Human-Computer Interaction
Beyond Counting Blessings: Tracing the Evolution of Gratitude Practices and Technology Needs
Joy Qiuyue Zhong, Jeongah Lee, Drishti Goel et al. (+4 more)
Gratitude technologies support well-being by prompting reflection on what people appreciate. But gratitude does not serve the same purpose in every circumstance: as life situations change, so does what people seek from it, and whether it feels appropriate at all. To understand how technology can adapt to and support such shifts, we conducted retrospective, artifact-elicitation interviews with 17 adults who had practiced gratitude for one to fifteen years. Participants' appraisals of their situations shaped what they needed, yielding six recurring practice patterns, including a boundary where gratitude felt forced. We contribute the Adaptive Gratitude Practice Model, which explains how appraisals shifted even within the same life situation, how participants adapted activities, modalities, and rhythms, lapsed under competing demands or emotional unreadiness, and resumed when gratitude again felt useful. Additionally, we derive design implications for situated support, self-understanding through past records, and relational care with changing life situations.
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All authors Joy Qiuyue Zhong, Jeongah Lee, Drishti Goel, Violeta J. Rodríguez, Dong Whi Yoo, Koustuv Saha, Ravi Karkar
Solar and Stellar Astrophysics
Orbital and stellar parameter determination of eclipsing $\beta$ Cep pulsators
C. I. Eze, G. Handler, F. Kahraman Aliçavuş et al. (+2 more)
Eclipsing binaries provide precise constraints on
stellar properties and
evolution, making those hosting $\beta$ Cep pulsators particularly valuable for characterising massive pulsating
stars. In this paper, thirteen eclipsing binaries with massive primary components are spectroscopically and photometrically analysed to derive the orbital and
stellar parameters, and infer their possible evolutionary status. The systems were spectroscopically observed using SALT HRS, HERMES, CHIRON and a spectrograph at Skalnate Pleso Observatory (SPO), and photometrically observed using TESS. Radial velocities and atmospheric parameters are determined, binary systems are modelled, and their absolute parameters are derived using appropriate modelling tools. The rotational properties, circularisation, and synchronisation of the systems are also investigated, and the general properties of the sample are discussed. The sample shows one slow rotator, two circularised and synchronised fast rotating systems, as well as five circular and five eccentric systems with asynchronous fast rotation. The systems are predominantly SB1 or SB2 with faint companions, resulting in dynamical mass estimates at $5$ – $12\%$ precision and radius estimates at $1.5$ – $3.9\%$ precision. The secondary components appear to cut across a wide mass spectrum ranging from low-mass to intermediate mass systems. The eccentricity of the systems shows certain trends with the projected rotational velocity ($v \sin i$) although there is no universal correlation between them. Also, there could be circularisation without co-rotation or synchronisation even for circularised short-period close binary systems.
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All authors C. I. Eze, G. Handler, F. Kahraman Aliçavuş, T. Pawar, P. De Cat
Analysis of PDEs
Quantization for Palais-Smale sequences of the Liouville functional on closed surfaces
Andrea Malchiodi, Francesco Malizia and Luca Martinazzi
In this paper we prove a quantization property for Palais-Smale sequences of functionals related to Liouville equations on compact surfaces. While these equations have been extensively studied over the past decades, such a quantization property had not been established so far, and has been often bypassed by the Struwe monotonicity trick. Our result, which relies on careful $L^p$ estimates to obtain gradient bounds and to perform neck analysis, allows to directly apply variational methods to obtain existence of solutions in non-resonant regimes. We also give an example of clustering of blow-up points and a stronger assumption that, on the contrary, guarantees that the blow-up points are isolated.
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High Energy Physics (Experiment)
Search for resonant and nonresonant production of pairs of dijet resonances with b jets in the final state in proton-proton collisions at $\sqrt{s}$ = 13 TeV
CMS Collaboration
A search is presented for pair-produced dijet resonances of identical mass, each decaying into a bottom (b)
quark and a light-
flavor quark. The search uses a data sample corresponding to an integrated luminosity of 136 fb$^{-1}$ collected with the CMS detector in
proton-
proton collisions at $\sqrt{s}$ = 13 TeV. Results are presented separately for nonresonant production and for the case where the four-jet production proceeds via an intermediate resonant state. Upper limits are reported on the production of four-jet and dijet resonances with b jets in the final state. This is the first LHC search for resonant production of pairs of fully resolved dijet resonances with b jets in the final state, in which all resonances considered correspond to non-standard-model states. For nonresonant production, the most significant excess occurs at an average dijet mass of 1.0 TeV, with a local significance of 2.1 standard deviations. Additionally, the results exclude pair production of top squarks with masses between 0.5 and 0.8 TeV, extending previous searches for $R$-parity-violating decays to strange and b
quarks. In the search for resonant production, the most significant excess occurs at a four-jet resonance mass of 3.1 TeV and a dijet resonance mass of 1.3 TeV, with a local significance of 2.6 standard deviations. The results are also used to set limits at 95% confidence level on the diquark-to-diquarks model and exclude the heavier diquark masses between 2 and 7 TeV.
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Machine Learning
The Weight Is Over - Interactive Diffusion on Consumer GPUs
Frieder Ganz and Maximilian Müller
On-device inference is booming, but the momentum is almost all in
language models.
