@article{11732, abstract = {We study the BCS energy gap Ξ in the high–density limit and derive an asymptotic formula, which strongly depends on the strength of the interaction potential V on the Fermi surface. In combination with the recent result by one of us (Math. Phys. Anal. Geom. 25, 3, 2022) on the critical temperature Tc at high densities, we prove the universality of the ratio of the energy gap and the critical temperature.}, author = {Henheik, Sven Joscha and Lauritsen, Asbjørn Bækgaard}, issn = {1572-9613}, journal = {Journal of Statistical Physics}, keywords = {Mathematical Physics, Statistical and Nonlinear Physics}, publisher = {Springer Nature}, title = {{The BCS energy gap at high density}}, doi = {10.1007/s10955-022-02965-9}, volume = {189}, year = {2022}, } @article{10642, abstract = {Based on a result by Yarotsky (J Stat Phys 118, 2005), we prove that localized but otherwise arbitrary perturbations of weakly interacting quantum spin systems with uniformly gapped on-site terms change the ground state of such a system only locally, even if they close the spectral gap. We call this a strong version of the local perturbations perturb locally (LPPL) principle which is known to hold for much more general gapped systems, but only for perturbations that do not close the spectral gap of the Hamiltonian. We also extend this strong LPPL-principle to Hamiltonians that have the appropriate structure of gapped on-site terms and weak interactions only locally in some region of space. While our results are technically corollaries to a theorem of Yarotsky, we expect that the paradigm of systems with a locally gapped ground state that is completely insensitive to the form of the Hamiltonian elsewhere extends to other situations and has important physical consequences.}, author = {Henheik, Sven Joscha and Teufel, Stefan and Wessel, Tom}, issn = {1573-0530}, journal = {Letters in Mathematical Physics}, keywords = {mathematical physics, statistical and nonlinear physics}, number = {1}, publisher = {Springer Nature}, title = {{Local stability of ground states in locally gapped and weakly interacting quantum spin systems}}, doi = {10.1007/s11005-021-01494-y}, volume = {112}, year = {2022}, } @article{10623, abstract = {We investigate the BCS critical temperature Tc in the high-density limit and derive an asymptotic formula, which strongly depends on the behavior of the interaction potential V on the Fermi-surface. Our results include a rigorous confirmation for the behavior of Tc at high densities proposed by Langmann et al. (Phys Rev Lett 122:157001, 2019) and identify precise conditions under which superconducting domes arise in BCS theory.}, author = {Henheik, Sven Joscha}, issn = {1572-9656}, journal = {Mathematical Physics, Analysis and Geometry}, keywords = {geometry and topology, mathematical physics}, number = {1}, publisher = {Springer Nature}, title = {{The BCS critical temperature at high density}}, doi = {10.1007/s11040-021-09415-0}, volume = {25}, year = {2022}, } @article{12184, abstract = {We review recent results on adiabatic theory for ground states of extended gapped fermionic lattice systems under several different assumptions. More precisely, we present generalized super-adiabatic theorems for extended but finite and infinite systems, assuming either a uniform gap or a gap in the bulk above the unperturbed ground state. The goal of this Review is to provide an overview of these adiabatic theorems and briefly outline the main ideas and techniques required in their proofs.}, author = {Henheik, Sven Joscha and Wessel, Tom}, issn = {0022-2488}, journal = {Journal of Mathematical Physics}, number = {12}, publisher = {AIP Publishing}, title = {{On adiabatic theory for extended fermionic lattice systems}}, doi = {10.1063/5.0123441}, volume = {63}, year = {2022}, } @inproceedings{17087, abstract = {We consider the problem of model compression for deep neural networks (DNNs) in the challenging one-shot/post-training setting, in which we are given an accurate trained model, and must compress it without any retraining, based only on a small amount of calibration input data. This problem has become popular in view of the emerging software and hardware support for executing models compressed via pruning and/or quantization with speedup, and well-performing solutions have been