Papers

We provide a theoretical derivation of the Hypergraph Minority Game with Local Hyperedge Payoffs (HMG-L), in which $N$ adaptive agents compete simultaneously in multiple overlapping groups modeled as hyperedges of a static hypergraph $\Hyper=(\Vset,\Eset)$. Each hyperedge constitutes an independent local minority game, and agents accumulate payoffs across all groups to which they belong. We derive the continuum-time limit of the score dynamics, from which we obtain a set of coupled nonlinear stochastic differential equations for the agents' strategy polarization variables. The deterministic drift is shown to derive from a global cost function that generalizes the standard Minority Game Hamiltonian to hypergraph-structured interactions. We perform a sparse-annealed replica analysis of the stationary state for the case of a $k$-uniform, $d$-regular random hypergraph, obtaining the saddle-point equations within the replica-symmetric ansatz, an explicit replicon stability criterion, and Bethe/cavity equations for sparse corrections. The leading sparse-regime transition occurs on a critical surface $\alphacrit(k,d)$, while the globally coupled MG value $\alphacrit\simeq0.3374$ is recovered only in the separate single-hyperedge limit. We derive expressions for the order parameters – global volatility $\sigma^2$, predictability $\theta$, hyperedge frustration $F_e$, and frozen fraction $\phi$ – and discuss their scaling behavior near criticality. The Fokker-Planck equation governing finite-$N$ fluctuations is presented, and the noise covariance matrix is computed from the hypergraph structure. Limiting cases ($k\to N$, $k\to2$, $d\to\infty$) are analyzed in detail, establishing connections to the standard MG, networked MG, and parallel MG models.

Hematologic toxicity (HT) is a major dose-limiting complication of pelvic radiotherapy for cervical cancer. Although radiomic and dosiomic features improve HT prediction beyond dosimetric metrics, their performance is highly sensitive to contour variability, limiting generalizability. We developed a cohort-aware representation-learning framework to address this challenge. We retrospectively analyzed 152 cervical cancer patients treated with pelvic radiotherapy without concurrent chemotherapy. Patients were divided into two cohorts based on the operators performing pelvic bone segmentation. HT prediction models were developed using cohort-specific training, pooled training, statistical harmonization, and a cohort-aware neural network (CANN) that learns shared and cohort-specific representations with contrastive regularization. Performance was evaluated using cross-validation and an independent test set. Cohort-specific models achieved test AUCs of 0.77 and 0.71, outperforming a dosimetry-only model (AUC=0.58). Directly pooling cohorts reduced performance (test AUC=0.64). Statistical harmonization provided limited benefit, while adversarial and correlation-based alignment further degraded performance. CANN achieved the best balance between robustness and generalizability (test AUC=0.72), with ablation studies confirming the importance of cohort-specific representations and contrastive alignment. These results demonstrate that cohort-aware representation learning effectively mitigates contour variability and improves the generalizability of radiomic and dosiomic models for HT prediction.

Machine-learning-accelerated materials discovery has yielded large numbers of computationally stable compounds, yet many remain experimentally unrealized, underscoring a persistent gap between prediction and synthesis. Here, we introduce a hierarchical screening framework that combines PBE-based thermodynamic stability, efficient dynamical-stability screening enabled by universal machine-learning interatomic potentials, and SCAN-based thermodynamic refinement. Applying this protocol to the 894 stable materials previously reported in Sci. Data 9, 302 (2022), we first curate 603 unique structures, of which only 298 remain thermodynamically stable on the complete PBE phase diagrams, demonstrating the critical role of competing phases in stability assessment. Dynamical screening then identifies 166 materials stable under both harmonic-phonon and finite-temperature molecular dynamics criteria, and SCAN phase diagrams further narrow this set to 109. Finally, by combining decomposition enthalpy with chemical-space completeness, we prioritize 25 candidates as high-confidence targets for experimental synthesis. This work provides a practical protocol for translating stability predictions into experimentally actionable synthesis targets, closing a key gap in machine-learning-driven materials discovery.