Diffusion pipelines are
memory hungry, latency-sensitive, and require orchestrating an embedder, a
transformer, a decoder, and often further postprocessing that is not as standardized as LLM inference loops are. We navigate the trade-off between performance, quality, and model footprint to reach as many client devices in the wild as possible. We make three contributions: an
embedding translator that maps a small text encoder into a large encoder space to cut weight and latency; a reproducible sweep recipe for navigating the speed/quality/
memory triangle in
diffusion pipelines; and an interactive on-device image generation editor achieving sub-second TTFI on recent GPUs.
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Distributed Computing
Distributed Balanced Butterfly Counting in Signed Bipartite Graphs
Kiran Mekala, Apurba Das and Suman Banerjee
The balanced butterfly is a fundamental primitive for analyzing signed bipartite graphs and provides a basis for studying higher-order structural properties, such as clustering coefficients and community structure. Despite its importance, existing approaches primarily rely on serial
algorithms for balanced butterfly counting, which become inefficient on large-scale graphs. To address this limitation, we propose a distributed
algorithm, D-BBC, based on a hybrid MPI+TBB framework that exploits MPI for inter-process communication and Intel TBB for intra-node parallelism. We conduct an experimental assessment of the proposed approach across 15 real-world
datasets. Experimental results demonstrate that, on a single-node distributed system, D-BBC achieves average speedups of 1321x and 16.2x over the serial BB2K and multi-core M-BBC implementations, respectively. Furthermore, D-BBC achieves a maximum speedup of 23.58x over the distributed baseline S-Monarch in terms of end-to-end execution time. These results demonstrate the efficiency of the proposed distributed approach and its potential to enable high- performance signed motif analysis on large-scale bipartite graphs.
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High Energy Physics (Phenomenology)
ALP Distributions from Hadron Structure
Shuai Zhao
We investigate how
hadron structure and
quark-
flavor couplings shape
axion-like particle (ALP) radiation in
hadron collisions. For the elastic pole, the virtuality integral is ultraviolet finite at fixed momentum fraction if the pseudoscalar form factor falls as a positive power of $1/Q^2$ at large $Q^2$, eliminating the point-particle beam-energy logarithm. Pion-pole and
lattice-QCD isovector
benchmarks suppress the process-weighted elastic contribution by roughly three orders of magnitude relative to the point-particle result. Two coefficient sets matched to the same leading low-energy nucleon source yield process-weighted resolved leading logarithms differing by four orders of magnitude, demonstrating the sensitivity of resolved ALP radiation to heavy-
quark coupling configurations.
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Quantum Physics
Sine-Gordon Model with Bosonic Tensor Networks: Continuum Matching and Soliton Scattering
Florian Hechenberger, Tommaso Rainaldi and Felix Ringer
We use bosonic tensor networks to connect the
lattice sine-Gordon model in the
Hamiltonian formulation quantitatively to its continuum theory. Matching the
lattice vertex operator to its conformal normalization at the free-
boson ultraviolet fixed point yields the exact relation between the bare
lattice coupling and the renormalized continuum mass parameter. The
soliton mass then approaches Zamolodchikov's exact continuum prediction throughout the studied parameter range, without adjustable parameters. Using uniform
matrix product states and a quasiparticle ansatz, we also recover the relativistic
soliton dispersion and the two lightest breather masses at the percent level. We simulate real-time collisions of Gaussian
soliton-antisoliton wave packets near a reflectionless point and extract the Wigner spatial displacement. We compare this displacement with the exact continuum prediction obtained from the momentum derivative of the transmission phase, recovering its characteristic rapidity dependence. Our bosonic simulations provide a foundation for nonintegrable extensions, offer lessons for renormalization in other
Hamiltonian lattice field theories, including gauge theories, and provide
benchmarks for continuous-variable
quantum simulations.
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Superconductivity
Strong-coupling multigap superconductivity in the Heusler compound ScAu$_2$Al
Jozef Kačmarčík, Zuzana Pribulová, Yevhen Petrenko et al. (+9 more)
ScAu$_2$Al is the Heusler
superconductor with the highest reported transition temperature, Tc, close to 5 K. Here, we combine high-resolution ac calorimetry and electrical-transport measurements with first-principles-based Eliashberg calculations. The large specific-heat jump, ${\Delta}C/{\gamma_nT_c} =$ 2.2, well above the weak-coupling BCS value of 1.43, together with an electron-
phonon coupling constant ${\lambda} = $1.1, establishes ScAu2Al as a strong-coupling
superconductor. The electronic specific heat is described better by a two-gap {\alpha} model, with $2{\Delta}_S/k_BT_c = $ 4.1 and $2{\Delta}_L/k_BT_c = $ 4.8, than by a single-gap model. The thermodynamic upper critical field follows a conventional WHH-like temperature dependence with $B_{c2}(0) = 0.18$ T, whereas the resistively determined critical field reaches values about three times larger and exhibits a pronounced positive
curvature. We attribute the enhanced resistive field scale to superconductivity in disordered grain-boundary and interfacial regions. The experimental results are supported by calculations of the heat capacity and upper critical field within the Eliashberg formalism using
Fermi-surface and electron-
phonon parameters obtained from first-principles calculations
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All authors Jozef Kačmarčík, Zuzana Pribulová, Yevhen Petrenko, Gabriel Kuderowicz, Paweł Wójcik, Michał J. Winiarski, Szymon M. Królak, Filip Košuth, Pavol Szabó, Tomasz Klimczuk, Bartlomiej Wiendlocha, Peter Samuely
Computation and Language
Reusing Latent Speech Representations for Query-Conditioned Topic Localization in Transcripts
Steffen Freisinger, Philipp Seeberger, Thomas Ranzenberger et al. (+2 more)
Long transcripts are costly inputs for downstream NLP systems and often contain irrelevant context. We study query-conditioned topic localization: predicting the sentence span in a transcript that best addresses a topic-title query. To improve span localization, we reuse ASR encoder states as sentence-level representations and fuse them with textual
embeddings. This lets lightweight span locators exploit
speech information without running a separate audio encoder. Experiments on two public
datasets show consistent gains over text-only baselines, especially under strict boundary-matching criteria. Cross-
dataset experiments further indicate that the benefits are strongest for structured or semi-structured
speech, while gains on spontaneous
speech are limited and mixed.
