Papers

To probe a bipartite quantum system, one may use arbitrary global operators or restrict to product operators acting separately on the two subsystems. We determine the sharp universal comparison between the resulting norms. For every $z\in M_n\otimes M_m$, we prove $\|z\|_1\leq\sqrt{2}\min\{n,m\}\|z\|_\varepsilon$, where $\|\cdot\|_1$ is the trace norm and $\|\cdot\|_\varepsilon$ is the injective tensor norm associated with the trace norms on $M_n$ and $M_m$. To prove the upper bound, we establish an $L_1$ noncommutative Khintchine inequality whose random coefficients are the entries of a Haar unitary. We also show that the coefficient $\sqrt{2}$ is sharp. As applications, we show that the same sharp constant governs the gap between bipartite correlation measured in trace norm and that measured by a correlation function, and obtain an improved universal upper bound for quantum data hiding. The upper bound has also been formalized and machine-checked in Lean.

Mobile impurities provide a powerful means of probing correlated and topological quantum matter, through their dressing by the surrounding medium and the practical probes granting access to the resulting composite object. Motivated by the recent observation of anyon-impurity composites in the solid state, as well as recent realizations of Laughlin-type states in engineered lattice systems, we investigate the formation of a bound state between a mobile impurity and a single pinned quasihole in the interacting Harper-Hofstadter model deep in the fractional Chern insulator regime. Combining analytical arguments with large-scale numerical simulations, we characterize the structure, energetics, and stability of hybrid anyon-impurity bound states, and show that their binding energy provides direct access to the fractional charge of the quasihole under conditions that we identify. We further demonstrate that the composite object can be coherently transported by externally steering the quasihole pinning potential. Our results establish a realistic pathway for controlled anyon-impurity manipulation in quantum-engineered platforms, enabling experimentally feasible protocols for braiding.

Quantum noise, arising from the quantisation of electromagnetic field, has been a limiting noise source for current gravitational wave (GW) detectors. Squeezed vacuum modifies quantum fluctuations and has been routinely employed. To reduce quantum noise, the current solution is to combine squeezed vacuum with a detuned over-coupled optical cavity (filter cavity) to achieve frequency-dependent squeezing (FDS). The sensitivity to GW signals can be decomposed into a noise budget. Depending on the detector configuration, the contribution from noise sources other than quantum noise can be significant. In particular, suspension noise from multi-stage pendulums is a key factor in quantum-noise reduction design. In the context of KAGRA post-O5, we have compared quantum noise reduction schemes, frequency-independent squeezing (FIS), FDS with a filter cavity (FC), FDS with an amplitude filter cavity (AFC), FDS with a frequency-dependent beam splitter (FDBS) and EPR scheme. The FC scheme was found to outperform the AFC and FDBS schemes at all frequencies. It was found that FIS scheme gives the largest Binary Neutron Star (BNS) range when low frequency noise is dominated by classical noise, while the FC scheme gives the largest BNS range when low-frequency noise becomes dominated by quantum noise. Optimised filter cavity parameters could substantially improve the BNS range. This would allow at least 23% increase in the detection rate for an 85 m filter cavity, compared with using FIS scheme. Once a filter cavity is constructed with optimised parameters, refining its detuning can fully compensate for the variations in arm power (from half to full design value) and for different intra-cavity loss conditions. The EPR scheme performs best for the detection of heavy binary systems.

We investigate dark matter admixed neutron stars in which the neutron star coexists with an anisotropic dark matter halo described by the Einasto density profile, a model recently shown to produce regular, singularity-free black hole solutions~[Phys. Rev. D 113, 043011 (2026)]. Solving the modified Tolman–Oppenheimer–Volkoff equations with two different equations of state (BSk19 and SLy4), we find that the dark matter halo significantly alters the neutron star structure. Furthermore, for a specific range of halo parameters, $g_{rr}^{-1}$ changes sign outside the stellar surface, forming an event horizon with the neutron star persisting as a regular configuration inside it— “neutron stars in black holes”. This configuration appears in both equations of state and does not depend on a specific choice of the equation of state. The discovery of this configuration provides a new perspective and a concrete computable instance for the study of what lies inside a black hole.