proposed independently for both compression approaches.In this paper, we introduce a new compression framework which covers both weight pruning and quantization in a unified setting, is time- and space-efficient, and considerably improves upon the practical performance of existing post-training methods. At the technical level, our approach is based on an exact and efficient realization of the classical Optimal Brain Surgeon (OBS) framework of [LeCun, Denker, and Solla, 1990] extended to also cover weight quantization at the scale of modern DNNs. From the practical perspective, our experimental results show that it can improve significantly upon the compression-accuracy trade-offs of existing post-training methods, and that it can enable the accurate compound application of both pruning and quantization in a post-training setting.}, author = {Frantar, Elias and Singh, Sidak Pal and Alistarh, Dan-Adrian}, booktitle = {36th Conference on Neural Information Processing Systems}, isbn = {9781713871088}, location = {New Orleans, LA, United States}, publisher = {ML Research Press}, title = {{Optimal brain compression: A framework for accurate post-training quantization and pruning}}, volume = {35}, year = {2022}, } @article{12286, abstract = {Inspired by the study of loose cycles in hypergraphs, we define the loose core in hypergraphs as a structurewhich mirrors the close relationship between cycles and $2$-cores in graphs. We prove that in the $r$-uniform binomial random hypergraph $H^r(n,p)$, the order of the loose core undergoes a phase transition at a certain critical threshold and determine this order, as well as the number of edges, asymptotically in the subcritical and supercritical regimes. Our main tool is an algorithm called CoreConstruct, which enables us to analyse a peeling process for the loose core. By analysing this algorithm we determine the asymptotic degree distribution of vertices in the loose core and in particular how many vertices and edges the loose core contains. As a corollary we obtain an improved upper bound on the length of the longest loose cycle in $H^r(n,p)$.}, author = {Cooley, Oliver and Kang, Mihyun and Zalla, Julian}, issn = {1077-8926}, journal = {The Electronic Journal of Combinatorics}, keywords = {Computational Theory and Mathematics, Geometry and Topology, Theoretical Computer Science, Applied Mathematics, Discrete Mathematics and Combinatorics}, number = {4}, publisher = {Electronic Journal of Combinatorics}, title = {{Loose cores and cycles in random hypergraphs}}, doi = {10.37236/10794}, volume = {29}, year = {2022}, } @unpublished{10788, abstract = {We determine an asymptotic formula for the number of integral points of bounded height on a certain toric variety, which is incompatible with part of a preprint by Chambert-Loir and Tschinkel. We provide an alternative interpretation of the asymptotic formula we get. To do so, we construct an analogue of Peyre's constant $\alpha$ and describe its relation to a new obstruction to the Zariski density of integral points in certain regions of varieties.}, author = {Wilsch, Florian Alexander}, booktitle = {arXiv}, keywords = {Integral point, toric variety, Manin's conjecture}, title = {{Integral points of bounded height on a certain toric variety}}, doi = {10.48550/arXiv.2202.10909}, year = {2022}, } @unpublished{18293, abstract = {Given a non-singular diagonal cubic hypersurface X⊂Pn−1 over Fq(t) with char(Fq)≠3, we show that the number of rational points of height at most |P| is O(|P|3+ε) for n=6 and O(|P|2+ε) for n=4. In fact, if n=4 and char(Fq)>3 we prove that the number of rational points away from any rational line contained in X is bounded by O(|P|3/2+ε). From the result in 6 variables we deduce weak approximation for diagonal cubic hypersurfaces for n≥7 over Fq(t) when char(Fq)>3 and handle Waring's problem for cubes in 7 variables over Fq(t) when char(Fq)≠3. Our results answer a question of Davenport regarding the number of solutions of bounded height to x31+x32+x33=x34+x35+x36 with xi∈Fq[t].