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All authors Steffen Freisinger, Philipp Seeberger, Thomas Ranzenberger, Tobias Bocklet, Korbinian Riedhammer
Software Engineering
Supporting Industrial Test-Failure Analysis with LLM-Based Systems: An Experience Report
Eric Jansson, Per Strandberg, Thomas Sörensen et al. (+2 more)
This study examines tool-augmented Large
Language Model (LLM) systems for supporting Root Cause Analysis (RCA) of nightly test failures at Westermo Network Technologies AB. Nightly test executions produce heterogeneous test data and logs that practitioners currently inspect manually across multiple sources. We implemented an RCA workflow in single-
agent and orchestrated multi-
agent configurations, both with access to test metadata and logs. An exploratory industrial case study used two real failure scenarios. Six practitioners evaluated the scenario reports through a survey and focus group, and operational measurements were collected from 120 repeated executions. The evaluation covered practitioner-perceived correctness,
reasoning quality, fix realism, clarity, usefulness, and trust, as well as cost, duration, and consistency. Neither configuration showed a consistent practitioner-perceived quality advantage across the two scenarios. The single
agent system generated reports faster and at lower cost, making it the more practical baseline in this context. The potential benefits of
agent architectures require further evaluation in more complex scenarios.
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All authors Eric Jansson, Per Strandberg, Thomas Sörensen, Eduard Paul Enoiu, Wasif Afzal
Computational Complexity
Restructuring Tree Decision Diagrams
Christoph Berkholz, Matthäus Micun and Igor Razgon
Tree Decision Diagrams (TDDs) are a data structure recently introduced by Capelli et al. (SAT 2026). They are structured along a vtree and the size of their canonical form lies between Ordered Binary Decision Diagrams (OBDDs) and deterministic structured DNNF
circuits (d-SDNNFs). While the succinctness gap between TDD and d-SDNNF is exponential, only a quasipolynomial separation between OBDD and TDD has been shown and it was left as open question whether this is optimal. We answer this question affirmatively by showing that every TDD can be transformed to an equivalent OBDD of quasipolynomial size. Although this might be seen as a weakness, our second result shows that TDDs share another desirable property with OBDDs that is not known to hold for d-SDNNF: Given a TDD and another target vtree, it is possible to construct the minimal and canonical TDD respecting the new vtree in time
polynomial in the input and output. As a result we also obtain that the equivalence test between TDDs over different vtrees can be done in
polynomial time.
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Artificial Intelligence
EnterpriseVal: Quantifying the Efficacy, Reliability and Value of Generative AI in the Enterprise
Abbas Raza Ali, Muhammad Ajmal Siddiqui and Moona Zahid
Frontier
language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valuable tasks, yet most enterprise GenAI initiatives fail to show a measurable business effect and a large fraction of agentic projects are expected to be cancelled. We argue that this is substantially a measurement problem: public
benchmarks answer "what can the model do?", whereas a deployment decision requires "is this workflow fit, reliable, safe and worth scaling - here, on our data, under our controls?". We present EnterpriseVal, a use-case-level evaluation system that closes this gap. It comprises (i) a formal specification of the use case and of the frozen socio-technical configuration under test, model,
prompts,
retrieval, tools, guardrails and human oversight, with an autonomy level and consequence tier that jointly set the required evaluation intensity; (ii) a metric catalogue spanning fidelity, utility, efficiency, reliability, assurance and oversight; (iii) a grading protocol that scales blinded expert judgement with calibrated LLM-as-judge scoring through prediction-powered inference; (iv) a two-tier threshold gate, stated as an executable
algorithm, that maps metric vectors with confidence bounds to REJECT/CONDITIONAL/SCALE decisions; and (v) a value-and-risk model in which the reviewer catch rate is a measured parameter. We report a pilot across three workflows in a global bank. In credit-memo drafting, human-graded citation precision reached 88% and
hallucination rate 1.6% for the best model against gates of 70% and 5%; in procedure transformation, analyst refinement effort fell from an estimated 27.4 to 2.9 hours per document. We separate established results, documented pilot evidence, the proposed system and open hypotheses, and specify the experiments required for full validation
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Computational Complexity
FPT iff PTIME for Homomorphism Problems on Sparse-Incidence and Bounded-Independence Patterns
Matthias Lanzinger
We show that fixed-parameter tractability and
