Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Entangling remote qubits through a two-mode squeezed reservoir
A. Andrés-Juanes, J. Agustí, R. Sett et al. (+5 more)
The distribution of
entanglement across distant
qubits is a central challenge for the operation of scalable
quantum computers and large-scale
quantum networks. Existing approaches rely on deterministic state transfer schemes or probabilistic protocols that require active control or measurement and postselection. Here we demonstrate an alternative, fully autonomous process, where two remote
qubits are entangled through their coupling to a
quantum-correlated photonic reservoir. In our experiment, a Josephson parametric converter produces a Gaussian, continuous-variable entangled state of propagating microwave fields that drives two spatially separated superconducting transmon
qubits into a stationary, discrete-variable entangled state. Beyond
entanglement distribution, we also show that superconducting
qubits can be used to directly certify two-mode squeezing, with higher sensitivity and without the need for calibrated noise-subtraction. These results establish networks of
qubits interfaced with distributed continuous-variable entangled states as a powerful new platform for both foundational studies and
quantum-technology relevant applications.
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All authors A. Andrés-Juanes, J. Agustí, R. Sett, E. S. Redchenko, L. Kapoor, S. Hawaldar, P. Rabl, J. M. Fink
Strongly Correlated Electrons · Cross-listed from quant-ph
Preparation of initial states with open and periodic boundary conditions on quantum devices using matrix product states
Yibin Guo, Manuel Schneider, Takis Angelides et al. (+3 more)
We present a framework for preparing
quantum states from
matrix product states (MPS) with open and periodic boundary conditions on
quantum devices. The MPS tensors are mapped to
unitary gates, which are subsequently decomposed into native gates on
quantum hardware. States with periodic boundary conditions (pbc) can be represented efficiently as
quantum circuits using ancilla
qubits and post-selection after measurement. We derive an exact expression for the success rate of this probabilistic approach, which can be evaluated a priori. The applicability of the method is demonstrated in two examples. First, we prepare the ground state of the Heisenberg model with pbc and simulate dynamics under a quenched
Hamiltonian. The volume-law
entanglement growth in the time
evolution challenges classical
algorithms but can potentially be overcome on
quantum hardware. Second, we construct
quantum circuits that generate excited states of the Schwinger model with high fidelities. Our approach provides a scalable method for preparing states on a
quantum device, enabling efficient simulations of strongly correlated systems on near-term
quantum computers.
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All authors Yibin Guo, Manuel Schneider, Takis Angelides, Karl Jansen, C.-J. David Lin, Yao Ting Su
Quantum Gases · Cross-listed from eess.SY
Identification and optimal control strategies for the transversal splitting of ultra–cold Bose gases
Nikolaus Würkner, Yevhenii Kuriatnikov, Karthikeyan Kumaran et al. (+5 more)
Splitting a Bose–Einstein condensate (BEC) is a key operation in fundamental physics experiments and emerging
quantum technologies, where precise preparation of well–defined initial states requires fast yet coherent control of the condensate's nonlinear dynamics. This work formulates the BEC splitting process as an optimal feedforward control problem based on a physically interpretable, reduced–order model identified from limited experimental data. We introduce a systematic calibration strategy that combines optimal experiment selection and constrained nonlinear parameter estimation, enabling accurate system identification with minimal experimental overhead. Using this calibrated model, we compute energy–optimal trajectories via indirect optimal control to realize shortcuts to adiabaticity (STAs), achieving rapid transitions to the ground state of a double–well potential while suppressing excitations. Experiments confirm that the proposed control framework yields high–fidelity state transfers across multiple configurations, demonstrating its robustness and scalability for
quantum control applications.
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All authors Nikolaus Würkner, Yevhenii Kuriatnikov, Karthikeyan Kumaran, M Venkat Ramana, Jörg Schmiedmayer, Andreas Kugi, Maximilian Prüfer, Andreas Deutschmann-Olek
Statistical Mechanics · Cross-listed from physics.soc-ph
Data as Commodity: a Game-Theoretic Principle for Information Pricing
Pasquale Casaburi, Giovanni Piccioli and Pierpaolo Vivo
Data is the central commodity of the digital economy. Unlike physical goods, data exhibits properties that defy the standard theory of supply and demand: it is non-rival (the same
dataset can be sold to multiple buyers without degradation), it is replicable at near-zero cost, and it is traded under heterogeneous licensing rules that restrict lawful use. Determining a new pricing principle to attach a fair price tag to
datasets is therefore a difficult but central problem. We propose a game-theoretic framework in which the value of a data string emerges from strategic competition among $N$ players betting on a
stochastic process with asymmetric information about past outcomes. A better-informed player may either exploit her advantage or sell part of her
dataset to less informed competitors. By analytically deriving the Nash
equilibrium, we identify the price range for a mutually beneficial trade. The model reveals
market dynamics that depart from textbook intuition: informed players may compete or jointly exploit the least informed; data can be shared even at zero price without reducing the seller`s utility; rivalry among well-informed players can benefit uninformed ones; and trades infeasible in small
markets can be viable in larger ones. These findings establish a theoretical foundation for the pricing of intangible goods in interacting digital
markets, which are in need of robust valuation principles.
