Materials Science · Cross-listed from cs.AR
YAP+: Pad-Layout-Aware Yield Modeling and Simulation for Hybrid Bonding
Zhichao Chen and Puneet Gupta
Three-dimensional (3D) integration continues to advance Moore's Law by facilitating dense interconnects and enabling multi-tier system architectures. Among the various integration approaches, Cu-Cu hybrid bonding has emerged as a leading solution for achieving high interconnect density in chiplet integration. In this work, we present YAP+, a yield modeling framework specifically tailored for wafer-to-wafer (W2W) and die-to-wafer (D2W) hybrid bonding processes. YAP+ incorporates a comprehensive set of yield-impacting failure mechanisms, including overlay misalignment, particle defects, Cu recess variations, surface roughness, and Cu pad density. Furthermore, YAP+ supports pad layout-aware yield analysis, considering critical, redundant, and dummy pads across arbitrary 2D physical layout patterns. To support practical evaluation, we developed an open-source yield simulator, demonstrating that our near-analytical model matches simulation accuracy while achieving over 1,000x speedup in runtime. This performance makes YAP+ a valuable tool for co-optimizing packaging technologies, assembly design rules, and system-level design strategies. Beyond W2W-D2W comparisons, we leverage YAP+ to investigate the impact of pad layout patterns, bonding pitch, and pad ratios across different pad types, and explore the benefits of strategically placing redundant pad replicas.
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Soft Condensed Matter
Aggregates in fluidized beds: the effect of bonding angles on fluidization
Vinícius Pereira da Silva Oliveira, Danilo da Silva Borges and Erick de Moraes Franklin
Fluidized beds consist of solid particles suspended in a tube by an ascending fluid. In
liquids, it is not rare that particles adhere to each other, decreasing the solid-
liquid contact area and the ratio between the tube and grain diameters, deteriorating fluidization. We inquire into this problem by carrying out experiments with trios of spheres fluidized by water flows, the spheres being glued in predefined angles. In our tests, we used a 25.4-mm-ID (internal diameter) tube and 5.95-mm-diameter spheres, and we varied the angle of trios within 60$^{\circ}$ and 180$^\circ$ and water velocities within 0.027 and 0.210 m/s. Due to the small ratio between the diameters of the tube and spheres (approximately 4.3), the bed is prone to the formation of plugs and clogs. Our experiments show that elutriation, fluidization with plugs, glass transitions (amorphous static structures), packed beds, clogging, and a transitional clogged-plug regime can appear in the bed, depending on the bonding angles and water velocities. We report the relations between the bed height, bonding angles, and flow velocity, and show that they correlate with the granular temperature. We also show that an angle of 90$^\circ$ maximizes fluidization for a given fluid velocity, and we propose a regime map that organizes the different patterns based on the bonding angle and flow velocity. The proposed map can serve as a guide for selecting the fluid velocities in order to keep the bed fluidized at all times, helping in the design and operation of fluidized beds.
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Materials Science · Cross-listed from physics.chem-ph
Foundation Models for Discovery and Exploration in Chemical Space
Alexius Wadell, Anoushka Bhutani, Victor Azumah et al. (+26 more)
Accurate prediction of atomistic, thermodynamic, and kinetic properties from molecular structures underpins materials innovation. Existing computational and experimental approaches lack the scalability required to navigate chemical space efficiently. Scientific foundation models trained on large unlabelled
datasets offer a path towards navigating chemical space across application domains. Here, we develop MIST, a family of molecular foundation models with up to an order of magnitude more parameters and data than prior works. Trained using a novel tokenizer, Smirk, which comprehensively captures
nuclear, electronic, and
geometric information, MIST learns a diverse range of molecules. MIST models have been fine-tuned to predict more than 400 structure-property relationships and have been shown to match or exceed state-of-the-art performance across diverse
benchmarks, from physiology to electrochemistry. We demonstrate the ability of these models to solve real-world problems across chemical space from multiobjective electrolyte solvent screening to stereochemical
reasoning for organometallics and mixture property prediction. The clearest demonstration of a foundation model is its ability to solve problems that were neither explicit targets of training nor central to the intentions of its developers. We identify olfactory perception mapping as such a problem, and show that MIST accurately predicted scent profiles and learned a hierarchical representation of olfactory space consistent with
hyperbolic geometry. We formulated hyperparameter aware
Bayesian neural scaling laws which eliminate the need for hyperparameter sweeps at every scale, making training large compute-optimal models feasible on a limited compute budget. The methods and findings presented here represent a significant step towards accelerating materials discovery, design, and optimization using foundation models.