polynomial-time solvability coincide for homomorphism problems specified by classes of pattern hypergraphs of bounded incidence degeneracy or bounded primal independence number, assuming $FPT \ne W[1]$. In both cases, tractability is characterised by bounded fractional hypertree width. This generalises a result of Grohe [JACM 2007] that established such an FPT-PTIME collapse for bounded-arity structures. We build on the fractional balanced-separator framework and rounding
theorem of Korchemna, Lokshtanov, Saurabh, Surianarayanan, and Xue [FOCS 2024] to prove near-linear bounds on fractional hypertree width ($fhw$) in terms of adaptive width ($adw$). Namely, for every hypergraph $H$ $$fhw(H)=O(\mu(H) adw(H)\log adw(H)), \quad fhw(H)=O(\log \alpha(H) adw(H)\log adw(H))$$ where $\mu(H)$ is the degeneracy of the incidence graph of $H$ and $\alpha(H)$ the independence number of the primal graph of $H$. As a consequence, we obtain a corresponding FPT-PTIME collapse for exact homomorphism decision and counting on every class in which either incidence degeneracy or independence number is bounded. This includes a number of natural classes such as pattern hypergraphs of bounded degree. Additionally, we observe that for every r.e. class of pattern hypergraphs, fixed-parameter tractability of the parameterised homomorphism problem implies quasipolynomial-time solvability of the corresponding unparameterised problem, assuming $FPT \ne W[1]$. Our results rely on the characterisation of fixed-parameter tractable decision of homomorphism problems in terms of submodular width of Marx [JACM 2013], conditional on ETH. In light of the very recent potential refutation of the ETH, we show that the characterisation of Marx holds also under the assumption that $FPT \ne W[1]$.
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Cosmology and Nongalactic Astrophysics
Intrinsic Tidal Shear at the Largest Scales: Galaxy Multiplet Alignment in DESI DR2
C. Lamman, J. Aguilar, S. Ahlen et al. (+45 more)
We measure the intrinsic
alignment (IA) of
galaxy multiplets with the large-scale
tidal field traced by
galaxy positions in DESI Data Release 2. Using the BGS, LRG, and ELG samples spanning $0.01 < z < 1.6$, we optimize the scales which define multiplets in each sample to minimize measurement noise. We measure multiplet
tidal alignment $\mathcal{E}_+$ on scales beyond 100 $h^{-1}$Mpc in all samples, and detect
alignment over 200 $h^{-1}$Mpc, up to 4.5$\sigma$ in the highest LRG
redshift bin. We additionally present the multiplet shape-shape autocorrelation, $\mathcal{E}_{++}$, which is independent of
galaxy bias and provides a consistency check of our NLA (nonlinear
alignment) model. We do not detect a
baryon acoustic feature in the projected
estimator. We also find the
alignment strength of multiplets is correlated with
redshift and
galaxy morphology. Multiplet
alignment offers direct access to the
tidal shear field in all
galaxy samples, even where individual
galaxy alignment cannot, and extends IA detection to the largest scales yet probed.
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All authors C. Lamman, J. Aguilar, S. Ahlen, A. Aviles, D. Bianchi, D. Brooks, A. Carnero Rosell, F. J. Castander, T. Claybaugh, A. de la Macorra, D. Eisenstein, A. Font-Ribera, J. E. Forero-Romero, C. Garcia-Quintero, E. Gaztañaga, G. Gutierrez, K. Honscheid, M. Ishak, S. Juneau, T. Karim, D. Kirkby, O. Lahav, M. Landriau, M. E. Levi, M. Manera, A. Meisner, R. Miquel, S. Nadathur, H. E. Noriega, N. Palanque-Delabrouille, W. J. Percival, M. Perdomo, F. Prada, I. Pérez-Ràfols, C. Ravoux, A. J. Ross, G. Rossi, R. Ruggeri, L. Samushia, E. Sanchez, C. Saulder, D. Schlegel, M. Schubnell, J. Silber, M. Siudek, G. Tarlé, R. Vaisakh, B. A. Weaver
Robotics
PopNavShift: Stress-Testing Social Navigation under Behavioral Population Shift
Kaizhen Tan, Diyu Zheng, Tim Guangyu Wu et al. (+1 more)
Social-
navigation algorithms are often evaluated under a fixed pedestrian-behavior distribution, despite substantial variation in pedestrian responses to
robots across individuals and social contexts. We introduce PopNavShift, a matched simulation framework for stress-testing social-
navigation strategies under pedestrian population shifts. PopNavShift constructs population-conditioned pedestrian motion profiles by prompting Gemini 3.7 Flash with 600 synthetic persona records from MatrAIx Persona 1M and deterministically mapping the responses into bounded motion parameters. It then compares three representative
navigation strategies, reactive avoidance, early yielding, and reciprocal collision avoidance, across eight population conditions and 7,488 matched
robot runs. In a matched intervention on the same 202 personas, changing only time pressure reverses 8.6% of controller rankings based on
robot travel time, but 22.4% based on mean pedestrian delay and 23.9% based on worst-decile delay. Across population conditions, this sensitivity is greater for pedestrian burden than for
robot travel time and increases in spatially constrained settings; the same qualitative pattern persists under a second pedestrian dynamics model. These findings support evaluating
navigation strategies across behavioral populations using both
robot performance and pedestrian burden.
