Statistical Mechanics · Cross-listed from hep-th
Mass quench in interacting finite-size quantum field system
Grachik A Simonian, Alexey G. Mikhaylenko and Andrew G. Semenov
In this work, we theoretically investigate the non-
equilibrium evolution of the correlation functions of a
quantum scalar field following a mass
quantum quench in a finite-size system. The self-consistent equation for the Keldysh (statistical) correlation function is solved numerically in the one-loop approximation. A specific spatio-temporal effect is observed: at a point in time approximately equal to half the system size, the effective mass experiences a strong disturbance. It is shown that this effect is driven by the interference of counter-propagating wave fronts of fluctuations that propagate within the light cone and is induced by periodic boundary conditions.
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Strongly Correlated Electrons
Strange-metal behavior in correlated molecular conductors
Savita Priya, Maxim Wenzel, Christian Prange et al. (+10 more)
The $\kappa$-BEDT-TTF salts are prototypical Mott systems, realizing a correlation-driven electronic transition from a Fermi-
liquid state to a Mott
insulator. The metallic compounds with spatially modulated Hg-containing anions, $\kappa$-(BEDT-TTF)$_4$Hg$_{3-\delta}X_8$ ($X$ = Br, and Cl), however, fall outside this classification. Our temperature-dependent transport and broad-range optical investigations reveal a $\rho(T)\propto T$ dependence of the resistivity up to elevated temperatures and a power-law behavior of the frequency-dependent conductivity $\vert\hat{\sigma} (\omega)\vert \propto \omega^{-0.7}$; well-known hallmarks of “strange metals”. The linear-in-frequency scattering rate of these strange metals scales to the Planckian dissipation. We demonstrate that this response only occurs in systems with incommensurate anion layers and establish a direct link to large-scale spatial modulations. Our conclusions can be extended to other strongly correlated strange-metal compounds
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All authors Savita Priya, Maxim Wenzel, Christian Prange, Bertold Rasche, Christian Sindlinger, Takuya Kobayashi, Hiromi Taniguchi, Dita Puspita Sari, Yasuyuki Ishii, Kazuya Miyagawa, Kazushi Kanoda, Simone Fratini, Martin Dressel
Materials Science
Emergent gold-induced interfacial magnetism in monolayer FePS$_3$
Giuseppe Buccoliero, Anita Polli, Marli dos Reis Cantarino et al. (+10 more)
Owing to their atomically clean interfaces and extreme thinness, two-dimensional (2D) materials are ideal hosts for strong proximity effects, whereby contact with an adjacent material reshapes their ground state. Here, we demonstrate such an effect within a hybrid
heterostructure, between the 2D antiferromagnet FePS$_3$ and an ultrathin gold film. Rather than a passive support, the latter profoundly changes the nature of the magnetism in the 2D magnet, inducing a sizeable interfacial moment. Large-area flakes from Au-assisted exfoliation, combined with element-selective X-ray absorption mapping, enable a layer-by-layer study from monolayer to bulk, benchmarked against an inert SiO$_2$ substrate reference. At 9 T and 5 K, the monolayer on gold shows a three-fold enhanced X-ray
magnetic circular dichroism relative to SiO$_2$, with a $\sim$40% reduction of the orbital-to-
spin moment ratio. Resonant inelastic X-ray scattering reveals a collapse of the
crystal-field (d-d) excitations and a massive spectral-weight transfer to the charge-transfer region, unveiling the microscopic mechanism behind this change. Supported by atomic multiplet calculations, we identify interfacial charge transfer and Fe 3d-Au hybridization as the origin of these effects, which decay over the first three layers and vanish at the pentalayer, establishing layer number combined with substrate engineering as an atomically precise handle.
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All authors Giuseppe Buccoliero, Anita Polli, Marli dos Reis Cantarino, Rachel Nickel, Aloïs Arrighi, Roberto Sant, Tristan Riccardi, Valérie Reita, Nedjma Bendiab, Laëtitia Marty, Kurt Kummer, Johann Coraux, Nicholas B. Brookes
Mesoscale and Nanoscale Physics
Symmetry-Dependent Polarity Reversal of Bulk Spin-Orbit Torque in Single-Layer MnCoGa
Rongkun Han, Mingsong Zhang, Dahai Wei et al. (+3 more)
Controlling the magnitude and polarity of
spin-orbit torque (SOT) is essential for manipulating magnetization in spintronic devices. Here, we realize bulk
spin-orbit torque (SOT) in a single-layer Mn1.6Co1.4Ga (MCG) Heusler
alloy and achieve
lattice strain-controlled reversal of SOT polarity. SOT-driven magnetization switching is achieved over a thickness range of 3-20 nm, with the switching polarity reversed between the strongly strained ultrathin regime and thicker films. First-principles calculations reveal a sizable intrinsic
spin Hall conductivity (SHC) in MCG originating from its topological band structure, which is enhanced by the tetragonal distortion without changing sign. Together with the thickness-dependent structural
evolution, we demonstrate that the reversal of SOT polarity does not originate from a sign change of the SHC, but rather from
lattice distortion induced
symmetry breaking that modifies the conversion of
spin current into a net bulk SOT, thereby controlling its polarity. These results establish strain-controlled structural
symmetry as an additional degree of freedom for tuning bulk SOT in
magnetic single layers.