}, author = {Glas, Jakob and Hochfilzer, Leonhard}, booktitle = {arXiv}, title = {{On a question of Davenport and diagonal cubic forms over Fq(t)}}, doi = {10.48550/arXiv.2208.05422}, year = {2022}, } @phdthesis{12072, abstract = {In this thesis, we study two of the most important questions in Arithmetic geometry: that of the existence and density of solutions to Diophantine equations. In order for a Diophantine equation to have any solutions over the rational numbers, it must have solutions everywhere locally, i.e., over R and over Qp for every prime p. The converse, called the Hasse principle, is known to fail in general. However, it is still a central question in Arithmetic geometry to determine for which varieties the Hasse principle does hold. In this work, we establish the Hasse principle for a wide new family of varieties of the form f(t) = NK/Q(x) ̸= 0, where f is a polynomial with integer coefficients and NK/Q denotes the norm form associated to a number field K. Our results cover products of arbitrarily many linear, quadratic or cubic factors, and generalise an argument of Irving [69], which makes use of the beta sieve of Rosser and Iwaniec. We also demonstrate how our main sieve results can be applied to treat new cases of a conjecture of Harpaz and Wittenberg on locally split values of polynomials over number fields, and discuss consequences for rational points in fibrations. In the second question, about the density of solutions, one defines a height function and seeks to estimate asymptotically the number of points of height bounded by B as B → ∞. Traditionally, one either counts rational points, or integral points with respect to a suitable model. However, in this thesis, we study an emerging area of interest in Arithmetic geometry known as Campana points, which in some sense interpolate between rational and integral points. More precisely, we count the number of nonzero integers z1, z2, z3 such that gcd(z1, z2, z3) = 1, and z1, z2, z3, z1 + z2 + z3 are all squareful and bounded by B. Using the circle method, we obtain an asymptotic formula which agrees in the power of B and log B with a bold new generalisation of Manin’s conjecture to the setting of Campana points, recently formulated by Pieropan, Smeets, Tanimoto and Várilly-Alvarado [96]. However, in this thesis we also provide the first known counterexamples to leading constant predicted by their conjecture. }, author = {Shute, Alec L}, isbn = {978-3-99078-023-7}, issn = {2663-337X}, pages = {208}, publisher = {Institute of Science and Technology Austria}, title = {{Existence and density problems in Diophantine geometry: From norm forms to Campana points}}, doi = {10.15479/at:ista:12072}, year = {2022}, } @article{9364, abstract = {Let t : Fp → C be a complex valued function on Fp. A classical problem in analytic number theory is bounding the maximum M(t) := max 0≤H

0 there exists a large subset of a ∈ F×p such that for kl a,1,p : x → e((ax+x) / p) we have M(kla,1,p) ≥ (1−ε/√2π + o(1)) log log p, as p→∞. Finally, we prove a result on the growth of the moments of {M (kla,1,p)}a∈F×p. 2020 Mathematics Subject Classification: 11L03, 11T23 (Primary); 14F20, 60F10 (Secondary).}, author = {Bonolis, Dante}, issn = {1469-8064}, journal = {Mathematical Proceedings of the Cambridge Philosophical Society}, number = {3}, pages = {563 -- 590}, publisher = {Cambridge University Press}, title = {{On the size of the maximum of incomplete Kloosterman sums}}, doi = {10.1017/S030500412100030X}, volume = {172}, year = {2022}, } @article{9199, abstract = {We associate a certain tensor product lattice to any primitive integer lattice and ask about its typical shape. These lattices are related to the tangent bundle of Grassmannians and their study is motivated by Peyre's programme on "freeness" for rational points of bounded height on Fano varieties.}, author = {Browning, Timothy D and Horesh, Tal and Wilsch, Florian Alexander}, issn = {1944-7833}, journal = {Algebra & Number Theory}, number = {10}, pages = {2385--2407}, publisher = {Mathematical Sciences Publishers}, title = {{Equidistribution and freeness on Grassmannians}}, doi = {10.2140/ant.2022.16.2385}, volume = {16}, year = {2022}, } @article{10827, abstract = {Titanium dioxide has been extensively studied in the rutile or anatase phase, while its high-pressure phases are less well-understood, despite that many are thought to have interesting optical, mechanical, and electrochemical properties. First-principles methods, such as density functional theory (DFT), are often used to compute the enthalpies of TiO2 phases at 0 K, but they are expensive and, thus, impractical for long time