Why does quantum relative entropy occupy such a privileged role among measures of distinguishability? We show that a single operational principle determines it. If one pair of states can be distinguished at least as successfully as another for every prior, when both are assisted by the same auxiliary pair, acting as a catalyst, a distinguishability measure should assign it no smaller value. Remarkably, for a normalized measure, this requirement singles out Umegaki relative entropy under mild classical continuity and expansibility on uniform distributions: adding impossible outcomes leaves their associated entropy unchanged. Qubit catalysts already suffice. No additivity or quantum continuity is assumed. We also prove that, without auxiliary assistance, respecting binary discrimination dominance uniquely determines the quantum extension of every regular classical divergence, including the Hirche–Tomamichel extensions of classical $f$-divergences. For additive classical divergences, these extensions respect classical catalysis; allowing noncommuting qubit catalysts is what singles out Umegaki relative entropy.

Recent observational studies have suggested that the Sun may be chemically peculiar relative to the majority of solar twins. Here, we re-analyse high-resolution, high signal-to-noise spectra of 79 nearby solar twins using a differential spectroscopic approach and Bayesian framework to test whether the Sun's chemical peculiarity arises from Galactic chemical evolution (GCE) or planetary ingestion. Using the spectroscopic tool Korg, we obtain highly precise, validated atmospheric parameters and abundances for 18 elements, with an average abundance precision of 0.015dex (3.5%). Employing an independent Bayesian indicator, we disentangle GCE and planetary engulfment signatures from other processes influencing stellar composition, including intrinsic abundance scatter. Our results indicate that the chemical peculiarity of the Sun relative to the average solar twin is largely driven by GCE effects, with 62.3$\pm$5.8% of our sample exhibiting abundance patterns well-described by GCE trends. We further identify 2–6 solar twin candidates exhibiting chemical signatures consistent with planetary engulfment that warrant further investigation. These findings reinforce the importance of accounting for GCE effects when interpreting solar twin abundance patterns, and suggest that the Sun may not be chemically peculiar relative to the majority of solar twins.

Non-standard cosmological histories with epochs of early matter domination (EMD) arise in various top-down models of the early universe. Typically, in the latter stage of EMD, temperature decreases more slowly than in a radiation dominated universe because of entropy generation from decay of the species that drives EMD. A time-dependent decay rate can significantly modify this picture and even lead to a period with increasing temperature. We study non-monotonic temperature evolution in a well-motivated scenario of EMD with a time-dependent decay rate that can give rise to multiple first-order phase transitions in both cooling and heating phases. The spectra of the ensuing gravitational waves (GW) exhibit characteristic features such as multiple peaks and a distinct behavior at high frequencies. These features allow us to determine the phase transition temperature as well as the reheating temperature at the end of the EMD. The future GW detectors can therefore provide a probe for the new physics and a window to the early thermal history.

Exploring thermal transport at cryogenic temperatures presents both significant challenges and valuable insights. By uncovering the thermal counterpart of well-known quantum phenomena, researchers investigated fascinating phenomena ranging from the violation of the Wiedemann-Franz law to the quantisation of phonons. One key frontier remains : no existing method can image local heat transport at the nanoscale under cryogenic conditions. In this Perspective, we review the current state state of the art of local heat transport characterisation techniques and highlight their limitations. As a motivation for the development of cryogenic Scanning Thermal Microscopy, we provide five case studies illustrating how this approach could deepen our understanding of exotic quantum phases and enable the emergence of transformative technologies.

Asymptotic zero Arnowitt-Deser-Misner (ADM) mass wormholes, such as the zero-mass traversable Ellis-Bronnikov wormhole, are of great interest for astrophysical applications such as in the galactic microlensing. However, when considered individually, they are unstable to small perturbations. On the other hand, there is a possibility that they can be stable as an interior partner of a traversable glued wormhole obtained by suitably gluing the interior to the observationally relevant massive exterior spacetimes across spherically symmetric thin shells. Although the exterior spacetime has non-zero ADM mass, massless interior partner remains massless sharing the stability of the glued wormhole. The dynamics of the thin-shell then demarcates the stability regions of the glued wormhole that we wish to study here by employing the novel concepts of thin-shell "mass" and of "external force" constraints discovered by Garcia, Lobo and Visser. We shall consider two classes, where the zero ADM mass interior are Kim-Lee wormholes glued to the exterior Schwarzschild vacuum and Reissner-Nordström spacetime respectively. It turns out that the stability regions in both cases are almost similar although the two interior Kim-Lee spacetimes are physically very different, one scalar charged and the other electrically charged. The conditions under which the stability of glued wormholes could be achieved are analyzed in detail.