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Materials Science
Understanding Polaronic Transport in Anatase TiO2 Films by Combining Precise Synthesis and First-Principles Many-Body Theory
F. Liu, Z. Yang, Y. Luo et al. (+8 more)
In complex
oxides, charge carriers often couple strongly with
lattice vibrations to form polarons-entangled electron-
phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical descriptions demand methods beyond low-order perturbation theory. Here, we combine the growth of high-quality oxygen-vacancy-doped anatase TiO2 films by hybrid molecular beam epitaxy (MBE) with a first-principles electron-
phonon diagrammatic Monte Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO2, in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 +/- 15 cm2V-1s-1 and a mobility-temperature scaling of mobility proportional to T^(-1.9 +/- 0.077). Microscopic analysis using scanning transmission electron microscopy and X-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy,
phonon cloud distribution,
lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results establish a predictive theory-experiment workflow to characterize polarons and provide a microscopic understanding of large-polaron transport in anatase TiO2, with broader implications for complex
oxides and other polaronic materials.
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All authors F. Liu, Z. Yang, Y. Luo, S. Guo, C. Zhang, S. Choo, X. Xu, X. Wang, K. A. Mkhoyan, M. Bernardi, B. Jalan
Materials Science
Anomalous strain-dependent thermal conductivity in superelastic screw-dislocated graphites
Yu Li, Zhiqiang Zhao, Zhuhua Zhang et al. (+2 more)
The design of strain-stable, or even strain-enhanced thermal transport materials is critical for stable operation of high-performance electronic devices. However, most nanomaterials suffer from strain-induced degradation, with even minor tensile strains markedly reducing thermal conductivity. Here, we demonstrate that screw-dislocated graphites (SDGs), recently identified as topological semimetals, display an unusual increase in cross-plane thermal conductivity under both tensile and compressive strains, revealed by high-accuracy machine-learning-potential-driven non-
equilibrium molecular dynamics. Notably, SDGs exhibit over 100% enhancement under tensile strains up to 80% along the dislocation axis, arising from strain-induced increase in dislocation interface tilt angle that elongates the effective heat transfer paths. Their thermal conductivity surpasses multilayer
graphene by an order of magnitude. An analytical model is further derived linking thermal conductivity to dislocation number and strain, offering a predictive framework for designing strain-tunable screwdislocated structures. These findings highlight SDGs as a promising platform for high-performance electronic and wearable devices with tunable thermal properties.
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All authors Yu Li, Zhiqiang Zhao, Zhuhua Zhang, Yong-Wei Zhang, Jin-Wu Jiang
Other Condensed Matter · Cross-listed from physics.optics
Dispersion and the transport of exciton-polaritons in an optical conveyor belt
Xingran Xu, Chunyu Jia and Xin-Xin Yang
The growing interest in
exciton-polaritons has driven the need to manipulate their motion and engineer their band structures to the forefront of contemporary research. This study explores the band structures that emerge from a spatially modulated potential, ingeniously realized through the use of an optical conveyor belt. By leveraging Bloch theory and conducting a meticulous analysis of the time
evolution of polariton intensity in
Fourier space, we have derived the energy dispersion relations both analytically and numerically within the context of a static
lattice model. For time-dependent potentials, we employ the Lagrange variational method to elucidate the dynamics of polariton motion. Our results reveal that polaritons exhibit linear dispersion and follow linear trajectories with minor oscillations superimposed. This investigation not only deepens our fundamental understanding of
exciton-polaritons but also provides a robust tool for advancing photonic devices and exerting precise control over current transport in
quantum computing. Our findings pave the way for future innovations in high-speed and high-performance technologies.