Controlling nanoparticle size during synthesis remains a central challenge in nanoscience, particularly in systems where external magnetic fields are used as continuous control parameters. Existing descriptions of magnetic-field-assisted nucleation are typically material-specific or rely on computationally intensive atomistic methods. Here, we reformulate classical nucleation theory as a geometrically closed thermodynamic framework by introducing a sphere-packing representation of atomic assembly. This construction establishes a direct link between discrete atomic structure and continuum free-energy contributions under applied magnetic fields, yielding a field-driven evolution equation for the critical nucleus size. The resulting theory provides a unified description of nanoparticle nucleation across superparamagnetic, paramagnetic, and diamagnetic systems within a single formalism. It quantitatively reproduces previously unresolved experimental observations for magnetite and nickel nanoparticles, namely the systematic reduction of mean particle size and narrowing of size distributions with increasing magnetic field. In the diamagnetic limit, the framework recovers our earlier analytical susceptibility-based description of silver nanoparticles, in which the field-dependent critical radius is governed by the induced-magnetization contribution to the nucleation free energy. Beyond modeling the reduction of mean particle size with increasing magnetic field, the framework reveals that the narrowing of size distributions emerges naturally from the curvature of the field-modified free-energy landscape. These results establish magnetic-field-assisted nucleation as a geometrically constrained thermodynamic process, providing a computationally efficient route for controlling nanoparticle size across distinct magnetic material classes.

Electric Hall Effect (EHE), a unique phenomenon in two-dimensional (2D) magnetic systems, refers to the generation of Hall current by an out-of-plane electric field $\Ez$. Here, we demonstrate that for 2D magnetic Weyl semimetals that host doubly degenerate nodal points, the EHE features multiple unconventional scaling laws. At zero temperature, the EHE exhibits a topological $E_F^{-1}$ Fermi-energy scaling. Remarkably, the prefactor of the scaling is determined by the global topological charge of the point without any dependence on the local parameters of the system, leading to a universal and significant enhancement of Hall response in any species of Weyl points as the Fermi energy approaches the Weyl point. This significant response enables a weak electric field to be directly converted into a measurable Hall signal. Surprisingly, this enhanced Hall response is not diminished by temperature, but evolves into an unconventional logarithmically corrected scaling at finite temperature $\sigma_{xy}\propto\Ez\ln(1/|\Ez|)$ for weak $\Ez$, still yielding a divergent electric-field susceptibility. Thus, our work not only unveils intriguing scaling laws resulting from the interaction between magnetism and topology, but also suggests a novel scaling-enhanced and temperature-robust mechanism that may enable weak electric-field sensing through a practical and all-electric route.

Quantum optimization has attracted growing interest as quantum hardware continues to improve, yet state-of-the-art classical solvers remain a formidable benchmark for practical utility. Rather than seeking a fully quantum replacement for classical optimization, we propose a hybrid strategy that uses quantum information to enhance leading classical heuristics. Specifically, we introduce a warm-start method based on local correlators obtained from the Quantum Approximate Optimization Algorithm (QAOA), and use this information to initialize the Burer-Monteiro (BM) rank-two relaxation. We demonstrate numerically that, compared to a random, multi-start initialization baseline (a standard strategy used for BM), this quantum-informed initialization offers a significant head start, i.e., high-quality solutions with very small number of iterations, for two problem classes – random Erdős Rényi graphs with edge density of $10\%$ (ER-10) and fully-connected Sherrington Kirkpatrick (SK) spin glass models, at $n=500$ and $n=1000$ qubits. At the same time, given enough iterations, the random baseline often eventually catches up and slightly outperforms the warm-start strategy on average, an effect visibly stronger for $n=500$ than for $n=1000$. The results demonstrate an exploitation/exploration tradeoff of using WS to quickly arrive at very good solutions vs exploring slightly better solutions with a larger iterations budget via a standard strategy. Our results highlight how low-depth quantum circuits can provide useful structural information for classical optimization and suggest a promising route toward near-term quantum utility through quantum-assisted initialization.

