Peer Revenue Publish or profit

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Physics Applied Physics

physics.app-ph Watch Applied Physics

Wednesday 16 September

Applied Physics · Cross-listed from cs.LG

Radio-Frequency Convolutional Neural Networks

Zhihui Gao, Shi-Yuan Ma, Yiran Chen et al. (+2 more)

Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalability, and data privacy, but these devices rarely carry the computing capability that modern neural networks demand. Edge accelerators have been developed in response, yet each adds computing hardware to devices already constrained in size, weight, power, and cost (SWaP-C). An alternative lies in what these devices already carry: the frequency mixer in every wireless radio multiplies signals in time, natively performing convolution in the frequency domain. Here we introduce radio-frequency convolutional neural networks (RF-CNNs), which repurpose existing communication hardware for CNN inference. Multi-channel convolutions are mapped onto frequency tones for a passive mixer to execute in a single pass. We experimentally demonstrate that RF-CNN runs deep CNNs up to 26.4 million parameters and nine layers from classification of wireless signals and images to controllable image generation, close to full-precision performance. Because the weights arrive over the air and the analog hardware is shared with communication, the edge device spends energy only on data preparation and readout-down to 0.72 femtojoules per multiply-accumulate, two orders of magnitude less than it would cost on an added digital processor. These results suggest that deployed wireless infrastructure can bring efficient, state-of-the-art AI inference to the billions of devices it already connects.
Read the full abstract

All authors Zhihui Gao, Shi-Yuan Ma, Yiran Chen, Dirk Englund, Tingjun Chen

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Epitaxial inversion of spontaneous polarization in {\epsilon}-Ga2O3

Yan Wang, Zhigao Xie, Weihua Tang et al. (+1 more)

Polar wide bandgap semiconductors offer the unique capability to manipulate internal electric fields and induce two-dimensional electron gases (2DEG). The emerging orthorhombic {\epsilon}-Ga2O3 is a promising candidate owing to its large spontaneous polarization (Psp). However, exploiting this material is hindered by fundamental ambiguities surrounding its absolute Psp vectors and the inability to govern its epitaxial direction. Here we show the resolution of the absolute Psp vectors in {\epsilon}-Ga2O3 and control of its macroscopic polarity via substrate engineering. By correlating interferometric piezoresponse with atomic configurations, we establish an identification criterion where opposing polarities are assigned through the geometric elevation within an asymmetric four-atom sequence. Guided by this signature, we demonstrate that epitaxy on Al-polar AlN and sapphire yields uniformly Ga-polar (upward Psp) and O-polar (downward Psp) architectures, respectively, whereas deteriorated crystallinity disrupts this registry and triggers mixed-polarity. This atomic-to-macroscopic correlation eliminates long-standing ambiguities regarding absolute polar orientations in non-centrosymmetric oxides. Analogous to mature III-Nitride architectures, this blueprint provides the foundational platform for designing macroscopic polarization discontinuities at heterointerfaces, unlocking {\epsilon}-Ga2O3 for advanced polarization electronics.
Read the full abstract

All authors Yan Wang, Zhigao Xie, Weihua Tang, Chee Keong Tan

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Adaptive Substrate Support Based on Thin-Film Piezoelectric Actuators

Ertuğ Şimşek, Bas Jansen, Marcelo Ackermann et al. (+1 more)

Advanced lithography scanners require extreme substrate flatness in the range of nanometers to prevent focus errors. Such a flatness is challenging to reach and maintain using static substrate supports. Active correction concepts using bulk piezoelectric or linear actuators become prohibitive due to wiring and volume limitations, considering the thousands of pillars required. In this work, we present to our knowledge the first ever demonstration of an active substrate support concept based on thin-film piezoelectric actuators. The working principle, fabrication steps, and characterization of a proof-of-principle device, supported by finite element modeling (FEM), are presented in detail. The fabricated device shows a displacement above 9 nm, which is sufficient to correct some of the focus errors in lithography systems. We foresee that this new concept may open the way towards smaller chip dimensions and improved yield.
Read the full abstract

All authors Ertuğ Şimşek, Bas Jansen, Marcelo Ackermann, Muharrem Bayraktar

Applied Physics · Cross-listed from physics.comp-ph

Braided endovascular implants for intracranial aneurysms: mechanics, hemodynamics, and clinical translation

Ratnadeep Pramanik, Duygu Dengiz, Mariya S. Pravdivtseva et al. (+9 more)

Endovascular implants prevent intracranial aneurysm rupture by altering the mechanical and hemodynamic environment at the aneurysm neck. Yet many in silico workflows prescribe or reconstruct the post-deployment geometry before computing flow, leaving unresolved the mechanics that create the clinically relevant interface. Here we review braided intraluminal flow diverters, intrasaccular devices, and emerging flow-disruption concepts across deployment mechanics, inter-wire and wire-wall contact, superelasticity, wall apposition, pore geometry, computational fluid dynamics, and fluid-structure interaction. We connect these modeling choices to neck coverage, malapposition, migration, deformation, and durability, and distinguish established evidence from mechanistic inference and prospective hypotheses. We argue that model fidelity should match the clinical question: prescribed or fast placement may support screening, whereas questions of coverage, apposition, compaction, and migration benefit from mechanically plausible deployment states. An interface-resolved mechanics-to-flow framework, supported by measurable validation targets and standardized reporting, could improve device design and enable more reliable patient-specific treatment planning.
Read the full abstract

All authors Ratnadeep Pramanik, Duygu Dengiz, Mariya S. Pravdivtseva, Martin Frank, Ivo Steinbrecher, Prasanth Velvaluri, Matthias Mayr, Philipp Berg, Sylvia Saalfeld, Naomi Larsen, Olav Jansen, Alexander Popp

