Strongly Correlated Electrons · Cross-listed from quant-ph
Universal quantum computation with group surface codes
Naren Manjunath, Vieri Mattei, Apoorv Tiwari et al. (+1 more)
We introduce group surface codes, which are a natural generalization of the $\mathbb{Z}_2$ surface code, and equivalent to
quantum double models of finite groups with specific boundary conditions. We show that group surface codes can be leveraged to perform non-Clifford gates in $\mathbb{Z}_2$ surface codes, thus enabling universal computation along with established means of performing logical Clifford gates. Moreover, for suitably chosen groups, we demonstrate that arbitrary reversible classical gates can be implemented transversally in the group surface code. We present the logical operations in terms of a set of elementary logical operations, which include transversal logical gates, a means of transferring encoded information into and out of group surface codes, and preparation and readout. By composing these elementary operations, we implement a wide variety of logical gates and provide a unified perspective on recent constructions in the literature for sliding group surface codes and preparing magic states. We furthermore use tensor networks inspired by ZX-calculus to construct spacetime implementations of the elementary operations. This spacetime perspective also allows us to establish explicit correspondences with topological gauge theories. Our work extends recent efforts in performing universal
quantum computation in topological orders without the braiding of anyons, and shows how certain group surface codes allow us to bypass the restrictions set by the Bravyi-König
theorem, which limits the computational power of topological Pauli stabilizer models.
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All authors Naren Manjunath, Vieri Mattei, Apoorv Tiwari, Tyler D. Ellison
Quantum Gases
Spin-resolved microscopy of $^{87}$Sr SU($N$) Fermi-Hubbard systems
Carlos Gas-Ferrer, Antonio Rubio-Abadal, Sandra Buob et al. (+3 more)
Quantum-gas microscopes provide direct access to the phases of the Hubbard model, bringing microscopic insight into the complex competition between interactions, SU(2) magnetism, and doping. Alkaline-earth(-like)
fermions extend this
spin-1/2 paradigm by realizing higher
symmetries and giving access to SU($N$) Hubbard models, with rich phase diagrams to be unveiled. Despite its fundamental interest, a microscopic exploration of SU($N$)
quantum systems has remained elusive. Here we report the realization of a
quantum-gas microscope for fermionic $^{87}$Sr. Our imaging scheme, based on cooling and fluorescence on the narrow intercombination line at 689 nm, enables
spin-resolved single-atom detection. By implementing a
spin-selective optical pumping protocol, we determine the occupation of each of the 10
spin states in a single experimental realization, a crucial capability for probing site-resolved
magnetic correlations. We
benchmark our method by observing single-particle Larmor precession across the full
spin-9/2 ground-state
manifold and use numerical simulations of SU($N$)
Fermi-Hubbard chains, incorporating the measured detection fidelities, to demonstrate its capability to resolve many-body
spin correlations. Our results establish $^{87}$Sr
quantum-gas microscopy as a powerful approach to study exotic magnetism in the SU($N$)
Fermi-Hubbard model, and provide a new detection tool for studies in
quantum simulation, computation, and metrology.
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All authors Carlos Gas-Ferrer, Antonio Rubio-Abadal, Sandra Buob, Leonardo Bezzo, Jonatan Höschele, Leticia Tarruell
Mesoscale and Nanoscale Physics
Manipulation of ferromagnetism with a light-driven nonlinear Edelstein-Zeeman field
Yinchuan Lv, W. Joe Meese, Azel Murzabekova et al. (+7 more)
Optical control of magnetization is often
symmetry-forbidden because electric fields and magnetization transform differently under inversion and time-reversal. However, through even-order nonlinear response, optical excitation can generate a nonequilibrium
magnetic density (the nonlinear Edelstein effect) that acts as an internal Edelstein-Zeeman field coupling to slower
magnetic degrees of freedom. Here we demonstrate non-thermal, ultrafast optical control of ferromagnetism in the centrosymmetric van der Waals
semiconductor Cr$_2$Ge$_2$Te$_6$ via a resonant nonlinear Edelstein effect. Using time-domain THz emission spectroscopy under near-infrared excitation, we directly observe
magnetic dipole radiation arising from optically driven magnetization dynamics. The polarization, fluence, and temperature dependences of the THz emission are quantitatively captured by a mean-field description of a weakly anisotropic Heisenberg ferromagnet subject to an Edelstein-Zeeman field. Our results establish a general nonequilibrium route to optical control of magnetism in centrosymmetric materials.
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All authors Yinchuan Lv, W. Joe Meese, Azel Murzabekova, Jennifer Freedberg, Changjun Lee, Yiming Sun, Joshua Wakefield, Takashi Kurumaji, Joseph Checkelsky, Fahad Mahmood
Quantum Gases
Efficient simulation of Bose-Einstein condensates in nontrivial topologies
Abel Beregi, Jean-Baptiste Gerent and Nathan Lundblad
Bubble-shaped Bose-Einstein condensates (BECs) constitute a unique class of
quantum fluids with a hollow, thin-shell geometry that supports a wide variety of phenomena that are distinct from those of compact condensates. Numerical simulation of such systems is particularly challenging due to their inherently three-dimensional structure and extreme aspect ratios. We present an efficient finite-difference simulation framework designed for solving partial differential equations in such nontrivial
topologies with a focus on the static and dynamical modeling of bubble-shaped BECs. By employing selective spatial sampling on a semi-structured grid, our method substantially reduces
memory usage and achieves more than an order-of-magnitude improvement in computational performance compared to conventional split-step
Fourier solvers. The
algorithm is naturally extendable for highly parallel execution on GPUs, enabling large-scale, time-dependent simulations of thin-shell condensates. We apply this framework to simulate the formation of bubble BECs through a controlled hollowing-out protocol using ab initio trapping potentials relevant to the Cold Atom Laboratory aboard the International Space Station. From these simulations, we identify characteristic timescales and parameter ramps required to achieve adiabatic
evolution, thereby assessing the feasibility of experimentally realizing bubble-shaped condensates in microgravity environments.