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All authors Kaizhen Tan, Diyu Zheng, Tim Guangyu Wu, ChengHe Guan
Instrumentation and Detectors
A Deep Neural Network based Level-1 Trigger for the Magnetic Monopole Search in the SCEP Experiment
Changqing Ye, Yunhan Wang, Yifan Qiao et al. (+4 more)
The Search for
Cosmic Exotic Particles (SCEP) experiment proposes a multilayer
magnetic monopole (MM) detection array with a target exposure of O(10^4) m^2 year. Continuously recording the raw waveforms at this scale would generate approximately O(10) EB of data per year, making full waveform storage impractical. A Level-1 trigger is therefore required to reduce the stored-data volume while retaining rare MM signals. MM waveforms vary with particle velocity and trajectory, so a single filter kernel cannot match all possible signals. A mismatch between the kernel and the signal waveform can reduce the detection probability. This work therefore develops a compact template-bank construction method for MM detection. Each incoming waveform is filtered with all kernels in the bank, and the best-matched kernel is identified from their responses. A multilayer perceptron (MLP) trigger is further developed to combine all template responses and improve signal detection. With a 31-sample window and a stored-data fraction of 10^(-3), the MLP increases the mean net acceptance P_net from 6.72% for the conventional template-bank trigger to 8.79%, a relative improvement of 30.8%. The network is then implemented on a Xilinx AC701 board equipped with a field-programmable gate array (FPGA) to process a 20-bit input waveform sampled at 1 MHz using 200 MHz trigger logic. At the target stored-data fraction, the fixed-point implementation reduces P_net by only 3/(3.2 x 10^6) relative to the floating-point reference. On-board tests reproduce the bit-accurate reference trigger outputs and sustain continuous 1 MHz processing without dropped input samples, verifying the functional correctness and real-time operation of the FPGA-based Level-1 trigger.
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All authors Changqing Ye, Yunhan Wang, Yifan Qiao, Zhe Cao, Beige Liu, Qing Lin, Lei Zhao
Solar and Stellar Astrophysics
SN 2026dix: a nearby, transitional Type IIb/Ib supernova consistent with a warm supergiant progenitor
Tamás Szalai, Schuyler D. Van Dyk, Dominik Bánhidi et al. (+20 more)
Understanding the final
evolution stages of (very) massive
stars and their explosive outcomes, stripped-envelope
supernovae (SESNe), represent a long-term challenge for astrophysics. The latest results support a continuous distribution within the traditional SESN subclasses (IIb, Ib, Ic). The nearby ($D \approx 17.5$ Mpc) SN 2026dix seems to be another member of the recently identified group of transitional Type IIb/Ib explosions. A point source is located at the SN position within the uncertainties on multiple pre-explosion HST images. Together with post-explosion photometry and spectroscopy, it provides a good opportunity to study a rare type of SN in detail. We carried out a thorough comparative light-curve (LC) and spectral analysis of SN 2026dix. We also constructed its bolometric LC and modeled it semi-analytically. In addition, we constructed the spectral energy distribution of the presumed progenitor and compared this to model
stellar atmospheres and binary
stellar evolution tracks. We infer that SN 2026dix arose from an explosion in an interacting binary system, consistent with the properties of a warm ($T_\textrm{eff} \approx 6750-$7750 K; spectral type F2 to A7), luminous ($\log(L_{\rm bol}/L_{\odot})\approx 4.9-5.3$) supergiant primary and a less luminous, less massive hot
dwarf companion. The nature of the identified progenitor closely resembles that of some other known cases of SNe IIb and also well aligns with both the results of our semi-analytical LC modeling and the comparison of the LCs and spectra of SN 2026dix with the output of radiative-transfer models of an exploding
star with $M_\textrm{ini}$ = 18 $M_{\odot}$.
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All authors Tamás Szalai, Schuyler D. Van Dyk, Dominik Bánhidi, Andrea P. Nagy, Réka Könyves-Tóth, Alexei V. Filippenko, Thomas G. Brink, WeiKang Zheng, Imre Barna Bíró, István Csányi, Zsófia Bora, Zsóka Horváth, Ágoston Horti-Dávid, András. P. Joó, Dávid Koller, Levente Kriskovics, Klára Lelkes, Katalin Nagy, Krisztián Sárneczky, Ádám Sódor, Róbert Szakáts, András Pál, József Vinkó
Superconductivity
Failure of Conventional Roughness Metrics in Assessing Field-Limiting Mesoscopic Topography in SRF Nb Films on Cu
Eric M. Lechner, Brandi Redman, Theodore S. Cahall et al. (+1 more)
A characteristic corrugated surface morphology of Nb films on Cu is identified, with mesoscopic features comparable to the London penetration depth and coherence length, and its impact on superconducting
radio frequency cavity performance metrics is examined.
