Statistical Mechanics
When Normality Tests Detect Equilibrium Distributions of Finite N-Body Systems
Jae Wan Shim
The particle number $N$ can be used as a quantitative gauge of non-Gaussianity. This idea extends to systems that are not literally finite by assigning them a notional $N$ that captures the same deviation. For an ideal gas with $N$ insufficiently large for the thermodynamic limit, the velocity distribution that maximises Havrda-Charvát
entropy departs markedly from the Maxwell–Boltzmann (Gaussian) form obtained in that limit. We explore how five standard normality tests – Kolmogorov-Smirnov, Anderson-Darling, Cramér–von Mises, Jarque-Bera and Shapiro-Wilk – respond to samples drawn from this finite-$N$
equilibrium distribution. A large-scale Monte Carlo study maps the tests' statistical power across system size $N$ and sample size $n$, providing practical reference tables and a heuristic scaling law, visualised as a contour plot, that together indicate when finite-size effects remain detectable.
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Statistical Mechanics
Dynamics of stochastic oscillator chains with harmonic and FPUT potentials
Emilio N.M. Cirillo, Matteo Colangeli, Claudio Giberti et al. (+1 more)
Inspired by recent studies on deterministic oscillator models, we introduce a
stochastic one-dimensional model for a chain of interacting particles. The model consists of $N$ oscillators performing continuous-time random walks on the integer
lattice $\mathbb{Z}$ with exponentially distributed waiting times. The oscillators are bound by confining forces to two particles that do not move, placed at positions $x_0$ and $x_{N+1}$, respectively, and they feel the presence of baths with given inverse temperatures: $\beta_L$ to the left, $\beta_B$ in the middle, and $\beta_R$ to the right. Each particle has an index and interacts with its nearest neighbors in index space through either a quadratic potential or a
Fermi-Pasta-Ulam-Tsingou type coupling. This local interaction in index space can give rise to effective long-range interactions on the spatial
lattice, depending on the instantaneous configuration. Particle hopping rates are governed either by the Metropolis rule or by a modified version that breaks detailed balance at the interfaces between regions with different baths.
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All authors Emilio N.M. Cirillo, Matteo Colangeli, Claudio Giberti, Lamberto Rondoni
Materials Science · Cross-listed from cs.LG
SHA-256 Infused Embedding-Driven Generative Modeling of High-Energy Molecules in Low-Data Regimes
Siddharth Verma and Alankar Alankar
High-energy materials (HEMs) are critical for propulsion and defense domains, yet their discovery remains constrained by experimental data and restricted access to testing facilities. This work presents a novel approach toward high-energy molecules by combining Long Short-Term
Memory (LSTM) networks for molecular generation and Attentive Graph Neural Networks (GNN) for property predictions. We propose a transformative
embedding space construction strategy that integrates fixed SHA-256
embeddings with partially trainable representations. Unlike conventional regularization techniques, this changes the representational basis itself, reshaping the molecular input space before learning begins. Without recourse to pretraining, the generator achieves 67.5% validity and 37.5% novelty. The generated library exhibits a mean Tanimoto coefficient of 0.214 relative to training set signifying the ability of framework to generate a diverse chemical space. We identified 37 new super explosives higher than 9 km/s predicted detonation velocity.
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Materials Science
Preliminary Demonstration of Diamond-GaN pn Diodes via Grafting
Jie Zhou, Yi Lu, Chenyu Wang et al. (+18 more)
Ultrawide bandgap (UWBG)
semiconductors exhibit exceptional electrical and thermal properties, offering strong potential for high power and high frequency electronics. However, efficient doping in UWBG materials is typically limited to either n type or p type, constraining their application to unipolar devices. The realization of pn junctions through heterogeneous integration of complementary UWBG or WBG
semiconductors is hindered by
lattice mismatch and thermal expansion differences. Here, we report the preliminary demonstration of diamond GaN heterojunction pn diodes fabricated via grafting. A single crystalline p plus diamond nanomembrane was integrated onto an epitaxially grown c plane n plus GaN substrate with an ultrathin ALD Al2O3 interlayer. The resulting diodes exhibit an ideality factor of 1.55 and a rectification ratio of over 1e4. Structural and interfacial properties were examined by AFM, XRD, Raman, and STEM, providing critical insights to guide further optimization of diamond GaN pn heterojunction devices.