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Materials Science
High-Pressure Inelastic Neutron Spectroscopy: A true test of Machine-Learned Interatomic Potential energy landscapes
Jeff Armstrong, Adam Jackson and Alin Elena
Machine-learned interatomic potentials (MLIPs) promise to provide near density-functional theory accuracy at a fraction of the computational cost, offering a transformative route toward genuinely predictive chemistry. Yet their predictive validity beyond the training regime remains largely untested experimentally. Here we use pressure-dependent broadband inelastic
neutron spectroscopy (INS) as a direct experimental probe of MLIP transferability. Employing a newly developed high-pressure superalloy clamp
cell, we measure INS spectra of crystalline 2,5-diiodothiophene at 10~K under ambient conditions and at 1.5~GPa. A MACE-based MLIP, fine-tuned on targeted DFT data, reproduces the experimental spectra across 0–1200~cm$^{-1}$ at both pressures and remains thermodynamically stable under rigorous molecular dynamics validation at 300~K. The model captures systematic pressure-induced blue shifts arising from steric stiffening and reproduces an anomalous red shift at 453~cm$^{-1}$ driven by pressure-modified intermolecular interactions, providing direct validation of its many-body character. This constitutes the first experimental demonstration of MLIP transferability across distinct thermodynamic states using
neutron spectroscopy, and establishes high-pressure INS as a stringent
benchmark for predictive machine-learned potentials.
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Statistical Mechanics · Cross-listed from quant-ph
Measurement Induced Asymmetric Entanglement in a Deconfined Quantum Critical Ground State
K. G. S. H. Gunawardana
In this work, we numerically study the effect of weak measurement on deconfined
quantum critical point(DQCP). Particularly, we consider the ground state of an one-dimensional
spin $1/2$ system with next-nearest-neighbour exchange interactions($K$), which shows analogues phase transition to DQCP in the thermodynamic limit. This system is in the
ferromagnetic phase below the critical exchange interaction $K_c$ and in the valance bond solid phase above $K_c$. The weak measurement is carried out by coupling a secondary ancilla system to the critical system via
unitary interactions and later measuring the ancilla
spins projectively. We numerically calculate
entanglement entropy,correlation length, and order parameters of leading post-measurement states using uniform
matrix product state representation of the
quantum many-body state in the thermodynamic limit. We report asymmetric restructuring of
entanglement of the post measurement states across the phase boundary under weak measurements. Especially, the trajectory $\left(\downarrow \downarrow\right)$ describing a uniform measurement outcome given the all ancilla
spins initiated in the same $\left(\downarrow \right)$ state, shows anomalous
entanglement when increasing the strength of weak measurement. The bipartite
entanglement entropy strongly increases when $K<K_c$ whereas it weakly decreases when $K>K_c$. We argue with numerical evidences that observed asymmetry in
entanglement would lead to a weak first order phase boundary in the thermodynamic limit. We also discuss important aspects in experimental observation of measurement induced effects linked to the strength of weak measurement and probability of post-measurement states.
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Disordered Systems and Neural Networks · Cross-listed from quant-ph
Extreme Quantum Cognition Machines for Deliberative Decision Making
Francesco Romeo and Jacopo Settino
We introduce Extreme
Quantum Cognition Machines, a class of
quantum learning architectures for deliberative decision making designed to operate under coarse-grained, ambiguous, and potentially contradictory information. Inspired by the
quantum cognition paradigm, Extreme
Quantum Cognition Machines are closely related to
quantum extreme learning and
quantum reservoir computing, where fixed
quantum dynamics generates a nonlinear feature map and learning is confined to a linear readout. A dynamical
attention mechanism, implemented through an input-dependent interaction term in the
Hamiltonian, modulates the
quantum evolution and biases the resulting feature
embedding toward task-relevant correlations. The approach is validated on linguistic classification tasks, which serve as paradigmatic examples of deliberative inference. Hardware-compatible
quantum implementations of the proposed framework are discussed, together with potential applications in symbolic inference, sequence analysis, anomaly detection, and automatic diagnosis, with direct relevance to domains such as biology, forensics, and cybersecurity.