Bayesian quantum estimation offers a finite-data framework for quantum sensing and metrology, yet a unified geometric formulation for multiparameter Bayes risk has been lacking. We introduce Bayesian monotone metrics by evaluating Petz monotone metrics on the prior-averaged state, providing a Bayesian extension of the full class of statistically meaningful (CPTP) quantum metrics. This framework yields Bayesian quantities, including quantum posterior-mean operators and a quantum Bayesian dual Fisher-information matrix, and it leads to a systematic family of computable lower bounds on the Bayes risk. The resulting bounds naturally incorporate multiparameter measurement incompatibility and, for every monotone metric in the family, we prove a universal dominance over the corresponding quantum van Trees (Bayesian Cramér–Rao) bound. Moreover, we show that optimizing over all operator monotone functions collapses to a one-parameter subfamily, turning the tightest bound into a tractable optimization with a clear geometric interpretation. In representative examples, the optimized bounds are strictly tighter than the Bayesian SLD and RLD bounds. Our results establish Bayesian monotone metrics as a unifying information-geometric perspective on Bayesian quantum estimation, enabling systematic and computable performance limits in multiparameter settings.

Density functional theory (DFT) is widely used to model twisted bilayers, but the accuracy of the local stacking energetics underlying such models remains uncertain. Here, we benchmark the local-registry landscape of bilayer InSe using diffusion quantum Monte Carlo (DMC). DFT predicts that AB, AAr, and ABr stackings, which share the same interfacial Se registry, are nearly degenerate within 1.5 meV/f.u. and exhibit nearly indistinguishable DFT charge-density responses. DMC instead separates these stackings by 8(5) and 41(4) meV/f.u., while the energy difference between the most stable and least stable registries reaches 60(7) meV/f.u.. These large energy separations show that the stacking energetics are not determined by the interfacial atomic motif alone but depend on the full registry and its associated many-body electronic response. More broadly, these results show that DFT-based moiré models can substantially underestimate local stacking-energy corrugation, with direct consequences for predicted structural relaxation, domain formation, and electronic reconstruction in twisted layered materials.

With the data-driven artificial intelligence/machine learning (AI/ML) models having demonstrated their ability to extend the prediction horizon of large-scale weather at a fraction of computational cost of numerical weather prediction models, a pertinent question is, could these models do the same for sub-seasonal to seasonal (S2S) prediction? A key challenge in developing a S2S prediction system is the requirement for a coupled ocean-atmosphere Earth system emulator that can stably simulate the observed intraseasonal and interannual variability with fidelity. In the rapidly evolving field of AI/ML weather models, such a deep learning 3D ocean-atmosphere coupled model has become available, called SamudrACE. With our interest in developing an AI/ML S2S model for Indian monsoon, here we examine the extent to which SamudrACE faithfully simulates Indian monsoon intraseasonal and interannual variability. Compared to observation, we found biases in SamudrACE's simulation of monsoon intraseasonal and interannual variability. Our systematic documentation and analyses of these biases provide a useful benchmark for improving not only SamudrACE but also coupled emulators in general and could fast track the development of a deep learning 3D global S2S prediction system.