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All authors Jie Zhou, Yi Lu, Chenyu Wang, Luke Suter, Aaron Hardy, Tien Khee Ng, Kai Sun, Yifu Guo, Yang Liu, Tsung-Han Tsai, Xuanyu Zhou, Connor S Bailey, Michael Eller, Stephanie Liu, Zetian Mi, Boon S. Ooi, Matthias Muehle, Katherine Fountaine, Vincent Gambin, Jung-Hun Seo, Zhenqiang Ma
Strongly Correlated Electrons
Finite-Temperature Study of the Hubbard Model via Enhanced Exponential Tensor Renormalization Group
Changkai Zhang and Jan von Delft
The two-dimensional (2D) Hubbard model has long attracted interest for its rich phase diagram and its relevance to high-$T_c$ superconductivity. However, reliable finite-temperature studies remain challenging due to the exponential complexity of many-body interactions. Here, we introduce an enhanced $1\text{s}^+$ eXponential Tensor Renormalization Group
algorithm that enables efficient finite-temperature simulations of the 2D Hubbard model. By exploring an expanded space, our approach achieves two-site update accuracy at the computational cost of a one-site update, and delivers up to 50% acceleration for Hubbard-like systems, which enables simulations down to $T\!\approx\!0.004t$. This advance permits a direct investigation of superconducting order over a wide temperature range and facilitates a comparison with zero-temperature infinite Projected Entangled Pair State simulations. Finally, we compile a comprehensive
dataset of snapshots spanning the relevant region of the phase diagram, providing a valuable reference for Artificial Intelligence-driven analyses of the Hubbard model and a comparison with cold-atom experiments.
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Mesoscale and Nanoscale Physics
Optical excitations and disorder in two-dimensional topological insulators
Alejandro José Uría-Álvarez
Topological phases of matter have garnered significant interest over the past two decades for two main reasons: their identification, via topological invariants, relies on the
quantum geometry of the Bloch states, bringing
attention to an aspect of electronic band structure overlooked up to their discovery. Secondly, these classes of materials present electronic states with unusual properties, leading to exotic phenomena and making them relevant for potential applications. In this thesis we explore both fundamental and technological aspects of the first discovered topological phase: the topological
insulator. To this end, we consider different models of topological
insulators with a particular emphasis on Bismuth compounds, evaluating their viability for photovoltaic applications, and separately, the impact of structural disorder on their properties.
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Statistical Mechanics · Cross-listed from cs.NE
Maximum-Entropy Analog Computing Approaching ExaOPS-per-Watt Energy-efficiency at the RF-Edge
Aswin Undavalli, Kareem Rashed, Zhili Xiao et al. (+3 more)
In this paper, we demonstrate how the physics of
entropy production, when combined with
symmetry constraints, can be used for implementing high-performance and energy-efficient analog computing systems. At the core of the proposed framework is a generalized maximum-
entropy principle that can describe the
evolution of a mesoscopic physical system formed by an interconnected ensemble of analog elements, including devices that can be readily fabricated on standard integrated
circuit technology. We show that the maximum-
entropy state of this ensemble corresponds to a margin-propagation (MP) distribution and can be used for computing correlations and inner products as the ensemble's macroscopic properties. Furthermore, the limits of computational throughput and energy efficiency can be pushed by extending the framework to non-
equilibrium or transient operating conditions, which we demonstrate using a proof-of-concept
radio-frequency (RF) correlator integrated
circuit fabricated in a 22 nm SOI CMOS process. The measured results show a compute efficiency greater than 2 Peta ($10^{15}$) Bit Operations per second per Watt (PetaOPS/W) at 8-bit precision and greater than 0.8 Exa ($10^{18}$) Bit Operations per second per Watt (ExaOPS/W) at 3-bit precision for RF data sampled at rates greater than 4 GS/s. Using the fabricated prototypes, we also showcase several real-world RF applications at the edge, including spectrum sensing, and code-domain communications.