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All authors Alexius Wadell, Anoushka Bhutani, Victor Azumah, Austin R. Ellis-Mohr, Andrew J. Stier, Kareem Hegazy, Alexander Brace, Hancheng Zhao, Celia Kelly, Anuj K. Nayak, Yuhan Chen, Dimitrios Simatos, Hongyi Lin, Murali Emani, Venkatram Vishwanath, Kevin Gering, Melisa Alkan, Tom Gibbs, Jack Wells, Wesley W. Qian, Richard C. Gerkin, Benjamin Amorelli, Alexander B. Wiltschko, Lav R. Varshney, Bharath Ramsundar, Karthik Duraisamy, Michael W. Mahoney, Arvind Ramanathan, Venkatasubramanian Viswanathan
Materials Science
Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling
Yongliang Ou, Lena Scholz, Sanath Keshav et al. (+7 more)
Improving solid electrolytes is critical for high-performance all-solid-state batteries, yet the microstructural features that enable fast ion transport remain poorly understood. Here, we use multiscale modeling to resolve polycrystalline ion transport from atomic-scale hopping at grain boundaries to continuum-scale percolation, thereby providing insights into realistic solid-electrolyte microstructures. Accurate lightweight machine-learning potentials – developed via closed-loop active learning for exemplar argyrodites Li$_6$PS$_5$X, X $\in$ {Cl, Br, I} – are employed to integrate molecular dynamics with finite element simulations. We find that
diffusion barriers of the anion-ordered bulk scale linearly with anion radius. Grain boundaries exert opposite effects depending on the bulk: enhancing ion
diffusion in low-diffusivity phases but suppressing it in fast-diffusing ones. Li$_6$PS$_5$I exhibits non-Arrhenius transport behavior consistent with experimental observations. Our results clarify the pivotal role of grain boundaries in ion transport and guide a priori microstructural design of advanced solid electrolytes.
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All authors Yongliang Ou, Lena Scholz, Sanath Keshav, Yuji Ikeda, Marvin Kraft, Sergiy Divinski, Rafael Gómez-Bombarelli, Wolfgang G. Zeier, Felix Fritzen, Blazej Grabowski
Materials Science
Anisotropic-Strain Control of The Magnetic Structure in Mn\textsubscript{3}GaN
Roman Malyshev, Ingeborg-Helene Svenum, Sverre M. Selbach et al. (+1 more)
A first principles study is conducted to explore the changes in the
magnetic structure of Mn\textsubscript{3}GaN under anisotropic biaxial strain. Mn\textsubscript{3}GaN is an antiperovskite with a structure similar to that of an ideal cubic perovskite. Several manganese nitride antiperovskites including Mn\textsubscript{3}GaN were reported to have a frustrated noncollinear
antiferromagnetic structure. Successful electric switching of its
magnetic structure has been reported. Furthermore, despite a cubic
lattice symmetry, the
magnetic symmetry is rhombohedral, allowing a piezomagnetic response. Tensile biaxial strain has been shown to produce a net
magnetic moment by inducing in-plane
spin canting. Compressive biaxial strain has been used to induce a
spin-polarized ferro- or ferrimagnetic phase. In this study, anisotropic strain in the (001) plane is applied, outlining a
magnetic phase diagram that can predict the properties when growing Mn\textsubscript{3}GaN thin films on noncubic substrates. The
lattice vectors along the a and b crystallographic axes are strained by -5% to 5% in percentwise increments in all permutations. An extensive phase diagram is mapped, revealing multiple combinations of strain applied to the two
lattice vectors that result in a ferro- or ferrimagnetic transition. Unlike previous results, not only strictly compressive strain on both
lattice vectors, but combinations of tensile and compressive strain, as well as uniaxial strain, are seen producing the
magnetic phase transitions. Furthermore, while biquadratic strain was seen producing a net moment in the [110] direction under tensile strain and [\bar{1}\bar{1}0] under compressive strain, anisotropic strain allows tuning the direction of the net magnetization.