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Disordered Systems and Neural Networks · Cross-listed from quant-ph
Optimal Decoding with the Worm
Zac Tobias, Nikolas P. Breuckmann and Benedikt Placke
We propose a new decoder for "matchable” qLDPC codes that uses a Markov Chain Monte Carlo
algorithm - called the worm
algorithm - to approximately compute the probabilities of logical error classes given a syndrome. The
algorithm hence performs (approximate) optimal decoding, and we expect it to be computationally efficient in certain settings. The
algorithm is applicable to decoding random errors for the surface code, the honeycomb Floquet code, and
hyperbolic surface codes with constant rate, in all cases with and without measurement errors. The efficiency of the decoder hinges on the mixing time of the underlying Markov chain. We give a rigorous mixing time guarantee in terms of a quantity that we call the defect susceptibility. We connect this quantity to the notion of disorder operators in statistical mechanics and use this to argue (non-rigorously) that the
algorithm is efficient for typical errors in the entire decodable phase. We also demonstrate the effectiveness of the worm decoder numerically by applying it to the surface code with measurement errors as well as a family of
hyperbolic surface codes. For most codes, the matchability condition restricts direct application of our decoder to noise models with independent bit-flip, phase-flip, and measurement errors. However, our decoder returns soft information which makes it useful also in heuristic "correlated decoding” schemes which work beyond this simple setting. We demonstrate this by simulating decoding of the surface code under depolarizing noise, and we find that the threshold for "correlated worm decoding” is substantially higher than for both minimum-weight perfect matching and for correlated matching.
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Materials Science
Equilibrium Thermochemistry and Crystallographic Morphology of Manganese Sulfide Nanocrystals
Junchi Chen, Tamilarasan Subramani, Deep Mekan et al. (+8 more)
Manganese sulfide (MnS) is a p-type
magnetic semiconductor whose physicochemical properties are sensitive to nanocrystal (NC) morphology, yet the thermodynamic driving forces governing morphology across MnS polymorphs remain poorly understood. Here, we use density functional theory (DFT) to predict the
equilibrium morphologies of rock salt (RS), zinc blende (ZB), and wurtzite (WZ) MnS NCs as a function of the relative chemical potential of sulfur, $\Delta \mu_{S}$. Benchmarking against Heyd$\unicode{x2013}$Scuseria$\unicode{x2013}$Ernzerhof (HSE06) hybrid functional calculations reveals that the r$^2$SCAN meta-generalized gradient approximation reproduces experimental
lattice constants and thermochemical reaction energies but underestimates S-terminated polar surface energies by up to a factor of five; applying a Hubbard $U$ correction (r$^2$SCAN+$U$, $U = 2.7$ eV) to the Mn 3d states brings the results into close agreement with HSE06. Using the benchmarked r$^2$SCAN+$U$ framework with the Gibbs$\unicode{x2013}$Wulff
theorem, we predict that RS-MnS NCs favor nanocubes across nearly the entire stability window, ZB-MnS NCs transform from rhombic dodecahedra (Mn-rich) to polyhedra with 16 triangular faces (S-rich), and WZ-MnS NCs adopt rod-like morphologies with $\Delta \mu_{S}$-sensitive base truncation. Synthesized RS-MnS NCs confirm the predicted cubic morphology, and high-temperature oxidative solution calorimetry yields an apparent surface energy of 1.15 $\pm$ 0.38 J$\cdot$m$^{-2}$, higher than the theoretical
equilibrium value (0.42$\unicode{x2013}$0.43 J$\cdot$m$^{-2}$), which we attribute to high-index facet exposure, surface area uncertainty, and non-ideal surface configurations in real samples. This work establishes a framework for predicting the
equilibrium morphologies of metal chalcogenide NCs.
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All authors Junchi Chen, Tamilarasan Subramani, Deep Mekan, Danielle Gendler, Ray Yang, Manish Kumar, Megan Householder, Alexis Rosado Ortiz, Emil A. Hernandez-Pagan, Kristina Lilova, Robert B. Wexler
Mesoscale and Nanoscale Physics
Odd-Parity-Wave Magnons and Nonrelativistic Thermal Edelstein Effect
Robin R. Neumann, Rodrigo Jaeschke-Ubiergo, Ricardo Zarzuela et al. (+3 more)
Odd-parity-wave magnets are noncollinear compensated magnets with
spin-split band structure in the absence of
spin-orbit coupling and dipolar interactions. In contrast to altermagnets, their
spin-polarized band structure breaks inversion
symmetry, but preserves time-reversal
symmetry rendering their
spin texture odd in momentum space. Here, we study the
spin dynamics of the
magnetic texture and compute the band structure and
spin polarization of
magnons. We present minimal
spin models of noncoplanar odd-parity-wave magnets purely stabilized by exchange interactions that host p- and f-wave
spin textures for the
magnetic excitations. We demonstrate that two of these models exhibit collinear
spin textures, i.e., the
magnon spin polarization is restricted to a global (quantization) axis independent of the momentum giving rise to single-component odd-parity-wave magnetism, previously associated primarily with coplanar ground states. Finally, the nonrelativistic magnonic thermal Edelstein effect – a nonequilibrium magnetization induced by a temperature gradient – is shown to exist for p-wave magnets in linear response and inherits its anisotropic angular dependence from the partial-wave character of the
spin-polarized band structure. Our findings suggest that insulating odd-parity-wave magnets are promising candidates for
magnon spintronics applications.