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All authors Aswin Undavalli, Kareem Rashed, Zhili Xiao, Arun Natarajan, Shantanu Chakrabartty, Aravind Nagulu
Materials Science
Trichome entanglement enhances damage tolerance in microstructured biocomposites
Israel Kellersztein, Mathieu Desgranges and Chiara Daraio
Achieving damage tolerance in composite materials remains a central challenge in materials science. Conventional strategies often rely on filler incorporation or chemical modification, which can limit energy dissipation and constrain structural stability. Here, we leverage the unique morphology of Spirulina trichomes to investigate a reinforcement mechanism based on physical filament
entanglement. By comparing helical trichomes with their morphologically straightened counterparts, we isolate filament geometry as the key parameter governing mechanical performance. Trichome-based suspensions exhibit enhanced viscoelastic response and a threefold increase in yield stress. When processed via extrusion-based 3D printing using hydroxyethyl cellulose (HEC) as a
matrix, entangled trichomes yield a 290% improvement in bending strength and a 15-fold enhancement in work of fracture. Fracture surface analysis reveals a transition from interfacial debonding and pull-out (in filaments) to crack propagation through the entangled network, indicating structure-mediated toughening. These findings establish trichome
entanglement as a scalable, physically driven mechanism for enhancing damage tolerance through microstructural architecture.
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Mesoscale and Nanoscale Physics
Magneto-optical spectroscopy based on pump-probe strobe light
Shihao Zhou, Yujie Zhu, Chunli Tang et al. (+12 more)
We demonstrate a pump-probe strobe light spectroscopy for sensitive detection of magneto-optical dynamics in the context of hybrid magnonics. The technique uses a combinatorial microwave-optical pump-probe scheme, leveraging both the high-energy resolution of microwaves and the high-efficiency detection using optical
photons. In contrast to conventional stroboscopy using a continuous-wave light, we apply microwave and optical pulses with varying pulse widths, and demonstrate magnetooptical detection of magnetization dynamics in Y3Fe5O12 films. The detected magneto-optical signals strongly depend on the characteristics of both the microwave and the optical pulses as well as their relative time delays. We show that good magneto-optical sensitivity and coherent stroboscopic character are maintained even at a microwave pump pulse of 1.5 ns and an optical probe pulse of 80 ps, under a 7 megahertz clock rate, corresponding to a pump-probe footprint of ~1% in one detection cycle. Our results show that time-dependent strobe light measurement of magnetization dynamics can be achieved in the gigahertz frequency range under a pump-probe detection scheme.
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All authors Shihao Zhou, Yujie Zhu, Chunli Tang, Rui Sun, Junming Wu, Yuzan Xiong, Ingrid E. Russell, Yi Li, Dali Sun, Frank Tsui, Binbin Yang, Valentine Novosad, Jia-Mian Hu, Wencan Jin, Wei Zhang
Soft Condensed Matter
Flow-Induced Phase Separation for Active Brownian Particles in Four-Roll-Mill Flow
Soni D. Prajapati, Kusum Seervi, Akshay Bhatnagar et al. (+1 more)
We investigate the collective dynamics of active Brownian particles (ABPs) subjected to a steady two-dimensional four-roll-mill flow using numerical simulations. By varying the packing fraction ($\phi$), we uncover a novel flow-induced phase separation (FIPS) that emerges beyond a critical density ($\phi \geq 0.6$). The mean-square displacement (MSD) exhibits an intermediate bump between ballistic and diffusive regimes, indicating transient trapping and flow-guided clustering. The effective diffusivity decreases quadratically with $\phi$, while the drift velocity remains nearly constant, demonstrating that large-scale transport is primarily dictated by the background flow. Number fluctuations show a crossover from normal to
giant scaling, signaling the onset of long-range density inhomogeneities in the FIPS regime. Our findings provide new insights into the coupling between activity, crowding, and flow, offering a unified framework for understanding phase behavior in driven active matter systems.
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All authors Soni D. Prajapati, Kusum Seervi, Akshay Bhatnagar, Anupam Gupta
Materials Science · Cross-listed from astro-ph.EP
The Fate of Hydrogen and Helium: From Planetary Embryos to Earth- and Neptune-like Worlds
Akash Gupta, Haiyang Luo, Jie Deng et al. (+1 more)
Hydrogen, helium, silicates, and iron are key building blocks of rocky and gas-rich
planets, yet their chemical interactions remain poorly constrained. Using first-principles molecular dynamics and thermodynamic integration, we quantify hydrogen and helium partitioning between molten silicate mantles and metallic cores for Earth-to-Neptune-mass
planets. Hydrogen becomes strongly siderophilic above $\sim$25 GPa but weakens beyond $\sim$200 GPa, whereas helium remains lithophilic yet increasingly soluble in metal with pressure. Incorporating these trends into coupled structure-chemistry models suggests that majority of hydrogen and helium reside in planetary interiors, not atmospheres, with abundances strongly depending on
planet mass. Such volatile exchange may influence the redox states of secondary atmospheres, longevity of
primordial envelopes, predicted CHNOPS abundances, and emergence of helium-enriched atmospheres, while He 1083 nm and H Lyman-$\alpha$ lines provide potential probes of atmosphere-interior exchange. These findings link atomic-scale interactions to planetary-scale observables, providing new constraints on the origins of Earth-to-Neptune-sized worlds.