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All authors Rongkun Han, Mingsong Zhang, Dahai Wei, Yuan Lu, Wenxu Zhang, Jianhua Zhao
Mesoscale and Nanoscale Physics
Field-Free Reconfigurable Spin Logic in Compositionally Graded MnxCoAl Layer
Haohang Cheng, Pengju Wang, Hongrui Qin et al. (+4 more)
Spintronic logic-in-
memory provides a route to reducing data-transfer energy consumption and accelerating computation by integrating nonvolatile storage and logic functions within a single physical unit. Here, we investigate field-free
spin-orbit-torque (SOT) switching and reconfigurable
spin logic in a vertically composition-graded MnxCoAl/Pt
heterostructure. In contrast to the uniform-composition Mn1.8CoAl/Pt and Mn2.5CoAl/Pt control devices, the Mn1.8-2.5CoAl gradient device exhibits deterministic SOT switching under zero external
magnetic field. Dzyaloshinskii-Moriya interaction (DMI)-related measurements reveal a finite characteristic effective-field scale, indicating the involvement of chiral magnetization-reversal processes. Meanwhile, the vertical composition gradient introduces
magnetic inhomogeneity that can modify domain nucleation and propagation, and the combined effects are consistent with the observed field-free switching behavior. The composition-gradient device further exhibits accumulative multistate switching with stable intermediate Hall-resistance states under zero
magnetic field, whereas the uniform-composition controls do not show comparable stable multistate behavior. By tailoring the amplitude, polarity, and sequence of current pulses, the device can be tuned between binary and multilevel switching modes, enabling the experimental realization of AND, OR, NAND, and NOR Boolean operations within the same Hall-bar device without any external
magnetic field. These results extend Mn-Co-Al Heusler
heterostructures from field-assisted SOT switching toward field-free magnetization control, multistate operation, and reconfigurable
spin logic through vertical composition engineering.
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All authors Haohang Cheng, Pengju Wang, Hongrui Qin, Rongkun Han, Dong Pan, Dahai Wei, Jianhua Zhao
Materials Science
Multifunctional synaptic learning and neuromorphic computing using crystalline TiO$_x$/NiO$_x$ heterojunction-based memory devices
Dip Manna, Koushik Mondal, Subhajit Karmakar et al. (+5 more)
An attempt is made here to mimic different properties of biological synapses using Ag/TiO$_x$/NiO$_x$/p$^{++}$-Si memristor structure by studying its different transport properties under dc and pulsed bias. The presence of crystalline NiO$_x$ with smaller gains is found to be helpful to get TiO$_x$ deposited on its top with crystalline properties and larger grains. The
heterostructure offers stable bipolar forming free non-volatile resistive switching characteristics under reverse biased condition with gradual set and reset features. These devices are also able to successfully implement the classical Pavlov's learning, study artificial nociceptor and Morse code detection. While incorporating synaptic weights derived from the measured conductance programming pulse relationship, an artificial neural network achieves nearly 95% accuracy in MNIST digit recognition. In brief, NiO$_x$/TiO$_x$ heterojunction plays the pivotal role in getting such reproducible $I-V$ characteristics for mimicking different properties of biological synapses.
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All authors Dip Manna, Koushik Mondal, Subhajit Karmakar, Pawan Kumar Ojha, Sourav Roy, Biswarup Satpati, Prasanta Karmakar, Supratic Chakraborty
Mesoscale and Nanoscale Physics
Magnon dynamics driven by the symplectic quantum metric in a chiral soliton lattice
Sidhartha Chatterjee, Andreas Haller, Peter P. Orth et al. (+1 more)
We investigate the effects of
quantum geometry on the motion of
magnon wave packets in one-dimensional
quantum spin chains. In contrast to fermionic systems, where transport phenomena driven by the
quantum metric have been extensively studied, we show that the dynamics in bosonic
magnon systems are strongly affected by the symplectic structure and the pseudo-unitarity of the transformation of the
magnon Bogoliubov-de Gennes
Hamiltonian. A chiral
soliton lattice provides a setting in which the symplectic
quantum metric strongly influences the longitudinal
magnon dynamics. We derive the semiclassical response of a
magnon wave packet in such a system to a weak, slowly varying perturbation and demonstrate that the wave packet velocity acquires a
geometric contribution proportional to the momentum derivative of the symplectic
quantum metric, which dominates over the conventional group velocity for a nearly flat band. Solving the resulting equations of motion, we obtain a bounded trajectory in real time with a phase-space area determined by the symplectic
quantum metric.