With the rapid development of integrated electro-optic and nonlinear optical devices based on lithium niobate (LiNbO$_3$, LN), thermal management is becoming a critical area of focus. However, experimental measurement of thermal transport in stoichiometric LiNbO$_3$ (sLN) remains scarce, and the intrinsic microscopic mechanisms remain to be established. Here, we combine the laser pump-probe technique of frequency-domain thermoreflectance (FDTR) with state-of-the-art machine-learned atomistic simulations to comprehensively investigate thermal transport in sLN. The measured and simulated room-temperature thermal conductivity ($\kappa$) values of sLN agree well, which are orders-of-magnitude lower than that of many classic and emerging semiconductors such as silicon. Furthermore, the temperature-dependent $\kappa$ exhibits a $T^{-\alpha}$ scaling with $\alpha$ near unity, suggesting that thermal transport is dominated by intrinsic phonon-phonon scattering. By comparing sLN with cubic boron arsenide (cBAs) which serves as an ultrahigh-$\kappa$ benchmark, we reveal that harmonic properties are not responsible for the low $\kappa$ of sLN, which feature phonon heat capacity and group velocities that are either higher than or comparable to those in cBAs. Instead, the low $\kappa$ originates from substantially stronger anharmonicity and larger scattering phase space. These two factors collectively suppress phonon lifetimes by 1-2 orders of magnitude, leading to a maximum phonon mean free path of approximately 140 nm. As a result, notable size effects emerge in thin-film sLN below 1 $\mu$m, with $\kappa$ dropping to half the bulk value at 10 nm. Altogether, our findings establish a fundamental understanding of thermal transport in sLN and provide atomistic insights for thermal management in advanced lithium niobate technologies.

3I/ATLAS, the third confirmed interstellar object discovered in the Solar System, provides a unique opportunity for targeted technosignature searches. We report a periodic radio technosignature search toward 3I/ATLAS using the Five-hundred-meter Aperture Spherical Telescope (FAST) L-band multibeam receiver. To search for periodically modulated signals and distinguish center-beam-dominated candidates from multibeam radio-frequency interference, we apply canonical polyadic decomposition (CPD) to the multibeam dynamic spectra. CPD factorizes the multibeam data tensor into a set of separable components, with associated time, frequency, and beam signatures. Candidate components are then selected through periodogram and autocorrelation diagnostics. We find no credible artificial periodic radio technosignature above 0.146 W is detected from the direction of 3I/ATLAS. This search expands the range of signal types explored for this target by including periodic modulated signal, and illustrates that CPD is a promising framework for multibeam periodic technosignature searches.

Substrate-agnostic perspectives are currently attracting increased attention. For example, it has become customary to refer to agnostic biosignatures to reflect the range of alternative extraterrestrial biospheres and to account for the deeper philosophical dependence of candidate biosignatures on the underlying theory of life. Analogously, one can formulate a concept of agnostic technosignatures, reflecting that the more we expand the search for technosignatures, the more we invite theories of technology that undo the terrestrial bias. For this reason, this paper argues that there exists a strong theoretical justification for an integrated study of technosignatures and biosignatures, articulated in a unified perspective on substrate-agnostic ecologies. The paper introduces the concept of substrate-agnostic ecology as an abstraction unconstrained by terrestrial circumstances, anchored instead in a functional understanding of agent-ecology coupling provided by niche construction theory.

Numerical modeling of aortic valve dynamics is essential for understanding the complex fluid-structure interaction (FSI) governing valve biomechanics in health and disease. Immersed methods provide a flexible computational framework for simulating the large deformations of valve leaflets and associated blood flow without requiring body-fitted meshes. Among these approaches, the Resistive Immersed Surface (RIS) and Immersed Boundary (IB) methods are widely used. However, systematic comparative analysis of these methods for realistic aortic valve simulations has not been performed. In this work, we compare a prescribed-kinematics RIS workflow implemented in SimVascular's svMultiPhysics solver with a fully coupled IB workflow using IBAMR for trileaflet and bicuspid aortic valve configurations. The RIS method represents the valve as a surface with prescribed kinematics embedded in the fluid domain and introduces a penalty force that drives the surrounding fluid velocity toward the prescribed leaflet velocity. This formulation reduces modeling complexity and provides useful hemodynamic predictions when representative leaflet kinematics are available. In contrast, the IB method models the leaflets as elastic structures fully immersed in the fluid domain and resolves leaflet deformation through fully coupled two-way FSI. The study focuses on the extent to which RIS reproduces bulk hemodynamic features and transvalvular pressure gradients. Results show that the RIS method captures the large-scale flow structures and predicts the mean transvalvular pressure gradient with a relative error within 15% of the fully coupled IB simulation, improving to within 5% when inlet boundary conditions are matched, while reducing computational cost by approximately 60%.

