Today's most accurate clocks are based on laser spectroscopy of electronic transitions in single trapped ions and feature fractional frequency uncertainties below $1\times10^{-18}$. Scaling these systems to multiple, simultaneously interrogated ions reduces measurement times, driving recent advances in multi-ion clocks. However, maintaining state-of-the-art systematic uncertainties while increasing the number of ions remains a central challenge. Here, we report on a multi-ion optical atomic clock with a fractional frequency uncertainty of $5.3\times10^{-19}$ and up to 10 \Sr ions. Ion-resolved state detection enables minimization of position-dependent shifts, with residual effects suppressed below the $10^{-20}$-level. Clock operation with eight to ten ions reduces the measurement time by a factor of 4.8 compared to single-ion operation. A comparison with an established \Yb single-ion clock yields an unperturbed frequency ratio of $0.6926711632159660405(20)$, with a statistical uncertainty of $0.9\times10^{-18}$ and a combined uncertainty of $2.9\times 10^{-18}$. These results demonstrate robust multi-ion clock operation with reduced averaging time and state-of-the-art accuracy.

Acupoint therapy is a core therapeutic method of Traditional Chinese Medicine (TCM), and it requires a high level of expertise and skills to detect acupoints and perform acupuncture and moxibustion. Existing mixed reality (MR)-based training methods often fall short in accurate real-time detection and visualization of acupoints on the hand, limb, or torso of a real person and do not support various techniques of acupuncture and moxibustion. Moreover, evaluation standards and visual guidance with fine details for each step during MR-based training are typically missing. To this end, we propose the MR-based TCM Acupoint Therapy Teaching System (MRATTS)--an MR-based acupoint therapy teaching and training framework. MRATTS is based on a real-time hand, limb, and torso acupoint detection method to accurately track and visualize acupoints on real patients through MR. On top of that, in collaboration with an experienced acupoint therapist, we design a practice method with interactive visual guidance for various acupoint therapy techniques that simulate acupressure, acupuncture (insertion, lifting-thrusting, and twisting), and moxibustion (mild, sparrow-pecking, and whirling). A set of TCM theory-based evaluation standards is formulated within MRATTS to enable the scoring and visualization of the accuracy and proficiency of acupoint therapy. The effectiveness and usefulness of MRATTS are evaluated through a controlled user study and expert feedback. Results of the study indicate that the MRATTS group shows clear improvements in understanding 3D locations of acupoints and proficiency in acupoint therapy compared to control groups.

We introduce the Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Majorana Propagation Eigensolver (ADAPT-VMPE), a quantum-inspired classical algorithm that exploits Majorana Propagation (MP) to produce circuits for approximating the ground state of molecular Hamiltonians. Equipped with the theoretical guarantees of MP, which provide controllable bounds on the approximation error, ADAPT-VMPE offers an efficient and scalable approach for iterative ansatz construction. A theoretical analysis of the computational complexity demonstrates that it is polynomial in both the number of qubits and the number of iterations. We present an in-depth analysis of circuit construction strategies, analyzing their impact on convergence and provide practical guidance for efficient ansatz generation. Using ADAPT-VMPE, we construct up to 100-qubit ansätze for a strongly correlated photosensitizer currently undergoing human clinical trials for cancer treatment. Our results demonstrate that constant overlap with the ground state across system sizes can be reached in polynomial time with polynomially sized circuits.

Nanoalloys (or alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their structure and chemical ordering is rather challenging. Part of this difficulty stems from the lack of information on their metastable and stable structures. Here, we develop a general computational framework to construct a structural chart of nanoalloys using 38-atom AgCu nanoalloys as a model system. Initially, the equilibrium structural distribution is sampled using parallel tempering combined with molecular dynamics (PTMD). Using a machine learning (ML) based approach, the vast number of sampled configurations are classified into various structural classes. This ML approach produces a single three-dimensional map in which all structures and compositions can be visualized and discriminated. Finally, a finite-temperature structural chart is constructed which provides information on the dominant structures across the entire range of compositions and temperatures. In addition, the structural chart reveals significant differences in thermal stability between nanoalloys and bulk alloys. The presented framework provides an effective route to compute and map the vast structural and chemical space of multicomponent nanoparticles, paving the way to the rational design of functional nanoalloys.