scale and large system-size simulations at finite temperatures. On the other hand, cheap empirical potentials fail to capture the relative stabilities of various polymorphs. To model the thermodynamic behaviors of ambient and high-pressure phases of TiO2, we design an empirical model as a baseline and then train a machine learning potential based on the difference between the DFT data and the empirical model. This so-called Δ-learning potential contains long-range electrostatic interactions and predicts the 0 K enthalpies of stable TiO2 phases that are in good agreement with DFT. We construct a pressure–temperature phase diagram of TiO2 in the range 0 < P < 70 GPa and 100 < T < 1500 K. We then simulate dynamic phase transition processes by compressing anatase at different temperatures. At 300 K, we predominantly observe an anatase-to-baddeleyite transformation at about 20 GPa via a martensitic two-step mechanism with a highly ordered and collective atomic motion. At 2000 K, anatase can transform into cotunnite around 45–55 GPa in a thermally activated and probabilistic manner, accompanied by diffusive movement of oxygen atoms. The pressures computed for these transitions show good agreement with experiments. Our results shed light on how to synthesize and stabilize high-pressure TiO2 phases, and our method is generally applicable to other functional materials with multiple polymorphs.}, author = {Lee, Jacob G. and Pickard, Chris J. and Cheng, Bingqing}, issn = {1089-7690}, journal = {The Journal of chemical physics}, number = {7}, publisher = {AIP Publishing}, title = {{High-pressure phase behaviors of titanium dioxide revealed by a Δ-learning potential}}, doi = {10.1063/5.0079844}, volume = {156}, year = {2022}, } @article{12128, abstract = {We introduce a machine-learning (ML) framework for high-throughput benchmarking of diverse representations of chemical systems against datasets of materials and molecules. The guiding principle underlying the benchmarking approach is to evaluate raw descriptor performance by limiting model complexity to simple regression schemes while enforcing best ML practices, allowing for unbiased hyperparameter optimization, and assessing learning progress through learning curves along series of synchronized train-test splits. The resulting models are intended as baselines that can inform future method development, in addition to indicating how easily a given dataset can be learnt. Through a comparative analysis of the training outcome across a diverse set of physicochemical, topological and geometric representations, we glean insight into the relative merits of these representations as well as their interrelatedness.}, author = {Poelking, Carl and Faber, Felix A and Cheng, Bingqing}, issn = {2632-2153}, journal = {Machine Learning: Science and Technology}, keywords = {Artificial Intelligence, Human-Computer Interaction, Software}, number = {4}, publisher = {IOP Publishing}, title = {{BenchML: An extensible pipelining framework for benchmarking representations of materials and molecules at scale}}, doi = {10.1088/2632-2153/ac4d11}, volume = {3}, year = {2022}, } @article{12249, abstract = {The chemical potential of a component in a solution is defined as the free energy change as the amount of that component changes. Computing this fundamental thermodynamic property from atomistic simulations is notoriously difficult because of the convergence issues involved in free energy methods and finite size effects. This Communication presents the so-called S0 method, which can be used to obtain chemical potentials from static structure factors computed from equilibrium molecular dynamics simulations under the isothermal–isobaric ensemble. This new method is demonstrated on the systems of binary Lennard-Jones particles, urea–water mixtures, a NaCl aqueous solution, and a high-pressure carbon–hydrogen mixture. }, author = {Cheng, Bingqing}, issn = {1089-7690}, journal = {The Journal of Chemical Physics}, keywords = {Physical and Theoretical Chemistry, General Physics and Astronomy}, number = {12}, publisher = {AIP Publishing}, title = {{Computing chemical potentials of solutions from structure factors}}, doi = {10.1063/5.0107059}, volume = {157}, year = {2022}, } @article{11937, abstract = {Most experimentally known high-pressure ice phases have a body-centred