Applied Physics

A Scaling Framework for Mechanical Memristance: Dimensionless Metrics and Material Design Maps

Abdulla Alhembar, Fabrizio Scarpa, Chrystel D. L. Remillat et al. (+6 more)

Mechanical memristors are systems whose dissipative response depends on the history of previous loading through an evolving internal state. History-dependent forces and dissipation occur in a wide range of materials and devices, including viscoelastic polymers, shape-memory materials, piezoelectrics, granular media and field-responsive fluids. Determining which of these responses admits a mechanical-memristor representation requires a constitutive test, as well as a comparison of scales. In this work, a fractional-order mechanical memristor model is developed and cast into a nondimensional form to identify the governing parameters controlling memory-dependent dissipation. The formulation leads to a set of dimensionless groups that characterise dissipation magnitude, memory-state scale and memory transfer. These quantities are combined into an effective mechanical memristance screening index \(\Mh = \beta\gamma |\mathcal H_\alpha(\Omega)|\), which provides a conditional measure of local damping modulation at matched response amplitude, constitutive slope and reference scales. Illustrative parameter scenarios are then constructed for material classes including shape-memory polymers, shape-memory alloys, hydrogels, nanocellulose, lignin-rich materials, natural fibres, piezoelectric polymers, piezoelectric ceramics, electrorheological fluids, magnetorheological fluids and granular dampers. The framework establishes a common basis for comparing memory-dependent damping within the adopted constitutive description and identifies the calibration required for its application to candidate materials and devices
Read the full abstract

All authors Abdulla Alhembar, Fabrizio Scarpa, Chrystel D. L. Remillat, Rodrigo J. da Silva, Ross Anderson, Ludovico Cademartiri, Abderrezak Bezazi, James P. K. Armstrong, Adam W. Perriman

Applied Physics · Cross-listed from physics.optics

Wavelength-Multiplexed Nonlinear Computing with a Single-Layer Diffractive Optical Processor

Yongkang Cheng, Che-Yung Shen, Yuntian Wang et al. (+2 more)

Diffractive optical processors provide a promising platform for high-throughput, low-latency analog computing by exploiting engineered wave propagation to transform optical fields. However, implementing nonlinear mappings in optical hardware remains challenging. Here, we introduce a wavelength-multiplexed encoding-and-decoding (E+D) diffractive processor that exploits multiple illumination wavelengths to enhance the nonlinear function-approximation capability of a compact single-layer diffractive architecture, without cascading multiple diffractive layers or increasing the trainable degrees of freedom. Under sequential wavelength scanning, each wavelength-detector channel implements a distinct nonlinear function at the output of the diffractive processor. Numerical simulations using 100 wavelength channels and 10,000 spatial detector regions at the output of the diffractive processor demonstrate the implementation of one million distinct nonlinear functions through wavelength multiplexing. We also demonstrate a simultaneous multiwavelength illumination configuration in which the E+D diffractive processor performs wavelength-division multiplexing and nonlinear function approximation concurrently. This multiwavelength illumination configuration is experimentally validated by optically implementing 64 distinct nonlinear functions under simultaneous illumination at eight wavelengths from 495 to 635 nm. Through numerical simulations and visible-light experimental demonstrations, our results indicate that this wavelength-multiplexed nonlinear function approximation framework provides a scalable route toward compact, high-capacity diffractive processors for large-scale analog optical computing and optical information processing.
Read the full abstract

All authors Yongkang Cheng, Che-Yung Shen, Yuntian Wang, Shiqi Chen, Aydogan Ozcan

Applied Physics · Cross-listed from physics.ao-ph

Tropospheric Ozone Formation Potential and Related Design Considerations for Radiative Coolers

Jyothis Anand, Piero Di Carlo, Eleonora Aruffo et al. (+2 more)

Recently, radiative coolers have been widely explored for reducing cooling loads or lowering temperatures in buildings, and at urban scales as a heat-mitigation measure. However, the potential impacts of radiative cooler deployment on the chemical composition of the atmosphere remain largely unexplored. A defining feature of recently-designed radiative coolers is their high ultraviolet (UV) reflectance, which is required for sub-ambient cooling under strong sunlight. Yet, wide adoption of such UV-reflective radiative coolers could substantially increase the UV actinic flux in the atmosphere above. This, in turn, may affect tropospheric ozone concentrations, particularly in urban atmospheres with high NOx concentrations. Here, as a case study, we use a 0-dimensional photochemical box model, constrained by field measurements of meteorological conditions and chemical concentrations in the urban environment of Houston, Texas, to explore the potential impact of the widespread use of UV-reflective radiative coolers on ozone concentrations. Our calculations show that complete deployment of radiative coolers may increase tropospheric ozone levels by as much as 30% during specific meteorological conditions in Houston. Informed by the wavelength-dependent modelling results, we propose specific designs, namely pigmented radiative coolers with different UV reflectances, and UV-absorptive visible-reemitting fluorescent radiative coolers, that could minimize negative ozone formation while retaining appreciable cooling performance. Our results motivate further study on the effects of widespread deployment of radiative cooling designs like superwhite roof paints on air quality, and materials that simultaneously minimize adverse photochemical impact and maximize cooling performance.
Read the full abstract

All authors Jyothis Anand, Piero Di Carlo, Eleonora Aruffo, Paul E. Ohno, Jyotirmoy Mandal

Applied Physics · Cross-listed from cond-mat.mtrl-sci

High-performance orbital-torque magnetic memory on the 300-mm platform

Dinggui Zeng, Yang Gao, Jinyu Duan et al. (+24 more)