Mutation testing is a technique to assess the effectiveness of test suites by introducing artificial faults into programs. Although mutation testing plugins are available for many platforms and languages, none is currently available for Remix-IDE, the most widely used Integrated Development Environment for the entire contract development journey, used by users of all knowledge levels, and serves as a learning lab for teaching and experimenting with Ethereum. The quality and security of smart contracts are crucial in blockchain systems, as even minor issues can result in substantial financial losses. This paper proposes MuSe, a mutation testing plugin for the Remix-IDE. MuSe includes traditional, Solidity-specific, and security-oriented mutation operators. Its integration into the Remix-IDE eliminates the need for additional setup and lowers the entry barrier. As a result, developers and researchers can immediately leverage mutation testing to assess the effectiveness of their test suites and identify potential issues in smart contracts. We provide a demo video showing MuSe: https://www.youtube.com/watch?v=MIFk9exTDu0 and its repository: https://github.com/GerardoIuliano/MuSe-Remix-Plugin.

For G a group, we present a G-graded version of chromatic maps and skein modules and use them to define a 2+1-G-HQFT out of a G-chromatic category. The construction applies to the representations of unrestricted quantum groups at root of unity and recovers the modified Turaev-Viro 3-dimensional invariants.

We develop a notion of exponential motives on general prestacks equipped with a $\mathbf{G}_a$-action, and compare them with Whittaker motives via Gaitsgory's Kirillov model. We then establish foundational results for exponential motives on affine flag varieties concerning Tate motives and t-structures. We use this to prove a motivic Casselman-Shalika equivalence, relating exponential Tate motives on the affine Grassmannian to ind-coherent sheaves on the classifying stack of the Langlands dual group. The decategorification of this equivalence provides a new construction of the Whittaker module for the spherical Hecke algebra which works for arbitrary coefficients, including a generic version.

For a non-decreasing sequence $S = (s_1, s_2, \ldots, s_k)$ of positive integers, a packing $S$-coloring of a graph $G$ is a partition of $V(G)$ into $V_1, V_2, \ldots, V_k$ such that each $V_i$ has pairwise distance at least $s_i+1$. The packing chromatic number (PCN) of a graph $G$ is the minimum $k$ such that $G$ has a packing $(1,2, \ldots, k)$-coloring. The $1$-subdivision of $G$ is obtained by replacing each edge of $G$ with a path of two edges. In 2016, Gastineau and Togni asked an open question whether the $1$-subdivision of every subcubic graph has PCN at most $5$, and later Bre\v sar, Klav\v zar, Rall, and Wash conjectured it is true. Balogh, Kostochka, and Liu proved the first upper bound of $8$, and it was later improved to $6$ by Liu, Zhang, and Zhang. In this paper, we prove that every connected subcubic graph except the Petersen graph is packing $(1,1,2,2)$-colorable. Our result implies a solution to the conjecture of Bre\v sar, Klav\v zar, Rall, and Wash, and answers the question of Gastineau and Togni in the affirmative. Furthermore, our result answers an open question of Kostochka and Liu and solves a conjecture of Liu, Zhang, and Zhang.

Dynamics of open quantum systems with structured reservoirs can often be simulated efficiently with tensor network influence functionals. The standard variants of the time-evolving matrix product operator (TEMPO) method are applicable when the systems is coupled to Gaussian bosonic baths via hermitian coupling operators that mutually commute. In this work we introduce a generalization to cases where the system is coupled to a single reservoir through multiple non-commuting operators, representing the most general form of linear system-bath coupling. We construct a Gaussian influence functional that properly handles Trotter errors arising from a finite evolution time step, thus ensuring convergence for long evolution times. Based on this result, the uniform TEMPO scheme can be employed to obtain a matrix product operator form of the influence functional, enabling efficient simulations of the real-time dynamics of the open system. As a demonstration, we simulate the time evolution of driven two-level emitters coupled to a bosonic lattice at different lattice sites.