cubic (bcc) oxygen lattice. Our large-scale molecular-dynamics simulations with a machine-learning potential indicate that, amongst these bcc ice phases, ices VII, VII′ and X are the same thermodynamic phase under different conditions, whereas superionic ice VII″ has a first-order phase boundary with ice VII′. Moreover, at about 300 GPa, the transformation between ice X and the Pbcm phase has a sharp structural change but no apparent activation barrier, whilst at higher pressures the barrier gradually increases. Our study thus clarifies the phase behaviour of the high-pressure ices and reveals peculiar solid–solid transition mechanisms not known in other systems.}, author = {Reinhardt, Aleks and Bethkenhagen, Mandy and Coppari, Federica and Millot, Marius and Hamel, Sebastien and Cheng, Bingqing}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Thermodynamics of high-pressure ice phases explored with atomistic simulations}}, doi = {10.1038/s41467-022-32374-1}, volume = {13}, year = {2022}, } @article{9695, abstract = {Real-world data typically contain a large number of features that are often heterogeneous in nature, relevance, and also units of measure. When assessing the similarity between data points, one can build various distance measures using subsets of these features. Using the fewest features but still retaining sufficient information about the system is crucial in many statistical learning approaches, particularly when data are sparse. We introduce a statistical test that can assess the relative information retained when using two different distance measures, and determine if they are equivalent, independent, or if one is more informative than the other. This in turn allows finding the most informative distance measure out of a pool of candidates. The approach is applied to find the most relevant policy variables for controlling the Covid-19 epidemic and to find compact yet informative representations of atomic structures, but its potential applications are wide ranging in many branches of science.}, author = {Glielmo, Aldo and Zeni, Claudio and Cheng, Bingqing and Csanyi, Gabor and Laio, Alessandro}, issn = {2752-6542}, journal = {PNAS Nexus}, number = {2}, publisher = {Oxford University Press}, title = {{Ranking the information content of distance measures}}, doi = {10.1093/pnasnexus/pgac039}, volume = {1}, year = {2022}, } @article{12237, abstract = {Thermoelectric technology requires synthesizing complex materials where not only the crystal structure but also other structural features such as defects, grain size and orientation, and interfaces must be controlled. To date, conventional solid-state techniques are unable to provide this level of control. Herein, we present a synthetic approach in which dense inorganic thermoelectric materials are produced by the consolidation of well-defined nanoparticle powders. The idea is that controlling the characteristics of the powder allows the chemical transformations that take place during consolidation to be guided, ultimately yielding inorganic solids with targeted features. Different from conventional methods, syntheses in solution can produce particles with unprecedented control over their size, shape, crystal structure, composition, and surface chemistry. However, to date, most works have focused only on the low-cost benefits of this strategy. In this perspective, we first cover the opportunities that solution processing of the powder offers, emphasizing the potential structural features that can be controlled by precisely engineering the inorganic core of the particle, the surface, and the organization of the particles before consolidation. We then discuss the challenges of this synthetic approach and more practical matters related to solution processing. Finally, we suggest some good practices for adequate knowledge transfer and improving reproducibility among different laboratories.