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All authors Roman Malyshev, Ingeborg-Helene Svenum, Sverre M. Selbach, Thomas Tybell
Mesoscale and Nanoscale Physics
Magnetic-field-free parity-protected qubit based on a narrow altermagnet Josephson junction
Sakineh Vosoughi-nia and Michał P. Nowak
Altermagnets provide a new route to engineer superconducting
circuits without
magnetic fields. We theoretically study the Andreev bound state (ABS) spectrum of a finite-width altrmagnet-based Josephson junction and show how the $d$-wave altermagnetic
symmetry and
geometric confinement shape its low-energy excitations. We find a clear distinction between the two $d$-wave
symmetries: $d_{x^2-y^2}$ order produces
spin splitting, whereas $d_{xy}$ order preserves
spin degeneracy and exhibits splitting of the ABS spectrum induced by intermode hybridization. Leveraging these novel features, we propose applying a transverse electric field to tune the system and realize a
magnetic-field-free, parity-protected superconducting
qubit that we call altermon.
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Strongly Correlated Electrons
Probing Hidden Symmetry and Altermagnetism with Sub-Picometer Sensitivity via Nonlinear Transport
Subin Mali, Yufei Zhao, Yu Wang et al. (+8 more)
X-ray and
neutron diffraction are foundational tools for determining
crystal structures, but their resolution limits can lead to misassignments, especially in materials with subtle distortions or competing phases. Here, we demonstrate the use of nonlinear transport as a complementary approach to uncover hidden
crystal symmetries, using the strongly correlated Ca$_3$Ru$_2$O$_7$ as a case study. Below 48 K (T$_S$), where the
magnetic moments of the
antiferromagnetic phase reorient from the a- to the b-axis, leading to a pseudogap opening, our measurements, with support of DFT, reveal a previously overlooked lower-
symmetry phase. This is manifested by the emergence of longitudinal nonlinear resistance (NLR) along the b-axis below T$_S$, providing direct evidence of combined translational and time-reversal
symmetry breaking. This response also suggests a transformation from a conventional antiferromagnet into an altermagnet. The lower-
symmetry phase arises from a subtle
lattice distortion (~0.1 pm) associated with the
magnetic transition at T$_S$, below the detection limit of conventional diffraction. Moreover, this NLR below T$_S$ is accompanied by a nonlinear
Hall effect, both of which are enhanced by the large
quantum metric associated with Weyl chains near the
Fermi surface. Our findings demonstrate nonlinear transport as a sensitive probe of hidden
symmetry breaking and altermagnetism, complementing and extending beyond the reach of traditional diffraction and spectroscopic techniques.
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All authors Subin Mali, Yufei Zhao, Yu Wang, Saugata Sarker, Yangyang Chen, Zixuan Li, Jun Zhu, Ying Liu, Venkatraman Gopalan, Binghai Yan, Zhiqiang Mao
Soft Condensed Matter
Elastohydrodynamic instabilities of a soft robotic arm in a viscous fluid
Mohamed Warda and Ronojoy Adhikari
The design and control of soft
robots operating in fluid environments requires a careful understanding of the interplay between large elastic body deformations and hydrodynamic forces. Here we show that this interplay leads to novel elastohydrodynamic instabilities in a clamped soft robotic arm driven terminally by a constant pressure in a viscous fluid. We model the arm as a Cosserat rod that can stretch, shear and bend. We obtain invariant, geometrically exact, non-linear equations of motion by using Cartan's method of moving frames. Stability to small perturbations of a straight rod is governed by a non-Hermitian linear operator. Eigenanalysis shows that stability is lost through a
Hopf bifurcation with the increase of pressure above a first threshold. A surprising return to stability is obtained with further increase of pressure beyond a second threshold. Numerical solutions of the non-linear equations, using a geometrically exact spectral method, confirms stable limit-cycle oscillations between these two pressure thresholds. An asymptotic analysis in the beam limit rationalizes these results analytically. This counterintuitive sequence of bifurcations underscores the subtle nature of the elastohydrodynamic coupling in Cosserat rods and emphasizes their importance for the control of the viscous dynamics of soft
robots.