Contemporary memory technologies are increasingly constrained by the fundamental trilemma of storage capacity, access latency, and power consumption. Among the emerging technologies, spin-orbit torque magnetic random-access memory (SOT-MRAM) shows promise to circumvent these challenges, owing to its fast switching dynamics and high endurance. However, the application of SOT-MRAM is hindered by the relatively low write and read efficiencies, resulting in a large bitcell area and an insufficient sensing margin. Meanwhile, the involvement of an ultrathin spin-source channel, typically within a few nanometers, imposes technological challenges for mass production. Here, we resolve these issues on a 300-mm wafer platform by exploiting the emerging orbital degree of freedom and the resultant orbital torque (OT) from the relatively thick Ti/W bilayer. In particular, OT memory nanodevices exhibit a giant tunnel magnetoresistance (TMR) of 182%, nanosecond-scale response, 1012 endurance, together with an enhanced switching efficiency (E_b/I_c), which consequently enables an ultra-low write energy of less than 0.1 pJ/bit. Our findings demonstrate that orbital angular momentum can be implemented for building energy-efficient MRAM devices, offering a practical pathway towards low-latency memory that is demanded for high-performance computing and AI applications.
Read the full abstract

All authors Dinggui Zeng, Yang Gao, Jinyu Duan, Lei Zhao, Yuhao An, Xing He, Jintao Ke, Yonglong Ga, Shasha Wang, Zhenghui Ji, Muyuan Chen, Hengan Zhou, Xuejie Xie, Enlong Liu, Junlu Gong, Qijun Guo, Yihui Sun, Zejie Zheng, Weiming He, Xiaolei Yang, Fantao Meng, Yaohua Wang, Hongxin Yang, Delin Zhang, Yong Jiang, Wanjun Jiang, Shikun He

Applied Physics · Cross-listed from quant-ph

Rényi and Tsallis information entropies for a harmonic position-dependent mass

Dorcas A. Addo, Daniel Sabi-Takou, Eugene Adjei et al. (+1 more)

In this paper, we study Renyi and Tsallis information entropies for a Hamiltonian system with position-dependent mass confined in harmonic oscillator potential. Gegenbauer polynomials are used to obtain the position eigenfunction of such a system, and the modified Bessel function of the second kind is used to determine the equivalent momentum eigenfunction. By means of probability densities of both representations, we analytically and numerically evaluate the Heisenberg-like uncertainty of this system. Because the Renyi and Tsallis information entropies in position representation are described by integral functionals of the Gegenbauer polynomials, these quantities are much more difficult to calculate. To get around this problem, we evaluate these information entropies at the system s asymptotical limit, which corresponds to the behavior of an undeformed harmonic oscillator. Nevertheless, no approximation method is used to obtain the Tsallis and Renyi information entropies in momentum representation. In both representations, we find that these information entropies approach the Shannon entropy when the entropic parameter alpha-> 1 and are closed to the results of similar models of the literature. Finally, we evaluate the related entropic uncertainty relations numerically to validate the latter obersevations.
Read the full abstract

All authors Dorcas A. Addo, Daniel Sabi-Takou, Eugene Adjei, Latévi M. Lawson

Tuesday 15 September

Applied Physics · Cross-listed from quant-ph

QiT: Quantum-Inspired Transformer for Visual Recognition Task

Badri N. Patro and Vijay Agneeswaran

Quantum machine learning offers a compelling representational perspective: angle-encoded states inhabit Hilbert spaces in which periodic similarities and interactions can be expressed naturally. Realizing this perspective for visual recognition remains difficult, however, because present quantum neural networks are constrained by limited qubit counts, costly circuit simulation and measurement, noise, and unstable optimization on noisy intermediate-scale quantum devices. We investigate whether useful structural ideas from quantum models can instead be realized as scalable classical Transformer operations. We introduce QiT, a Quantum-inspired Transformer for vision tasks with three components: (i) angle-inspired encoding that maps image tokens to learned trigonometric Hilbert-space features analogous to quantum rotation-based state encoding; (ii) self-attention over these periodic features, inducing a classical cosine kernel approximated to quantum fidelity kernels; and (iii) gated multiplicative emulation, a trainable classical surrogate for interaction terms found in variational circuits. All components are differentiable tensor operations, so QiT claims neither quantum computation nor quantum speedup and retains the $\mathcal{O}(N^2D)$ attention complexity of a standard Vision Transformer. Across image-classification benchmarks, QiT is competitive with a matched classical Transformer while avoiding the severe runtime cost observed for a small simulated quantum Transformer. QiT-B reaches 78.3% ImageNet-1K top-1 accuracy with 45.7M parameters and 11.5 GFLOPs. These results position QiT as a scalable baseline for isolating and evaluating quantum-motivated inductive biases in visual recognition.
Read the full abstract

Applied Physics · Cross-listed from cond-mat.mtrl-sci

A Multipolar Approach to Sliding Ferroelectricity

Matthew Dykes

Traditional theoretical treatments of ferroelectricity do not straightforwardly extend to sliding ferroelectrics, which are increasingly-studied layered materials where a switchable electrical polarization is controlled by two-dimensional relative motion of the stacked layers. Therefore, in-depth analyses of the underlying processes which dictate their polarization behavior remain challenging. In this paper, we present a comprehensive approach for identifying the symmetry-adapted microscopic parameters which are responsible for driving the emergence of this polarization. First, we outline our approach, which appeals to group theory arguments and the distortion of Wannier orbital densities to connect macroscopic symmetries to the microscopic electronic distortions which dictate the appearance of ferroelectricity. Then, we illustrate this process by using density functional theory to apply our strategy to honeycomb bilayer systems, including hexagonal boron nitride. In this way, we find that combinations of dipole-like and quadrupole-like distortions of lone pair electron orbitals control electronic reorganization, and by extension, ferroelectricity in such systems.
Read the full abstract