The TRAPPIST-1 system offers seven terrestrial exoplanets with tight orbits and large radii ratios to the host star. If an atmosphere exists, transmission spectroscopy can be used to detect specific atmospheric features. Predictions of the atmospheric detectability of the TRAPPIST-1 planets prior to the launch of JWST assumed pristine stellar surfaces. However, initial JWST observations of the TRAPPIST-1 planets demonstrate that stellar contamination from unocculted active regions imparts significantly stronger spectral features than any planetary atmospheres. Here, we evaluate the atmospheric detectability of the habitable zone planet TRAPPIST-1f using atmospheric retrievals accounting for stellar contamination. We model a transmission spectrum given a CO$_2$-rich, habitable atmospheric model, and we include a "worst case" stellar contamination spectrum. We then perform atmospheric retrievals on simulated JWST observations with MIRI LRS (5-15 \micron) and NIRSpec PRISM (0.6-5.3 \micron), assuming accurate starspot spectral models. We find that NIRSpec observations alone achieve similar results as MIRI and NIRSpec together. We find $\sim$10 transits obtains strong evidence ($B>150$) for CO$_2$, and $\sim$50 transits finds weak evidence ($B>3$) for CH$_4$. We could not retrieve evidence of H$_2$O with up to 100 simulated transits with both instruments. Many challenges remain to accurately account for stellar contamination for ultra-cool M-dwarfs in atmospheric retrievals, and our results show that, while evidence for a CO$_2$-rich atmosphere around TRAPPIST-1f can be found with a short JWST program, other prominent atmospheric signatures can only be disentangled from strong stellar features with more observation time than previous studies have indicated.

We investigate the population of luminous red giant branch stars as a function of metallicity using Gaia XP metallicity combined with SDSS-V, GALAH, and LAMOST. After applying uniform selection criteria and extinction corrections, we construct absolute magnitude distributions across metallicity bins spanning [Fe/H] =-1 to >0.4. We find a systematic deficit of luminous giants at high metallicity, while the red clump and lower red giant branch populations remain largely unchanged. This behavior is consistent with enhanced mass loss at high metallicity, arising from either binary interactions or single-star evolution. This trend is robust across multiple surveys and persists within volume-limited subsamples (1-4 kpc), suggesting it is not driven by distance or selection effects. Synthetic stellar populations based on PARSEC isochrones reproduce the overall magnitude distributions but do not predict a decline in luminous giants with metallicity. Tests of potential systematics, including extinction effects and metallicity scale consistency using open clusters, do not account for the observed trend. We also find no evidence that survey-to-survey differences in metallicity drive the observed result. Together, these findings suggest a metallicity-dependent reduction in the number of luminous red giants that is not captured by current models. This result may have implications for stellar evolution at high metallicity, helium white dwarf formation, and the initial mass function as well as the UV upturn in metal-rich galaxies.

Near field radiative heat transfer provides a route for information processing in which thermal radiation, rather than charge transport, serves as the physical carrier of signals. Here, we propose and theoretically analyze a programmable near field radiative thermal computing framework in which radiative coupling, phase change nonlinearity, and thermal state memory are mapped onto neural network inspired operations. The framework is constructed from near field radiative thermal diodes, transistors, and multi terminal logic units separated by nanoscale gaps. Radiative heat flux represents the propagated thermal information, while geometry and material dependent radiative coupling provides physically constrained weighting, and the temperature dependent optical response of phase-change materials enables nonlinear modulation and logic state control. Based on these primitives, we formulate a radiative thermal convolutional network for spatial information processing and a radiative thermal recurrent network for history dependent computation. The recurrent response is associated with radiative feedback, thermal relaxation, and phase change hysteresis, with VO2 providing history dependent short term memory and GST offering a possible route toward non volatile phase storage. We further distinguish the physical radiative networks from a separate software based inverse identification study, in which recurrent machine-learning models are trained on simulated near field heat flux temperature characteristics to recover structural parameters. By establishing a bottom up connection between fluctuational electrodynamics, radiative thermal logic, programmable thermal states, and neural network inspired computation, this study provides a physically grounded basis for exploring non contact thermal information processing at the near field limit.