The NSF-DOE Vera C. Rubin Observatory will generate petabytes of data through the Legacy Survey of Space and Time (LSST) over the next decade, enabling discoveries across a broad range of astrophysical fields. Alongside these data products, Rubin maintains a large but heterogeneous collection of supporting documentation, including operational guides, technical notes, and scientific papers. Because this material is distributed across multiple platforms and formats, staff and scientists often struggle to efficiently locate accurate, up-to-date information. Many resources also reside on internal systems, limiting the ability of general-purpose language models to provide reliable answers to Rubin-specific questions. To address these challenges, we explore the use of Retrieval Augmented Generation (RAG) to improve information discovery. We present a prototype RAG-based virtual assistant that delivers context-aware, factual, conversational access to Rubin's vast and heterogenous documentation ecosystem. The system integrates material from multiple sources and enables semantic search through a conversational interface, using Weaviate for embeddings, LangChain for query orchestration, and an OpenAI GPT model as the LLM backend. By grounding responses in domain-specific knowledge, the assistant reduces hallucinations, improves accuracy, and demonstrates the potential of RAG to enhance access to distributed knowledge, streamline workflows, and support effective use of LSST data products.

The efficient preparation of correlated thermal states, such as the Thermofield Double (TFD) state, is a fundamental prerequisite for simulating quantum gravity models and many-body thermodynamics on quantum processors. In this work, we investigate the ground state preparation of the Two Coupled Sachdev-Ye-Kitaev model, known as the Maldacena-Qi model, which is dual to a traversable wormhole in $AdS_2$, utilizing feedback-based quantum algorithms. We demonstrate that the standard feedback-based quantum algorithm (FALQON) and its time-rescaled variant (TR-FALQON) face severe kinetic limitations in this system, failing to converge to the highly entangled ground state when initialized in trivial product states. To overcome these barriers, we propose the hybrid ITE-TR-FALQON protocol, which integrates the imaginary-time evolution present in imaginary-time-enhanced FALQON (ITE-FALQON) with the time-rescaling mechanism. Our numerical results indicate that the introduction of non-unitary dynamics is strictly necessary to break symmetry traps and filter out excited states, while time-rescaling drastically accelerates algorithm convergence. The proposed method achieves fidelities close to unity and reproduces the von Neumann and Rényi entropy spectra of the exact TFD state with high precision.

This article describes a dataset of total (spectrally-integrated rather than wavelength-dependent) emissivity values pertaining to gaseous media containing carbon dioxide (CO2) and/or water vapor (H2O) with the sum of their partial pressures being near the atmospheric level. These conditions may be particularly relevant to flue gases resulting from oxy-fuel combustion. The emissivities here are computed using the EM2C implementations of the statistical narrow band (SNB), and they are made conveniently available as 10 separate plain text files having a unified layout. Each data file in the dataset corresponds to a specific chemical composition (from pure CO2 to pure H2O), with eight intermediate H2O:CO2 molar ratios being 1:20, 1:8, 1:4, 1:2, 1:1, 2:1, 5:1, and 20:1. In addition, pure CO2 corresponds to the extreme lower-bound for the H2O:CO2 molar (as 0:1), and pure H2O corresponds to the extreme upper-bound for the H2O:CO2 molar ratio (1:0 or infinity). For each chemical composition, the total emissivity values are provided for different pressure-pathlengths and different absolute gas temperatures as two independent variables. The pressure-pathlength range spans about three orders of magnitude, from 0.01 atm.m to 50 atm.m, with 90 nonuniformly-distributed pressure-pathlength values. The absolute gas temperature spans a wide range from 300 K (room temperature) to 2900 K (high-temperature flames) with a uniform step of 25 K separating 105 temperature values. For each data file, there are 90 x 105 (9450) emissivity values; and the entire dataset contains 94500 emissivity values.