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All authors Robin R. Neumann, Rodrigo Jaeschke-Ubiergo, Ricardo Zarzuela, Libor Šmejkal, Jairo Sinova, Alexander Mook
Materials Science · Cross-listed from quant-ph
Extending spin-lattice relaxation theory to three-phonon processes
Nilanjana Chanda and Alessandro Lunghi
Spin-
lattice relaxation theory has been developed over almost a century, but some cardinal assumptions on the nature of the interactions involved have never been fully verified. This includes the weak coupling approximation, which makes it possible to describe
spin dynamics perturbatively and leads to the canonical description of
spin relaxation in terms of one- and two-
phonon processes. Here, we extend the first-principles theory of
spin relaxation to three-
phonon processes and apply it to the vdW
crystal of a
spin-1/2 Chromium nitride complex. Results show that three-
phonon contributions to
spin relaxation only become relevant at temperatures inaccessible to experiments for this molecule, thus providing unprecedented evidence for the validity of the weak
spin-
phonon coupling assumption in
spin relaxation theory. At the same time, we numerically show that a relatively small increase in
spin-
phonon coupling would lead to a crossover between three- and two-
phonon processes' efficiency at room temperature, illustrating the possibility for three-
phonon effects in molecular materials as well as paving the way to a systematic exploration of strong coupling in
spin systems.
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Statistical Mechanics
Extreme Values of Infinite-Measure Processes
Talia Baravi and Eli Barkai
We study the statistics of the maximum and minimum of a set of $N$ random variables whose dynamical and statistical properties fall within the scope of infinite ergodic theory. These non-stationary yet recurrent systems are described, in the long-time limit, by a non-normalizable infinite invariant density. Extreme events in such systems emerge in a joint limit where the observation time $t$ is long and the number of variables $N$ is large. We show that the resulting extreme value statistics are controlled by the return exponent $\alpha$ and the infinite invariant measure, and therefore depart from the classical Fréchet, Gumbel, and Weibull universality classes. We illustrate the theory for weakly chaotic intermittent maps, overdamped
diffusion in an asymptotically flat potential, and a
stochastic model of sub-
recoil laser cooling, and show how measurements of extremes can be used to infer the infinite-density structure.
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Other Condensed Matter
Evidence for Vortex Rings with Multiquantum Circulation in He II
Yiming Xing, Yousef Alihosseini, Sosuke Inui et al. (+1 more)
Quantized
vortex dynamics in superfluid $^4$He (He~II) are widely regarded as well established: circulation is quantized in units of $\kappa=h/m_4$,
vortices carrying more than one
quantum are expected to split into singly quantized filaments, and
vortex rings shrink while accelerating due to dissipation from thermal-quasiparticle scattering. Using particle tracking velocimetry with frozen deuterium tracers, we uncover rare
vortex-bound particle events that disrupt this canonical picture. In a class of events exhibiting the acceleration characteristic of shrinkage driven
vortex ring motion, the measured kinematics cannot be reconciled with a singly quantized ring. Instead, they require an effective circulation $n\kappa$ with $n>1$, directly challenging the standard expectation that multiquantum
vortices are short lived. A more prosaic possibility is that the inferred $n\kappa$ arises from a bundle of closely spaced singly quantized rings, which could generate similar large-scale motion. However, this scenario is disfavored by
vortex-filament simulations that show rapid bundle dispersion. Furthermore, the persistence of particle trapping at the observed high speeds suggests a much deeper core trapping potential, consistent only with a truly multiquantum core. Together, these results point to anomalously long-lived multiquantum rings, a striking puzzle that calls for dedicated scrutiny beyond the prevailing paradigm.
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All authors Yiming Xing, Yousef Alihosseini, Sosuke Inui, Wei Guo
Superconductivity
Temperature-Dependent Dielectric Function of Tantalum Nitride Formed by Atomic Layer Deposition for Tunnel Barriers in Josephson Junctions
Ekta Bhatia, Aaron Lopez Gonzalez, Yoshitha Hettige et al. (+9 more)
We report the dielectric functions of insulating tantalum nitride (TaN) films, deposited using atomic layer deposition (ALD) on 300 mm Si/SiO2 substrates, to demonstrate their suitability as tunnel barriers in tantalum-based Josephson junctions (JJ) for superconducting
quantum circuits. The temperature-dependent ellipsometric angles were measured using ALD TaN films with nominal thicknesses of 13 nm and 25 nm at an incidence angle of 70 degrees, across
photon energy ranges of 0.03 eV to 0.7 eV (80-300 K) and 0.5 eV to 6.5 eV (80-600 K). This data was used to develop a dispersion model for insulating ALD TaN films that incorporates a Tauc-Lorentz oscillator with a band gap of 1.5-1.8 eV to model the interband optical transitions. The extracted dielectric function of ALD TaN films shows an insulating behavior (mid-infrared transparency) at all temperatures and for both film thicknesses tested. ALD TaN does not exhibit infrared absorption due to free carriers, even at elevated temperatures, demonstrating its insulating nature, which is required for the tunnel barrier of the JJ in
quantum applications. The results of transmission electron microscopy, including selected area electron diffraction, and X-ray diffraction are also discussed. Sputter depth-profile X-ray photoelectron spectroscopy (XPS) shows an N/Ta ratio of ~1.2 throughout the film. The lower band gap, low roughness, and thermal stability of ALD TaN compared to AlOx suggest the possibility of fabricating JJs with thicker barriers while achieving critical current densities required for
qubits, better control of thickness and composition, reduced topography, and resistance to aging.