As computation becomes more central to physics education, creating scalable methods to assess authentic computational thinking (CT) in students remains a critical challenge. While student-written responses capture nuanced reasoning, they are difficult to evaluate at scale. In this study, we investigated the use of Large Language Models (LLMs) to analyze students' written explanations of computational physics problems on a pre- and post- semester survey. By first establishing a human-coded baseline, grounded in CT literature, we identified significant growth in Data Practices and Computational Problem-Solving Practices. When given the same responses, an LLM successfully mirrored the human evaluations and scaled up the detection of these key trends across a large dataset. Notably, both human raters and the LLM struggled to reliably evaluate more complex constructs such as Systems Thinking. Overall, this study demonstrates that LLMs offer a viable method to scale the evaluation of students' CT in large-enrollment physics courses

The development of a solid rind or carapace at the surface of lava flows and domes results in a transition in deformation mechanism from dominantly viscous to elastic or plastic. This transition has a significant impact on the rate and style of emplacement, including on the construction of channelized flows, over-steepened margins, and flow advance due to lava breakouts. These processes are particularly important in subaqueous, subglacial, and extraterrestrial environments in which cooling is accelerated, requiring models specifically calibrated for these environments. We present a new numerical model, Viscous-Elastic Numerically Unified Solver for Solidifying flows (VENUSS), for cooling and solidifying free surface flows. The model couples a viscous fluid interior with an elastic shell whose thickness grows in response to cooling. As a demonstration of the impact of including a solidified crust in the flow model, we show that a dome-like shape fed from below with an elastic shell coupled to the basal topography results in more lateral expansion and less vertical uplift than a comparable highly-viscous rind, demonstrating the need for lateral transfer of stress in solid layers to accurately interpret and predict dome deformation.

In this work, we introduce and experimentally validate a numerical model for a Multiple-Input-Multiple-Output Distributed Acoustic Sensing (MIMO-DAS) system that accounts for dynamic perturbations of fiber birefringence and of the common optical phase of the backscattered signal (or polarization-averaged phase, shared by both polarization tributaries). The MIMO-DAS system probes the fiber using polarization-multiplexed constant-power coded sequences that are suited for coexistence of DAS with WDM data transmission over the same fiber. We study the effect of both axisymmetric and anisotropic events on the two quantities. We demonstrate, through numerical simulations and lab experiments, the estimation of effective birefringence magnitude in static conditions, and the joint estimation of common phase and effective birefringence magnitude in the case of dynamic longitudinal strain and anisotropic transverse strain. This allows for event discrimination and increased sensitivity to disturbances that act transversely on the fiber, since polarization will be responsive to perturbations that break cylindrical symmetry, while the phase will strongly respond to longitudinal strain.

We derive two quantum fluctuation relations for systems undergoing repeated projective measurements. These fluctuation relations characterize the work that can be extracted from a quantum device when a first-detection event triggers a mechanical operation leading to positive work production. The correction to the standard quantum Jarzynski equality depends logarithmically on the mean first-detection time for the time-reversed dynamics. Application of Jensen's inequality leads to fundamental limits on both the total work involved in the repeated measurements and final mechanical operation, and the extracted work alone. The general case of a device connected to an external environment is also considered.