Joint full waveform inversion (FWI) of distributed acoustic sensing (DAS) and ocean-bottom node (OBN) data typically requires converting measured strain to particle velocity, introducing numerical noise and spectral distortion. To eliminate this, we present an elastic multi-parameter FWI framework using a velocity-stress-strain (VSS) formulation that directly models pressure, particle velocity, and gauge-length-averaged DAS strain from a single forward simulation. Data residuals are injected additively into a single backward simulation, making computational cost independent of the active sensor subsets. We benchmark individual and combined datasets on cross-talk and elastic Marmousi models. Our results show that joint inversion recovers elastic parameters more accurately than single deployments when the sensors offer complementary information. Specifically, pairing two-component geophones with a deviated borehole DAS cable yields the most accurate parameter recovery and mitigates inter-parameter cross-talk by providing a distinct physical observable and complementary depth aperture. We release our implementation as xFWI, an open-source, Devito-based Python package for scalable, multi-deployment inversions.

Using magnetohydrodynamic (MHD) fields and guiding-center test-particle calculations, this study investigates how time-dependent loop-top dynamics modulate the adiabatic energization of electrons in a solar flare. Our results indicate that a time-varying loop-top structure enhances acceleration efficiency compared to a quasi-steady one. In the quasi-steady velocity field, the net acceleration is suppressed due to the decelerating effect of betatron cooling. Conversely, in the unsteady velocity field, the betatron mechanism readily accelerates electrons within the compressed magnetic field at the edge of the loop-top. These findings suggest that the acceleration of electrons at the loop-top is driven not only by the static shape of the magnetic structure but also by dynamic events such as plasmoid collisions. While previous studies have primarily focused on acceleration processes within the reconnection outflow, such as at termination shocks or within plasmoids, our research highlights the importance of the acceleration and deceleration processes at the exit point where electrons escape from the loop-top.

We prove the existence of weak solutions to the surface Beris-Edwards model for nematic liquid crystals posed on a $d$-dimensional ($d \in \{2,3\}$) closed hypersurface of class $C^{2,1}$. This thermodynamically consistent model, recently introduced by Bouck, Nochetto and Yushutin (2024), couples the incompressible tangent Navier-Stokes equations with a kinematic equation for the Q-tensor field that encodes the orientation of the liquid crystal particles with a general state of orientational order. Extending ideas by Abels, Dolzmann and Liu (2014) and Guillén-González and Rodríguez-Bellido (2015) for the Beris-Edwards model in flat domains, we design a Faedo-Galerkin scheme based upon eigenfunctions of an appropriate tangent Stokes operator and tensor-valued Laplace-Beltrami operator and recover a weak solution via standard compactness arguments.

The production of $\Lambda_c^+$ baryons in Pb+Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV is investigated within the quark recombination framework, including the energy loss of light and charm quarks inside the hot and dense medium. The model simultaneously describes the transverse momentum ($p_T$) spectra of $\Lambda_c^+$ baryons, $\Lambda_c^+/D^0$ yield ratio, which is attributed to the dominance of quark recombination mechanism in the Quark-Gluon Plasma (QGP), and the second harmonic coefficient of $\Lambda_c^+$ baryons with emphasis on the effects of minijets on the azimuthal anisotropy. Furthermore, we extend the theoretical calculation to Pb+Pb collisions at $\sqrt{s_{NN}} =2.76$ TeV and make predictions for $\Lambda_c^+$ baryons and $\Lambda_c^+/D^0$ yield ratio. The simultaneous description of the yield, baryon-to-meson ratio, and azimuthal anisotropy further validates that the recombination model is an effective hadronization mechanism in heavy-ion collisions.

In this paper, we suggest a chiral interaction scheme to enhance magnon bundle emission by placing a qubit and a magnon into a cascaded-cavity setup, respectively. It is found that the unidirectional interaction prolongs the lifetime of the target excited state, thereby suppressing the magnon re-excitation and promoting both the average purity and number of two-magnon bundles. Consequently, the chiral interaction not only offers directional control but also improves the quality of the multi-magnon source, which may find potential applications in quantum information processing.