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All authors Akash Gupta, Haiyang Luo, Jie Deng, Adam Burrows
Materials Science
Stabilisation of hBN/SiC Heterostructures with Vacancies and Transition-Metal Atoms
Arsalan Hashemi, Nima Ghafari Cherati, Sadegh Ghaderzadeh et al. (+3 more)
When two-dimensional atomic layers of different materials are brought into close proximity to form van der Waals (vdW)
heterostructures, interactions between adjacent layers significantly influence their physicochemical properties. These effects seem particularly pronounced when the interface exhibits local order and near-perfect structural
alignment, leading to the emergence of Moiré patterns. Using
quantum mechanical density functional theory calculations, we propose a prototypical
bilayer heterostructure composed of hexagonal boron nitride (hBN) and silicon carbide (SiC), characterized by a
lattice mismatch of 18.77% between their primitive unit
cells. We find that the removal of boron atoms from specific
lattice sites can convert the interlayer interaction from weak vdW coupling to robust localized silicon-nitrogen covalent bonding. Motivated by this, we study the binding of transition-metal adatoms and formulate design guidelines to enhance surface reactivity, thereby enabling the controlled isolation of single-metal atoms. Our machine-learning-assisted molecular dynamics simulations confirm both dynamical stability and metal anchoring feasibility at finite temperatures. Our results suggest the hBN/SiC
heterostructure as a versatile platform for atomically precise transition-metal functionalization, having potential for next-generation catalytic energy-conversion technologies.
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All authors Arsalan Hashemi, Nima Ghafari Cherati, Sadegh Ghaderzadeh, Yanzhou Wang, Mahdi Ghorbani-Asl, Tapio Ala-Nissila
Soft Condensed Matter
Energy-Conserving Contact Dynamics of Nonspherical Rigid-Body Particles
Haoyuan Shi, Christopher J. Mundy, Gregory K. Schenter et al. (+1 more)
Understanding the contact dynamics of nonspherical particles beyond the microscale is crucial for accurately modeling colloidal and granular systems, where shape anisotropy dictates structural organization and transport properties. In this paper, we introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles, integrating vertex-boundary interactions in 2D with vertex-surface and edge-edge detection in 3D. This formulation enables continuous force evaluation and strictly prevents particle overlap while conserving total energy during translational and rotational motion. Simulations of polygonal and polyhedral particles confirm the framework's stability and demonstrate its capability to capture packing behavior, anisotropic
diffusion, and equations of state. The framework establishes a robust and extensible foundation for investigating the nonequilibrium dynamics of complex nonspherical particle systems, with potential applications in colloidal self-assembly, granular flow, and hydrodynamics.
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All authors Haoyuan Shi, Christopher J. Mundy, Gregory K. Schenter, Jaehun Chun
Soft Condensed Matter
Solute dispersion boosts the phoretic removal of colloids from dead-end pores
Yiran Li, Mobin Alipour and Amir Pahlavan
Predicting and controlling the transport of colloids in porous media is essential for a broad range of applications, from drug delivery to contaminant remediation. Chemical gradients are ubiquitous in these environments, arising from reactions, precipitation/dissolution, or salinity contrasts, and can drive particle motion via diffusiophoresis. Yet our current understanding mostly comes from idealized settings with sharply imposed solute gradients, whereas in porous media, flow disorder enhances solute dispersion, and leads to diffuse solute fronts. This raises a central question: does front dispersion suppress diffusiophoretic migration of colloids in dead-end pores, rendering the effect negligible at larger scales? We address this question using an idealized one-dimensional dead-end geometry. We derive an analytical model for the spatiotemporal
evolution of colloids subjected to slowly varying solute fronts and validate it with numerical simulations and microfluidic experiments. Counterintuitively, we find that diffuseness of solute front enhances removal from dead-end pores: although smoothing reduces instantaneous gradient magnitude, it extends the temporal extent of phoretic forcing, yielding a larger cumulative drift and higher clearance efficiency than sharp fronts. Our results highlight that solute dispersion does not weaken the phoretic migration of colloids from dead-end pores, pointing to the potential relevance of diffusiophoresis at larger scales, with implications for filtration, remediation, and targeted delivery in porous media.