In this paper we show that for any poset $P$ that is not an antichain, the number of induced $P$-free families in the Boolean lattice $2^{[n]}$ is at most $ 2^{O(\mathrm{La}^*(n,P))}$, where $\mathrm{La}^*(n,P)$ denotes the the largest size of an induced $P$-free subfamily of $2^{[n]}$. We also obtain related supersaturation results.

A suprathermal population of ions is present in tokamak plasmas due to external heating mechanisms and fusion reactions. These energetic particles (EP) can drive wave unstable, via inverse Landau damping. An example is the energetic-particledriven geodesic acoustic mode (EGAMs). In this work, we perform a systematic gyrokinetic investigation of the EGAM linear and nonlinear dynamics, using the global gyrokinetic particle-in-cell code ORB5. The nonlinear saturation given by the EP redistribution in phase space is characterized by a saturation level scaling quadratically with respect to the linear growth rate. The nonlinear EP dynamics in phase space has also effects on the EGAM frequency. To this extent, we investigate the frequency chirping, and we find that the chirping rate scales linearly with the linear growth rate over a wide range of EP concentrations. This scaling is consistent with the theoretical prediction of Chen-Zonca [L. Chen, and F. Zonca, Rev. Mod. Phys. 88, 015008 (2016)].

We characterize the theta functions for vectors in the imaginary wall in a cluster algebra of acyclic affine type and compute some of their structure constants. One of the structure constant computations can be interpreted as new "imaginary" exchange relations among cluster variables. We show that theta functions in the imaginary wall span a subalgebra of the cluster algebra that we call the imaginary subalgebra, which decomposes as a tensor product of tube subalgebras that are generalized cluster algebras of type C. Our proofs exploit mutation-symmetries of the exchange matrix, an earlier characterization of dominance regions in affine type, and combinatorial models for cluster scattering diagrams of acyclic affine type.

Exciton transport in molecular aggregates is a fundamental process governing the performance of organic optoelectronics and light-harvesting systems. While most theoretical studies have emphasized long-time transport behavior, recent advances in ultrafast spectroscopy have brought into focus the short-time regime, in which exciton motion remains ballistic on femtosecond-to-picosecond timescales. In this work, we develop an analytical framework for short-time exciton dynamics in a one-dimensional lattice subject to both on-site energetic (diagonal) disorder and intermolecular coupling (off-diagonal) fluctuations. Utilizing the reciprocal-space analysis, we derive closed-form expressions for the first and second spatial moments considering both localized excitation and moving Gaussian initial conditions. Our analytical and numerical results show that, while the long-time dynamics are influenced by diagonal disorder, the short-time ballistic expansion is governed primarily by off-diagonal disorder. Crucially, we reveal a synergistic interplay between the average intermolecular coupling and the off-diagonal coupling disorder strength, demonstrating that they contribute equivalently to short-time exciton transport. Moreover, we integrate this generic disorder model with a realistic molecular system within the framework of macroscopic quantum electrodynamics, thereby providing a theoretical foundation for characterizing and optimizing ultrafast energy flow of disordered molecular aggregates in complex dielectric media.

Materials that intrinsically possess both magnetism and topological states represent a key frontier of quantum materials research. Recently, Mn2(Bi/Sb)2Te5 has emerged as a promising candidate for hosting topological surface states coupled with intrinsic magnetic order, making it a potential magnetic Weyl semimetal. In this study, we investigate the magnetic and transport properties of Mn2Sb2Te5 single crystals. The magnetization measurements reveal a spin glass state with field-induced ferromagnetism. Although heat capacity measurement indicates the absence of long-range order, the intrinsic magnetization in Mn2Sb2Te5 significantly affects its electrical properties, as demonstrated by the anomalous Hall effect. This work provides valuable insights into the magnetism and the electronic properties of Mn2Sb2Te5, establishing Mn2(Bi/Sb)2Te5 system as a compelling platform for exploring the interplay between magnetism and non-trivial band topology, enabling emergent quantum phases and novel transport responses not accessible in non-magnetic systems.