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Superconductivity · Cross-listed from physics.ins-det
Experimental Results from Early Non-Planar NI-HTS Magnet Prototypes for the Columbia Stellarator eXperiment (CSX)
D. Schmeling, M. Russo, B. T. Gebreamlak et al. (+12 more)
The Columbia Stellarator eXperiment (CSX) is an upgrade of the Columbia Non-neutral
Torus (CNT) that aims to demonstrate a university-scale, quasi-axisymmetric stellarator using high-temperature superconducting (HTS) technology at an on-axis
magnetic field target of 0.5 T. Due to the strain sensitivity of ReBCO (Rare-earth Barium Copper
Oxides), adapting it to non-planar stellarator geometries requires new winding, structural, and cooling strategies. We report on the results of a staged prototype program (P1, P2, P3) employing 3D-printed, sectional aluminum coil frames with winding channels, gimballed constant-tension winding mechanics, and solder potting for radial current redistribution and passive quench mitigation. The first prototype, P1 (planar elliptical, double-pancake) tested additive manufacture, sectional joining and baseline winding, achieving predicted fields at 77 K. P2 (non-planar, higher strain) was wound to 42 turns, energized at 30-40 K to produce expected
magnetic fields, and studied thermal gradients and resistance at up to 4.5 kAt. Design
evolution in P3 introduces concave geometry with dual double-pancakes, 200 turns, and approaches the 70 kAt target at 20 K. In parallel, sub-microhm lap joints have been developed. Together, these results de-risk manufacturing, cooling interfaces, quench management, and diagnostics, paving the way for full-size non-planar HTS stellarator coils for CSX.
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All authors D. Schmeling, M. Russo, B. T. Gebreamlak, T. J. Kiker, A. R. Skrypek, A. R. Hightower, J. Xue, S. Chen, S. Sohaib, C. Martinez, K. F. Richardson, L. Filor, S. Komatsu, L. Liu, C. Paz-Soldan
Mesoscale and Nanoscale Physics
Noninteracting tight-binding models for Fock parafermions
Edward McCann
We model $p$-state Fock parafermions on a
lattice in one dimension (with occupation per orbital of $0,1 , \ldots ,p-1$). For $p$ a composite number, they may be mapped to $q_m$-state parafermions where $q_m$ are the
prime factors of $p$. For a
Hamiltonian with a single-particle spectrum, the parafermions decompose into $q_m$-state parafermions. When $p$ is a power of two, the decomposition is into
fermions. We use this to construct a parafermionic
Hamiltonian for $p=4$ with a single-particle spectrum using a fermionic tight-binding model which is bilinear in creation and annihilation operators. The single-particle levels may be determined by diagonalizing a square
matrix whose order scales linearly with system size, and they are the same as those of the fermionic model. We show that the intermediate statistics of the thermodynamic distribution function for the occupation numbers (known as Gentile statistics) are consistent with the mapping to
fermions, and we provide an example calculation of the internal energy and heat capacity for a simple linear chain.
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Soft Condensed Matter · Cross-listed from cs.RO
Tailoring materials into kirigami robots
Saravana Prashanth Murali Babu, Aida Parvaresh and Ahmad Rafsanjani
Kirigami, the traditional paper-cutting craft, holds immense potential for revolutionizing robotics by providing multifunctional, lightweight, and adaptable solutions. Kirigami structures, characterized by their bending-dominated deformation, offer resilience to tensile forces and facilitate shape morphing under small actuation forces. Kirigami components such as actuators, sensors, batteries, controllers, and body structures can be tailored to specific robotic applications by optimizing cut patterns. Actuators based on kirigami principles exhibit complex motions programmable through various energy sources, while kirigami sensors bridge the gap between electrical conductivity and compliance. Kirigami-integrated batteries enable energy storage directly within
robot structures, enhancing flexibility and compactness. Kirigami-controlled mechanisms mimic mechanical computations, enabling advanced functionalities such as shape morphing and
memory functions. Applications of kirigami-enabled
robots include grasping, locomotion, and wearables, showcasing their adaptability to diverse environments and tasks. Despite promising opportunities, challenges remain in the design of cut patterns for a given function and streamlining fabrication techniques.
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Strongly Correlated Electrons
Simulating Topological Order on Quantum Processors
Adam Gammon-Smith, Michael Knap and Frank Pollmann
It is an ongoing quest to realize topologically ordered
quantum states on different platforms including condensed matter systems,
quantum simulators and digital
quantum processors. Unlike conventional states characterized by their local order, these exotic states are characterized by their non-local
entanglement. The consequences of topological order can be as profound as they are surprising, ranging from the emergence of fractionalized anyonic excitations to potentially providing a scalable platform for
quantum error correction. This deep connection to
quantum computing naturally motivates the realization and study of topologically ordered
quantum states on
quantum processors. However, due to the non-local nature of these states, their study presents a challenge for near-term
quantum devices. This Perspective aims to review the recent progress towards the experimental realization of topologically ordered
quantum states, their potential applications, and promising directions of future research.