We introduce the design of the t0.technology Control and Readout System (CRS) F-Engine that will be used for the Canadian Hydrogen Observatory and Radio transient Detector (CHORD), a new radio interferometer currently being commissioned at the Dominion Radio Astrophysical Observatory (DRAO) in Canada. The CRS F-Engine will directly digitize and channelize 1024 individual RF signals from the 512 dual-polarized dishes of the core array using an array of 128 CRS boards, a multi-purpose microwave readout platform using an AMD Zynq Ultrascale+ RF-System-on-Chip (RFSoC) architecture. The CRS supports the required analog and digital signal processing and is appropriately scalable, with rack-mountable crates each supporting up to 16 CRS boards, equipped with a backplane for distribution of power, common clock and time synchronization signals, and a full-mesh network for intra-crate data transmission. Implemented on the CRS boards is the chFPGA firmware which supports the digitization of 8 analog signals at 3.2 GSPS and channelizes them with a CASPER-based PFB/FFT into 8,192 frequency bins with ~195 kHz of resolution, which are then re-quantized into (4 + 4i) bits for data offload to an external X-Engine. chFPGA supports multiple post-channelization signal processing options through separate bitstream files for different applications, such as a 100 GbE packet assembler-transmitter for CHORD to feed channelized data to its external GPU-based X-Engine, as well as FPGA-based N^2 correlators, including a single-board (N = 8) correlator (the “Pocket Correlator"), and a multi-board corner-turn engine coupled with a half-CRS crate (N = 64) correlator. We demonstrate the performance of chFPGA by injecting a wideband Gaussian noise source into a CRS board running the Pocket Correlator firmware, and find that recovered digitized timestream and channelized data are in excellent agreement with expectations.

The quantum Kramers-Wannier (KW) duality is a fundamental transformation mapping short-range entangled (SRE) states to long-range entangled (LRE) states. While spatially local unitary circuits require linear-in-system-size depth to implement this duality, the ultimate speed limit for purely unitary circuits equipped with nonlocal connectivity remains an open question. Here, we explicitly construct logarithmic depth, spatially nonlocal unitary circuits that realize the exact $\mathbb{Z}_2$ KW dualities in both one and two spatial dimensions. We further generalize the construction to arbitrary $\mathbb{Z}_n$ KW dualities. Unlike algorithms tailored to prepare specific target states, our circuits implement complete duality maps. Within the symmetric (charge-neutral) sector, these dualities exactly transform arbitrary non-fixed-point SRE states into their corresponding LRE duals. Consequently, our results establish an efficient, purely coherent pathway for exploring phase transitions and topological dualities on modern quantum platforms.

Two-dimensional transition metal dichalcogenides (TMDs) have emerged as promising materials for spin–orbitronics owing to their strong spin–orbit coupling and rich electronic phases. However, their orbital transport properties remain largely unexplored. Here, we demonstrate that the orbitronic response of $\mathrm{MoTe_2}$ is governed by a thickness-driven structural phase transition. RF-sputtered $\mathrm{MoTe_2}$ thin films exhibit a crossover at a critical thickness of approximately $4.5\,\mathrm{nm}$, stabilizing in the metallic $1T^\prime$ phase below this threshold and in the semiconducting $2H$ phase above it. Raman spectroscopy and scanning tunneling spectroscopy (STS) confirm the structural and electronic transition, revealing gapless behavior in ultrathin films and a finite band gap in thicker samples. Spin-pumping measurements detect an additional transverse charge-conversion signal exclusively in metallic $1T^\prime$-$\mathrm{MoTe_2}$, in agreement with first-principles calculations that identify a dominant orbital Rashba–Edelstein response as the underlying conversion mechanism.