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Superconductivity
Inverse proximity effect in thin-film superconductor/magnet heterostructures with metallic and insulating magnets
V. A. Bobkov, G. A. Bobkov and I. V. Bobkova
Proximity effect in thin-film
superconductor (S)/magnet
heterostructures with different types of magnets including ferromagnets, antiferromagnets and altermagnets is widely considered in the framework of an effective model, where the
heterostructure is replaced by a homogeneous
superconductor in the presence of a homogeneous exchange field of a corresponding type. Here we study the extent to which such a model is actually applicable to ballistic thin-film
superconductor/
magnetic heterostructures. In particular, a comparative analysis of thin-film
superconductor/
magnetic metal and
superconductor/
magnetic insulator heterostructures is performed. Metallic and insulating ferromagnets (FM, FI) and altermagnets (AM, AI) are considered. It is shown that in the S/FI and S/AI
heterostructures the the proximity effect creates a well-defined
spin splitting of the electronic spectra in the S layer. Thus, they are well described by the effective model. At the same time, the proximity effect in S/FM and S/AM
heterostructures also creates a
spin splitting of the spectra of the S layer, but it has a chaotic spectral and spatial distribution and unpredictable amplitude and, in general, cannot be detected via the
spin splitting of the superconducting density of states. Thus, the effective model is not applicable to such
heterostructures. Nevertheless, we demonstrate that they support well-pronounced triplet correlations and, thus, can be used for spintronics applications.
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Soft Condensed Matter
Geometric Field Theory for Elastohydrodynamics of Cosserat Rods
Mingjia Yan, Mohamed Warda, Balázs Németh et al. (+2 more)
Slender structures are ubiquitous in biological and physical systems, from bacterial flagella to soft robotic arms. The Cosserat rod provides a mathematical framework for slender bodies that can stretch, shear, twist and bend. In viscous fluid environments at low Reynolds numbers - as encountered in soft matter physics, biophysics, and soft continuum robotics - inertial effects become negligible, and hydrodynamic forces are well approximated by Stokes friction. We demonstrate that the resulting elastohydrodynamic equations of motion, when formulated using Cartan's method of moving frames, possess the structure of a
geometric field theory in which the configuration field takes values in SE(3), the Lie group of rigid body motions. This
geometric formulation yields coordinate-independent equations that are manifestly invariant under spatial isometries and naturally suited to constitutive modeling based on Curie's principle. We derive integrability conditions that determine when constitutive laws can be derived from an energy functional, thereby distinguishing between passive and active material responses. We also obtain the beam limit for small deformations. Our results establish a unified
geometric framework for the nonlinear mechanics of slender structures in slow viscous flow and enable efficient numerical solutions.
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All authors Mingjia Yan, Mohamed Warda, Balázs Németh, Lukas Kikuchi, Ronojoy Adhikari
Mesoscale and Nanoscale Physics
A Hall viscosity for skyrmion via magnon interaction
Bom Soo Kim
We identify a
Hall viscosity term directly from the Dzyaloshinskii-Moriya interaction (DMI), that breaks parity
symmetry, in the skyrmion motion of insulating magnets by time-averaging the
magnon contribution to all orders. The viscosity term is proportional to the skyrmion charge. Skyrmion
Hall angle shows significant dependence on the skyrmion shape and size, the ratio of exchange over DMI parameters, while roughly independent of the Gilbert damping parameter. The
Hall angles have the same magnitude for opposite skyrmion charges. We speculate a velocity-dependent
Hall viscosity contribution to seek asymmetric
Hall angles for the opposite charges.
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Statistical Mechanics
Reaching maximum efficiency in quantum Stirling engines using multilayer graphene
Bastian Castorene, Francisco J. Peña, Eric Suárez Morell et al. (+4 more)
In this work,
quantum Stirling engines based on monolayer, AB-stacked
bilayer, and ABC-stacked trilayer
graphene under perpendicular
magnetic fields are analyzed. Performance maps of the useful work \((\eta W)\) reveal a robust optimum at low
magnetic fields and moderately low temperatures, with all stackings capable of reaching Carnot efficiency under suitable configurations. The AB
bilayer achieves this across the broadest parameter window while sustaining finite work, the monolayer exhibits highly constrained regimes, and the trilayer shows smoother trends with sizable \(\eta W\). These results identify multilayer
graphene, particularly the AB
bilayer, as a promising platform for efficient Stirling engines, while also highlighting the versatility of the monolayer in realizing all four operational regimes of the Stirling cycle.