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Mesoscale and Nanoscale Physics
Thermal gradient-driven skyrmion dynamics with near-zero skyrmion Hall angle
Yogesh Kumar, Hurmal Saren and Pintu Das
Thermal gradient driven skyrmion dynamics offers a promising route toward green spintronics, enabling the utilization of waste heat for information transport and processing. Using micromagnetic simulations, we investigate Neel skyrmions in a Co-Pt
bilayer nanoracetrack and demonstrate that
stochastic torques induced by a thermal gradient drive skyrmion motion toward the hotter region with a nearly vanishing
Hall angle. The dynamics depends sensitively on intrinsic material parameters - the skyrmion velocity decreases with increasing damping constant, increases with stronger thermal gradients, and varies systematically with saturation magnetization, interfacial DMI strength, and uniaxial out of plane anisotropy. Importantly, we identify a specific range of material parameters within which the skyrmion velocity changes sharply while the
Hall angle remains strongly suppressed, saturating near zero. This comprehensive parameter-dependent study establishes a universal design framework for minimizing the
Hall effect in thermal gradient driven spintronic systems.
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Soft Condensed Matter · Cross-listed from physics.bio-ph
Space-filling discrete helices
Jayanth R. Banavar, Achille Giacometti, Trinh X. Hoang et al. (+2 more)
Proteins are linear chain molecules that play a central role in life and health.
Protein native state folds are modular assemblies of space-filling building blocks of {\alpha}-helices, \{beta}-sheets and tight turns. Here we deduce the structures of a countable set of space-filling helical forms of a uniform discrete thick string from first principles with no additional input or adjustable parameters. These forms occur in correspondence with the natural numbers, loosely analogous to the energy levels in a Bohr atom. We find the remarkable result that one of these helical forms is an excellent candidate for an {\alpha}-helix through seemingly improbable
quantum chemistry coincidences that fit the geometrical requirements. Our work suggests that geometry and chemistry are complementary ways of looking at
proteins and suggests a route for developing a unified framework for understanding
proteins.
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All authors Jayanth R. Banavar, Achille Giacometti, Trinh X. Hoang, Amos Maritan, Tatjana Škrbić
Mesoscale and Nanoscale Physics
Orbital Magnetization and Streda Formula of Interacting Electrons in the Mean-field Approximation
Jihang Zhu and Chunli Huang
We study the
magnetic-field response of interacting electron systems within mean-field theory using perturbation theory. We show that the linear response of the mean-field density-
matrix to a weak
magnetic field is purely
geometric: it depends only on wavefunction derivatives, the Berry connections linking the occupied and unoccupied subspaces, and does not explicitly depend on the interaction potential and the quasiparticle dispersion. This leads to compact, gauge-invariant projector expressions for both the Středa formula and the formula for orbital magnetization. Our calculation explicitly elucidates the role of exchange and self-consistency in defining current vertices for orbital magnetization calculations. Our work establishes a direct connection between mean-field theory,
quantum geometry and the non-interacting topological band theory.
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Materials Science
Benchmarking and advancing machine-learning interatomic potentials for 3C-SiC across equilibrium and extreme conditions
Ali Hamedani, Zijian Meng, Laurent Karim Béland et al. (+1 more)
Several machine-learning interatomic potentials (MLIPs) have been developed for cubic silicon carbide (3C-SiC). Here, we
benchmark seven existing MLIPs against a common set of structural, thermal, defect, radiation-damage, disordered-phase, and computational-performance tests. We also introduce two complementary MLIPs trained on DFT-labeled crystalline,
liquid, amorphous, and defective configurations. TGAP, a Gaussian approximation potential based on the \verb|soap_turbo| descriptor, provides consistently high accuracy across the sampled configurational space. MTP, a custom moment tensor potential, retains good accuracy across these regimes while offering substantially lower computational cost, GPU acceleration, and access to multi-million-atom simulations. As an application-level test, both potentials remain stable in displacement cascades spanning short-range repulsion, transient disorder, and recrystallization. Overall, MTP emerges as a particularly strong accuracy–cost compromise for large-scale and strongly non-
equilibrium simulations of 3C-SiC.
