生成并非发现：一个预注册的物理评判器用于AI提出的超导体，基于六种已知超导体和一个阴性对照进行校准
Generating is not discovering: a pre-registered physics judge for AI-proposed superconductors, calibrated on six known superconductors and one negative control
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中文总结 AI 辅助
本文提出一个预注册的物理评判器，从结构判断超导配对与可制造性，校准于六种已知超导体，发现AI生成仅重述已知，判断才是瓶颈。
中文摘要 AI 辅助
生成模型如今能提出数百万种“稳定”的晶体结构，而其自身的评审者已表明，稳定性并非发现；目前尚无公开基准来检验候选材料是否具备执行某项任务的物理性质。对于超导体而言，任务有两方面：一是以明确的能隙对称性形成库珀对，二是能够制成导线。我们提出一个物理评判器，仅从结构出发即可回答这两个问题（采用DFT+U方法、门控Wannier模型、在$24^3$网格上的完整四阶RPA磁化率、线性化能隙方程、不可约表示分类器以及可制造性漏斗），并衡量其对生成器所提结构的评判结果。在计算前预注册了答案密钥，评判器在六种已知超导体（Nb、Nb$_3$Sn、MgB$_2$、BaFe$_2$As$_2$、La$_{2-x}$Sr$_x$CuO$_4$、YBa$_2$Cu$_3$O$_7$）上进行了校准，经过两次过时修正后，六种材料均恢复了预期的类别。对于铁基砷化物的钌类似物，在预注册了两次运行及其判据（前一天）的情况下，在铁产生s±能隙的相同物理相互作用下，评判器给出了无效判定（$\u03bb_1 \u2264 0.0007$ 对比 0.096；临界U值为4.17 eV 对比 0.97 eV）；预注册的等alpha运行未能满足判据的字面要求，我们宣布支持绝对U值的判定为事后解释。漏斗在运行前固定阈值，重现了工业图谱。随后进行了三项生成审计：对150种Materials Project金属的描述符扫描重新发现了经典材料；1,248种MatterGen结构中，有0种是新的、稳定的且带有配对基序的候选材料；对47,893种化合物的机制过滤器（通过盲法保留集验证）重新推导了该领域的类比：几何加上d电子数是必要条件但非充分条件。生成只是重新发现已知内容；判断才是瓶颈。我们提议对十一份AI提出的超导体候选清单建立一个公开基准，目前这些清单均未对能隙对称性进行分类。
英文摘要
Generative models now propose millions of "stable" crystal structures, and their own referees have shown that stability is not discovery; no public benchmark asks whether a candidate has the physics to do a job. For superconductors the job is twofold: to pair, with a definite gap symmetry, and to become wire. We present a physics judge that answers both from a structure alone (DFT+U, a gated Wannier model, the full rank-4 RPA susceptibility on a $24^3$ mesh, the linearized gap equation, an irreducible-representation classifier, a manufacturability funnel) and measure what it says about what generators propose. With answer keys pre-registered before computing, the judge was calibrated on six known superconductors (Nb, Nb$_3$Sn, MgB$_2$, BaFe$_2$As$_2$, La$_{2-x}$Sr$_x$CuO$_4$, YBa$_2$Cu$_3$O$_7$), recovering the expected class in all six after two dated corrections. On the ruthenium analogue of the iron pnictide, with two runs and their criterion pre-registered the day before, it returns a null verdict at the same physical interaction where iron gives s$\pm$ ($λ_1 \le 0.0007$ versus 0.096; critical U 4.17 versus 0.97 eV); the pre-registered equal-alpha run fails the letter of the criterion, and we declare the resolution in favour of absolute U as post-hoc. The funnel reproduces the industrial map with thresholds fixed before running. Three generation audits follow: a descriptor sweep over 150 Materials Project metals re-finds the canon; 1,248 MatterGen structures yield 0 candidates that are new, stable and carry a pairing motif; mechanism filters over 47,893 compounds, validated by a blind hold-out, re-derive the community's analogies: geometry plus d-count is necessary but not sufficient. Generation re-finds what is known; judgment is the bottleneck. We propose a public benchmark over the eleven lists of AI-proposed superconductor candidates, none of which classifies gap symmetry.
发表机构
- BITA (Inova Simples)（BITA（Inova Simples））
机构由 AI 辅助整理，请以论文原文为准。