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All authors Sidhartha Chatterjee, Andreas Haller, Peter P. Orth, Thomas L. Schmidt
Materials Science
Homogeneous Charge Relaxation in Organic Mixed Ionic-Electronic Conductors
Silan Zhang, Scott T. Keene, Junfu Tian et al. (+11 more)
Organic mixed ionic-electronic conductors (OMIECs) couple ionic and electronic signals, enabling energy storage, neuromorphic computing, and bioelectronics. However, how charge relaxes in water once the bias is removed, which determines how long stored states persist, remains unclear. Using operando charge photometry, we tracked charge in OMIEC films during biasing and open-
circuit relaxation. Under bias, charges moved as redox fronts. After bias removal, charge instead relaxed uniformly across the channel. Modeling and cryo-electron microscopy indicate that swelling creates connected water-rich pathways through the bulk. These pathways speed ion motion but also let stored charge leak away. Tuning the terminal side chain of a polythiophene controls water uptake and ion trapping. Bulky hydrophobic side chains enable stable programmable states, whereas hydrophilic side chains support fast electrophysiology sensing.
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All authors Silan Zhang, Scott T. Keene, Junfu Tian, Georgina E. Lindop, Simon M. Fairclough, Zhengkang Qu, Xian Wei Chua, Christopher Slaughter, Christina J. Kousseff, Caterina Ducati, Iain McCulloch, Henning Sirringhaus, Akshay Rao, George G. Malliaras
Statistical Mechanics
Mutual Linearity of Complexes in Chemical Reaction Networks
Pedro E. Harunari, Guilherme Fiusa and Matteo Polettini
Exact statements about how a system far from
equilibrium responds to changes in its rate constants are scarce beyond linear response, yet they are central to the control of biochemical networks. A notable exception is mutual linearity: in a jump process, controlling the rates of a single transition makes any two stationary probabilities obey an exact affine relation, arbitrarily far from
equilibrium. With nonlinear mass-action kinetics, and conservation laws in place of a normalization, chemical reaction networks seem to defy mutual linearity since species concentrations obey no such relation. We show that it was there all along, in the complexes' activities (mass-action monomials) rather than in the concentrations of species. For zero-deficiency networks with a single linkage class, controlling one reaction makes any three stationary activities obey a linear relation whose coefficients are independent of the controlled rate constants, the conserved quantities (hence the initial state), and even of the stoichiometry of complexes. This predicts hidden activities and bounds the activity ratios the control can reach, while a violation signals nonzero deficiency or multiple linkage classes.
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Materials Science
Comprehensive study of massively overlapping cascades in common elemental metals
Aslak Fellman, Jesper Byggmästar and Fredric Granberg
Massively overlapping cascades simulations were carried out in 21 elemental metals: Be, Al, Ti, V, Cr, Fe, Co, Ni, Cu, Zr, Nb, Mo, Rh, Pd, Ag, Hf, Ta, W, Pt, Au and Pb. These elements have simple FCC, BCC and HCP
lattice structures. For each element, 2000 cumulative 5 keV cascades were simulated using molecular dynamics. The overlapping cascades were simulated using various classical analytical interatomic potentials as well as with machine-learning interatomic potentials for many of the elements. The general conclusion is that results from massively overlapping cascades simulations are very sensitive to the choice of interatomic potential across the periodic table. Furthermore, we see that FCC metals all form stacking fault tetrahedra due to irradiation, and also typically include interstitial type Shockley partial and Frank type dislocations. In BCC materials typically form interstitial 1/2$\langle$1 1 1$\rangle$ dislocations, but vacancy type 1/2$\langle$1 1 1$\rangle$ dislocations were also observed in V and Nb. HCP materials tend to form complex dislocation structures mainly consisting of a-type dislocations that can be of both vacancy or interstitial type. Correlations between saturated defect concentrations and fundamental underlying material properties are explored.
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Statistical Mechanics
The Fiedler dimension of networks of networks: from fractal to small-world architectures
Lorenzo Grimaldi, Andrea Gabrielli and Pablo Villegas
Is the relaxation of a modular network dictated by its modules or by the network that connects them? The answer fixes the time scales of
diffusion, consensus, and synchronization, all set by the Fiedler
eigenvalue. We show that, for bundled networks, the two levels act one after the other: a random walker must first escape from its module and then spread over the network that connects them. The equilibration time is the sum of these two times, the time needed to reach the base from inside a fiber and the relaxation time of the base, slowed down by the mass of the fibers. The consequences are unexpected. However large the modules are, a small-world core always imposes its own Fiedler dimension; the modules survive only as a logarithmic correction, which slows down equilibration and hides the true exponent up to sizes far beyond any real network. Effective dimensions measured on finite modular systems can therefore be systematically biased. We analytically work out all combinations of finite-dimensional and small-world bases and fibers, and compare them with numerically exact spectra of representatives of each category.
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Soft Condensed Matter
Fluid deformable surfaces with variable thickness - a Surface Shallow-Water-Helfrich model
Jan Magnus Sischka and Axel Voigt
Epithelial tissues play a fundamental role in morphogenesis. Mechanically they can be viewed as thin soft materials exhibiting a solid-fluid duality. The Surface Navier-Stokes-Helfrich model accounts for these properties by combining bending and surface hydrodynamics. In order to account for varying
cell thickness we incorporate a thickness field in the spirit of a shallow-water equation, but defined on the (self-)evolving surface. This replaces the inextensibility constraint of the two-dimensional fluid and with it the conservation of surface area by an incompressibility constraint of the thin film fluid allowing for changes in surface area. We develop a numerical scheme based on surface finite elements, perform convergence tests, demonstrate the impact on shape
evolution of closed surfaces with a constant enclosed volume and discuss implications on modeling morphogenesis.