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All authors Ali Hamedani, Zijian Meng, Laurent Karim Béland, Andrea E.Sand
Disordered Systems and Neural Networks · Cross-listed from cs.LG
Fisher Information, Training and Bias in Fourier Regression Models
Lorenzo Pastori, Veronika Eyring and Mierk Schwabe
Motivated by the growing interest in
quantum machine learning, in particular
quantum neural networks (QNNs), we study how recently introduced evaluation metrics based on the Fisher information
matrix (FIM) are effective for predicting their training and prediction performance. We exploit the equivalence between a broad class of QNNs and
Fourier models, and study the interplay between the effective dimension and the bias of a model towards a given task, investigating how these affect the model's training and performance. We show that for a model that is completely agnostic, or unbiased, towards the function to be learned, a higher effective dimension likely results in a better trainability and performance. On the other hand, for models that are biased towards the function to be learned a lower effective dimension is likely beneficial during training. To obtain these results, we derive an analytical expression of the FIM for
Fourier models and identify the features controlling a model's effective dimension. This allows us to construct models with tunable effective dimension and bias, and to compare their training. We furthermore introduce a tensor network representation of the considered
Fourier models, which could be a tool of independent interest for the analysis of QNN models. Overall, these findings provide an explicit example of the interplay between geometrical properties, model-task
alignment and training, which are relevant for the broader machine learning community.
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Soft Condensed Matter
Emergence of mixed orientational ordering in quasi-one-dimensional superdisk and superball fluids
Sakineh Mizani, Martin Oettel, Péter Gurin et al. (+1 more)
We report the discovery of a mixed orientational structure in the quasi-one-dimensional fluid of hard non-spherical bodies with the exact calculation of the thermodynamic and structural quantities using the transfer operator method. The mixed arrangement, which is spatially uniform, but orientionally ordered, cannot be identified with conventional mesophases such as tetratic, cubatic and nematic. It is found that the particles form a mixed orientational arrangement with preferred parallel and perpendicular orientations in a channel, where the number of parallel and perpendicularly oriented particles is not equal even at the close packing density. The mixed structure can be stabilized with hard bodies having equal side lengths in parallel and perpendicular orientations along the channel. These conditions can be realized with colloidal superdisks (superballs) if the
curvature of neighboring sides (faces) are different. We show that even a small stretching of the superparticle destabilizes mixed ordering due to perfect nematic order evolving upon approaching close-packing.
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All authors Sakineh Mizani, Martin Oettel, Péter Gurin, Szabolcs Varga
Materials Science
Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
Michael D. Atkinson, Michael D. White, Adam J. Plowman et al. (+1 more)
The development of next-generation structural materials for harsh environments requires rapid assessment of mechanical performance and its dependence on microstructure. While full-field
crystal plasticity (CP) models provide detailed insights, the high computational cost limits their use with uncertainty quantification workflows and in component-scale simulation. Surrogate models based on recurrent neural networks (RNNs) have shown promise in reproducing history-dependent mechanical behaviour but are applied to models with either fixed microstructure or representative volume elements. Here, we develop a microstructure sensitive RNN surrogate that predicts homogenised stress responses directly from three-dimensional grain structures and arbitrary deformation histories. The architecture employs a gated recurrent unit (GRU) with mappings from microstructure to both the initial hidden state and sequence inputs, allowing the model to capture path dependence and microstructure variability. Training data comprised of over 300,000 CP simulations generated using combinations of randomly generated microstructures and loading paths. The model was found to reproduce CP predictions for both in-distribution validation data and unseen deformation modes, with errors of 2 MPa to 3 MPa. Out-of-distribution microstructures were more difficult to predict, emphasising the need for representative training data with, for example, heavily textured microstructures.
Embedding the model into a multiscale framework demonstrates its ability to replace conventional constitutive updates, reducing computational cost while preserving key features of the stress distribution. These results establish microstructure-informed RNN surrogates as a promising alternative to direct CP simulations, offering a pathway toward rapid multiscale modelling and uncertainty quantification.
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All authors Michael D. Atkinson, Michael D. White, Adam J. Plowman, Pratheek Shanthraj
Materials Science
Uncovering domain morphology in an unconventional magnet with scanning diamond quantum magnetometry
Freya Johnson, Jan Zemen, Helena Knowles et al. (+1 more)
Unconventional
magnetic materials including non-collinear antiferromagnets, p-wave magnets and altermagnets, are an emerging frontier for
quantum spintronics and hybrid
quantum devices. Critical to the application of these materials is control over the
magnetic domain state, as their unique,
symmetry-driven properties vanish in a multi-domain limit. However, the mechanisms governing domain formation in materials with compensated local moments remain poorly understood. In this work, we examine the ferrimagnetic to non-collinear
antiferromagnetic phase transition of Mn3NiN using scanning nitrogen-vacancy centre magnetometry. We provide nanoscale mapping of the
magnetic domain
evolution on cooling and correlate the local stray fields with global magnetometry and anomalous
Hall effect measurements. We observe the formation of a disordered, dendritic domain structure whose roughness is quantified using its fractal dimension. The fractal dimension steadily increases on cooling through the transition, saturating at a value of ~ 1.55 in the non-collinear phase, but the domain area distribution does not show any significant changes. We show this behaviour cannot be explained by the balance of demagnetisation energy and domain wall energy, and conclude elastic contributions and defects are a critical factor to explain the domain size.