Specializing an OS to optimize the performance of a particular application is typically a manual process that requires great expertise. Specialization through configuration lends itself well to automation; however, it is challenging due to the sheer size of the configuration space of modern OSes, the difficulty to quantify that space, the long time it takes to evaluate a configuration, and the large number of invalid configurations. Hence, existing attempts at specializing OSes automatically are limited to switching features on and off to minimize memory consumption or attack surface, and cannot target metrics such as performance. We present Wayfinder, a framework specializing the configuration of OSes completely automatically and without expert knowledge. It can specialize all aspects of an OS configuration (compile-/boot-/run-time) towards any quantifiable performance, resource consumption, or security metric, for an application processing a given workload on a given hardware setup. Wayfinder consists of an automated OS benchmarking platform, and a neural network-based search algorithm driving the specialization process. This is achieved by learning on the fly which configuration parameters and values impact performance the most, and which ones lead to runtime failures. Optionally, a model pre-trained on one application can be reused to accelerate the specialization of related applications. We evaluate Wayfinder on two OSes, four applications, and two target metrics: Wayfinder fully automatically identifies specialized configurations with up to 24% application performance improvement and 8.5% memory usage reduction compared to default configurations. We highlight the benefits of our neural network, reaching good solutions faster than competing approaches (random and Bayesian), and successfully transferring knowledge between related applications.

Motzkin spin chain is a well-known mathematical model with connections to symmetry-protected topological phases, such as the Haldane phase, as well as to concepts in the AdS/CFT correspondence. They exhibit highly entangled ground states that violate the area law and are exceptionally difficult to simulate with conventional numerical methods. Numerical simulations of the Motzkin ground state become further challenging at large system sizes due to their high-dimensional spin structure, rendering it a natural test bed for quantum simulation with ultra-cold systems. Here, we propose a Rydberg-atom based quantum simulation scheme that effectively realizes Motzkin spins using an experimentally accessible set of parameters. We show that the resulting effective Motzkin ground state reproduces the characteristic entanglement scaling and the block-structure properties of the reduced density matrix associated with the ideal Motzkin state. Our results establish a pathway toward a concrete experimental realization of Motzkin spins beyond purely mathematical constructions, opening avenues for exploring other similar exotic non-area-law entangled phases in programmable Rydberg simulators.

Pulsed-gradient spin-echo (PGSE) MRI experiments probe molecular self-diffusion through spin phase accumulation under time-dependent magnetic field gradients. For diffusion confined to cylindrical surfaces, existing analytical signal models typically rely on the narrow-pulse limit, approximate treatments of finite gradient durations, or the Gaussian phase approximation, which become increasingly inaccurate at high diffusion weightings. Here, we derive an exact analytical solution of the Bloch-Torrey equation for diffusion confined to a cylindrical surface under finite PGSE gradients and obtain the corresponding diffusion MRI signal expression valid for arbitrary gradient durations and separations. The derivation is based on a spectral matrix formalism of the Laplace operator in the eigenbasis of the confining geometry. The signal is expressed as a product of non-commuting matrix exponentials, without approximations to the diffusion propagator or the spin phase distribution. We further introduce a reduced real spectral basis exploiting the symmetry of the cylindrical surface, substantially improving computational efficiency. Building on this exact formulation, we develop efficient numerical strategies for repeated signal evaluations, including a Strang splitting approximation of the matrix exponentials and an efficient computation of the spherical mean signal using Gauss-Legendre quadrature. The analytical signal is validated against Monte Carlo simulations over a wide range of cylinder radii and experimental parameters. The accelerated implementations are benchmarked against the exact formulation to quantify accuracy-runtime trade-offs. These results establish a computationally efficient framework for evaluating directional and orientationally averaged diffusion MRI signals in applications requiring large numbers of model evaluations.