Applied Physics · Cross-listed from quant-ph

Efficiency-Resolved Recovery Dynamics of an Free-Running InGaAs/InP Single Photon Avalanche Detector Operated in Gated Mode

Bruno Santos Souza, Vitor Tavares, Filippo Ghiglieno et al. (+2 more)

Detection efficiency in gated-mode single-photon avalanche detectors recovers gradually after each gate edge, limiting attainable count rates, yet quantitative recovery models exist only for free-running operation. We extract the gated recovery time constant of a free-running InGaAs/InP detector at 1550 nm by sweeping the gate frequency from 100 kHz to 1 MHz and globally fitting count rates across four dead times, requiring neither a pulsed laser nor a time-to-digital converter. The recovery time decreases linearly with detection efficiency, from 301 to 161 ns between 10 % and 25 %, at 9.3 ns per percentage point. We further resolve a periodic count-rate modulation consistent with bias-dependent capacitive gate feedthrough.
Read the full abstract

All authors Bruno Santos Souza, Vitor Tavares, Filippo Ghiglieno, Celso Jorge Villas-Boas, Paulo Henrique Dias Ferreira

Applied Physics

Fast, optimal readout of a tethered optomechanical pressure sensor

Stephen R. Chen, Yiliang Bao, John R. Lawall et al. (+2 more)

We demonstrate a fast readout method for tethered optomechanical pressure sensors. The fast readout method allows mechanical ring-down measurement rates that exceed the total mechanical damping rate $\Gamma_t$. We model the uncertainty of our ring-down measurements with the Cramér-Rao bound, including the effect of thermomechanical noise. Both our data and the Cramér-Rao bound indicate that measurement rates on the order of the mechanical damping rate produce the lowest uncertainty. At low pressures, using the optimal measurement rate allows 10$\times$ faster measurements or 3$\times$ lower uncertainty compared to allowing our sensor to ring down to the thermomechanical noise floor. Our results allow tethered optomechanical pressure sensors to operate at rates comparable to commercially available pressure gauges, removing an obstacle to adoption of optomechanical pressure sensors in industrial settings.
Read the full abstract

All authors Stephen R. Chen, Yiliang Bao, John R. Lawall, Jason J. Gorman, Daniel S. Barker

Applied Physics

Pushing the Dose Limit of Atomic-Resolution Imaging: A 4D-STEM case study of NaCl

Tamazouzt Chennit, Arno Annys, Songge Li et al. (+3 more)

Beam-induced damage fundamentally limits the characterization of beam-sensitive materials by scanning transmission electron microscopy (STEM), since structural information must be recorded before the electron beam irreversibly modifies the specimen. Here, sodium chloride (NaCl) is employed as a model beam-sensitive ionic crystal to investigate beam-induced structural evolution and the low-dose regime in which useful structural information can be recovered prior to significant damage. Four-dimensional STEM (4D-STEM) datasets were acquired at 200 kV using a Timepix3 direct electron detector and reconstructed using real-time integrated centre of mass (riCoM) imaging. We first establish the characteristic damage behavior of NaCl under high electron doses. Across different dwell times and raster scan orientations, damage develops reproducibly into square-faceted voids whose boundaries align with the 100 crystallographic directions of the rock-salt lattice, indicating that the morphology is governed predominantly by the intrinsic crystallography rather than the scan geometry. We then investigate the low-dose imaging regime using dose-fractionated acquisitions. At 130 e-A-2 per frame, normalized cross-correlation with respect to the first frame quantitatively tracks progressive structural degradation and enables the onset of measurable damage to be identified as a function of accumulated dose. A subsequent acquisition at 32 e-A-2 per frame demonstrates that atomic-scale spatial information can still be recovered below this damage threshold. These results demonstrate how dose-efficient 4D-STEM acquisition combined with riCoM imaging can extend the accessible imaging regime of highly beam-sensitive ionic materials while preserving atomic-scale information.
Read the full abstract

All authors Tamazouzt Chennit, Arno Annys, Songge Li, Nicolas Gauquelin, Hoelen L. Lalandec Robert, Jo Verbeeck

Applied Physics · Cross-listed from quant-ph

Portable Vector NV-Diamond Magnetometer for Shot-Noise-Limited, Drift-Free Operation in Unshielded Environments

Annirudh K P, Vinayak Rane, Shradha Atakar et al. (+5 more)

Ensemble nitrogen-vacancy (NV) diamond magnetometers combine high sensitivity with vector-field reconstruction, but practical deployment is limited by errors arising from high-frequency laser noise during short-duration operations and slow-varying gain fluctuations and offset drift during long-term operation. Here, we present an integrated digital architecture for achieving NV magnetometry stability across distinct timescales. A dynamic differential readout continuously balances fluorescence and reference channels to suppress correlated laser noise. Second-derivative Lorentzian lineshape tracking enables in-situ correction of slope variations arising from slow changes in gain and optical excitation. We further identify temperature-induced bias-magnet fluctuations as a dominant source of long-term drift and introduce a magnetic eigenvector transformation that uses the intrinsic response of NV resonances to eliminate these variations. We show, under unshielded ambient conditions, that this architecture achieves an off-resonance noise factor of 1.0 $\pm$ 0.1, matching the fundamental limit with ten-fold suppression of long-term drift, enabling stable, field-ready quantum magnetometry.
Read the full abstract

All authors Annirudh K P, Vinayak Rane, Shradha Atakar, Sanika Joshi, Maheshwar Mangat, Jay Gharat, Siddharth Tallur, Kasturi Saha

Applied Physics · Cross-listed from cs.LG

Can Deep Learning Achieve Cross-Physics Mapping?