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Soft Condensed Matter
Machine Learning the Entropy to Estimate Free Energy Differences without Sampling Transitions
Yamin Ben-Shimon, Barak Hirshberg and Yohai Bar-Sinai
Thermodynamic phase transitions, a central concept in physics and chemistry, are typically controlled by an interplay of enthalpic and entropic contributions. In most cases, the estimation of the enthalpy in simulations is straightforward but evaluating the
entropy is notoriously hard. As a result, it is common to induce transitions between the metastable states and estimate their relative occupancies, from which the free energy difference can be inferred. However, for systems with large free energy barriers, sampling these transitions is a significant computational challenge. Dedicated enhanced sampling
algorithms require significant prior knowledge of the slow modes governing the transition, which is typically unavailable. We present an alternative approach, which only uses short simulations of each phase separately. We achieve this by employing a recently developed deep learning model for estimating the
entropy and hence the free energy of each metastable state. We
benchmark our approach calculating the free energies of crystalline and
liquid metals. Our method features state-of-the-art precision in estimating the melting transition temperature in Na and Al without requiring any prior information or simulation of the transition pathway itself.
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Quantum Gases
Observation of vector rogue waves in repulsive three-component atomic mixtures
G. A. Bougas, G. C. Katsimiga, S. Mossman et al. (+3 more)
Rogue waves are extreme evanescent nonlinear structures that are challenging to observe in atomic gases, as their emergence requires a dynamically unstable attractive environment. Here, we report the experimental observation of vector extensions of Peregrine
solitons in highly particle-imbalanced, pairwise immiscible three-component repulsive Bose-Einstein condensates. The possibility of an effectively attractive character of the minority components is established by constructing a generalized reduction scheme for an imbalanced N -component setup with arbitrary interaction signs. These components are subject to intra- and inter-component modulation instability, which along with the presence of an attractive potential well induces the dynamical formation of highly reproducible vector rogue waves. Exploiting different Rb hyperfine states, it is possible to flexibly tune the effective interactions stimulating the realization of a plethora of vector rogue waves, including single and double Peregrine-like wave peaks. The experimental findings are in quantitative agreement with suitable three-dimensional mean-field simulations, while quasi-one-dimensional analysis of the non-
polynomial Schroedinger model provides additional insights into the rogue wave characteristics.
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All authors G. A. Bougas, G. C. Katsimiga, S. Mossman, P. Engels, P. G. Kevrekidis, S. I. Mistakidis
Materials Science · Cross-listed from quant-ph
Classically Prepared, Quantumly Evolved: Hybrid Algorithm for Molecular Spectra
Alessandro Santini, Stefano Barison and Filippo Vicentini
We introduce a hybrid classical-
quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body
quantum systems, with a focus on molecular systems. The method combines classical preparation of a perturbed ground state with short-time
quantum evolution of product states sampled from it. The resulting
quantum samples define an effective subspace of the
Hilbert space, onto which the
Hamiltonian is projected to enable efficient classical simulation of long-time dynamics. This subspace-based approach achieves high-resolution spectral reconstruction using shallow
circuits and few samples.
Benchmarks on molecular systems show excellent agreement with exact diagonalization and demonstrate access to dynamical timescales beyond the reach of purely classical methods, highlighting its suitability for near-term and early fault-tolerant
quantum hardware.
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Disordered Systems and Neural Networks
Emergence of Chimeras States in One-dimensional Ising model with Long-Range Diffusion
Alejandro de Haro García and Joaquín J. Torres
In this work, we examine the conditions for the emergence of chimera-like states in Ising systems. We study an Ising chain with periodic boundaries in contact with a thermal bath at temperature T, that induces
stochastic changes in
spin variables. To capture the non-locality needed for chimera formation, we introduce a model setup with non-local
diffusion of
spin values through the whole system. More precisely,
diffusion is modeled through
spin-exchange interactions between units up to a distance R, using Kawasaki dynamics. This setup mimics, e.g., neural media, as the
brain, in the presence of electrical (diffusive) interactions. We explored the influence of such non-local dynamics on the emergence of complex spatiotemporal synchronization patterns of activity. Depending on system parameters we report here for the first time chimera-like states in the Ising model, characterized by relatively stable moving domains of
spins with different local magnetization. We analyzed the system at T=0, both analytically and via simulations and computed the system's phase diagram, revealing rich behavior: regions with only chimeras, coexistence of chimeras and stable domains, and metastable chimeras that decay into uniform stable domains. This study offers fundamental insights into how coherent and incoherent synchronization patterns can arise in complex networked systems as it is, e.g., the
brain.