We analysis the $\sqrt{s}$-dependent line shapes of the $e^+e^-\to D_s^{+}D_{s1}^{*-}(2536)$, $D_s^{+}D_{s2}^{*-}(2573)$, $ϕχ_{c1,2}$, $K^+K^-J/ψ$, $K_S^0 K_S^0 J/ψ$, and $K^+K^-ψ(2S)$ cross sections measured by the BESIII experiment using the four resonant structures $ψ(4230)$, $ψ(4500)$, $ψ(4660)$, and $ψ(4710)$, by performing a simultaneous $χ^2$-minimized fit. Their masses and widths are obtained. We find that the processes $e^+e^-\to D_s^{+}D_{s1}^{*-}(2536)$, $e^+e^-\to D_s^{+}D_{s2}^{*-}(2573)$, and $e^+e^-\to ϕχ_{c1,2}$ are all dominantly produced via the $ψ(4660)$ and $ψ(4710)$ decays.

The one-way distillable entanglement is a central operational measure of bipartite entanglement, quantifying the optimal rate at which maximally entangled pairs can be extracted by one-way LOCC. Despite its importance, it is notoriously hard to compute, since it is defined by a regularized optimization over many copies and adaptive one-way protocols. At present, single-letter formulas are only known for (conjugate) degradable and PPT states. More generally, it has remained unclear when one-way distillable entanglement can still be additive beyond degradability and PPT settings, and how such additivity relates to additivity questions of quantum capacity of channels. In this paper, we address this gap by identifying three explicit families of non-degradable and non-PPT states whose one-way distillable entanglement is nevertheless single-letter. First, we introduce two weakened degradability-type conditions--regularized less-noisy and informationally degradable--and prove that each guarantees additivity and hence a single-letter formula. Second, we show a stability result for orthogonally flagged mixtures: when one component has orthogonal support on Alice's system and zero one-way distillable entanglement, the mixture remains single-letter, even though degradability is typically lost under such mixing. Finally, we propose a generalized spin-alignment principle for entropy minimization in tensor-product settings, which we establish in several key cases, including a complete Rényi-2 result. As an application, we obtain additivity results for generalized direct-sum channels and their corresponding Choi states.

Industrial deployments increasingly rely on Open Platform Communications Unified Architecture (OPC UA) as a secure and platform-independent communication protocol, while private Fifth Generation (5G) networks provide low-latency and high-reliability connectivity for modern automation systems. However, their combination introduces new attack surfaces and traffic characteristics that remain insufficiently understood, particularly with respect to machine learning-based intrusion detection systems (ML-based IDS). This paper presents an experimental study on detecting cyberattacks against OPC UA applications operating over an operational private 5G network. Multiple attack scenarios are executed, and OPC UA traffic is captured and enriched with statistical flow-, packet-, and protocol-aware features. Several supervised ML models are trained and evaluated to distinguish benign and malicious traffic. The results demonstrate that the proposed ML-based IDS achieves high detection performance for a representative set of OPC UA-specific attack scenarios over an operational private 5G network.

The integration of Generative AI (GenAI) into audio-visual production is often presented as a radical break from past traditions. However, through a sociomaterial and historical lens, this paper argues that GenAI represents a new development in the long-standing negotiation between creative labor and technological possibilities. Moving beyond the limiting framework of human-machine co-creativity, we adopt an STS-based approach to investigate creativity in the making within the Filmmaking industry. We analyze Filmmaking as a distributed process where agency is shared across diverse human experts and non-human actors, showing how technological innovations have historically reconfigured Filmmaking practices long before the advent of AI. The article introduces an analytical taxonomy of GenAI techniques to illustrate how these technologies do not merely "assist" but can actively reconfigure professional roles, production temporalities, and film aesthetics. By linking sociomaterial configurations to aesthetic outcomes, this reframing suggests that AI technologies in Filmmaking should be seen as mediators that could enable new aesthetic possibilities by blurring the boundaries of traditional filmmaking workflows.