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All authors Bastian Castorene, Francisco J. Peña, Eric Suárez Morell, Caio Lewenkopf, Martin HvE Groves, Natalia Cortés, Patricio Vargas
Materials Science
First-Principles Investigation of the Physical and Thermoelectric Properties of Chalcogenide Compounds for Waste-Heat Recovery
Md Hasan Shahriar Rifat, Tanvir Khan and K.M. Mehedi Hassan
Improving energy efficiency by recovering waste heat and providing thermal protection is of high technological importance. This work investigates the chalcogenide compounds CdGa2Te4 and ZnGa2Te4 using density functional theory and BoltzTraP2 calculations. Both materials are dynamically stable, brittle, and elastically anisotropic. Electronic structure calculations show direct band gaps that range from 1.0 to 2.2 electronvolt. Carrier effective masses are favorable, with CdGa2Te4 showing light electrons equal to 0.21 times the free electron mass and ZnGa2Te4 showing moderately heavy carriers equal to 0.39 times the free electron mass. Thermoelectric transport calculations yield large Seebeck coefficients of about 108 to 119 microvolt per kelvin. The thermoelectric figure of merit ZT increases from about 0.4 at 50 K to about 0.78 at 800 kelvin, indicating promising thermoelectric performance. For thermal barrier coating applications, both compounds combine ultralow
lattice thermal conductivity with moderate melting points around 790 to 850 K and small thermal expansion coefficients, which helps resist thermal stress. Overall, CdGa2Te4 and ZnGa2Te4 are multifunctional materials suitable for efficient waste heat recovery and durable thermal barrier operation below 900 K.
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Statistical Mechanics
Transitions driven by multibody interactions in an effective model of active matter
Thibaut Arnoulx de Pirey and Frédéric van Wijland
When out-of-
equilibrium particles interact by means of pairwise forces, their stationary distribution in general exhibits many-body interactions. In the particular case of active particles, it has been shown numerically that the Motility Induced Phase Separation cannot be explained by the effective attraction emerging from two isolated particles, thereby highlighting the role of multibody interactions. In this work, we study the thermodynamics of the Fox-UCNA approximation for active particles interacting by means of pairwise repulsive forces. Working at large space dimension we establish that multibody interactions up to infinite order are instrumental in giving rise to such collective phenomena as phase transitions. We recover a MIPS-like first order transition, but also find a
liquid-
liquid transition at somewhat lower persistence times. This new transition is connected to a
spin glass phase of orientational-like degrees of freedom with disordered interactions set by the particle positions themselves.
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Materials Science
Oxidation State Dynamics and Emerging Patterns in Magnetite
Emre Gürsoy, Gregor B. Vonbun-Feldbauer and Robert H. Meißner
Magnetite is an important mineral with many interesting applications related to its
magnetic, electrical and thermal properties. Typically studied by electronic structure calculations, these methods are unable to capture the complex ion dynamics at relevant temperatures, time and length scales. We present a hybrid Monte Carlo/Molecular Dynamics (MC/MD) method based on iron oxidation state exchange for accurate atomistic modelling of bulk magnetite, magnetite surfaces and nanoparticles that captures the complex ionic dynamics. By comparing oxidation state patterns with those obtained from density functional theory, we confirmed the accuracy of our approach.
Lattice distortions leading to the stabilisation of excess charges and a critical surface thickness at which the oxidation states transition from ordered to disordered were observed. This simple yet efficient approach paves the way for elucidating aspects of oxidation state ordering of inverse spinel structures in general and battery materials in particular.