This work aimed to study Miras in the bulge and halo of our galaxy, including those in globular clusters. The AAVSO International Variable Star Index VSX catalogue was used to retrieve Mira variable stars, while the information about globular clusters were taken from the Harris \citep{Harris1976}, McMaster catalogue \citep{33} and Holger Baumgardt \citep{34} table. Stellar characteristics such as metallicity, $T_{\rm eff}$, parallax and colors were obtained by Gaia EDR3 catalogue, Gaia DR3 VariSumarry, Gaia DR3 catalogue, 2MASS Point Source Catalogue, AllWISE, and ZTF catalogue. The UPSILoN program, color-color or color-magnitude diagrams were used to verify that our stars are indeed Miras-type variable stars and whether they are O or C type Miras. To deal with extinction, which affects stars mainly in the galactic bulge, we used IRSA DUST archive, OGLE-III and recalculation to the extiction-free Wesenheit magnitude. We obtained data for 1608 Miras in the bulge, of which 308 are located in 15 globular clusters. For the stars in the halo, we obtained data for 1954 Miras, of which 4 are located in 3 globular clusters. Miras in the bulge show a bimodal metallicity distribution with peaks at \text{–}0.4 dex and $+$0.5 dex, while Miras in the halo show only one peak at $+$0.5 dex. The period of Miras in the bulge is, on average, 30 days longer than for Miras in the halo, and O-type Miras are more abundant in the bulge than C-type Miras. The dependence of the logarithm of the base 10 period on magnitude in the infrared part of the spectrum gives us a linear dependence, with the dependence inverting when a filter is used in the optical part of the spectrum, because of the dust around the Miras.

We experimentally explore the absorption of a propagating wavepacket impinging upon a dissipative region in an engineered quantum system. We employ a 1D non-Hermitian synthetic lattice with an abrupt interface between dissipative and non-dissipative subchains, using the states of the electronic ground-state hyperfine manifold in a $^{87}$Rb Bose-Einstein condensate as sites. By tuning the dissipation rate, we observe a progression from ballistic propagation, to near-perfect absorption, to quantum Zeno reflection. Guided by numerical simulations, we identify that optimal absorption occurs when tunneling and dissipation are properly matched, and find qualitative agreement with an idealized semi-infinite model across all dissipation regimes. Our results establish synthetic lattices as a versatile Quantum simulation platform for dissipation-engineered quantum transport and highlight controlled dissipation as a resource for tailoring quantum dynamics.

We construct explicit error-detecting surgery gadgets—small systems of auxiliary qubits and checks—for the high-rate Iceberg codes $[[2N,2N-2,2]]$, to perform fault-detected measurements of logical Pauli products. The construction follows the perspective of surgery as the gauging of a logical operator, regarded as a symmetry of the code. We give a complete classification of logical Pauli operators under the permutation automorphism group of the Iceberg code, reducing the construction to one gadget per orbit, and we verify with circuit-level simulations that the gadgets are fault-detecting, with the expected post-selected logical error rate. The gadgets require reconfigurable long-range connectivity, available on platforms such as neutral-atom arrays, making an error-detected demonstration of Pauli-based computation a natural near-term experiment. The paper doubles as a self-contained introduction to gauging and code surgery, developed alongside a simple worked example.

Full-tensor anisotropy transforms rigorous coupled-wave analysis (RCWA) into a large, fully coupled non-Hermitian eigenproblem, making eigendecomposition expensive and difficult to differentiate. We introduce a differentiable, eigendecomposition-free RCWA framework for spatially patterned media with fully coupled permittivity tensors, using boundary fields rather than internal eigenmodes as the layer representation. A boundary-value cascade constructs scattering operators directly from these fields, enabling automatic differentiation and efficient GPU execution. Benchmarks against finite-element and transfer-matrix solutions show close agreement in scattering responses, while automatic-differentiation gradients agree with finite differences and enable topology optimization. At 529 Fourier harmonics, layer construction is 22.8 times faster than conventional eigendecomposition on the same GPU. Our framework offers a general computational route toward scalable forward modeling and inverse design in anisotropic photonic systems.