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Other Condensed Matter · Cross-listed from q-bio.NC
Statistical Field Theory and Neural Structures Dynamics V: Synthesis and extensions
Pierre Gosselin and Aïleen Lotz
We present a unified field-theoretic framework for the dynamics of activity and connectivity in interacting neuronal systems. Building upon previous works, where a field approach to activity–connectivity dynamics, formation of collective states and effective fields of collective states were successively introduced, the present paper synthesizes and extends these results toward a general description of multiple hierarchical collective structures. Starting with the dynamical system representing collective states in terms of connections, activity levels, and internal frequencies, we analyze its stability, emphasizing the possibility of transitions between configurations. Then, turning to the field formalism of collective states, we extend this framework to include substructures (subobjects) participating in larger assemblies while retaining intrinsic properties. We define activation classes describing compatible or independent activity patterns between objects and subobjects, and study stability conditions arising from their
alignment or mismatch. The global system is described as the collection of landscapes of coexisting and interacting collective states, each characterized both by continuous (activity, frequency) and discrete (class) variables. A corresponding field formalism is developed, with an action functional incorporating both internal dynamics and interaction terms. This nonlinear field model captures cascading transitions between collective states and the formation of composite structures, providing a coherent theoretical basis for emergent neuronal assemblies and their mutual couplings.
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Materials Science
Improved operating voltage in InGaN-capped AlGaN-based DUV LEDs on bulk AlN substrates
H-W S. Huang, S. Agrawal, D. Bhattacharya et al. (+2 more)
Better wall plug efficiency of deep-ultraviolet light emitting diodes (DUV-LEDs) requires simultaneous low resistivity p-type and n-type contacts, which is a challenging problem. In this study, the co-optimization of p-InGaN and n- AlGaN contacts for DUV LEDs are investigated. We find that using a thin 7%InGaN cap is effective in achieving ohmic p-contacts with specific contact resistivity of 3.10x10^{-5} Ohm.cm^2. Upon monolithic integration of p- and n- contacts for DUV LEDs, we find that the high temperature annealing of 800C required for the formation of low resistance contacts to n-AlGaN severely degrades the p-InGaN layer, thereby reducing the hole concentration and increasing the specific contact resistivity to 9.72x10^{-4} Ohm.cm^2. Depositing a SiO2 cap by
plasma-enhanced atomic layer deposition (PE-ALD) prior to high temperature n-contact annealing restores the low p-contact resistivity, enabling simultaneous low-resistance p- and n-contacts. DUV-LEDs emitting at 268 nm fabricated with the SiO2 capping technique exhibit a 3.5 V reduction in operating voltage at a current level of 400 A/cm^2 and a decrease in differential ON-resistance from 6.4 mOhm.cm^2 to 4.5 mOhm.cm^2. This study highlights a scalable route to high-performance, high-Al-content bipolar AlGaN devices.
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All authors H-W S. Huang, S. Agrawal, D. Bhattacharya, H.G. Xing, D. Jena
Materials Science
Molecular simulations of Perovskites CsXI3 (X = Pb,Sn) Using Machine-Learning Interatomic Potentials
Atefe Ebrahimi, Franco Pellegrini and Stefano De Gironcoli
Cesium based halide perovskites, such as CsPbI3 and CsSnI3, have emerged as exceptional candidates for next generation photovoltaic and optoelectronic technologies, but their practical application is limited by temperature dependent phase transitions and structural instabilities. Here, we develop machine learning interatomic potentials within the LATTE framework to simulate these materials with near experimental accuracy at a fraction of the computational cost compared to previous computational studies. Our molecular dynamics simulations based on the trained MLIPs reproduce energies and forces across multiple phases, enabling large scale simulations that capture cubic tetragonal orthorhombic transitions,
lattice parameters, and octahedral tilting with unprecedented resolution. We find that Pb based perovskites exhibit larger octahedral tilts and higher phase transition temperatures than Sn based analogues, reflecting stronger bonding and enhanced structural stability, whereas Sn based perovskites display reduced tilts and lower barriers, suggesting tunability through compositional or interface engineering. Beyond these systems, our work demonstrates that MLIPs can bridge first principles accuracy with simulation efficiency, providing a robust framework for exploring phase stability, anharmonicity, and rational design in next generation halide perovskites.
