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We analyze experimental data on double diffusive convection in an electrochemical cell in the finger regime. All fingers in the experiments are bounded on at least one end by a solid wall. The properties of these fingers are compared with those of fingers in other experiments which are surrounded by fluid on all sides. The compositional boundary layers are found to be thinner than the finger width. The finger thickness agrees well with half the wavelength of the fastest growing mode obtained in linear stability analysis. The ion transport through the boundary layers is reduced by two orders of magnitude compared with unbounded fingers. The overturning layers in staircases contribute negligibly to salinity mixing because of efficient transport between finger layers and convection rolls.

We report the masses, sizes, and orbital properties of 86 planets orbiting 55 stars observed by NASA's K2 Mission with follow-up Doppler measurements by the HIRES spectrometer at the W. M. Keck Observatory and the Automated Planet Finder at Lick Observatory. Eighty-one of the planets were discovered from their transits in the K2 photometry, while five were found based on subsequent Doppler measurements of transiting planet host stars. The sizes of the transiting planets range from Earth-size to larger than Jupiter (1-3 REarth is typical), while the orbital periods range from less than a day to a few months. For 32 of the planets, the Doppler signal was detected with significance greater than 5-sigma (51 were detected with >3-sigma significance). An important characteristic of this catalog is the use of uniform analysis procedures to determine stellar and planetary properties. This includes the transit search and fitting procedures applied to the K2 photometry, the Doppler fitting techniques applied to the radial velocities, and the spectral modeling to determine bulk stellar parameters. Such a uniform treatment will make the catalog useful for statistical studies of the masses, densities, and system architectures of exoplanetary systems. This work also serves as a data release for all previously unpublished RVs and associated stellar activity indicators obtained by our team for these systems, along with derived stellar and planet parameters., Comment: 156 pages, 86 planets, 55 stars, 104 figures, 48 tables. Accepted to ApJS

We investigate the increase in efficiency of simulated and parallel tempering MCMC algorithms when using non-reversible updates to give them "momentum". By making a connection to a certain simple discrete Markov chain, we show that, under appropriate assumptions, the non-reversible algorithms still exhibit diffusive behaviour, just on a different time scale. We use this to argue that the optimally scaled versions of the non-reversible algorithms are indeed more efficient than the optimally scaled versions of their traditional reversible counterparts, but only by a modest speed-up factor of about 42%.

We present the results of the Distant Giants Survey, a three-year radial velocity (RV) campaign to search for wide-separation giant planets orbiting Sun-like stars known to host an inner transiting planet. We defined a distant giant to have $a$ = 1--10 AU and $M_{p} \sin i = 70-4000$ \mearth~ = 0.2-12.5 \mj, and required transiting planets to have $a<1$ AU and $R_{p} = 1-4$ \rearth. We assembled our sample of 47 stars using a single selection function, and observed each star at monthly intervals to obtain $\approx$30 RV observations per target. The final catalog includes a total of twelve distant companions: four giant planets detected during our survey, two previously known giant planets, and six objects of uncertain disposition identified through RV/astrometric accelerations. Statistically, half of the uncertain objects are planets and the remainder are stars/brown dwarfs. We calculated target-by-target completeness maps to account for missed planets. We found evidence for a moderate enhancement of distant giants (DG) in the presence of close-in small planets (CS), P(DG|CS) = $30^{+14}_{-12}\%$, over the field rate of P(DG) = $16^{+2}_{-2}\%$. No enhancement is disfavored ($p \sim$ 8%). In contrast to a previous study, we found no evidence that stellar metallicity enhances P(DG|CS). We found evidence that distant giant companions are preferentially found in systems with multiple transiting planets and have lower eccentricities than randomly selected giant planets. This points toward dynamically cool formation pathways for the giants that do not disturb the inner systems., Comment: 32 pages, 20 figures, 4 tables. Comments welcome

Retrieval-augmented generation (RAG) has recently become a very popular task for Large Language Models (LLMs). Evaluating them on multi-turn RAG conversations, where the system is asked to generate a response to a question in the context of a preceding conversation is an important and often overlooked task with several additional challenges. We present MTRAG: an end-to-end human-generated multi-turn RAG benchmark that reflects several real-world properties across diverse dimensions for evaluating the full RAG pipeline. MTRAG contains 110 conversations averaging 7.7 turns each across four domains for a total of 842 tasks. We also explore automation paths via synthetic data and LLM-as-a-Judge evaluation. Our human and automatic evaluations show that even state-of-the-art LLM RAG systems struggle on MTRAG. We demonstrate the need for strong retrieval and generation systems that can handle later turns, unanswerable questions, non-standalone questions, and multiple domains. MTRAG is available at https://github.com/ibm/mt-rag-benchmark.

