiband Boltzmann model for transport we derive analytical expressions that capture the magnetic behavior of the whole set of experimental data both in the paramagnetic and in the nematic phase. These findings indicate that a multiband framework can robustly describe the magneto-elasto-transport properties in FeSe and arguably in other iron-based superconductors.

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