Bubble growth in silicate melts drives significant volume expansion, which has a first order control on magma transport dynamics. When magmas are exposed to external environments, heat and volatile loss at free surfaces can reverse bubble growth, leading to shrinkage and complex feedbacks between diffusion, rheology, and flow. To resolve how magma flow controls, or is controlled by, bubble expansion, we couple a micro-mechanical model for volatile diffusion into individual bubbles, with a macro-scale thermal evolution and fluid flow of the surrounding magmatic suspension. This two-way coupling captures the co-evolution of bubble size, melt viscosity, and pressure gradients, allowing both growth and resorption to emerge naturally from local conditions. We identify distinct dynamical regimes governed by (i) bubble growth limited by (a) viscous resistance or (b) diffusion at the bubble scale, (ii) viscous transport of the suspension, (iii) outgassing through permeable porous networks and exposed magma-fluid interfaces, and (iv) thermal quenching. Across these regimes, thin, high-viscosity boundary layers arising from temperature and volatile concentration gradients play a central role in modulating flow and bubble evolution. The model is implemented in a flexible, modular numerical framework (Multiscale Vesiculation, Fluid flow, Failure, and Interaction Nonlinear model: MVFFIN) enabling extension to a wide range of systems and applications, including conduit flow and pyroclast evolution. By resolving the interplay between internal bubble dynamics and external boundary conditions, this approach provides a unified framework for understanding multiscale degassing and its impact on magmatic transport and fragmentation.

The physics of spreading in static networks is well understood through mappings to percolation. We show that spreading dynamics on temporal networks can analogously be mapped to reachability in temporal event graphs. This provides a theoretical and computational framework for a class of processes, such as variants of the susceptible-infected-susceptible model. Without explicit simulations, through the component analysis of event graphs, we obtain epidemic prevalence and derive epidemic thresholds for temporal networks with arbitrary degree and inter-event time distributions, with significant computational advantages as compared to explicit simulations.

Compact cesium beam clocks are major frequency references for deployable timing systems. However, further improvement of their short-term frequency stability is limited by the clock signal-to-noise ratio (SNR). Although two-laser optical pumping can increase the effective atomic utilization, the achievable clock SNR has long been limited by laser-induced frequency-to-amplitude noise conversion. Here, we demonstrate a compact dual-Faraday-laser-pumped (DFP) Cs beam clock enabled by a low-frequency-noise atom-referenced laser architecture. The intracavity Faraday anomalous dispersion optical filter provides inherent alignment to the Cs D$_2$ resonances, while modulation transfer spectroscopy offers suppressed frequency noise and drift. The resulting laser system supports robust turnkey operation with a Lorentzian linewidth of 2.12 kHz. The DFP Cs clock achieves a clock SNR of 46,365 in a 1-Hz bandwidth and a fractional Allan deviation of $7.7\times 10^{-13}/\sqrt\tau$ , with Hadamard deviation reaching $7.7\times 10^{-15}$ at 10,000 s. This work pushes the fractional frequency stability of a compact Cs beam clock into the $10^{-13}/\sqrt\tau$ regime, providing a pathway toward high-performance Cs frequency references for field-deployable precision timing, navigation, and synchronization.

Can one neural wave function describe both a Bose condensate and a chiral topological liquid? We introduce ChernFormer, which combines a fermionic transformer with a fixed Chern-Simons phase that attaches one statistical vortex to every particle pair. Each factor changes sign under exchange, so their product is exactly bosonic. The fixed phase changes statistics but not probability, making every bosonic learning problem equivalent to a fermionic one with the same approximation error and overlap. With enough capacity, ChernFormer can approximate any normalizable bosonic wave function on the plane at fixed particle number. A finite, smooth network still vanishes when particles meet, yet this contact hole can shrink while the wave function and condensate fraction approach those of a nodeless condensate. Following the needle-in-a-haystack target-reconstruction benchmark introduced in \cite{NazaryanGaggioliTengFu2025}, we test ChernFormer on the Kalmeyer–Laughlin ground state and its first two chiral edge states. The overlap curves stay close to unity through their largest sampled sizes, while independent amplitude and phase maps at $N=20$ for all three states recover both local Laughlin vortices and the collective edge vortex. By contrast, a continuous, nonzero product of identical particle-wise factors misses these elementary edge sectors. ChernFormer therefore provides one variational language for conventional bosonic order and chiral topological matter.