We present timing solutions spanning nearly two decades for five redback (RB) systems found in globular clusters (GC), created using a novel technique that effectively "isolates" the pulsar. By accurately measuring the time of passage through periastron ($T_0$) at points over the timing baseline, we use a piecewise-continuous, binary model to get local solutions of the orbital variations that we pair with long-term orbital information to remove the orbital timing delays. The isolated pulse times of arrival can then be fit to describe the spin behavior of the millisecond pulsar (MSP). The results of our timing analyses via this method are consistent with those of conventional timing methods for binaries in GCs as demonstrated by analyses of NGC 6440D. We also investigate the observed orbital phase variations for these systems. Quasi-periodic oscillations in Terzan 5P's orbit may be the result of changes to the gravitational-quadruple moment of the companion as prescribed by the Applegate model. We find a striking correlation between the standard deviation of the phase variations as a fraction of a system's orbit ($\sigma_{\Delta T_0}$) and the MSP's spin frequency, as well as a potential correlation between $\sigma_{\Delta T_0}$ and the binary's projected semi-major axis. While long-term RB timing is fraught with large systematics, our work provides a needed alternative for studying systems with significant orbital variations, especially when high-cadence monitoring observations are unavailable., Comment: 23 pages, 10 figures, 3 tables, Submitted for publication in ApJ

Many quantum systems exhibit high sensitivity to their initial conditions, where microscopic quantum fluctuations can significantly influence macroscopic observables. Understanding how quantum states may influence the behavior of nonlinear dynamic systems may open new avenues in controlling light-matter interactions. To explore this issue, we analyze the sensitivity of a fundamental quantum optical process - parametric oscillation - to quantum initializations. Focusing on optical parametric oscillators (OPOs), we demonstrate that the quantum statistics of arbitrary initial states are imprinted in the early-stage dynamics and can persist in the steady-state probabilities. We derive the "quantum sensitivity" of parametric oscillators, linking the initial quantum state to the system's steady-state outcomes, highlighting how losses and parametric gain govern the system's quantum sensitivity. Moreover, we show that these findings extend beyond OPOs to a broader class of nonlinear systems, including Josephson junction based superconducting circuits. Our work opens the way to a new class of experiments that can test the sensitivity of macroscopic systems to quantum initial conditions and offers a pathway for controlling systems with quantum degrees of freedom., Comment: 6 pages, 4 figures; added references

We investigate lower bounds on the subgeometric convergence of adaptive Markov chain Monte Carlo under any adaptation strategy. In particular, we prove general lower bounds in total variation and on the weak convergence rate under general adaptation plans. If the adaptation diminishes sufficiently fast, we also develop comparable convergence rate upper bounds that are capable of approximately matching the convergence rate in the subgeometric lower bound. These results provide insight into the optimal design of adaptation strategies and also limitations on the convergence behavior of adaptive Markov chain Monte Carlo. Applications to an adaptive unadjusted Langevin algorithm as well as adaptive Metropolis-Hastings with independent proposals and random-walk proposals are explored.

We present the results of a Keck and NOEMA spectroscopic survey of 507 galaxies, where we confirm the presence of two massive overdensities at $z = 3.090 - 3.110$ and $z = 3.133 - 3.155$ in the neighborhood of the GOODS-N, each with over a dozen spectroscopically confirmed members. We find that both of these have galaxy overdensities of NIR-detected galaxies of $\delta_{\rm gal, obs} = 6 - 9$ within corrected volumes of $(6 - 7) \times 10^3~{\rm cMpc}^3$. We estimate the properties of the $z = 0$ descendants of these overdensities using a spherical collapse model and find that both should virialize by $z \simeq 0.5 - 0.8$, with total masses of $M_{\rm tot} \simeq (6 - 7) \times 10^{14}~{\rm M}_\odot$. The same spherical collapse calculations, as well as a clustering-of-clusters statistical analysis, suggest a >80% likelihood that the two overdensities will collapse into a single cluster with $M_{\rm tot} = (1.0 - 1.5) \times 10^{15}~{\rm M}_\odot$ by $z \sim 0.1-0.4$. The $z = 3.14$ substructure contains a core of four bright dusty star-forming galaxies with $\Sigma {\rm SFR} = 2700 \pm 700~{\rm M}_\odot~{\rm yr}^{-1}$ in a volume of only 280 ${\rm cMpc}^3$., Comment: 18 pages, 8 figures. Accepted to ApJ

We present a 34-year timing solution of the redback pulsar system Terzan 5A (Ter5A). Ter5A, also known as B1744$-$24A or J1748$-$2446A, has a 11.56 ms pulse period, a $\sim$0.1 solar mass dwarf companion star, and an orbital period of 1.82 hours. Ter5A displays highly variable eclipses and orbital perturbations. Using new timing techniques, we have determined a phase-connected timing solution for this system over 34 years. This is the longest ever published for a redback pulsar. We find that the pulsar's spin variability is much larger than most globular cluster pulsars. In fact, of the nine redback pulsars with published or in preparation long-term timing solutions, Ter5A is by far the noisiest. We see no evidence of strong correlations between orbital and spin variability of the pulsar. We also find that long-term astrometric timing measurements are likely too contaminated by this variability to be usable, and therefore require careful short-term timing to determine reasonable positions. Finally, we measure an orbital period contraction of $-2.5(3) \times 10^{-13}$, which is likely dominated by the general relativistic orbital decay of the system. The effects of the orbital variability due to the redback nature of the pulsar are not needed to explain the observed orbital period derivative, but they are constrained to less than $\sim$30% of the observed value.