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Statistical Mechanics
Spin Glass Dynamics on Complex Hardware Topologies: A Bond-Correlated Percolation Approach
Viviana Gómez, Gabriel Téllez and Fernando J. Gómez-Ruiz
Understanding how frustration and disorder shape relaxation in complex systems is a central problem in statistical physics and
quantum annealing.
Spin-glass models provide a natural framework to explore this connection, as their energy landscapes are governed by competing interactions and constrained
topologies. We investigate the non-exponential relaxation behavior of
spin glasses on network architectures relevant to
quantum annealing hardware – such as finite size Chimera, Pegasus, and Zephyr graphs – where
embedding constraints and finite connectivity strongly modulate the distribution of barriers and metastable states. This slow relaxation arises from the combined effects of frustration and disorder, which persist even beyond the conventional
spin-glass transition. Within the Fortuin-Kasteleyn-Coniglio-Klein (FKCK) cluster formalism, the appearance of unfrustrated cluster regions gives rise to multiple relaxation scales, as distinct domains follow different dynamical pathways across a rugged energy landscape. This framework enables a more comprehensive characterization of
spin-glass energy landscapes and offers valuable insight into how topological constraints and disorder jointly govern relaxation dynamics, providing quantitative
benchmarks for evaluating the performance and limitations of
quantum annealing architectures.
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Materials Science · Cross-listed from physics.optics
Extracting Spectral Diffusion in Two-Dimensional Coherent Spectra via the Projection Slice Theorem
Cesar Perez and Steven Cundiff
A robust and streamlined method is presented for efficiently extracting spectral
diffusion from two-dimensional coherent spectra by employing the projection-slice
theorem. The method is based on the optical Bloch equations for a single resonance that include a Frequency-Frequency Correlation Function (FFCF) in the time domain. Through the projection slice
theorem (PST), analytical formulation of the diagonal and cross-diagonal projections of time-domain two-dimensional spectra are calculated that include the FFCF for arbitrary inhomogeneity. The time-domain projections are
Fourier transformed to provide frequency domain slices that can be fit to slices of experimental spectra. Experimental data is used to validate our lineshape analysis and confirm the need for the inclusion of the FFCF for
quantum wells that experience spectral
diffusion.
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Soft Condensed Matter
Impacting spheres: from liquid drops to elastic beads
Saumili Jana, John Kolinski, Detlef Lohse et al. (+1 more)
A
liquid drop impacting a non-wetting rigid substrate laterally spreads, then retracts, and finally jumps off again. An elastic solid, by contrast, undergoes a slight deformation, contacts briefly, and bounces. The impact force on the substrate - crucial for engineering and natural processes - is classically described by Wagner's (
liquids) and Hertz's (solids) theories. This work bridges these limits by considering a generic viscoelastic medium. Using direct numerical simulations, we study a viscoelastic sphere impacting a rigid, non-contacting surface and quantify how the elasticity number ($El$, dimensionless elastic modulus) and the Weissenberg number ($Wi$, dimensionless relaxation time) dictate the impact force. We recover the Newtonian
liquid response as either $El \to 0$ or $Wi \to 0$, and obtain elastic-solid behavior in the limit $Wi \to \infty$ and $El \ne 0$. In this elastic-
memory limit, three regimes emerge - capillary-dominated, Wagner scaling, and Hertz scaling - with a smooth transition from the Wagner to the Hertz regime. Sweeping $Wi$ from 0 to $\infty$ reveals a continuous shift from materials with no
memory to materials with permanent
memory of deformation, providing an alternate, controlled route from
liquid drops to elastic beads. The study unifies
liquid and solid impact processes and offers a general framework for the
liquid-to-elastic transition relevant across systems and applications.
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All authors Saumili Jana, John Kolinski, Detlef Lohse, Vatsal Sanjay