Pengfei Zhu, Julien Lecompagnon and Mathias Ziegler

Can deep learning translate physical fields governed by fundamentally different equations? We address this question by introducing Cross-Physics Mapping (CPM), an operator-learning framework for mappings between heterogeneous physical domains. We formulate sufficient conditions for such mappings through compatible latent representations and propose a dimensionless scaling principle that aligns the characteristic evolution scales of the source and target systems without assuming their dynamical equivalence. As a representative test, paired diffusion and wave fields are generated independently from their respective parabolic and hyperbolic equations while sharing the same latent geometry, material heterogeneity, excitation, and dimensionless scale. Seven architectures-ResUNet, DeepONet, Fourier, latent, wavelet, U-shaped, and Galerkin neural operators-are evaluated for both diffusion-to-wave and wave-to-diffusion mappings. The results reveal a strong directional asymmetry. Diffusion-to-wave reconstruction is more challenging because it requires recovering wavefront, phase, and time-of-flight information attenuated by diffusion; U-NO performs best in this direction, achieving a relative $\ell_2$ error of $0.307$ and an $R^2$ of $0.905$. Wave-to-diffusion mapping is considerably more stable, with GNO attaining a relative $\ell_2$ error of $0.154$ and an $R^2$ of $0.935$. Neural operators generally outperform the conventional convolutional baseline, highlighting the nonlocal nature of cross-physics transformations. These findings demonstrate that deep learning can establish useful mappings between distinct physical modalities on a shared latent manifold, while the achievable accuracy remains fundamentally constrained by the direction-dependent information content of the governing physics.
Read the full abstract

Applied Physics · Cross-listed from cond-mat.mes-hall

Generation of pure spin currents via nonadiabatic quantum pumping in an antiferromagnetic chain

Leila Eslami, Fatemeh Bourbour, Somaieh Ahmadi et al. (+1 more)

In this study, quantum spin pumping in an antiferromagnetic chain driven by time-dependent potential is investigated. The aim is to explore the possibility of generating and controlling spin currents in the absence of external bias and to examine the role of exchange field and periodic driving in the separation of spin-up and spin-down currents. The system is described using a tight-binding model, and spin-resolved currents are calculated employing the Keldysh non-equilibrium Green's function formalism. Two time-dependent potentials with a specific phase difference are applied to the two ends of the chain, while the chemical potentials of both electrodes are set equal. The results demonstrate that in the adiabatic regime (low frequencies), the response of the two spin channels is nearly identical. However, as the driving frequency increases and the system enters the nonadiabatic regime, absorption and emission processes of energy quanta become activated, leading to significant differences between spin-up and spin-down currents. The pumped current exhibits strong dependence on the chemical potential, allowing for the control of both magnitude and direction of the spin current through its adjustment. With increasing frequency, the spin current enhances, and parameters can be tuned such that the charge current nearly vanishes while a considerable spin current persists. This finding indicates the feasibility of achieving nearly pure spin pumping without net charge transfer in the antiferromagnetic chain. The results provide a promising perspective for designing spin-pumping devices based on antiferromagnetic systems.
Read the full abstract

All authors Leila Eslami, Fatemeh Bourbour, Somaieh Ahmadi, Santanu K. Maiti

Applied Physics · Cross-listed from physics.optics

Singly resonant InGaP microresonators for efficient, low-threshold second-order nonlinear optics

Yiming Pang, Xuefeng Li, Lucas Wang et al. (+7 more)

Strong $\chi^{(2)}$ interactions at low optical powers are key to scalable nonlinear and quantum photonics. Although doubly resonant microresonators exhibit exceptional efficiencies, they require simultaneous resonance and phase matching of widely separated optical frequencies, making them inherently sensitive to fabrication and operating conditions. Singly resonant cavities eliminate this constraint by resonating at only the fundamental frequency while the second-harmonic field propagates in a single pass, but they have traditionally sacrificed nonlinear efficiency. Here, we demonstrate a singly resonant InGaP-on-insulator microresonator that overcomes this tradeoff. Combining the large $\chi^{(2)}$ nonlinearity of InGaP with high-quality-factor resonators, we achieve efficient and widely tunable second-harmonic generation, broadband quantum-frequency-comb generation, and low-threshold optical parametric oscillation. Unlike conventional centimeter-long singly resonant devices, our millimeter-scale InGaP devices deliver nonlinear performance comparable to, and even exceeding, doubly resonant systems. By overcoming the conventional efficiency-robustness tradeoff of singly resonant devices, this work opens a new route to low-power, broadband, and widely tunable $\chi^{(2)}$ nonlinear and quantum photonics.
Read the full abstract

All authors Yiming Pang, Xuefeng Li, Lucas Wang, Lillian Thiel, Melissa A. Guidry, Joshua E. Castro, Max Meunier, Nergis Mavalvala, John E. Bowers, Galan Moody

Monday 14 September

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Two-Dimensional Materials toward CMOS-Compatible Scalable Quantum Hardware

Mara Lieberegts and Ye Wang

Manufacturability is one of several constraints on developing solid-state quantum processors, along with qubit performance, control, connectivity, cryogenic operation, and fault tolerance. Chemical residues, structural disorder, and non-uniform interfaces introduced during fabrication can compromise qubit coherence. Two-dimensional (2D) materials, with their atomically thin crystals and van der Waals interfaces, offer routes to address some of these challenges. Their concurrent development as next-generation CMOS channel materials motivates an examination of whether relevant processes can be transferred to quantum chips. This Perspective evaluates the opportunities and limitations of 2D materials for CMOS-compatible quantum hardware.
Read the full abstract

Applied Physics · Cross-listed from physics.flu-dyn

A deep dive into Tollmien-Schlichting wave control via passive wall deformations: The battle between local and downstream stabilization, lessons learned, and implications for phononic subsurfaces