We report on the search performed for a diffuse astrophysical neutrino flux from the full sky and from a specific region of the Galactic plane, the Galactic Ridge. The study uses the dataset collected with the first KM3NeT/ARCA configurations with 6, 8, 19, and 21 active detection units, corresponding to a total livetime of 640 days. For the all-sky analysis, the fitted single-flavour astrophysical neutrino flux parameters, under the single power-law assumption, are $\phi_0^{1f} = 3.0^{+2.1}_{-2.0} \times 10^{-18}$ GeV$^{-1}$ cm$^{-2}$ s$^{-1}$ sr$^{-1}$ with spectral index $\gamma = 3.00^{+0.30}_{-0.35}$ at 68% credible level. The Galactic Ridge fit does not yield constraints for the flux parameters with the current sensitivity. For both analyses upper limits are derived and compared with state-of-the-art measurements. While the analysis of these datasets has not yielded statistically significant results, the developed methods provide a solid basis for future measurements with the KM3NeT detector.

We present a formulation and numerical results for positronium (Ps) laser cooling. The formulation is based on the Lindblad master equation and follows the time evolution of the density matrix of Ps atoms. It therefore accounts for atomic coherence, which is necessary to describe the interaction of Ps with the train of short laser pulses generated by the system developed by Shu $\textit{et al.}$ [K. Shu $\textit{et al.}$, Phys. Rev. A $\textbf{109}$, 043520 (2024)]. Using this formulation, we calculate the time evolution of the populations in each internal and momentum state and thereby quantitatively predict the momentum distribution after laser cooling. We present the representative time evolution of the internal-state populations and momentum distribution, together with a comprehensive scan of the laser parameters used to optimize the cooling efficiency. A prominent feature of the simulated distributions is sub-recoil cooling through velocity-selective coherent population trapping, a coherent effect captured by the quantum-mechanical treatment.

Objective: To quantify the impact of high-resolution deep silicon photon-counting CT (dSi-PCCT) on coronary stenosis quantification in anatomically realistic calcified coronary artery phantoms using Micro-CT as ground truth. Methods: Twelve vessel sections representing four calcification geometries (Type I-IV) and three luminal iodine concentrations (10, 15, and 20 mg/mL) were scanned under static conditions using energy-integrating detector CT (EID-CT), dSi-PCCT, and Micro-CT. Images were registered to Micro-CT and segmented using an automated threshold-based pipeline. The primary analysis compared longitudinal profiles of Micro-CT-referenced percent area stenosis and segmented vessel area. A secondary analysis evaluated ellipse-derived percent area stenosis and percent vessel-area deviation at the maximum-calcification cross-section. Results: dSi-PCCT reduced whole-profile mean absolute error in Micro-CT-referenced percent area stenosis from 3.10% with EID-CT to 1.62% (p=0.027) and reduced segmented vessel-area error from 0.55 to 0.31 mm2 (p=0.001). In the secondary analysis, absolute deviations in ellipse-derived percent area stenosis ranged from 0.1% to 6.5% for dSi-PCCT and from 0.8% to 24.2% for EID-CT (p<0.001). Mean absolute differences in percent vessel-area deviation from Micro-CT were also lower with dSi-PCCT than with EID-CT (15.0% vs 26.6%, p<0.001). Conclusion: Under static, resolution-optimized conditions, dSi-PCCT improved task-based coronary stenosis quantification and vessel delineation relative to EID-CT, supporting further evaluation in dynamic phantoms and clinical CCTA.

Scattering amplitudes admit a factorised structure in special kinematic limits, such as the soft and collinear limits. In this work, we investigate the multi-particle collinear limits of massless amplitudes at high perturbative orders, focusing on the exploration of the mechanisms via which strict collinear factorisation of $n$-particle scattering amplitudes is realised when $m$ particles become collinear. We show through four loops that the requirements on the structure of the massless soft anomalous dimension that are imposed by strict collinear factorisation in all two-particle collinear limits are enough to guarantee factorisation also in any multi-particle collinear limit. Demanding that strict collinear factorisation of massless partons is satisfied also for amplitudes that contain a massive coloured particle, we derive new constraints on the soft anomalous dimension by considering the collinear limit of three massless particles.