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Materials Science
Beyond special quasirandom structures: free energies from energy cumulants
Yann L. Müller and Anirudh Raju Natarajan
Predicting the finite-temperature stability of a disordered phase requires its free energy. It is traditionally approximated by combining the energy of a special quasirandom structure (a small
cell mimicking a random
alloy) with the ideal configurational
entropy. This approximation neglects the short-range order that develops on cooling. In this study, we show that the conventional approximation is the first term of an infinite expansion of the free energy in energy cumulants. Higher-order cumulants are estimated from energies of random arrangements, without Monte Carlo or molecular dynamics. In a nine-element refractory system, adding the second cumulant reduced free energy errors by about an order of magnitude. The expansion gives phase diagrams with order–disorder transitions, defect concentrations, and short-range order. To demonstrate its utility, we used a foundation interatomic potential to screen lithium-excess rocksalt oxides across 26 elements for synthesizable disordered phases rich in the Li$_4$ clusters needed for lithium percolation. The approach applies to any
lattice and chemistry, and brings disordered phases within reach of routine screening.
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Materials Science
Benchmarking Universal Machine-Learning Interatomic Potentials for Temperature-Dependent Elasticity of Binary and High-Entropy Refractory Carbides
Miroslav Lebeda, Jan Drahokoupil, Šimon Svoboda et al. (+1 more)
Accurate prediction of temperature-dependent elasticity is important for assessing refractory carbides under high-temperature conditions, but the computational cost of ab initio molecular dynamics (AIMD) limits systematic investigations across compositions and temperatures. Universal machine-learning interatomic potentials (uMLIPs) offer an efficient alternative, yet their accuracy for this task remains insufficiently established. Here, we
benchmark nine uMLIPs against consistent AIMD reference data for five binary and two high-
entropy (HE) carbides between 300 and 1200 K. Elastic constants and the corresponding bulk, shear, and Young's moduli are obtained using stress-strain molecular dynamics, explicitly sampling thermal atomic motion and anharmonic effects beyond thermal expansion alone. We assess absolute elastic properties and normalized thermal softening separately. MACE-MH-1 achieves the lowest overall mean absolute percentage error (5.7%). MACE-MH-1 and DPA4-Mini reproduce thermal softening most accurately, with mean deviations of 2.5 and 2.3 percentage points, respectively. All models generally underestimate stiffness, with larger
equilibrium volumes relative to the AIMD reference likely contributing to this trend for most models. C12 exhibits the largest model-dependent errors. The HE carbides are described with accuracy comparable to that of the binary carbides, indicating no apparent accuracy penalty from chemical complexity. Accuracy instead varies with transition-metal composition, with group-V carbides, particularly TaC, presenting the greatest challenge. These results identify promising pretrained models for finite-temperature elasticity in carbides and show why accurate absolute stiffness and thermal softening must be assessed independently.
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All authors Miroslav Lebeda, Jan Drahokoupil, Šimon Svoboda, Petr Vlčák
Statistical Mechanics · Cross-listed from math.PR
Explicit upper bounds on the threshold of one-dimensional long-range percolation
Guy Amit
We study bond percolation on the one-dimensional
lattice in which two sites at distance $r$ are connected with probability $p_r=C/r^{1+\sigma}$, where $0 < \sigma < 1$. An infinite cluster exists if $C$ exceeds a critical value $C_c(\sigma)$, which is not known exactly: the available results are the lower bound of Schulman, $C_c\ge1/[2\zeta(1+\sigma)]$, and numerical estimates. Here we prove explicit upper bounds. We apply a second-moment argument to a family of random monotone paths whose steps have a heavy-tailed (Sibuya) distribution. Two such paths meet only a finite number of times, and their overlap is computed exactly by renewal theory. The result is a closed-form bound, which gives $C_c\le\sigma+O(\sigma^2)$ as $\sigma\to0$ and is below $1$ for $\sigma < 0.667$. Since the paths are monotone, the bound holds also for oriented percolation, and it determines the oriented threshold asymptotically: $C_c^{\rightarrow}\zeta(1+\sigma)\to1$ as $\sigma\to0$. A coarse-grained version of the argument, with blocks of sites in place of sites, gives an explicit bound $C_c < 1$ for every $\sigma < 1$. We compare the bounds with the known numerical values of $C_c$.