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All authors Freya Johnson, Jan Zemen, Helena Knowles, Lesley F. Cohen
Superconductivity
Field-Induced SIT in Disordered 2D Electron systems: The case of amorphous Indium-Oxide thin films
Tsofar Maniv and Vladimir Zhuravlev
The phenomenon of field-induced
superconductor to
insulator transition (SIT) in disordered 2D electron systems has been a subject of controversy since its discovery in the early 1990s. Here we present a phenomenological quantitative theory of this phenomenon which is not based exclusively on the
boson-
vortex duality used commonly in the field. Within a new low-temperature framework of the time-dependent Ginzburg-Landau (TDGL) functional approach to superconducting fluctuations we propose and develop a scenario in which
bosons of Cooper-pair fluctuations (CPFs) condense and localize in real-space mesoscopic puddles under increasing
magnetic field due to diminishing stiffness of the fluctuation modes at low temperatures in a broad range of momentum space.
Quantum tunneled CPFs relieving the condensed mesoscopic puddles, which consequently pair break into fermionic quasi-particle excitations, dominate the thermally activated inter-puddles transport. The spatially shrinking puddles of CPFs, embedded in expanding normal-state regions, upon further increasing field, suppress the quasi-particle excitation gap and so lead to high-field negative magneto-resistance (MR). Application to amorphous Indium-
Oxide thin films shows good quantitative agreement with experimental sheet resistance data. In particular, in agreement with the experiment at low temperatures (i.e. well below the
quantum tunneling pair breaking "temperature"), the sheet resistance isotherms are predicted to show a single crossing point at a
quantum critical field not far below the MR peak.
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Materials Science
Exploring the Physical Properties, Hydrogen Storage Capacity and Thermal Barrier Performance of LaMg2H7: A First-Principles Investigation
Tanvir Khan, Md Hasan Shahriar Rifat, M. Ibrahim et al. (+3 more)
LaMg2H7 is a ternary wide band gap
semiconductor that is a member of the hydride family. The bulk physical characteristics of the LaMg2H7 compound, including its structural, electronic band structure, elastic, thermal, and optical characteristics, have been examined in this work utilizing density functional theory (DFT). The elastic constants indicate that LaMg_2H_7 is mechanically stable, brittle in nature, and anisotropic. This studied compound possesses a moderate level of hardness. The band structure and density of states have been examined to have a better understanding of its electronic behavior. The intrinsic carrier concentrations and effective masses have been determined using the band structure. The gravimetric hydrogen storage capacity (Cwt%) has been calculated, indicating that this compound is suitable for hydrogen storage applications. This compound is dynamically stable, as confirmed by its
phonon dispersion. Here, the details of this wide-band-gap
semiconductor's reflectivity, absorption coefficient, refractive index, dielectric function, optical conductivity, and loss function are investigated. The substance is a moderate reflector of ultraviolet (UV) light. The absorption and conductivity support the gap in the band structure. The thermodynamic properties, such as bulk modulus, internal energy, specific heat capacity,
entropy, thermal expansion coefficient, and Debye temperature, have been explored at varying temperatures and pressures. LaMg_2H_7 has a moderate level of melting temperature with higher
lattice thermal conductivity. The value of the thermal expansion coefficient and minimum thermal conductivity is highly recommended for use as a thermal barrier coating (TBC).
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All authors Tanvir Khan, Md Hasan Shahriar Rifat, M. Ibrahim, J.H. Abir, Saptak Roy, S.H. Naqib
Mesoscale and Nanoscale Physics
Signatures of broken symmetries in the excitations of a periodic 2DEG coupled to a cylindrical photon cavity
Vidar Gudmundsson, Vram Mughnetsyan, Hsi-Sheng Goan et al. (+6 more)
In a two-dimensional electron gas (2DEG) in a periodic lateral superlattice subjected to an external homogeneous
magnetic field and in a cylindrical far-infrared
photon cavity we search for effects of broken
symmetries: Static ones, stemming from the unit
cell of the system, and the external
magnetic field together with the dynamic ones caused by the vector potential of the cavity promoting
magnetic types of transitions, and the chirality of the excitation pulse. The Coulomb interaction of the electrons is described within density functional theory, but the electron-
photon interactions are handled by a configuration interaction formalism within each step of the density functional approach, both for the static and the dynamic system. In the dynamical calculations we observe weak
chiral effects that change character as the strength of the electron-
photon interaction and the external
magnetic field are increased. From the analysis of the
chiral effects we identify an important connection of the para- and diamagnetic electron-
photon interactions that promotes the diamagnetic interaction in the present system when the interaction strength is increased. Furthermore, the asymmetric potential in the unit
cell of the square array activates collective oscillation modes that are not present in the system when the unit
cell has a higher
symmetry.