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All authors Ekta Bhatia, Aaron Lopez Gonzalez, Yoshitha Hettige, Tuan Vo, Sandra Schujman, Kevin Musick, Thomas Murray, Kim Kisslinger, Chenyu Zhou, Mingzhao Liu, Satyavolu S. Papa Rao, Stefan Zollner
Materials Science
Correcting hybrid density functionals to model Y6 and other non-fullerene acceptors
Tom Ward, Isabel Creed, Tim Rein et al. (+1 more)
Recently developed fused-ring electron-acceptors such as Y6 (BTP-4F) have strong oscillator strength, good charge-carrier transport and a small bandgap. They therefore have enormous current technical application to organic optoelectronics, such as
solar cells. To design new materials, it would be useful to predict the electronic structure accurately. Due to the large number of atoms involved in representative aggregates of these materials, we need an efficient electronic structure method. Standard density functional theory poorly describes charge-transfer states, and were typically parameterised for
vacuum calculations of individual molecules. In this work we tune a range-separated hybrid functional for Y6, and characterise representative dimers extracted from the solid-state. We demonstrate that the extensive solvatochromic effects of Y6 are due, in part, to oscillator strength borrowing between the charge-transfer and Frenkel
excitons. We provide an explanation for the short optimally-tuned range-separation parameter, based on the Penn model for the frequency dependent dielectric of a
semiconductor. We caution that non-tuned range-separated hybrids are less accurate than global hybrids for these, and similar, materials. We show how reducing the range-separation length improves the accuracy of standard range-separation functionals, without an involved tuning process.
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All authors Tom Ward, Isabel Creed, Tim Rein, Jarvist Moore Frost
Statistical Mechanics
Finite-size scaling in quasi-3D stick percolation
Ryan K. Daniels
This work extends the universal finite-size scaling framework for continuum percolation from two-dimensional (2D) to quasi-three-dimensional (Q3D) stick systems, in which sequentially deposited wires of finite diameter stack vertically on a flat substrate. Using Monte Carlo simulation, the percolation threshold is determined for isotropic Q3D stick systems as $N_c l^2 = 6.850923 \pm 0.000014$, approximately $21.5\%$ above the established 2D value of $5.6373$. The threshold is shown to be independent of the wire diameter-to-length ratio $d/l$, reflecting the scale invariance of the contact
topology under sequential deposition. Simulation results indicate that, as for 2D networks, the spanning probability of Q3D stick percolation on square systems with free boundary conditions collapses onto a single universal scaling function once a nonuniversal metric factor is introduced. This collapse is consistent with the universal scaling function established for 2D continuum and
lattice percolation.
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Materials Science
PolyRapid: Automated High-Throughput Screening of Polymers Using a Computational Workflow
Lois Smith, Samuel Ericson, Vittoria Fantauzzo et al. (+3 more)
High-throughput computational screening of
polymers offers a powerful way to address the imbalance between the vast number of
polymers synthesised for diverse applications and the relatively small subset that can be studied using atomistic simulations. This work presents PolyRapid: an automatic workflow designed to enable the rapid and efficient screening of an extensive
polymer library. In this work it is deployed on a library of 103 homopolymers. The workflow integrates an automated annealing protocol with adaptive control, allowing for reproducible simulations with minimal human intervention and minimisation of the computational cost. To this end, we test a number of quantitative conformational and energetic convergence metrics. It achieves equilibration in 95% of systems within four 30 ns annealing cycles, and 100% within nine annealing cycles saving, for our
dataset, more than 2500 hours of compute compared to a fixed equilibration protocol. The simulation results are compared with experimental data and compiled into a publicly available repository which reports
polymer temperature, tacticity and crystallinity. The availability of a homogenous large set of simulations enables the adoption of machine learning approaches for a variety of tasks. We exemplify this possibility by proposing rapid machine-learning-based method to predict the (computed)
polymer density (F1-score = 0.91) and (experimental) glass transition temperature (F1-score = 0.76), using both chemical fingerprint representations and physically meaningful MD-derived descriptors.
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All authors Lois Smith, Samuel Ericson, Vittoria Fantauzzo, Chin Yong, Paola Carbone, Alessandro Troisi
Materials Science
A Shift-Invariant Deep Learning Framework for Automated Analysis of XPS Spectra
Issa Saddiq, Yuxin Fan, Robert G. Palgrave et al. (+3 more)
X-ray Photoelectron Spectroscopy (XPS) is a crucial technique for material surface analysis, yet interpreting its spectra is often challenging for both human analysts and automated methods due to the prevalence of variable spectral shifts and overlapping peaks. This project introduces a machine learning solution using a Spatial
Transformer Network (STN), a type of neural network that implicitly learns to align spectra. An STN model was designed to classify the chemical environments present in an input spectrum, using functional groups as a proxy. The model was trained and tested on a large synthetic
dataset of 100,000 spectra, created by linearly combining real experimental data from a library of 104
polymers. \cite{RN22} To simulate experimental variability, random uniform shifts and broadening were applied to the data. The STN was found to effectively correct for random electrostatic shifts (up to 3.0 eV) and achieved relatively high accuracy ($\sim$ 82%) in identifying functional groups, despite utilizing a much simpler architecture than previous work. These findings demonstrate that neural networks can effectively learn the underlying relationships between spectral features and chemical composition when they are able to intrinsically account for variable shifts. This work advances the development of more reliable automated XPS analysis, offering potential as an assistive tool for researchers and as a core component in future autonomous systems like self-driving laboratories.