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Mesoscale and Nanoscale Physics
Tunable Ultrastrong Magnon-Magnon Coupling and Squeezed States in a Triaxial Van der Waals Antiferromagnet
Xiao Xiao, Zishuang Li, Zui Tao et al. (+6 more)
Achieving and quantifying ultrastrong
magnon-
magnon coupling (USC) remains a key challenge for
quantum magnonics. Here, we demonstrate widely tunable USC between chiral (right- and left-handed) and acoustic or optical
magnon modes in the van der Waals antiferromagnet $CrPS_4$. Using a full
quantum model, we decompose the interaction into three microscopic interaction channels: the co-rotating term $g_1$ (mode hybridization), the counter-rotating term $g_2$ (two-mode squeezing), and, uniquely in the chiral regime, the self-squared term $g_3$ that mediates single-mode squeezing. The normalized coupling ratio reaches $g/f_g$ $\sim$ 0.41, entering the USC regime. Most significantly, we establish a complete protocol linking these USC parameters to a measurable
quantum phenomenon: a squeezed
magnon vacuum state. Our simulations not only visualize the chirality and polarization
evolution of the hybrid modes but also demonstrate how to directly extract quadrature fluctuations and a substantial squeezing factor (up to $\sim$ 9.7 dB) from thermal noise-driven magnetization dynamics. This work provides a material-specific
quantum framework for USC and a practical pathway to detect and exploit non-classical
magnon states in low-damping two-dimensional magnets, opening a route toward
quantum-enhanced spintronics and hybrid
quantum information platforms.
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All authors Xiao Xiao, Zishuang Li, Zui Tao, Lina Chen, Ping Liu, Shuai Zhang, Haozhe Wang, Yong Pu, Ronghua Liu
Strongly Correlated Electrons
Magnon band splitting without altermagnetism in CuF2
Ioannis Rousochatzakis, Oleg Janson and Alexander A. Tsirlin
Conclusive identification of an altermagnetic state requires going beyond mere
symmetry arguments. We illustrate this in a combined computational and experimental study of the rutile-like material CuF$_2$, which is on the list of predicted altermagnets. Using ab initio and linear
spin-wave calculations supplied by magnetization measurements, we show that CuF$_2$ in its experimental monoclinic structure can be described by a
spin-$\frac12$ model of weakly coupled square-
lattice layers with the in-plane coupling $J_1\simeq 115$ K and two synergistic antiferromagnetic interplane couplings amounting to 4% and 8% of $J_1$, respectively. Driven by long-range superexchange, these interlayer couplings are oblique to the square planes, resulting in the unit-
cell doubling in the magnetically ordered state, thus effectively suppressing any altermagnetic band splitting. Concurrently, we identify unusually strong Dzyaloshinskii-Moriya interactions, $|\mathbf D|/J_1\simeq 0.3$, that produce
spin canting and, together with order-by-disorder effect, pin the Néel vector to the crystallographic $b$-axis. Additionally, DM anisotropy promotes
magnon band splitting, but these bands remain non-chiral. Our results highlight the importance of relativistic effects even in $3d$ magnets with altermagnetic
symmetries.
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Soft Condensed Matter
Elastic polymer networks of exceptional strength by deconcentrating tension
Yu Zhou, Chenghai Li, Zheqi Chen et al. (+2 more)
The strength of a
polymer network is orders of magnitude below that of a
polymer chain, because the network concentrates high tension in a small fraction of
polymer strands. Here we show that the strength of a network can be greatly amplified by recruiting a larger fraction of strands to bear high tension. We develop approaches to fabricate hydrogels of exceptional strength while maintaining low hysteresis. The strength of the hydrogel increases from ~0.05 MPa for a regular network, to ~1 MPa for a highly entangled network, and further to ~10 MPa for a prestretched interpenetrating network. Similar amplifications of strength are achieved for elastomers. Furthermore, experimental data suggest a scaling relation between strength and strand length. This work provides design principles for creating elastic and strong
polymer networks.
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All authors Yu Zhou, Chenghai Li, Zheqi Chen, Xianyang Bao, Zhigang Suo
Statistical Mechanics
Controlling transitions between nonequilibrium states through active bath engineering
Dima Boriskovsky, Salambô Dago, Cyriaque Genet et al. (+6 more)
We develop a family of control protocols for finite-time transitions between active nonequilibrium steady states using the noise-color (correlation rate) as the sole control parameter. By reverse-engineering the second moment dynamics of an active Ornstein-Uhlenbeck process, we determine the time-dependent correlation rate required to realize a prescribed
evolution of the system's state. We experimentally implement these protocols with a micrometer-sized optically trapped particle coupled to an engineered active bath, demonstrating transitions substantially faster than the natural relaxation while keeping the confining potential, noise amplitude, and temperature fixed. Our approach extends engineered swift-equilibration methods to far-from-
equilibrium steady states by directly controlling the temporal correlations of an active environment. We show how physical constraints impose a speed limit on finite-time transitions, while the freedom in choosing the prescribed system
evolution can be exploited to eliminate control discontinuities, minimize the admissible transition time, or optimize a thermodynamic cost.