Magnetic field enhancement factors and superheating field suppression factors are calculated within the London model for a representative corrugated geometry. These results demonstrate that roughness trends derived from buffered chemical polished and electropolished Nb cavities do not capture the impact of nanoscale surface morphology on SRF Nb thin film performance, as even surfaces that possess low average roughness can contain
geometric features that generate substantial local field enhancement and significantly suppress the Bean Livingston barrier. The influence of surface roughness on
impurity diffusion is also investigated, which highlights the roles of increased surface area and local
geometric confinement in modifying near surface
impurity distributions. Tracking the effect of
impurity diffusion on the
evolution of
magnetic field enhancement, we show that geometrically confined
impurity distributions can mitigate nanoscale
magnetic field enhancement substantially.
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All authors Eric M. Lechner, Brandi Redman, Theodore S. Cahall, Anne-Marie Valente-Feliciano
Optimization and Control
Beyond Shadow Weights: Quantization-Aware Training as Quantized-Endpoint Descent
Sheng-An Xu, Hanyang Li, Jianhao Ma et al. (+1 more)
Quantization-aware training (QAT) updates a full-precision shadow weight $\mathbf{x}$ but deploys the quantized endpoint $Q(\mathbf{x})$. Existing explanations for QAT largely view its success through the lens of shadow weights: QAT can move $\mathbf{x}$ toward flatter basins, gain robustness from quantization-induced oscillations, or balance the shadow loss $f(\mathbf{x})$ against the quantization error $\|\mathbf{x}-Q(\mathbf{x})\|_2$. These perspectives do not directly explain the empirical observation that the deployed endpoint loss $f(Q(\mathbf{x}))$ improves while the shadow loss $f(\mathbf{x})$ does not, and can even increase substantially. In this paper, we offer a different explanation by treating QAT as finite-grid endpoint dynamics. Motivated by the approximate normality of rescaled pretrained weights, we propose an idealized model for the residual phase, which records where each shadow weight sits inside its quantization
cell as a fraction of the
cell width. This model leads to a crossing law that determines which coordinates cross quantization boundaries after a shadow update. Inspired by the idealized model and signal-imbalance phenomenon in QAT, we further propose QAR (Quantization with Amplified Routing), an algorithmic framework that directly operates on the quantization code. In contrast to QAT, QAR is both theoretically grounded and
memory-efficient: it admits feasible-gradient bounds for a family of power amplifiers up to unavoidable finite-grid floors without retaining a full-precision shadow weight copy. Experiments on post-training of large
language models provide evidence consistent with the endpoint view and show that QAR can be comparable to or better than QAT with smaller
memory cost.
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All authors Sheng-An Xu, Hanyang Li, Jianhao Ma, Ying Cui
Statistical Mechanics
Non-negative differential mobility of one-dimensional underdamped Langevin dynamics: Proof via mapping to a marginally stable oscillator
Udo Seifert
For an underdamped particle driven by a constant non-conservative force across a periodic potential in one spatial dimension at finite temperature, numerical studies have shown that the differential mobility is non-negative. Here, an analytical proof will be given that is based on expressing the differential mobility by the long-time mean position of a marginally stable harmonic oscillator subject to noise in its stiffness.
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General Topology
Singular Submodules of Abelian Groups over Their Endomorphism Rings
Jiang Yang and Xin Zhang
Let $A$ be an abelian group and $E=\Endo_{\Z}(A)$. We give a module-theoretic description of the singular $E$-submodules asked for in Fuchs' Problem~1.2. For a unital ring $R$ and a left $R$-module $M$, put $W=I_R({}_RR)\oplus I_R(M)$ and $J=\Jaco(\Endo_R(W))$, and let $u$ be the image of $1_R$. The classical essential-kernel criterion yields \[ Z_R(M)=M\cap Ju. \] For $R=E$ and $M=A$, all singular submodules are therefore the $E$-submodules of $A\cap Ju$. Writing $T=t(A)$ and $B=A/T$, we prove a torsion-transfer formula, identify the torsion part as $\bigoplus_p pT_p$, and describe simultaneous
prime lifting by a canonical obstruction. The resulting extension gives an $\Extt/\Homm$ parametrization of all singular submodules. We obtain explicit formulas for torsion groups and for $\Z(p^\infty)\oplus B$ with $B$ torsion-free; in the latter case the fully invariant subgroup
lattice of $B$ occurs as an interval. The general description retains the induced endomorphism action and extension data, rather than giving a classification by classical group invariants.
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Optimization and Control
A Tight Surrogate-Based Adaptive Step Size for the Multiobjective Conditional Gradient Method
Wang Chen, Yong Zhao, Liping Tang et al. (+1 more)
The multiobjective conditional gradient (MCondG) method is an effective descent-type
algorithm for solving constrained multiobjective optimization problems. In this
algorithm, the adaptive step size is derived by minimizing a one-dimensional convex quadratic surrogate function, which guarantees a sufficient decrease in all objective functions at each iteration. However, we observe that this surrogate function is relatively conservative, producing overly small step sizes and consequently slowing the convergence of the
algorithm. This conservativeness stems from the fact that the surrogate function is dominated by the largest Lipschitz constant among the gradients of all objective functions. Motivated by this observation, we develop a tighter quadratic surrogate function that exploits the individual gradient Lipschitz constants. Based on this surrogate, we propose a new adaptive step size strategy obtained by evaluating this surrogate over a finite candidate set. We prove that the proposed step size preserves the descent property of the MCondG method, and has an improved worst-case complexity bound compared with the original adaptive step size strategy. Numerical experiments on
benchmark and real-world problems demonstrate the effectiveness of the proposed strategy in terms of computational efficiency and solution quality.