}, author = {Fiedler, Christine and Kleinhanns, Tobias and Garcia, Maria and Lee, Seungho and Calcabrini, Mariano and Ibáñez, Maria}, issn = {1520-5002}, journal = {Chemistry of Materials}, keywords = {Materials Chemistry, General Chemical Engineering, General Chemistry}, number = {19}, pages = {8471--8489}, publisher = {American Chemical Society}, title = {{Solution-processed inorganic thermoelectric materials: Opportunities and challenges ∇}}, doi = {10.1021/acs.chemmater.2c01967}, volume = {34}, year = {2022}, } @article{11700, abstract = {This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou–Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport. Secondly, in the spirit of Jordan–Kinderlehrer–Otto, we show that McKean–Vlasov equations can be formulated as gradient flow of the free energy in the Wasserstein space of probability measures. The proofs of these results are based on careful regularisation arguments to circumvent some of the difficulties arising in metric graphs, namely, branching of geodesics and the failure of semi-convexity of entropy functionals in the Wasserstein space.}, author = {Erbar, Matthias and Forkert, Dominik L and Maas, Jan and Mugnolo, Delio}, issn = {1556-181X}, journal = {Networks and Heterogeneous Media}, number = {5}, pages = {687--717}, publisher = {AIMS}, title = {{Gradient flow formulation of diffusion equations in the Wasserstein space over a metric graph}}, doi = {10.3934/nhm.2022023}, volume = {17}, year = {2022}, } @inproceedings{12299, abstract = {Transfer learning is a classic paradigm by which models pretrained on large “upstream” datasets are adapted to yield good results on “downstream” specialized datasets. Generally, more accurate models on the “upstream” dataset tend to provide better transfer accuracy “downstream”. In this work, we perform an in-depth investigation of this phenomenon in the context of convolutional neural networks (CNNs) trained on the ImageNet dataset, which have been pruned-that is, compressed by sparsifiying their connections. We consider transfer using unstructured pruned models obtained by applying several state-of-the-art pruning methods, including magnitude-based, second-order, regrowth, lottery-ticket, and regularization approaches, in the context of twelve standard transfer tasks. In a nutshell, our study shows that sparse models can match or even outperform the transfer performance of dense models, even at high sparsities, and, while doing so, can lead to significant inference and even training speedups. At the same time, we observe and analyze significant differences in the behaviour of different pruning methods. The code is available at: https://github.com/IST-DASLab/sparse-imagenet-transfer.}, author = {Iofinova, Eugenia B and Peste, Elena-Alexandra and Kurtz, Mark and Alistarh, Dan-Adrian}, booktitle = {2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition}, issn = {2575-7075}, location = {New Orleans, LA, United States}, pages = {12256--12266}, publisher = {IEEE}, title = {{How well do sparse ImageNet models transfer?}}, doi = {10.1109/cvpr52688.2022.01195}, year = {2022}, } @inproceedings{12161, abstract = {We introduce LIMES, a new method for learning with non-stationary streaming data, inspired by the recent success of meta-learning. The main idea is not to attempt to learn a single classifier that would have to work well across all occurring data distributions, nor many separate classifiers, but to exploit a hybrid strategy: we learn a single set of model parameters from which a specific classifier for any specific data distribution is derived via classifier adaptation. Assuming a multiclass classification setting with class-prior shift, the adaptation step can be performed analytically with only the classifier’s bias terms being affected. Another contribution of our work is an extrapolation step that predicts suitable adaptation parameters for future time steps based on the previous data. In combination, we obtain a lightweight procedure for learning from streaming data with varying class distribution that adds no trainable parameters and almost no memory or computational overhead compared to training a single model. Experiments on a set of exemplary tasks using Twitter data show that LIMES achieves higher accuracy than alternative approaches, especially with respect to the relevant real-world metric of lowest within-day accuracy.}, author = {Tomaszewska, Paulina and Lampert, Christoph}, booktitle = {26th International Conference on Pattern Recognition}, issn = {2831-7475}, location = {Montreal, Canada}, pages = {2128--2134}, publisher = {IEEE}, title = {{Lightweight conditional model extrapolation for streaming data under class-prior shift}}, doi = {10.1109/icpr56361.2022.9956195}, volume = {2022}, year = {2022}, }