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Materials Science
Benchmarking 34 OpenKIM Nickel Potentials with an Emphasis on Surfaces and Extended Defects
Matthew Thoms, Hao Sun and Laurent Karim Béland
We present an automated benchmarking suite for face-centered-cubic (FCC) nickel that evaluates 47 quantitative metrics spanning both standard tests (equation of state, elastic constants, surface energies and
phonons) and application-specific scenarios such as defect formation and migration, grain boundaries, step edges, close-range interactions, and vacancy cluster energetics. Using this framework, we assess 34 interatomic potentials from the OpenKIM repository, including pairwise, embedded-atom, modified-embedded-atom, angular-dependent, and spectral neighbor analysis potentials (SNAP). Results are compared against ab initio
benchmarks compiled from the literature. Most potentials accurately reproduce
lattice parameters, elastic constants, and surface energies, whereas predictive accuracy degrades for migration barriers and short-range compression. Principal-component analysis identifies correlated property groups and a partially orthogonal component associated with migration and short-range physics, revealing Pareto trade-offs between accuracy domains. SNAP models occupy the lowest-error frontier, although several embedded-atom potentials remain competitive across many metrics. The framework provides a reproducible baseline for potential selection, highlights systematic limitations across formalisms, and supports benchmarking-in-the-loop strategies for developing next-generation machine-learning potentials for Ni and Ni-based
alloys.
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Materials Science
SimplySQS: An Automated and Reproducible Workflow for Special Quasirandom Structure Generation with ATAT
Miroslav Lebeda, Jan Drahokoupil, Petr Vlčák et al. (+2 more)
The special quasirandom structure (SQS) method is widely used for modeling disordered materials under periodic boundary conditions, with the ATAT mcsqs module being one of the most established implementations. However, SQS generation with mcsqs typically relies on manual preparation of input files, ad hoc execution scripts, and post-processing steps, which introduces user-dependent errors and limits reproducibility. Here, we present SimplySQS (https://simplysqs.com), an automated and reproducible workflow for SQS generation that is delivered through an online, interactive interface. SimplySQS guides users through structure import, compositional and supercell definition, and cluster parameter selection, while automatically generating all required ATAT input files and a single all-in-one execution script that encapsulates the complete search process. By standardizing input preparation, execution, and output analysis, the framework minimizes errors associated with manual file handling and enables consistent reproducibility of SQS searches. The workflow is demonstrated on the Pb1-xSrxTiO3 (PSTO, including PbTiO3 (PTO) and SrTiO3 (STO)) perovskite system. SQSs spanning the entire concentration range were generated using a single automated bash script produced by SimplySQS, after which all resulting structures were subjected to geometry optimization using a universal machine-learning interatomic potential (MACE MATPES-r2SCAN-0). This approach reliably reproduced the experimentally observed cubic-to-tetragonal transition near x = 0.5, with
lattice parameters deviating by less than 1 % in the cubic region (x > 0.5) and less than 4 % in the tetragonal region (x < 0.5). Overall, SimplySQS transforms SQS generation with ATAT into an intuitive, reproducible, and systematic framework for modeling disordered materials.
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All authors Miroslav Lebeda, Jan Drahokoupil, Petr Vlčák, Šimon Svoboda, Axel van de Walle
Statistical Mechanics · Cross-listed from physics.comp-ph
Committors without Descriptors
Peilin Kang, Jintu Zhang, Enrico Trizio et al. (+2 more)
The study of rare events is one of the major challenges in atomistic simulations, and several enhanced sampling methods towards its solution have been proposed. Recently, it has been suggested that the use of the committor, which provides a precise formal description of rare events, could be of use in this context. We have recently followed up on this suggestion and proposed a committor-based method that promotes frequent transitions between the metastable states of the system and allows extensive sampling of the process transition state ensemble. One of the strengths of our approach is being self-consistent and semi-automatic, exploiting a variational criterion to iteratively optimize a neural-network-based parametrization of the committor, which uses a set of physical descriptors as input. Here, we further automate this procedure by combining our previous method with the expressive power of graph neural networks, which can directly process atomic coordinates rather than descriptors. Besides applications on
benchmark systems, we highlight the advantages of a graph-based approach in describing the role of solvent molecules in systems, such as ion pair dissociation or ligand binding.