Numerous microlensing survey programs have constrained the possibility of dark matter existing in the form of compact objects within the Galactic halo. These constraints on the dark matter fraction were derived under the assumption of isolated, widely separated objects. This work investigates microlensing by primordial black holes (PBHs) organized into clusters. In this scenario, it is necessary to account for both the influence of neighboring PBHs and the collective gravitational potential of the entire cluster, which significantly complicates the microlensing light curve. Events exhibiting such complex light curves elude detection in observational experiments such as MACHO, EROS, OGLE, POINT-AGAPE, and HSC. It is demonstrated that a significant fraction of PBH dark matter (up to 93\% for the models studied) remains undetected in these observational data. However, for all considered cluster models, a substantial population of PBHs still behaves as isolated lenses. Consequently, the clustering of PBHs does not completely eliminate the microlensing constraints on the PBH contribution to dark matter.

In order to quantize systems involving second-class constraints, one should use Dirac bracket instead of Poisson bracket. Furthermore, one can specify a star product in which the term linear in $\hbar$ is proportional to the Dirac bracket. In this way an oscillator system in a deformed fermionic phase space is analyzed and the corresponding energy level and Wigner functions are evaluated according to scheme of deformation quantization. We also study the entanglement entropy induced by the deformation of the fermionic phase space.

Achieving climate neutrality in Europe requires rapid electrification alongside carbon management strategies for residual emissions. Existing analyses of the European energy system often focus on collocated carbon capture and geological sequestration, with limited attention to the interactions among carbon capture and utilization, transport, sequestration, and diverse carbon dioxide removal (CDR) options. Moreover, existing literature focuses on discussing the optimal, neglecting that near-optimal solutions might provide very different system configurations at a marginal higher cost. Here, we integrate afforestation, biochar, enhanced rock weathering, and perennialization into a sector-coupled European energy system model (PyPSA-Eur) clustered to 39 nodes with 750 aggregated time steps. We explore their contributions using a Modelling to Generate Alternatives (MGA) approach. The approach combines minimization, maximization, and random vectors to explore the near-optimal solution space for up to 5% increased total system costs. Our results show that, in a carbon-neutral system, multiple configurations of carbon management options can achieve net-zero emissions with only marginal cost increases. We find that a 5% total system cost increase is sufficient to accommodate the full spectrum from zero to full deployment of the individual CDR options, as well as a wide range of synthetic fuel use across different fuel types. Increased reliance on CDR options offers no clear cost advantage compared to greater utilization of synthetic fuels.

Generative quantum machine learning models are trained to deduce the probability distribution underlying a given dataset, and to produce new, synthetic samples from it. The majority of such models proposed in the literature, like the Quantum Circuit Born Machine (QCBM), fundamentally work on a binary level. Real-world data, however, is often numeric, requiring the models to translate between binary and continuous representations. We analyze how this transition influences the performance of quantum models and show that it requires the models to learn correlations that are solely an artifact of the way the data is encoded, and not related to the data itself. At the same time, structure of the original data can be obscured in the binary representation, hindering generalization. To mitigate these effects, we propose a strategy based on Gray-codes that can be implemented with essentially no overhead, conserves structures in the data, and avoids artificial correlations in situations in which the standard approach creates them. Considering datasets drawn from various one-dimensional probability distributions, we verify that, in most cases, QCBMs using the reflected Gray code learn faster and more accurately than those with standard binary code.

We study the Kondo effect induced by a topological soliton in a one-dimensional Dirac system with the sign-changing mass term. The soliton hosts a localized zero mode whose spatially extended wavefunction leads to a momentum-dependent exchange coupling with itinerant electrons. We show that this structure generates a nontrivial form factor that suppresses high-energy scattering processes, resulting in an energy-dependent effective Kondo coupling. As a consequence, the real-space structure of the soliton directly controls the emergent Kondo scale. This work establishes a mechanism by which topological defects control many-body energy scales through their wavefunction structure, suggesting a general principle for engineering many-body energy scales via topology.