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All authors Wang Chen, Yong Zhao, Liping Tang, Xinmin Yang
Optics
Performance of Capacitively Loaded RF Electrodes on SiO2/Si Substrates for High-Speed Electro-Optic Modulators
Ayed Sayem, Ting-Chen Hu, Mark Cappuzzo et al. (+3 more)
We experimentally investigate conventional and capacitively loaded traveling-wave RF electrodes fabricated on thermally grown SiO$_2$ on high-resistivity silicon substrates for high-speed electro-optic modulators. The capacitively loaded electrodes exhibit RF attenuation coefficients as low as approximately $0.23~\mathrm{dB/cm}/\sqrt{\mathrm{GHz}}$, comparable to values reported for electrodes fabricated on insulating quartz substrates, while retaining the silicon handle and avoiding substrate removal or undercut processing. By varying the SiO$_2$ buried-
oxide (BOX) thickness and the capacitive-loading geometry, the microwave effective index can be engineered over a broad range while maintaining low RF propagation loss. This enables microwave-optical velocity matching over a wide range of optical wavelengths, from the ultraviolet to the telecom C-band. These results demonstrate that thermally oxidized silicon provides a simple and scalable substrate platform for low-loss traveling-wave electrodes in thin-film lithium niobate and thin-film lithium tantalate electro-optic modulators, as well as for high-speed RF interconnects in integrated transceivers and co-packaged optical systems.
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All authors Ayed Sayem, Ting-Chen Hu, Mark Cappuzzo, Alaric Tate, Rose Kopf, Mark Earnshaw
Machine Learning
Federated Deep Clustering Networks for High-Dimensional and Heterogeneous Data
Morris Stallmann, Charalampos S. Kouzinopoulos, Marcin Pietrasik et al. (+1 more)
Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized data scenario, this task is commonly solved using deep clustering methods that utilize deep neural network architectures to learn clustering-friendly latent space representations. In
Federated Learning, where data is distributed between clients and is private, deep clustering methods are less explored. In particular, recently introduced
federated deep clustering methods, despite showing very promising performance, still fall short in reliably providing good performance if data across clients are non-identically-independently distributed. In this work, we introduce a generalization of Deep Clustering Networks to the
federated scenario, named FedDCN, that simultaneously optimizes a reconstruction loss and a clustering loss. To ensure robustness and latent space
alignment in non-identically-independently distributed data scenarios, FedDCN generates synthetic data augmentations, and its learning objective includes a
geometric regularization for latent space
alignment. Through experimental evaluation, the effectiveness of the approach under IID and non-IID assumptions is demonstrated, and future research directions are identified.
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All authors Morris Stallmann, Charalampos S. Kouzinopoulos, Marcin Pietrasik, Anna Wilbik
Human-Computer Interaction
Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments
George Xi Wang, Xiangyu Li, Shaoyue Wen et al. (+8 more)
Blind and low-
vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing
vision-
language-model-based assistants can provide semantic descriptions but may introduce latency,
hallucinations, and guidance that is poorly aligned with
embodied action. We present Touvigation, a hands-free object acquisition system that combines
vision-
language understanding with persistent local spatial modeling to provide low-latency, body-relative guidance. Drawing on formative interviews with eight blind and low-
vision participants, we design a multi-stage guidance framework that adapts spatial references as users transition from orienting, to walking, to reaching and tactile verification. We evaluated Touvigation with 12 blind and low-
vision participants against a
multimodal large-
language-model assistant and unassisted search. Touvigation achieved 100% task success, compared with 58% for the
multimodal assistant and 85% for unassisted search, while reducing completion time and cognitive workload. Our findings demonstrate how persistent spatial grounding and adaptive
embodied guidance can improve object acquisition for blind and low-
vision users.