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All authors Peilin Kang, Jintu Zhang, Enrico Trizio, TingJun Hou, Michele Parrinello
Mesoscale and Nanoscale Physics
Magnus Induced Magnetic Diode Effect in Skyrmion Systems
J. C. Bellizotti Souza, C. J. O. Reichhardt, C. Reichhardt et al. (+1 more)
We show that skyrmions can exhibit what we call a
magnetic diode effect, where there is a nonreciprocal response in the transport when the
magnetic field is reversed. This effect can be achieved for skyrmions moving in a channel with a sawtooth potential on one side and a reversed sawtooth potential on the other side. We consider the cases of both
spin-transfer torque (STT) and
spin-orbit torque (SOT) driving. When the
magnetic field is held fixed, the velocity response of the skyrmion is the same for current applied in either direction for both STT and SOT driving, so there is no current diode effect. When the
magnetic field is reversed, under STT driving the velocity of the skyrmion reverses and its absolute value changes. Under SOT driving, the velocity remains in the same direction but drops to a much lower value, resulting in negative differential conductivity. For a fixed current, we find a nonreciprocal skyrmion velocity as a function of positive and negative applied fields, in analogy to the velocity-current curves observed in the usual diode effect. The nonreciprocity is generated by the Magnus force, which causes skyrmions to interact preferentially with one side of the channel. Since the channel sides have opposite asymmetry, a positive
magnetic field can cause the skyrmion to interact with the "hard" asymmetry side of the channel, while a negative
magnetic field causes the skyrmion to interact with the easy asymmetry side. This geometry could be used to create new kinds of
magnetic-field-induced diode effects that can be harnessed in new types of skyrmion-based devices.
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All authors J. C. Bellizotti Souza, C. J. O. Reichhardt, C. Reichhardt, A. Saxena
Statistical Mechanics
First-passage properties of the jump process with a drift. The general case
Ivan N. Burenev
We study the first-passage properties of a jump process with constant drift where jump amplitudes and inter-arrival times follow arbitrary light-tailed distributions with smooth densities. Using a mapping to an effective discrete-time random walk, we identify three regimes determined by the drift strength: survival (weak drift), absorption (strong drift), and critical. We derive explicit expressions for exponential decay rates in the survival and absorption regimes, and characterize algebraic decay at the critical point. We also obtain asymptotic behavior of the mean first-passage time, number of jumps, and their variances for processes starting either close to the origin or far from it.
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Mesoscale and Nanoscale Physics
Interplay of Noise and Reservoir-induced Decoherence in Persistent Currents
Samudra Sur and Thierry Giamarchi
Persistent current is a hallmark of
quantum phase coherence. We study the fate of the persistent current in a non-
equilibrium setting, where a tight-binding ring is subjected to
stochastic disorder as well as a fermionic reservoir attached to each site. We evaluate the current using Keldysh technique and find that it exhibits non-monotonic behavior, suggesting two distinct mechanisms of decoherence. While coupling to the reservoirs introduces a coherence length scale given by the inverse of the coupling strength, the other mechanism is more subtle and driven by the ratio of noise strength to reservoir coupling. The interplay of noise and reservoir constitutes a purely non-
equilibrium steady state with a flatter distribution function that we effectively describe using classical rate equations. We discuss possibilities of realizing our findings in ultracold-atom experiments.
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Quantum Gases · Cross-listed from quant-ph
Experimental preparation of $W$ states through frustration on a programmable quantum simulator
Alberto Giuseppe Catalano, Ceren Dağ, Gianpaolo Torre et al. (+2 more)
$W$ states are a central class of multipartite entangled states with applications in
quantum information processing, yet their scalable and deterministic preparation remains challenging. Here we propose a protocol based on topological ring frustration, where an
antiferromagnetic ring with an odd number of sites hosts a delocalized excitation corresponding to a $W$ state. We implement this protocol on a Rydberg atom array – a programmable
quantum simulator – generating $W$ states of up to 11 atoms. Our results demonstrate a fidelity of $\mathcal{F} \approx 0.77$, and numerical simulations indicate scalability to larger system sizes accessible with near-term hardware improvements. To enable certification of these many-body entangled states, we introduce a novel and efficient
Bayesian tomography method that, leveraging on classical simulations, enables their certification with a cost that avoids the exponential scaling of full
tomography. These results establish topological frustration as a practical mechanism for engineering multipartite
entanglement and provide a scalable route toward the certification of correlated
quantum many-body states in
quantum simulators.