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All authors Vidar Gudmundsson, Vram Mughnetsyan, Hsi-Sheng Goan, Jeng-Da Chai, Nzar Rauf Abdullah, Chi-Shung Tang, Wen-Hsuan Kuan, Valeriu Moldoveanu, Andrei Manolescu
Soft Condensed Matter
The Hidden Wheel-Within
Falko Ziebert and Igor M. Kulić
There is this old, eternal question: Why don't animals have wheels? In this perspective we show that they actually do. And they do so in a physically extraordinary way – by combining incompatible elasticity, differential geometry and dissipative self-organization. Nature's wheel – the “wheel-within” – has been mysteriously concealed in plain sight, yet it
spins in virtually every slender-body organism: in falling cats, crocodilians spinning to subdue their prey, rolling fruit-fly larvae, circumnutating plants and even in some of our own body movements. Flying somehow under the radar of our cognition, in recent years the wheel-within also tacitly entered the field of soft robotics, finally opening our eyes for its ubiquitous role in Nature. We here identify its underlying physical ingredients, namely the existence of a neutrally-stable, shape-invariant and actively driven elastic mode. We then reflect on various man-made realizations of the wheel-within and outline where it could be spinning from here.
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Statistical Mechanics
Thermodynamics of data
Borko Stosic
The recently introduced concept of generalized thermodynamics is explored here in the context of 1d, 2d and 3d data analysis, performed on samples drawn from a 3d X-ray soil sample image. Different threshold levels are used to binarize the 3d sample, wherefrom relative frequencies of binary patterns are found and then used to address finite size scaling behavior of the response functions as a function of the disorder parameter (equivalent of temperature in thermodynamics). It is found that for different threshold levels response functions for increasing sample sizes approach the thermodynamic limit from different directions, with a crossover reminiscent of a transition from open to periodic boundaries of the Ising model, implying existence of a characteristic correlation scale. It is argued here that this characteristic scale corresponds to the "natural" properties of the data, where correlations within finite size samples are neither underestimated nor overestimated. In the current context of soil this scale may be related to the so-called Representative elementary volume (REV), while in other situations this characteristic scale should be interpreted in the context of the phenomenon under study.
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Materials Science
Ground state magnetic structure of Mn3Sn
Jeppe Jon Cederholm, Zhian Xu, Yanfeng Guo et al. (+11 more)
We use spherical
neutron polarimetry to determine the ground state
magnetic structure of Mn3Sn. We find that Mn3Sn adopts an inverse triangular structure with
spins parallel to <100> (Type III) rather than
spins parallel to <110> (Type IV). Density functional theory calculations reveal no energy difference between these two structures, suggesting that the selection is caused by subtle effects such as sixth-order anisotropy. Partial control of the
magnetic domain population through a moderate
magnetic field is key to distinguish between the two models. We find that three of the six domains are approximately equally populated, while the others have negligible population. Upon entering the low temperature incommensurate phase, the domain structure is lost. The domains decouple from the
magnetic field, and can therefore not be controlled by any known method.
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All authors Jeppe Jon Cederholm, Zhian Xu, Yanfeng Guo, Martin Ovesen, Thomas Olsen, Kristine M. L. Krighaar, Chrystalla Knekna, Jian Rui Soh, Youngro Lee, Navid Qureshi, Jose Alberto Rodriguez Velamazan, Eric Ressouche, Andrew T. Boothroyd, Henrik Jacobsen
Statistical Mechanics
Similarities and differences of typicality in quantum and classical systems
Peter Reimann and Nicolas Nessi
Typicality is a well-established and very general property of
quantum many-body systems, referring to the phenomenon that the expectation values of any given observable are practically indistinguishable for the overwhelming majority of all pure states (normalized vectors) in a sufficiently high-dimensional
Hilbert (sub-)space. Here, we provide very simple and general arguments that analogous typicality properties of pure states (phase space points) in classical many-body systems are still expected to hold true for macroscopic observables, but not any more for microscopic (few-body) observables.