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All authors George Xi Wang, Xiangyu Li, Shaoyue Wen, Jiaqian Hu, Junan Xie, Yupeng Wang, Ziyue Shi, Qijun Chen, Maaike Bouwmeester, Yuhua Jin, Jing Qian
Computation and Language
RheoSampling: Resolving the One-Hot Dilemma in Stochastic Dynamic-Tree Speculative Decoding
Qiao Hu, Yepeng Weng, Bo Zhang et al. (+1 more)
Speculative decoding accelerates LLM inference by drafting multiple
tokens in parallel, with tree-based methods further improving efficiency through hierarchical structures. Dynamic-tree methods such as EAGLE-3 perform well under greedy decoding via deterministic top-K expansion and global
pruning. However, in
stochastic decoding (T>0), this mechanism collapses the draft distribution into one-hot probabilities, causing a severe drop in acceptance rate. This creates a dilemma: dynamic-tree methods sacrifice
stochastic sampling to preserve context-aware
topology, while static-tree methods preserve
stochastic sampling with context-agnostic structures. The issue arises because the same probability distribution is used for two conflicting tasks: constructing the tree and verifying
tokens. This coupling makes direct injection of randomness challenging due to the resulting
stochastic process. We resolve this by decoupling these roles: RheoSampling assigns a
token sampled from the draft distribution a proxy probability for tree expansion and
pruning alongside its true sampling probability for verification. Specifically, we inject a sampled
token among the deterministic top-K slots and treat it with different probabilities during construction and verification, making RheoSampling the first dynamic-tree method with both context-aware top-K construction and
stochastic sampling while maintaining losslessness. We establish the lossless guarantee through an equivalence-class analysis that compresses the
stochastic tree space into tractable classes. An OT-based verification strategy and a sparse draft mechanism ensure that theoretical gains translate into practical efficiency. Experiments across LLMs and
benchmarks demonstrate improvements in acceptance rate and speedup over state-of-the-art dynamic tree methods. This framework may provide a template for analyzing
stochastic tree structures.
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All authors Qiao Hu, Yepeng Weng, Bo Zhang, Takehisa Yairi
Game Theory
Fair Prophets
Paul Duetting, Michal Feldman and Mathieu Molina
We initiate the study of $\alpha$-fair prophet inequalities. This interpolates between utilitarian welfare $(\alpha=0)$, Nash welfare $(\alpha=1)$, and Rawlsian max-min
fairness $(\alpha\to\infty)$. Given the non-linearity of the objective, it matters when the expectation is applied. For instance, for the Rawlsian objective, it matters whether we aim to maximize $\min \mathbb{E}[u_i]$ or $\mathbb{E}[\min u_i]$. We refer to the former as the ex-ante model, and the latter as the ex-post model. For ex-ante
fairness, full distributional knowledge yields a tight competitive ratio of exactly $1/2$ for every $\alpha\ge 0$. Under sample access, $O(n\log n)$ samples per distribution suffice for a constant competitive ratio when $\alpha\in(0,1]$. In contrast, for every $\alpha>1$, no finite number of samples improves upon the trivial $1/n$ guarantee. Thus, unlike in the utilitarian setting, full-information and sample-access prophet inequalities become fundamentally separated. For ex-post
fairness, under full information, we obtain a uniform constant ratio for all $\alpha\in(0,1)$, while for every $\alpha>1$ the competitive ratio collapses to $1/n$. In the sample-access model, one sample per distribution suffices for each fixed $\alpha<1$, but no sample budget depending only on $n$ yields a uniform constant guarantee as $\alpha\to 1$. Beyond these phase transitions for $\alpha$-
fairness, our results open the door to a broader theory of prophet inequalities for non-linear welfare objectives.
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Superconductivity
Topological properties and gap structure of the paired state in twisted TMD bilayers within a two-band effective model
Palash Saha and Michał Zegrodnik
We present a theoretical study motivated by the recent experimental results which demonstrate superconductivity emerging from flat topological bands of twisted transition metal dichalcogenide (TMD)
bilayers. To capture the non-trivial band
topology of the system, we employ an effective two-band Kane-Mele-like model and substitute it with Coulomb repulsion and inter-site pairing interactions treated at the Hartree-Fock mean-field level. Assuming a real-space pairing scenario, we analyze the resulting superconducting gap
symmetry and the stability of the paired state as a function of band filling and applied displacement field. Finally, we highlight the interplay between superconductivity and non-trivial
topology, detailing how interaction-induced effects and the
evolution of the density of states shape the resulting superconducting phase diagram.
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Materials Science
Multivalley 3D Electronic Structure of PbSe from Soft-X-Ray ARPES and First-Principles Calculations
Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak et al. (+7 more)
PbSe is a narrow-gap IV-VI
semiconductor, whose multivalley valence bands, with maxima at the L, $\Sigma$, and $\Delta$ points, underpin its intermediate-temperature thermoelectric properties. We combine soft-X-ray angle-resolved photoemission spectroscopy (SX-ARPES) with first principles simulations to study the valence band structure of bulk PbSe. High resolution measurements are conducted at
photon energies of 400-900 eV to map the valence
manifold along X$\Gamma$X, WXW, and K$\Gamma$K, and iso-energy surfaces are collected in the $k_z=0$ plane. Comparison to ARPES enables a rigorous assessment of the performance of density functional theory (DFT), using semi-local and hybrid functionals, as well as many-body perturbation theory within the quasiparticle self-consistent $GW$ approximation. We find that the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional and QP$GW$ reproduce the measured band dispersions to within 0.1-0.2 eV over the entire valence band. In contrast, the semi-local Perdew-Burke-Ernzerhof (PBE) functional compresses the band width and deviates from experiment by up to 0.6 eV. We further show that an accurate band structure and band gap are vital to obtaining a correct description of the dependence of the Seebeck coefficient of p-type PbSe on the hole concentration (Pisarenko relation). This has implications for computational efforts to discover thermoelectric materials.
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All authors Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak, Enrico Della Valle, Hantian Liu, Moritz Hoesch, Sergey M. Frolov, Tomasz Story, Vladimir N. Strocov, Noa Marom