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All authors Dima Boriskovsky, Salambô Dago, Cyriaque Genet, Rémi Goerlich, Vincent Hardel, Paul-Antoine Hervieux, Harry L. F. Ip, Giovanni Manfredi, Laurent Mertz
Materials Science
Solution-Based Synthesis of Fe-Co-Ni Prussian Blue Analogue Powders: A Comparative Structural, Spectroscopic and Thermal Study
Larissa de O. Garcia, Lindiomar Borges de Avila Jr, Mengmeng Wang et al. (+3 more)
Prussian Blue (Fe-PBA) and its Co and Ni analogues (Co-PBA and Ni-PBA) were synthesized by an additive-free aqueous co-precipitation route using K$_4$[Fe(CN)$_6$] and FeCl$_3$, CoCl$_2$, or NiCl$_2$, respectively. The three powders were systematically compared by X-ray diffraction, ATR-FTIR and Raman spectroscopy, FEG-SEM/EDS, and TG/SDTA. All compositions exhibit the characteristic cubic cyanide-bridged PBA framework, with apparent
lattice parameters of 10.10 +/- 0.02, 10.01 +/- 0.02, and 10.10 +/- 0.03 Angstrom for Fe-PBA, Co-PBA, and Ni-PBA, respectively. The dominant C$\equiv$N stretching band in ATR-FTIR shifts from 2062 to 2071 and 2087 cm$^{-1}$ across the Fe-Co-Ni series, indicating composition-dependent changes in the local cyanide environment. Fe-PBA contains less potassium than the Co- and Ni-containing powders and exhibits a substantially larger low-temperature mass loss. Sharp reflections assigned to crystalline KCl are observed in all three diffraction patterns, while additional unassigned reflections in Ni-PBA indicate the presence of at least one further crystalline phase. These results show that differences among Fe-, Co-, and Ni-based PBAs cannot be attributed solely to transition-metal identity, as precursor oxidation state and washing efficiency also influence the composition and thermal response of the resulting powders.
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All authors Larissa de O. Garcia, Lindiomar Borges de Avila Jr, Mengmeng Wang, Yann Garcia, Christian K. Muller, Flavio Abreu Araujo
Materials Science
Photoinduced Odd- and Mixed-Parity Magnetism in Collinear Antiferromagnets
Jin-Yang Li, Ruo-Yu Ning, Ying Zhang et al. (+3 more)
Altermagnetism, characterized by compensated collinear
magnetic moments in real space and momentum-dependent
spin splitting with even-parity
symmetry, has recently emerged as a distinct form of
magnetic order beyond the conventional ferro- and antiferromagnetic paradigms. However, realizing odd- and mixed-parity magnetism in fully compensated collinear magnets remains challenging. Here, we demonstrate that light irradiation can induce odd- and mixed-parity magnetism in conventional collinear antiferromagnets. Taking monolayer CoS and CoSe as representative systems, and combining Floquet theory with first-principles calculations, we show that circularly polarized light (CPL) induces odd-parity $f$-wave
spin splitting, whereas elliptically polarized light (EPL) induces odd-parity $p$-wave
spin splitting. Uniaxial strain combined with CPL provides an alternative route to realizing the $p$-wave state. More remarkably, applying an electric field together with CPL or EPL transforms the
spin splitting into mixed-parity forms. The light-induced breaking of $\mathcal{PT}$
symmetry, together with
spin-orbit coupling, further gives rise to a finite anomalous Hall response. Our work establishes a versatile strategy for engineering odd- and mixed-parity
spin splitting in compensated antiferromagnets, offering a route toward light-controlled electronic and
magnetic phenomena.
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All authors Jin-Yang Li, Ruo-Yu Ning, Ying Zhang, Qiu-Qiu Li, Si Li, Wen-Li Yang
Materials Science · Cross-listed from physics.chem-ph
Optical absorption spectra from the $GW$-Bethe-Salpeter framework for thousands of atoms
Maximilian Graml, Ritaj Tyagi, Rémi Pasquier et al. (+2 more)
The frequency-dependent absorption and emission of light determine the colors of matter and underpin today's technologies, from solar
cells to light-emitting diodes. Predicting optical properties from first principles remains a computational challenge, especially for large and disordered systems. The $GW$ plus Bethe-Salpeter equation ($GW$-BSE) approach provides predictive accuracy for optical properties, but conventional implementations become costly as system size grows. Here, we present a $GW$-BSE framework combining real-time propagation, atom-centered basis sets, and a locally optimized real-space resolution of the identity. The cost of each propagation step scales quadratically with system size and roughly equals the cost of one self-consistent-field iteration in a density-functional calculation with a semilocal functional. This computational efficiency allows us to calculate the absorption spectrum of a nanographene containing 4616 atoms and opens a path toward routine calculations of optical properties for large disordered systems.
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All authors Maximilian Graml, Ritaj Tyagi, Rémi Pasquier, Štěpán Marek, Jan Wilhelm
Materials Science
Can end-to-end learning from raw electronic structure explain magnetic anisotropy?