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All authors Issa Saddiq, Yuxin Fan, Robert G. Palgrave, Mark A. Isaacs, David Morgan, Keith T. Butler
Materials Science · Cross-listed from physics.optics
Pulse-duration-sensitive high harmonics and attosecond locally-chiral light from a chiral topological Weyl semimetal
Alba de las Heras, Ofer Neufeld and Angel Rubio
High harmonic generation (HHG) in solids results from an interplay between intraband acceleration and electron-hole recombination driven by a high-intensity
laser pulse. Here, we theoretically reveal that the driving pulse duration can play a major role in extending HHG to higher
photon energies by promoting higher conduction band excitations. The effect is present in a conventional
semiconductor as Si, restricted in a large-gap
insulator as MgO, and most prominent in RhSi, a prototypical
chiral Weyl semimetal presenting numerous band crossings. Further, we elucidate the HHG selection rules in RhSi required for the synthesis of attosecond locally
chiral light. The
chiral crystal structure enables the generation of a local 3D electric field exhibiting an asymmetric instantaneous torsion on attosecond timescales. A pronounced circular dichroism emerges when the driving helicity is either aligned with or opposite to the
crystal handedness. Our findings motivate future experiments in
chiral Weyl semimetals to track high-energy band crossings and in-situ locally
chiral light, paving the way for
chiral compact light sources and light-wave driven topological electronics.
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Mesoscale and Nanoscale Physics
Observation of Superfluidity and Meissner Effect of Composite Bosons in GaAs Quantum Hall System
Yuanze Li, Renfei Wang, Jiahao Chen et al. (+7 more)
The
quantum Hall effect (QHE) is theoretically understood as a superfluid condensate of composite
bosons (CBs) – bound states of electrons and
magnetic flux quanta. While dissipationless transport is consistent with this picture, other signatures of superfluidity, such as the Meissner effect, remain elusive. Here, we present direct experimental evidence for CB superfluidity by probing the system's response to a controlled, time-varying
magnetic field in Corbino disk geometries. We simultaneously observe the quantized Laughlin charge pumping and a new, quantized charge accumulation phenomenon, governed by the relation $\Delta Q_{\rm a}/e = \nu\,(\Delta \Phi/\Phi_0)$. This relation signifies that the system actively maintains the fixed electron-to-flux ratio that defines the CBs, neutralizing excess flux by drawing in a precise number of electrons. Crucially, devices with multiple concentric top gates reveal that this charge accumulation is uniformly distributed across the bulk of the QHE fluid, demonstrating that it is a collective, bulk property rather than an edge effect – a key signature of a superfluid condensate. Furthermore, the presence of a top gate determines the screening mechanism: in a "grand canonical" setting with a gate, low Coulomb energy favors a charge-mediated screening (generalized Meissner effect); without a gate, the system enters a "canonical" regime, exhibiting fixed electron density like type-II
superconductors. These observations confirm the CB superfluid nature of the QHE ground state and establish a versatile platform for studying macroscopic
quantum coherence and its screening transitions in two dimensions.
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All authors Yuanze Li, Renfei Wang, Jiahao Chen, Wenfeng Zhang, Adbhut Gupta, Kirk W. Baldwin, Loren Pfeiffer, Rui-Rui Du, Yang Liu, Tian Liang
Disordered Systems and Neural Networks
Strong zero modes in random Ising-Majorana chains
Saurav Kantha and Nicolas Laflorencie
We investigate the fate and robustness of topological strong zero modes (SZMs) in random Ising-Majorana chains using the SZM fidelity, ${\cal F}_{\rm SZM}$, as a many-body diagnostic that quantifies how accurately SZM operators map the entire spectrum between opposite parity sectors. In clean systems, ${\cal F}_{\rm SZM}=1$ in the topological phase, vanishes in the trivial regime, and takes the universal value $\sqrt{8}/\pi$ at the $(1+1)$D Ising critical point. Here we study how quenched disorder modifies this picture across the infinite-randomness fixed point (IRFP) governing the criticality of the random chain. In both microcanonical and canonical ensembles, SZMs persist throughout the topological phase, including the gapless Griffiths regime, with fidelities converging exponentially to unity. At the IRFP, however, the fidelity distributions become ensemble dependent: the microcanonical ensemble displays bimodal peaks at $\{0.5,1\}$, while the canonical ensemble develops a triple-peak structure at $\{0,0.5,1\}$ with power-law singularities. Our results establish ${\cal F}_{\rm SZM}$ as a robust probe of localization-protected topological order and uncover distinctive topological features of infinite-randomness criticality. Unlike the clean Ising CFT, where the finite critical value arises from a cancellation of power laws, the IRFP seems to exhibit an intrinsically stronger topological character. The edge-selective structure of the critical distributions may suggest a boundary manifestation of the average Kramers-Wannier duality
symmetry at the IRFP.