H. Yousef, H. Hassan, I. Roy et al. (+3 more)

A decade ago, a landmark study on flow control via subsurface phonons transformed our understanding of fluid-structural interactions, compelling us to reimagine ways by which to suppress boundary layer instabilities. While subsequent investigations have steadily enriched this landscape, several questions remain largely unanswered. The notion of Tollmien-Schlicting (TS) wave stabilization relies on phase-engineered surface interactions, which destructively engage with the wave and impede its growth. Although the fundamental drivers of the phenomenon are established, its granular physics remain insufficiently resolved, particularly as it pertains to directional effects, competing energy production mechanisms, and the precise streamwise locations governing the process. Revisiting this initial vision, we confront these open questions, revealing fresh insights, and establishing broad foundational strokes to guide the next era of investigations. We begin by defining the amplitude and phase criteria of an elastic wall admittance driving perturbation energy changes relative to a rigid wall. The established framework isolates the roles of the work-rate, viscous energy, production, and dissipation in shaping the fluid's response and clarifies how each contributes to the collective outcome. Crucially, we demonstrate how streamwise translation of the interaction surface significantly alters these parameters, revealing critical thresholds at which the control result is fully reversed. Our model identifies specific pathways to sustained TS wave attenuation, and defines the limits of what can be accomplished passively. Finally, we conceptualize a two-dimensional phononic subsurface, whose tailored and disproportional response to the flow in the wall-normal and streamwise directions, brings about the elusive combination of local and downstream stabilization.
Read the full abstract

All authors H. Yousef, H. Hassan, I. Roy, T. Toki, C. Scalo, M. Nouh

Applied Physics · Cross-listed from quant-ph

Probing Residual Noise at a Decoherence Sweet Spot in a $^{28}$Si/SiGe Spin Qubit

Shinwoo Lee, Hanseo Sohn, Jaemin Park et al. (+7 more)

In $^{28}$Si/SiGe spin qubits with micromagnets, the longitudinal stray field gradient transduces charge noise into qubit frequency noise and limits coherence. We compare two neighboring qubits in the same device with 800 ppm residual $^{29}$Si, one near a decoherence sweet spot where the gradient is locally minimized and the other at a position with a larger gradient. At the sweet spot, $T_2^*$ reaches 67 $\mu\mathrm{s}$ and the Carr-Purcell-Meiboom-Gill coherence time reaches 4.6 ms, whereas $T_2^*$ is 5.2 $\mu\mathrm{s}$ at the neighboring qubit. Near 1 Hz, the frequency noise power spectral density at the sweet spot is nearly two orders of magnitude lower than at the neighboring qubit. The magnitude and low-frequency decay of the residual spectrum are compatible with the prediction for $^{29}$Si nuclear spin noise, and the weak interqubit correlation indicates that local noise becomes important for dephasing at the sweet spot. Despite a finite correlation with the charge sensor, sweet-spot operation strongly reduced the transduction of charge noise, bringing the residual frequency noise close to the level predicted for $^{29}$Si nuclear spin fluctuations.
Read the full abstract

All authors Shinwoo Lee, Hanseo Sohn, Jaemin Park, Hyeongyu Jang, Jonginn Yun, Jun Yoneda, Lucas E. A. Stehouwer, Davide Degli Esposti, Giordano Scappucci, Dohun Kim

Applied Physics · Cross-listed from cs.CE

Block-modular grey-box identification of a short-stroke seawater-pump power take-off for wave energy: loss decomposition and multi-regime validation

Mahdi Tayyebati, Amir Hamza Siddiqui, Mian Masoud et al. (+2 more)

Physically interpretable power take-off models support wave-energy development at every stage. For the seawater-pump class, few have been identified on a real machine and validated at the system level. This paper presents a block-modular grey-box model of a short-stroke seawater pump, identified from bench data alone. The pump decomposes into chamber, relief valve, piston seal and tip check valve, each structured by component physics, and the few parameters are identified block by block from terminal pressure, displacement, force and discharged-mass measurements, with a closed-cycle mass balance that decouples the degenerate seal and valve losses and closes to within 1% of the inflow. Over the sinusoidal campaign, the pressure-energised piston seal carries 84% of the lost mass and 97% of the lost energy, and the pump delivers about four-fifths of its input as high-pressure flow. Generalisation is demonstrated rather than assumed. With parameters fixed on ramps and sinusoids, the model reproduces 360 s sea-state records in free run to about 10% of range, captures 80% of several thousand peaks within 5 bar, transfers to a re-sprung valve on cracking strokes once its crack pressure is identified, follows thousand-cycle endurance records that drift below 0.1 bar, and reproduces the force and cycle-mean absorbed power, 0.1 to 5.7 kW, to a 4% median error. A practical-identifiability and uncertainty analysis confirms the terminal data resolve the retained parameters; thirty-seven repeated records set the experimental floor. The result is a compact, physically labelled model for design, energy assessment and model-based control of seawater-pump power take-offs.
Read the full abstract

All authors Mahdi Tayyebati, Amir Hamza Siddiqui, Mian Masoud, Kristian Glejbøl, Christian Berggreen

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Beyond binary at submicron dimensions: crossed-ellipse MTJ free layers as multi-state cells for spintronic crossbars

Arup Ghosh, Ariel Zaig, Colin Ducarme et al. (+3 more)