Rafał Topolnicki, Jan Navrátil and Piotr Błoński
Machine-learning models trained directly on electronic spectra can predict
spin–orbit-driven properties, yet models with comparable predictive accuracy may learn different electronic dependencies. We examine this problem using
magnetic anisotropy in atomic-scale magnets and a validation strategy designed to assess the physical relevance of learned spectral relationships. We compare a bidirectional gated recurrent unit and a one-dimensional convolutional neural network, both trained to predict
magnetic anisotropy energy (MAE) from
spin- and orbital-resolved scalar-relativistic densities of states (SR-DOS). Despite comparable in-domain (ID) accuracy, the architectures learn only partly overlapping spectral dependencies. Shapley additive explanations identify spectral features shared between the two architectures that can be associated with plausible
spin–orbit-coupling pathways consistent with second-order perturbation theory (PT2). Adding PT2-derived MAE contributions to the model inputs has little effect on ID performance but can improve transfer beyond the training domain, with gains differing between architectures. Controlled spectral perturbations further demonstrate that similar attribution patterns do not imply the same functional dependence of the predicted MAE on spectral weight. The contrasting responses provide a functional context for architecture-dependent out-of-domain transfer. End-to-end learning can identify candidate electronic signatures of
magnetic anisotropy. Their credible microscopic interpretation, however, rests on convergent evidence from predictive performance, model comparison, physical theory, controlled spectral interventions, and evaluation under distribution shift.
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Materials Science
A General Algorithm for Minimal Uncoupled Stress–Strain Calculations of Elastic Constant
S. I. Simak and Utkarsh Singh
We have developed a general
algorithm for constructing the minimum number of strain configurations required to extract second-order elastic constants from first-principles stress-strain calculations without algebraic coupling between the constants targeted for extraction. The method operates on the sparsity structure of the
symmetry-reduced elastic stiffness
matrix, represented by an auxiliary binary
matrix, and generates admissible strain patterns algorithmically rather than prescribing separate strain sets for individual
crystal symmetries. Each independent elastic constant is obtained from a single stress component, while additional stress relations generated by the same deformation provide internal consistency checks. Because the six-dimensional strain space contains only 2^6-1=63 non-empty strain patterns, the minimality of the resulting sets can be verified exactly for every elastic-
symmetry type considered. The construction reproduces established high-efficiency strain sets in cases where they are minimal and yields improved sets for
symmetry classes in which previously tabulated schemes require additional configurations. Because the formulation is based on stress-strain derivatives, it can also be readily extended to finite temperatures using consistently sampled ensemble-averaged thermodynamic stresses. Explicit strain sets are derived for all elastic-
symmetry types spanning the 230 crystallographic space groups, and their accuracy and computational efficiency are benchmarked against established approaches.
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Materials Science
Interlayer ferromagnetic order revealed through pressure-enhanced interlayer exchange coupling in Fe$_3$GaTe$_2$
Riku Iimori and Takashi Kimura
Van der Waals ferromagnets possess finite interlayer
magnetic coupling despite their layered
crystal structures, and this coupling plays an important role in determining their
magnetic properties. In this study, we performed magnetization measurements on high-quality Fe$_3$GaTe$_2$ single
crystals while selectively tuning the interlayer coupling using hydrostatic pressure. We identified two characteristic temperatures, $T_{\rm inf1}$ and $T_{\rm inf2}$, below the Curie temperature with opposite pressure dependences: $T_{\rm inf1}$ is associated with thermally activated domain-wall depinning, whereas $T_{\rm inf2}$ reflects the formation of interlayer ferromagnetic order. Both temperatures exhibit pronounced pressure dependences, in sharp contrast to the nearly pressure-independent Curie temperature associated with intralayer ferromagnetic order. First-principles calculations revealed a substantial pressure-induced enhancement of the interlayer exchange interaction and reasonably reproduced $T_{\rm inf2}$ and its pressure dependence. These results demonstrate that the emergence of interlayer
magnetic ordering can be predicted from the microscopic interlayer exchange coupling, establishing a predictive framework for understanding and designing interlayer coupling phenomena in layered
magnetic materials.
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Superconductivity
Electric and Heat Transport in One-Dimensional SNS Junctions with Energy-Dependent Transmission
Kai Tsutsumi and Shun Uchino
We investigate the phase-independent dc components of the electric and heat currents through a one-dimensional
superconductor-normal-metal-
superconductor (SNS) junction subject to chemical-potential and temperature differences between two superconducting reservoirs. Using a scattering approach based on the Bogoliubov-de Gennes equations, we incorporate multiple Andreev reflections while retaining the energy dependence of transmission through the normal region. We compare energy-independent,
quantum-dot-type, and
quantum-point-contact transmission profiles. At low bias, both currents exhibit nonlinear features associated with the superconducting gap and multiple Andreev reflections. Their responses to a temperature difference depend remarkably on the transmission profile. At a small finite bias, the electric current depends weakly on the temperature difference for the energy-independent and
quantum-dot-type profiles, whereas the
quantum-point-contact profile produces a pronounced nonlinear response. The heat current depends nonlinearly on the temperature difference for all three profiles over the parameter range investigated. These results highlight the role of the transmission profile in nonlinear electric and heat transport through SNS junctions and provide a microscopic reference for related transport studies in mesoscopic fermionic superfluid junctions.