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Soft Condensed Matter
Dynamic Wettability Modulation of Textured, Soft and LIS Interfaces Using Electrowetting
Deepak J., Suman Chakraborty, Shubham S. Ganar et al. (+1 more)
Electrowetting on textured and lubricant infused surfaces is conventionally expected to promote enhanced droplet spreading by reducing apparent contact angles. Contrary to this intuition, we report rapid tangential droplet ejection at applied DC voltages on specific microtextured, lubricant infused surfaces. Using high speed imaging and a precisely controlled electrowetting setup, we reveal the dependence of droplet dynamics on surface
topology, wetting state, and the presence of a lubricant. On densely textured thick PDMS substrates of post spacing 5 to 10 um in a low hysteresis non-wetting Cassie state, and on all lubricant infused textured surfaces, droplets experience sudden lateral motion and eventual detachment. We attribute this counterintuitive phenomenon to unbalanced electrocapillary forces at the contact line combined with minimal pinning, which allows asymmetries in electric stresses to translate directly into net lateral motion. In contrast, Wenzel state droplets or surfaces with larger texture spacing exhibit conventional spreading with strong adhesion. By capturing the fundamental interplay among electrostatic driving forces, contact line pinning, and interfacial mobility, our results provide a new paradigm for controlled droplet transport and ejection in electrowetting systems mediated by dense micro posts and lubricant induced interfaces.
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All authors Deepak J., Suman Chakraborty, Shubham S. Ganar, Arindam Das
Statistical Mechanics
Dynamical quantum phase transitions through the lens of mode dynamics
Akash Mitra and Shashi C. L. Srivastava
We study the mode dynamics of a generic quadratic fermionic
Hamiltonian under a sudden quench protocol in momentum space. Modes with zero energy at any given time, $t$, are referred to as dynamical critical modes. Among all zero-energy modes,
spin-flip
symmetry is restored in the eigenvector corresponding to selected zero-energy modes. This
symmetry restoration is used to define the dynamical
quantum phase transition (DQPT). This shows that the occurrence of these dynamical critical modes is necessary but not sufficient for a DQPT. We show that the conditions on the quench protocol and time for such dynamical
symmetry restoration are the same as the divergence of the rate function and integer jump in the dynamical topological order parameter, which have been the traditional identifiers of a DQPT. This perspective also naturally explains when one or both of DQPT and ground-state
quantum phase transitions will occur.
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Statistical Mechanics · Cross-listed from physics.soc-ph
Wealth Taxation as a Drift Modification: A Fokker-Planck Approach to Tax Neutrality
Anders G Frøseth
We reformulate the neutral wealth tax framework of Froeseth (2026; arXiv:2603.05264) in the
language of
stochastic dynamics and statistical physics. Individual wealth under
geometric Brownian motion satisfies a Langevin equation with multiplicative noise; the probability density of wealth across a population then evolves according to a Fokker-Planck equation. A proportional wealth tax at
market value enters as a uniform reduction of the drift coefficient, preserving the
diffusion structure and all relative probability currents. This drift-shift
symmetry is the physical content of tax neutrality. Each channel through which neutrality breaks down in practice - book-value assessment, liquidity frictions, forced dividend extraction, migration, and
market impact - corresponds to a specific violation of this
symmetry: a state-dependent, asset-dependent, or flow-dependent modification of the Fokker-Planck equation. The framework clarifies when wealth taxation is a benign rescaling of the dynamics and when it introduces genuinely new physics.
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Materials Science
Lattice dynamics of the charge density wave compounds TaTe$_4$ and NbTe$_4$ and their evolution across solid solutions
D. Silvera-Vega, G. Cardenas-Chirivi, J. A. Galvis et al. (+2 more)
Understanding
lattice dynamics is central to elucidating the microscopic origin of charge density waves (CDWs), particularly in materials where electron-
phonon coupling can play a dominant role. Raman spectroscopy, combined with first-principles calculations, offers a direct means to identify the vibrational modes involved and to monitor their
evolution under controlled perturbations. In this work, we combine density functional theory calculations and Raman spectroscopy measurements to investigate the vibrational properties of the quasi-one-dimensional transition metal tetrachalcogenides TaTe$_4$ and NbTe$_4$, as well as their solid solutions Ta$_{1-x}$Nb$_{x}$Te$_4$ ($x$ = 0.0 - 1.0). For the stoichiometric compounds, first-principles calculations predict a
phonon instability consistent with the trimerization associated with the CDW phase, providing theoretical evidence for the
lattice distortion driving the transition. The calculated Raman-active modes show good agreement with room-temperature experimental spectra, enabling a systematic assignment of the observed peaks. Across the solid solution, most Raman modes evolve smoothly with composition. In contrast, the highest-frequency E$_{g}$ mode, dominated by transition-metal motion, exhibits a distinct behavior: its frequency remains close to that of the parent compounds while its intensity redistributes with stoichiometry. This
evolution highlights the short-range character of this vibrational mode and suggests its relevance to the CDW-related
lattice distortion in these materials.
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All authors D. Silvera-Vega, G. Cardenas-Chirivi, J. A. Galvis, A. C. García-Castro, P. Giraldo-Gallo
Strongly Correlated Electrons
Higher harmonics in Mott-Hubbard insulators as sensors
Abdelrahman Azab, Friedemann Queisser, Gulloo Lal Prajapati et al. (+2 more)
Using strong-coupling time-dependent perturbation theory, we study the response of Mott and charge-transfer
insulators to an oscillating electric field. We derive analytical expressions for the resulting higher-harmonic currents and show that they encode information about
spin order and microscopic hopping pathways. The results demonstrate that higher harmonics can serve as probes of correlated materials and as sensors of the applied driving field.