I analyze the pseudoreal confining $\mathcal{N}=1$ SUSY gauge theories deformed by anomaly mediated SUSY breaking (AMSB). Taking the conjecture that the AMSB and non-SUSY limits are in the same universality class, I find broadly that the non-SUSY confining pseudoreal gauge theories of this class have no massless vectors in their spectra, and that all but one are fully gapped. This contradicts recent expectations from tumbling. I explore whether or not non-standard tumbling could reconcile the two pictures, and find that it would require condensation in repulsive channels in three of the cases, and that in one case it would require condensation in a higher-order channel. I briefly comment on the additional theories that may be in the conformal window, and find that their SUSY versions are consistent with flowing to superconformal fixed points.

Solving the Vehicle Routing Problem (VRP) in Stochastic Transportation Networks (STNs), a core task in Intelligent Transportation Systems (ITS), introduces estimation challenges for stochastic path travel times and the resulting VRP objective function. These challenges have typically been addressed through computationally expensive sampling-based techniques such as Monte Carlo simulation, whose performance depends on sample size, the sampling strategy, and the underlying travel time distributions. To address these issues, this study proposes and validates a quantum computing technique, Quantum Amplitude Estimation (QAE) for path-level travel time estimation in STNs. Without relying on sampling or prior assumptions of the travel time distribution, the proposed framework encodes all feasible travel time realizations into a quantum superposition, enabling a theoretical quadratic speed-up over Monte Carlo simulation. Four QAE variants are implemented in IBM's Qiskit framework, namely Canonical AE (CAE), Iterative AE (IAE), Maximum Likelihood AE (MLAE), and Faster AE (FAE), together with four rotation-angle scaling strategies for handling different discrete travel time distributions. Experiments on a small-scale STN show that the choice of scaling method and rotation-angle range significantly affects estimation accuracy, while the four QAE variants produce comparable estimates across all tested conditions, with IAE exhibiting the most stable overall performance. The results provide practical guidance on parameter selection for future hybrid quantum-classical optimization frameworks in ITS applications.

A thermodynamic theory for transport coefficients in hard-sphere fluids is developed from a general expression for the Onsager matrix. The theory predicts the ratio $\sigma/\sigma_{\rm id}$, where $\sigma$ is a transport coefficient and $\sigma_{\rm id}$ denotes its dilute-gas value. This ratio depends exclusively on equilibrium thermodynamic properties and can therefore be computed directly from the equation of state. Compact expressions are obtained for the thermal conductivity, viscosity, and self-diffusion coefficient. These expressions agree closely with simulation data at low and intermediate densities and remain useful across the fluid range, although deviations increase near freezing, particularly for viscosity. The self-diffusion prediction substantially improves upon Enskog theory. These results support a thermodynamic description of transport coefficients relative to their dilute-gas values.

Modal synthesis is a widely-used technique for simulation of musical instrument dynamics. In the linear case, a modal decomposition leads to an uncoupled system of damped and forced harmonic oscillators which can be efficiently solved by standard time-stepping methods. However, extensions to nonlinear problems are challenging due to the presence of products of modal expansions in the governing equations. In the case of the Föppl-von Kármán plate, the nonlinear coupling between the modes is described by a fourth-order tensor and is prohibitively expensive to evaluate in the modal domain. In this work, we propose a pseudospectral method in which the products are evaluated on a grid in the spatial domain while spatial derivatives are computed exactly in the modal domain. Discrete sine and cosine transforms between the modal and spatial domains are used to impose simply supported boundary conditions for the plate. Finally, we prove non-negativity of the nonlinear potential energy of the system and employ a scalar auxiliary variable technique for explicit and stable time integration in the modal domain. As a result, we reduce the computational cost of modal synthesis while preserving its advantages like a precise control over the simulated frequency range. Sound examples are presented.