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All authors Alberto Giuseppe Catalano, Ceren Dağ, Gianpaolo Torre, Salvatore Marco Giampaolo, Fabio Franchini
Strongly Correlated Electrons
Lukasz Fidkowski, Cenke Xu and Carolyn Zhang
In this work we realize the 3 + 1 dimensional non-invertible ${\mathbb{Z}}_N$
chiral symmetry generator as an operator in a many body
lattice Hilbert space. A crucial ingredient in our construction is the use of infinite dimensional $U(1)$ rotor site
Hilbert spaces. Specifically, our
Hilbert space is that of a $U(1)$
lattice gauge theory coupled to a charge $1$ scalar in the Villain formulation, which allows for direct access to monopoles and for a simple definition of a
magnetic ${\mathbb{Z}}_N$ one-form
symmetry $Z^{(1)}_m$ , at the
lattice Hamiltonian level. We construct the generator of the ${\mathbb{Z}}_N$
chiral symmetry as as a
unitary operator in the subspace of $Z^{(1)}_m$-invariant states, and show that it cannot be extended to the entire
Hilbert space while preserving locality and unitarity. Using a
lattice-level duality based on gauging $Z^{(1)}_m$, we find a dual description of this subspace, as the subspace of a charge $1/N$ gauge theory invariant under an electric one-form
symmetry $Z^{(1)}_e$. We show that in this dual formulation, the
chiral symmetry generator does extend unitarily to the entire
Hilbert space, but has a mixed anomaly with the $Z^{(1)}_e$
symmetry.
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Materials Science
XDXD: End-to-end crystal structure determination with low resolution X-ray diffraction
Jiale Zhao, Cong Liu, Yuxuan Zhang et al. (+4 more)
Determining
crystal structures from X-ray diffraction data is fundamental across diverse scientific fields, yet remains a significant challenge when data is limited to low resolution. While recent deep learning models have made breakthroughs in solving the crystallographic phase problem, the resulting low-resolution electron density maps are often ambiguous and difficult to interpret. To overcome this critical bottleneck, we introduce XDXD, to our knowledge, the first end-to-end deep learning framework to determine a complete atomic model directly from low-resolution single-
crystal X-ray diffraction data. Our
diffusion-based generative model bypasses the need for manual map interpretation, producing chemically plausible
crystal structures conditioned on the diffraction pattern. We demonstrate that XDXD achieves a 70.4% match rate for structures with data limited to 2.0~Å resolution, with a root-mean-square error (RMSE) below 0.05. Evaluated on a
benchmark of 24,000 experimental structures, our model proves to be robust and accurate. Furthermore, a case study on small peptides highlights the model's potential for extension to more complex systems, paving the way for automated structure solution in previously intractable cases.
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All authors Jiale Zhao, Cong Liu, Yuxuan Zhang, Chengyue Gong, Zhenyi Zhang, Shifeng Jin, Zhenyu Liu
Strongly Correlated Electrons
Mott vs Kondo: Influence of Various Density Functional Based Methods on the Ce Isostructural Phase Transition Mechanism
Brenden W. Hamilton, Alexander R. Muñoz, Travis E. Jones et al. (+1 more)
The cerium iso-structural phase transition (gamma to alpha) is dominated by f-electron localization changes that results in a
magnetic ordering change and a volume collapse. Generally, these physics are difficult to capture with ab initio and first principles methods. However, previous works have shown various methods to be successful in predicting at least some of the physics of the gamma to alpha phase transition. Therefore, here, we perform a broad survey of density functional based methods across three levels of theory and types of functions (GGA, MetaGGA, and Hybrid functionals) and compare the results, focusing on hydrostatic compression across the phase boundary at zero Kelvin. For the methods that best reproduce experimental results, we directly probe the predicted mechanisms and frame the results in the Mott/Kondo debate, assessing how the underlying methods and assumptions of different functionals can assess the physical drivers in the phase transition, providing insight into the governing dynamics of this unique phase transition.
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All authors Brenden W. Hamilton, Alexander R. Muñoz, Travis E. Jones, Benjamin T. Nebgen