Niobium is a practical material platform for superconducting microwave circuits; however, device-level performance can vary significantly depending on film growth and processing conditions. We compare three epitaxial Nb films grown on $c-$plane sapphire substrates under nominally identical conditions, except for the deposition temperature. To correlate internal quality factors, $Q_{\mathrm {i}}$, with material properties, we combine magneto-optical imaging of magnetic flux distribution with quasiparticle spectroscopy via measurements of the London penetration depth, $λ(T)$. In the low-$Q_{\mathrm i}$ film, there is a lesser ability to screen the magnetic field and an irregular temperature variation of $λ(T)$, implying the existence of localized in-gap states. High $Q_{\mathrm i}$ films show the opposite trend. We conclude that our measurements provide an efficient method for characterizing and optimizing superconducting films for quantum informatics applications.

We introduce a zero-bias superconducting voltage amplifier that harvests energy from a thermal gradient by exploiting negative differential resistance (NDR) in an asymmetric tunnel junction. The device is based on an asymmetric superconductor-insulator-superconductor (SIS) junction with an energy-gap ratio of $Δ_1/Δ_2 = 0.5$, connected in series with a load resistor. Owing to the superconducting bipolar thermoelectric effect, the current-voltage characteristic of the junction exhibits a region of NDR, in which the net current flows opposite to the applied voltage. This mechanism enables voltage amplification in the absence of any external electrical bias, relying solely on the temperature difference between the electrodes ($T_H \simeq 1$ K, $T_B \simeq 20$ mK). Numerical simulations predict a voltage gain of 20 dB, a 1 dB compression point at an input amplitude of 2 $μ$V, and a total harmonic distortion below $-50$ dB. The input-referred noise is approximately 1 nV/$\sqrt{Hz}$, with an associated thermal load on the order of nanowatts. The frequency response is broadband from near DC, with a $-3$ dB cutoff around 180 MHz, set by the RC time constant of the junction. Using Al-, Al-Cu-, and AlO$_x$-based technologies, the amplifier is compatible with conventional superconducting circuit fabrication processes. These findings demonstrate that thermoelectric superconducting junctions can deliver bias-free voltage amplification from near DC up to about 200 MHz, making them promising candidates for transition-edge sensor readout, quantum circuit instrumentation, and low-frequency cryogenic signal processing.

Let $k$ be a field of characteristic $0$ and let $K = k(B)$ be the function field of a geometrically irreducible projective curve $B$ over $k$. Let $A/K$ be a $g$-dimensional abelian variety with $\mathrm{Tr}_{K/k}(A) = 0$. We prove that any $K$-rational torsion point $x$ of $A$ has order uniformly bounded in terms of $g$ and the gonality of $B$. We also prove a uniform lower bound on the Néron-Tate height $\widehat{h}_{A,L}(x)$ in terms of the stable Faltings height $h_{\mathrm{Fal}}(A)$ for any $K$-rational point $x$ whose forward orbit is Zariski dense, proving the Lang-Silverman conjecture over function fields of characteristic $0$.

Explaining the observed charged fermion mass hierarchies points to flavour symmetries inducing a suppression of the lighter species' masses. When the symmetries are global, it is expected that such symmetries are broken by gravity via Planck scale suppressed effective operators. The potential of the spontaneous symmetry-breaking "flavon" field, if the symmetry is discrete, then possesses several minima, with the vacuum-degeneracy lifted by the gravity effects. In such scenarios, domain walls might be generated in the process of symmetry breaking. Due to the bias, however, they potentially annihilate sufficiently before Big Bang nucleosynthesis, avoiding conflict with observations and generating a characteristic contribution to the stochastic gravitational wave background. We discuss whether and how minimalistic supersymmetric and non-supersymmetric realisations of such theories can give rise to observable gravitational waves.