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Materials Science
Predicting plasmonic pole representations of complex dielectric spectra using convolutional neural networks
Dario A. Leon
Extracting spectral properties such as energy position, broadening, and spectral weight from dielectric spectra is critical for interpreting collective electronic excitations in many-body physics. Conventional approaches typically rely on nonlinear fitting procedures that can be computationally demanding and highly sensitive to initialization and fitting choices. In this work, we develop a convolutional neural-network framework for the direct inversion of dielectric spectra into their underlying plasmonic pole structures using a multipole-Padé representation. Rather than training on a constrained database of spectra associated with a specific set of materials, the network is trained entirely on synthetic spectra generated from the analytical multipole-Padé expression with randomized parameters. This enables the network to learn the general mapping between the spectra and their features in an unbiased way, without requiring large, material-specific
datasets derived from real materials. We demonstrate that the synthetically trained network generalizes to complex first-principles and experimental dielectric spectra, extracting the underlying pole parameters with high accuracy in a single forward pass. This approach provides an efficient and robust alternative to conventional nonlinear fitting, enabling high-throughput, automated analysis of dielectric spectra across diverse materials and applications.
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Materials Science
Mode-selective electron-phonon coupling drives charge density waves in the kagome metals YRu$_3$Si$_2$ and LaRu$_3$Si$_2$
Wenqian Tu, Run Lv, Dingfu Shao et al. (+2 more)
YRu$_3$Si$_2$ and LaRu$_3$Si$_2$ host the highest charge density wave (CDW) transition temperatures ever reported in kagome metals, $T_{\mathrm{CDW}}\approx 800$ and 400~K, with propagation vectors $Q_{\mathrm{CDW}}\approx(1/2,0,0)$ and $(1/4,0,0)$, respectively. The microscopic mechanism behind these record values has remained unresolved. Here, we combine anharmonic
phonon renormalization extracted from molecular dynamics driven by a machine-learned force field with mode-resolved electron-
phonon coupling (EPC) analysis to identify this mechanism. The CDW is driven by mode-selective EPC: the Ru out-of-plane
phonon modes couple the Ru-$d_{xz}/d_{yz}$ and Si-$p_x/p_y$ orbitals, and the
phonon linewidth peaks sharply at $Q_{\mathrm{CDW}}$, while the featureless electronic susceptibility rules out Fermi-surface nesting.
Phonon anharmonicity melts the CDW, and the anharmonic
phonon spectra reproduce both $Q_{\mathrm{CDW}}$ and $T_{\mathrm{CDW}}$ in good agreement with experiments. Molecular dynamics simulations also visualize the CDW melting in real space. Chemical bonding analysis further shows that the smaller Y$^{3+}$ radius strengthens the Ru-Ru bonds, enhancing
lattice rigidity and accounting for the factor-of-two higher $T_{\mathrm{CDW}}$ of YRu$_3$Si$_2$. Our results establish a unified microscopic picture of CDW formation and melting in kagome metals YRu$_3$Si$_2$ and LaRu$_3$Si$_2$.
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All authors Wenqian Tu, Run Lv, Dingfu Shao, Yuping Sun, Wenjian Lu
Materials Science
Robust skyrmion nucleation and transport via composition gradient in rare earth-transition metal ferrimagnets
Pietro Diona, Luca Maranzana and Sergey Artyukhin
Magnetic skyrmions are typically nucleated via localized excitation methods, such as
laser heating,
spin-orbit torques, or engineered defects, and their controlled transport is often limited by the skyrmion Hall effect. Here, we demonstrate that spatial gradients in rare-earth–transition-metal
alloys, achievable through patterned
laser writing, enable both deterministic nucleation and controlled transport. The strategy leverages engineered compositional gradient to cross the magnetization compensation point, defining regions with opposite magnetization. An out-of-plane
magnetic field selectively reverses the magnetization, generating a skyrmion. Crucially, the same compositional design enables a channel tuned to the
spin angular momentum compensation point, where skyrmions are driven by
spin-orbit torques at high velocity with vanishing skyrmion Hall effect. Local composition variations act as pinning sites, enabling threshold-controlled trapping and release.
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Soft Condensed Matter
Autonomous thermodynamic cycles via robotic mobility and sensing
Sofia Kuperman, Ezra Ben-Abu, Yaron Veksler et al. (+3 more)
Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these cycles traditionally operate between fixed thermal reservoirs, restricting them to specific locations and temperature differences. Here, we introduce autonomous thermodynamic cycles enabled by robotic mobility and sensing, allowing
robots to perform thermodynamic cycles by accessing spatially varying temperature fields. We experimentally realize this concept using multistable gas-filled capsules that circulate within the system across a thermal gradient. Our model reveals that rapid transitions in the capsules' energy states allow the system to operate as a mobile heat engine that harvests and stores energy. By linking the capsule-scale internal energy dynamics to the
robot's large-scale navigation strategy, we optimize locomotion paths that balance motion cost and energy harvesting. These findings demonstrate that thermodynamic cycles can emerge when autonomous systems navigate their environments, offering an artificial analog of organisms that forage for energy across spatial resources.
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All authors Sofia Kuperman, Ezra Ben-Abu, Yaron Veksler, Anna Zigelman, Sefi Givli, Amir D. Gat