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Soft Condensed Matter
Tuning pair interactions in colloidal systems using random light fields
Augustin Muster, Diego Romero Abujetas, Frank Scheffold et al. (+1 more)
We propose a method to tune interactions between absorptionless colloidal particle pairs. This is achieved via optimization of the spectral energy density of a homogeneous random optical field. Several standard and more exotic interaction potentials, as well as their negative counterparts, are shown to be successfully tuned. We show that the effective dimensionality of the space of potential functions that can be created by this means can reach up to several tens.
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All authors Augustin Muster, Diego Romero Abujetas, Frank Scheffold, Luis S. Froufe-Pérez
Quantum Gases
Quartic level repulsion in a quantum chaotic three-body system without symplectic symmetry
Alex D. Kerin, Barbara Dietz and Joachim Brand
Among the fundamental
symmetry classes of
quantum chaotic systems in Dyson's threefold way, the
symplectic class is rarely observed in nature. Characterized by the strongest possible level repulsion in the energy spectrum, the
symplectic symmetry class also implies a double (Kramers) degeneracy of levels. Studying the spectral statistics of three
quantum particles (identical
bosons or mass-imbalanced
fermions) in a harmonic trap, we find numerical evidence for strong level repulsion in the regime of weak contact interactions. While the statistical indicators are consistent with
quantum chaos in systems with
symplectic symmetry, the absence of Kramers degeneracy rules out this
symmetry. In the strongly-interacting
unitary limit either Poissonian or stick statistics are observed (depending on commensurability of the mass ratio) indicating regular dynamics.
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Materials Science
Modular Reactor for In Situ X-ray Scattering, Spectroscopy, and ATR-IR Studies of Solvothermal Nanoparticle Synthesis
Sani Y. Harouna-Mayer, Melike Gumus Akcaalan, Jagadesh Kopula Kesavan et al. (+14 more)
Understanding the chemical processes that occur during the solvothermal synthesis of functional nanomaterials is essential for their rational design and optimization for specific applications. However, these processes remain poorly understood, primarily due to the limitations of conventional ex situ characterization techniques and the technical challenges associated with in situ studies, particularly the design and implementation of suitable reactors. Here, we present a versatile
cell suitable for in situ X-ray scattering, X-ray spectroscopy, and infrared spectroscopy studies performed during solvothermal synthesis under autoclave-like, inert conditions. The reactor enables precise control of the temperature between -20 C and 200 C, pressures up to 8 bar,
magnetic stirring, and injection of gas or
liquids. The reactor's capabilities are demonstrated by comprehensively studying the solvothermal synthesis of magnetite nanoparticles from iron acetylacetonate in benzyl alcohol through in situ X-ray scattering and spectroscopy, and ATR-IR spectroscopy.
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All authors Sani Y. Harouna-Mayer, Melike Gumus Akcaalan, Jagadesh Kopula Kesavan, Tjark R. L. Groene, Lars Klemeyer, Sarah-Alexandra Hussak, Lukas Grote, a Davide Derelli, Francesco Caddeo, Cecilia Zito, Paul Stützle, Dorota Speer, Ann-Christin Dippel, Blanka Detlefs, Yannik Appiarius, Axel Jacobi von Wangelin, Dorota Koziej
Soft Condensed Matter
SAOS and LAOS rheology for differentiating chemical and physical crosslinking: A case study on PVA hydrogels
David Kogan and Moshe Gottlieb
In this work, we have studied the viscoelastic behavior of chemically and physically crosslinked Poly(vinyl alcohol) (PVA) hydrogels near the critical gel point (GP) as well as further away from it, by means of small amplitude (SAOS) and large amplitude (LAOS) oscillatory shear experiments. Chemical crosslinking involved covalent bonding by means of glutaraldehyde as a crosslinker, while physical crosslinking was induced by freeze-thaw cycles. SAOS data analysis allowed evaluation of critical parameters such as the critical relaxation exponent n, gel strength S, and
equilibrium modulus Ge, based on the dynamic self-similarity and fractal network structures at the GP. LAOS rheological data analysis showed that the chemically crosslinked system exhibited moderate strain-dependance due to the permanent covalent bonds, whereas the physically crosslinked system displayed significant strain-dependent nonlinearity due to strain dependent interactions at the crosslink entities. LAOS experiments, supported by Chebyshev coefficients and Lissajous-Bowditch plots, highlighted pronounced differences in nonlinear responses, underscoring the influence of crosslinking mechanisms on the network rheological behavior. The findings establish LAOS as a powerful tool for differentiating polymeric network structures, providing insights beyond those attained by conventional linear rheology. 50 pages 1 figures
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