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All authors Abdelrahman Azab, Friedemann Queisser, Gulloo Lal Prajapati, Jan-Christoph Deinert, Ralf Schützhold
Materials Science
Precise control of crystallography and magnetism in focused-ion-beam transformed iron-nickel thin films
Jakub Holobrádek, Libor Vojáček, Ondřej Wojewoda et al. (+2 more)
Focused ion beam irradiation of metastable Fe$_{78}$Ni$_{22}$ thin films grown on Cu(100) substrates results in the localized transformation of the originally paramagnetic, face-centered-cubic continuous film into
ferromagnetic patterns with body-centered-cubic structure. The direction of the
magnetic easy axis can be controlled by the focused ion beam scanning strategy, resulting in eight differently oriented crystallographic domains with different
magnetic properties. We study the local crystallographic orientations of the transformed areas by electron backscatter diffraction and correlate these results with local magnetometry measurements. The observed
magnetic anisotropy can be explained as a result of residual
lattice strain after the fcc$\to$bcc transformation. These results extend the understanding of this material system and its transformation and allow for the patterning of high-quality
magnetic nanostructures with precisely controlled magnetization landscapes.
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All authors Jakub Holobrádek, Libor Vojáček, Ondřej Wojewoda, Michael Schmid, Michal Urbánek
Materials Science
Multi-fidelity Machine Learning Interatomic Potentials for Charged Point Defects
Xinwei Wang, Irea Mosquera-Lois and Aron Walsh
Machine learning interatomic potentials (MLIPs) can now reproduce the energy, forces and stresses of bulk materials with high accuracy compared to first-principles calculations. The description of imperfections, where coordination environments and electron counts deviate from those found in pristine reference structures, remains a challenge. We find that the current generation of foundation MLIPs do not describe the defect physics of the
semiconductor Sb2Se3. We introduce global defect charge
embeddings that distinguish the bonding characteristics of different charge states. We further employ a multi-fidelity approach that combines low-cost (semi-local exchange-correlation functional) reference data with high-quality (non-local hybrid functional) energies and forces that describe well the subtleties of the defect energy landscape. The resulting defect-capable force fields can find stable structural configurations and predict defect thermodynamics in quantitative agreement with direct
quantum mechanical calculations, at a fraction of the computational cost.
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Statistical Mechanics
The bliss of dimensionality: how an unsupervised criterion identifies optimal low-resolution representations of high-dimensional datasets
Margherita Mele, Daniel Campos Moreno and Raffaello Potestio
Selecting the optimal resolution for discretizing high-dimensional data is a central problem in physics and data analysis, particularly in unsupervised settings where the underlying distribution is unknown. The resolution-relevance (Res-Rel) framework addresses this issue through an information-theoretic trade-off between descriptive detail and statistical reliability. Here we provide a systematic validation of this approach by comparing its characteristic optima - maximum relevance and the -1 slope point - with the discretization that minimizes the Kullback-Leibler divergence from a known or physically motivated ground truth distribution. Across unstructured and structured synthetic
datasets, Gaussian clones of MNIST, and molecular dynamics simulations of the alanine dipeptide, we find that as the dimensionality or informative content increases the KL-optimal discretization consistently lies within the Res-Rel optimality region. Furthermore, in high-dimensional regimes the -1 slope criterion closely matches the KL divergence minimum. These results establish the quantitative consistency of unsupervised information-theoretic selection with distribution-based optimality.
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Soft Condensed Matter
Theories of the Glass Transition Based on Local Excitations
Massimo Pica Ciamarra, Jeppe C. Dyre, Edan Lerner et al. (+1 more)
The dramatic slowdown of dynamics in supercooled
liquids approaching the glass transition remains one of the central unresolved problems in condensed matter physics. We review approaches that attribute this slowdown to growing thermodynamic or structural length scales and discuss their difficulties in accounting for recent numerical results. These limitations motivate the present review, which critically examines alternative theories in which the glassy slowdown is instead controlled by localized excitations and their elastic interactions. After reviewing key phenomenology with a focus on the fragility of
liquids, dynamical heterogeneities, thermodynamics-dynamics correlation, and the effect of kinetic rules and swap
algorithms, we compare elastic descriptions based on homogeneous and local heterogeneous elasticity to excitation-based theories incorporating nonlinear responses. Results are compiled to relate global and local elastic
moduli, the Debye-Waller factor, and the density of excitations, leading to a quantitative theory testable in experiments. The thermal
evolution of the excitation spectrum provides a parameter-free account of the activation energy, while their elastic interactions quantitatively reproduce dynamical heterogeneities via thermal avalanche processes. Synthesized together, these results lead to a framework where the
evolution of the excitation spectrum, rather than the growth of a thermodynamic length scale, governs fragility in simple glass-forming
liquids – yet mean-field concepts of dynamical transitions remain central to describing excitations and building a real-space picture of relaxation.
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All authors Massimo Pica Ciamarra, Jeppe C. Dyre, Edan Lerner, Matthieu Wyart