Spintronic crossbars are promising hardware platforms for energy-efficient neuromorphic computing, but conventional magnetic tunnel junctions (MTJs) are binary, limiting the information density and synaptic precision of each crosspoint. Here, MuMax3 micromagnetic simulations are used to investigate how size and aspect ratio control the switching and remanent-state landscape of crossed-ellipse MTJ free layers, with permalloy as the main model system and CoFeB checks for transferability. At fixed 8:1 aspect ratio, shrinking the device from 16 micron x 2 micron to 80 nm x 10 nm lowers the absolute switching current but raises the switching field from about 11 Oe to about 301 Oe and increases the SOT current density. At fixed major axis 1.6 micron, aspect-ratio tuning produces a low-field four-state regime, while lower aspect ratios stabilize additional remanent states with lower switching fields and current densities. A 1.6 micron x 0.8 micron device exhibits twelve accessible remanent plateaus in its angle-resolved planar Hall response, with the resolved state count depending on both aspect ratio and absolute size. Projected MTJ readout gives multiple electrical levels, while minimum-energy-path calculations show that the twelve configurations are not all thermally independent. Independent MuMax+ calculations reproduce the multistate topology and reveal lower-barrier multistep escape pathways between nominally distant states. These results define a geometry-dependent design window for scalable multistate spintronic crossbar cells.
Read the full abstract

All authors Arup Ghosh, Ariel Zaig, Colin Ducarme, Thomas Coppée, Flavio Abreu Araujo, Lior Klein

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Quantitative control and recording of materials-synthesis processes using an automated experimentation platform

Yusuke Hashimoto, Takaya Muramoto, Hikari Terada et al. (+3 more)

Data-driven materials development requires the collection of large amounts of high-quality materials data. Full autonomy of materials experiments is anticipated, but its technical hurdles are high and its adoption remains limited. In this study, we constructed a simple, easy-to-deploy automated experimentation platform that focuses not on full autonomy but on the reliable automation and quantitative recording of experimental processes. Specifically, commercially available instruments such as robot arms, electric pipettes, web cameras, and an electronic balance are combined, components such as fixtures are fabricated with a 3D printer, and the instruments are operated by control code generated by an AI agent based on a large language model. As a demonstration, we applied the platform to a two-solution mixing experimental system and synthesized ZIF-8, a metal-organic framework. A white suspension phase was observed in the product, and X-ray diffraction measurements confirmed that it was ZIF-8. We also found that its particle size distribution depends strongly on the solution dispensing speed of the electric pipette, which is a parameter that is difficult to control or record in manual operation. This dependence was reproduced in repeated runs, confirming the repeatability of the automated synthesis. This result is a good example showing that the control and recording of process parameters that are rarely quantified in manual work can govern the quality of materials data. All control code, CAD models, and documentation are made publicly available to encourage the spread of laboratory-scale automation of experiments.
Read the full abstract

All authors Yusuke Hashimoto, Takaya Muramoto, Hikari Terada, Harim Song, Yuan Wang, Takaaki Tomai

Sunday 13 September

Applied Physics · Cross-listed from physics.ins-det

A rotation-based Hall-probe magnetic compass

B. Wojtsekhowski, C. Cuevas, R. Dawson et al. (+4 more)

In many physics and space experiments the direction of a magnetic field must be known to one milliradian or better. We have developed a new type of magnetic compass, based on rotation, in which a spinning Hall probe (HP) produces an alternating signal proportional to the component of the magnetic field transverse to the axis of rotation. Aligning the rotation axis so that this signal vanishes gives the direction of the field. The device requires no calibration and is insensitive to electronics drift. A spinning-HP compass was built and used in a recent experiment at Jefferson Lab, where it determined the direction of the 25~G holding field of a polarized $^3$He target to about 1~mrad; the direction of the rotation axis was transferred to the laboratory frame with a laser and a flat mirror attached to the rotor. A second implementation of the rotation approach, a spinning field concentrator (SFC) with a stationary Hall probe, was also built. With 10 seconds of averaging the SFC compass resolves a transverse field of 18~$\mu$G, corresponding to a directional resolution of 70~$\mu$rad in a field of 0.25 G, close to the Earth's field.
Read the full abstract

All authors B. Wojtsekhowski, C. Cuevas, R. Dawson, W. Henry, N. Liyanage, G. Ron, J. Wilson

Applied Physics · Cross-listed from physics.flu-dyn

Topological Flame Bifurcation, Aerodynamic Flashback Margins, and Multi-Pathway NOx Scaling in a 3D Swirl-Stabilized 100% Pure Hydrogen Aero-Engine Combustor

Prashant Suresh Kamble

Burning neat hydrogen in aircraft turbines eliminates carbon emissions, yet rapid reaction rates trigger nozzle flashback hazards and high nitrogen oxide emissions across flight throttles. This study investigates aerothermal holding mechanisms, flashback safety margins, and emission pathways in a dual-swirl combustor across equivalence ratios from 0.55 to 1.00. Three-dimensional simulations combine curvature-corrected shear-stress transport turbulence closure, dual-rate finite-rate and eddy-dissipation chemical kinetics, and discrete ordinates radiation, validated against experimental laser benchmarks using ASME grid standards. Advancing engine throttle triggers a topological flame transition from a faceplate-attached M-flame at lean idle to a lifted V-flame above equivalence ratio 0.895, while wall flashback safety indices consistently exceed 3.42. Nitric oxide emissions transition from water-chaperoned nitrous oxide intermediate reactions at lean idle (28.01 ppm, EINOx = 1.85 g/kg), scaling to 319.21 ppm (EINOx = 35.40 g/kg) at takeoff under thermal Zeldovich dominance, governed by a power-law exponent of 4.92. These findings deliver validated operability limits and establish an accessible workstation-based screening methodology for practical zero-carbon aero-engine combustor development.
Read the full abstract