We show that exchange symmetry in collisions of identical particles enables symmetry-protected coherent control of the total scattering cross section. For identical fermions, antisymmetrization enforces a common control phase among contributing channels within a given parity sector, yielding maximal control visibility. For identical bosons, phase-locking persists but with reduced visibility due to additional exchange (satellite) contributions. Collisions of distinguishable particles lack this symmetry-imposed phase-locking, leading to lower controllability and visibility. We elucidate these principles through coupled-channel quantum-scattering calculations for lithium-lithium collisions, comparing the $^{6}\mathrm{Li}{-}^{6}\mathrm{Li}$ (identical fermions), $^{7}\mathrm{Li}{-}^{7}\mathrm{Li}$ (identical bosons), and $^{6}\mathrm{Li}{-}^{7}\mathrm{Li}$ (distinguishable) systems. Furthermore, in the identical-particle cases, symmetry-enforced phase-locking enables full control over the parity of the final state even beyond the ultracold regime. This mechanism is broadly applicable to identical-particle collisions, including homonuclear molecules for which established approaches–DC electric fields or microwave shielding–are ineffective or unavailable.

All-optical (AO) microwave-free magnetometry using nitrogen-vacancy (NV) centers in diamond simplifies experimental design and broadens sample compatibility. While continuous-wave (cw) detection of AO photoluminescence (PL) changes is commonly employed, its performance is susceptible to systematic fluctuations such as optical intensity noise. To address these challenges, we introduce a pulsed AO protocol that employs two PL measurements within an optical pulse to suppress common-mode noise. At near-zero magnetic field, we experimentally demonstrate that the pulsed AO protocol resolves AO-PL contrast features arising from NV-NV cross-relaxation, achieving up to 10$\times$ improvement in the low-frequency noise floor compared to conventional cw AO techniques. We further investigate the dependence of AO-PL contrast on PL readout timing and the dark time duration $\tau$ between optical pulses, with the optimal $\tau$ varying based on NV concentrations. These findings provide insights into optimizing NV-diamond samples for effective AO operation across diverse applications.

Since the complexity of quantum state tomography (QST) scales exponentially with system size, exploiting priors such as low-rankness, tensor-network structures, and neural-network representations is essential for scalable QST in terms of sample complexity and parameter complexity. In this paper, we introduce a unified framework, termed structured factorization, that builds on BurerMonteiro-type factorization by parametrizing the density matrix as $FF^\dagger$, where the factor $F$ is constrained to belong to a structured model class. This factorization guarantees physical validity by construction while allowing a broad range of structural priors to be incorporated directly through the choice of the factor space, ranging from the generic Cholesky decomposition to low-rank matrices, matrix product operators, and neural density operators based on multilayer perceptron and transformer architectures. Building on this structured factorization framework, we formulate QST as an optimization problem over the factor space from measurement data. We first develop a unified statistical analysis of the sample complexity of least-squares estimation for a broad class of structured quantum states. We then propose a projected gradient descent method that operates directly on the factor space and accommodates a wide range of structural parametrizations and reconstruction objectives. To further exploit the geometry of the maximum-likelihood estimation formulation and the constraints on the factors, we derive a power method that yields a step-size-free algorithm with fast convergence, recovering Covers method as a special case when the factor is unconstrained.

X-ray interband time lags are key diagnostics of jet physics and are frequently detected in high-frequency peaked BL Lac (HBL) objects at different epochs with various X-ray telescopes. In this work, we theoretically investigate Fourier lag-frequency spectra using a generic one-zone leptonic model incorporating the stochastic turbulent acceleration (STA), which plays a crucial role in shaping the emitted photon spectra. We demonstrate that the competition between STA, radiative cooling, and escape processes not only gives rise to two well-defined time-lag regimes: hard/positive and soft/negative lags, but also reveals the existence of a transition between the two regimes. Our results indicate that time lags in the transitional and soft-lag regimes can be clearly amplified and modified by STA's suppression of high-energy electron cooling, and nonlinear synchrotron self-Compton (SSC) cooling can further amplify the emergence of time lags. We conclude that the adopted model offers a unifying quantitative framework for interpreting the diverse time-lag signatures observed in the X-ray flares of HBLs. Additionally, SSC cooling effects can account for the relatively large lags observed in TeV-bright flares, as well as the observed trend between lag amplitude and flare duration: the larger the flare duration, the larger the lag.