Applied Physics

A Review of ERA5 Equatorial Wind Data and Impact on a Space Elevator

Blaise Gassend and Jonathan Gassend

This paper uses the ERA5 weather dataset to assess the impact of the wind on an equatorial space elevator. An analytical formulation establishes that the effect of wind on tether inclination and payload capacity can be captured by a single scalar: RMS wind velocity, averaged over air pressure. This formulation clarifies what constitutes excessive wind for a particular elevator and provides a direct link between wind data and elevator design parameters. Analysis of equatorial ERA5 data shows that equatorial wind loading varies strongly with geography with lower values over continents and higher values over oceans, with the majority contribution coming from the lowest 20 km of atmosphere. The data indicate that realistic equatorial winds pose a significant constraint on thin-ribbon elevator designs if align to face the wind. Combining wind and lightning statistics highlights several promising equatorial regions for anchor sites. Finally, the implications of wind loading for elevator design are examined, and several mitigation strategies are discussed to improve survivability and operational payload capacity under realistic wind conditions.
Read the full abstract

Applied Physics

Shape- and Cation-Engineered Ferrite Nanoparticles for Enhanced Theranostic Performance in Ovarian Cancer Tumor-Mimicking Phantom

Bahareh Rezaei, Md Shahriar, Shahriar Mostufa et al. (+5 more)

Magnetic hyperthermia integrated with magnetic resonance imaging (MRI) requires nanoparticles that combine strong heating, T2 contrast, and hemocompatibility after systemic administration. Here, we prepared citrate-stabilized ferrite nanoparticles (Fe3O4, Co0.6Fe2.4O4, Zn0.3Fe2.7O4, and Zn0.35Mn0.25Fe2.4O4) in spherical (8-10.5 nm) and quasi-cubic (9-12.5 nm) forms, along with 35 nm Fe3O4 cubes. By coupling morphology engineering with spinel-lattice cation substitution, we tuned saturation magnetization, coercivity, T2-weighted signal attenuation, and heat dissipation in ovarian tumor-mimicking phantoms under clinically compatible alternating magnetic fields. The 35 nm Fe3O4 cube and quasi-cubic Zn0.35Mn0.25Fe2.4O4 generated the highest phantom temperature rises, whereas smaller spherical particles produced softer heating. All formulations were cytocompatible in SKOV3 cells, with >96% viability at 24 h. However, hemocompatibility distinguished the leading candidates: 35 nm Fe3O4 cubes induced red blood cell deformation despite minimal hemolysis, while 9 nm quasi-cubic Zn0.35Mn0.25Fe2.4O4 showed no change versus PBS up to 1,000 {\mu}g mL-1. Perfusable GelMA models under physiological flow further confirmed biocompatibility. MRI phantoms showed that Fe3O4 cubes produced extended signal voids that may obscure boundaries. Overall, 9.5 nm quasi-cubic Zn0.35Mn0.25Fe2.4O4 is the leading intravenous candidate, combining strong heating, T2 contrast, and hemocompatibility, whereas large Fe3O4 cubes are better suited for localized intratumoral hyperthermia.
Read the full abstract

All authors Bahareh Rezaei, Md Shahriar, Shahriar Mostufa, Karla Mercedes Paz González, Nguyen Thuy Linh Tran, Changxue Xu, Jenifer Gómez-Pastora, Kai Wu

Applied Physics · Cross-listed from cond-mat.mes-hall

Giant second-harmonic generation in few-atomic layer metals

Alessio Zaccone

Quantum confinement restructures the electronic phase space of ultrathin metals, but the resulting density-of-states (DOS) change is not generically large. We show that, within a three-dimensional confinement theory based on the suppression of long-wavelength electronic states, the Fermi-level DOS enhancement on the weak-confinement branch is bounded by $(4/3)^{1/3}-1\simeq10.1\%$. Instead, confinement-induced redistribution of electronic phase space can be strongly amplified by resonant denominators in the second-order susceptibility. A minimal double-resonance closure predicts giant amplification when the film thickness approaches $L_c=(2\pi/n)^{1/3}$, where $n$ is the carrier density, and a dominant optical pathway lies within a dephasing linewidth of resonance. Applied to recent Ag(111) measurements, the theory gives an effective phase-space carrier density parameter $n_{\rm eff}\simeq3.6\times10^{20}\,\mathrm{cm}^{-3}$, a tenfold enhancement of $|\chi^{(2)}|$, and hence the observed $\sim100$-fold increase of thickness-normalized second-harmonic-generation efficiency, together with the observed non-oscillatory thickness dependence.
Read the full abstract

Applied Physics · Cross-listed from physics.optics

Hybrid Nanocone-Nanohole Light Trapping for High-Efficiency Thin-Film Silicon Solar Cells

Nishat Tasnim, Kawshik Nath and Ahmed Zubair

Thin-film silicon solar cells exhibit weak absorption at longer wavelengths of visible light due to their limited optical thickness. To overcome this inherent limitation, a hybrid nanocone-nanohole light-management architecture is proposed by integrating front-surface silicon nanocones with embedded air-filled nanoholes in the absorber layer. The nanocones provide a gradual refractive-index transition that suppresses front-surface reflection, while the nanoholes enhance optical confinement through multiple scattering and internal reflection. The structural parameters are systematically optimized using finite-difference time-domain (FDTD) simulations coupled with electrical device modeling. Under optimized doping conditions and isothermal steady-state operation, the optimized design yields a short-circuit current density of 34.64 mA cm-2, an open-circuit voltage of 0.82 V, a fill factor of 86.27%, and a power conversion efficiency of 24.42%, representing a 17.74% improvement over a comparable nanohole-based design. Furthermore, coupled opto-electro-thermal simulations show that the proposed hybrid nanocone-nanohole structure retains 95.21% of its efficiency under non-isothermal operation up to45 degree celsius, demonstrating excellent thermal stability. These results highlight the potential of the proposed hybrid nanocone-nanohole design as an effective light-management strategy for high-efficiency and thermally robust thin-film silicon solar cells.
Read the full abstract