With plasma currents up to 8.7 MA, the SPARC tokamak runs the risk of forming multi-MA beams of relativistic "runaway" electrons (REs) which could damage plasma facing components if unmitigated. The infrared (IR) and visible imaging and visible spectroscopy systems in SPARC are designed with measurements of synchrotron emission from REs in mind. Synchrotron radiation is emitted by REs along their direction of motion, opposite the plasma current. Matched clockwise and counterclockwise wide views are proposed to detect synchrotron and background radiation, allowing observation of RE synchrotron emission in both plasma current configurations. Due to SPARC's high toroidal magnetic field strength, 12.2 T on axis, the synchrotron light spectrum is expected to peak in the visible-IR wavelength range. The synthetic diagnostic tool SOFT (Synchrotron Orbit-Following Toolkit) is used to model synchrotron images and spectra for three scenarios, with appropriate magnetic equilibria for each: REs generated during plasma current ramp-up, steady-state flattop (although unlikely, but serving as a reference), and disruptions. Required time resolutions, achievable spatial coverage, and appropriate spectral ranges for various RE energies are assessed.

We study the complexity of testing properties of quantum channels. First, we show that testing identity to any channel $\mathcal N: \mathbb C^{d_{\mathrm{in}} \times d_{\mathrm{in}}} \to \mathbb C^{d_{\mathrm{out}} \times d_{\mathrm{out}}}$ in diamond norm distance requires $\Omega(\sqrt{d_{\mathrm{in}}} / \varepsilon)$ queries, even in the strongest algorithmic model that admits ancillae, coherence, and adaptivity. This is due to the worst-case nature of the distance induced by the diamond norm. Motivated by this limitation and other theoretical and practical applications, we introduce an average-case analogue of the diamond norm, which we call the average-case imitation diamond (ACID) norm. In the weakest algorithmic model without ancillae, coherence, or adaptivity, we prove that testing identity to certain types of channels in ACID distance can be done with complexity independent of the dimensions of the channel, while for other types of channels the complexity depends on both the input and output dimensions. Building on previous work, we also show that identity to any fixed channel can be tested with $\tilde O(d_{\mathrm{in}} d_{\mathrm{out}}^{3/2} / \varepsilon^2)$ queries in ACID distance and $\tilde O(d_{\mathrm{in}}^2 d_{\mathrm{out}}^{3/2} / \varepsilon^2)$ queries in diamond distance in this model. Finally, we prove tight bounds on the complexity of channel tomography in ACID distance.

Machine Learning as a Service (MLaaS) is often provided as a pay-per-query, black-box system to clients. Such a black-box approach not only hinders open replication, validation, and interpretation of model results, but also makes it harder for white-hat researchers to identify vulnerabilities in the MLaaS systems. Model extraction is a promising technique to address these challenges by reverse-engineering black-box models. Since training data is typically unavailable for MLaaS models, this paper focuses on the realistic version of it: data-free model extraction. We propose a data-free model extraction approach, CaBaGe, to achieve higher model extraction accuracy with a small number of queries. Our innovations include (1) a novel experience replay for focusing on difficult training samples; (2) an ensemble of generators for steadily producing diverse synthetic data; and (3) a selective filtering process for querying the victim model with harder, more balanced samples. In addition, we create a more realistic setting, for the first time, where the attacker has no knowledge of the number of classes in the victim training data, and create a solution to learn the number of classes on the fly. Our evaluation shows that CaBaGe outperforms existing techniques on seven datasets -- MNIST, FMNIST, SVHN, CIFAR-10, CIFAR-100, ImageNet-subset, and Tiny ImageNet -- with an accuracy improvement of the extracted models by up to 43.13%. Furthermore, the number of queries required to extract a clone model matching the final accuracy of prior work is reduced by up to 75.7%.

For random-walk Metropolis (RWM) and parallel tempering (PT) algorithms, an asymptotic acceptance rate of around 0.234 is known to be optimal in the high-dimensional limit. However, its practical relevance is uncertain due to restrictive derivation conditions. We synthesise previous theoretical advances in extending the 0.234 acceptance rate to more general settings, and demonstrate its applicability with a comprehensive empirical simulation study on examples examining how acceptance rates affect Expected Squared Jumping Distance (ESJD). Our experiments show the optimality of the 0.234 acceptance rate for RWM is surprisingly robust even in lower dimensions across various proposal and multimodal target distributions which may or may not have an i.i.d. product density. Parallel tempering experiments also show that the idealized 0.234 spacing of inverse temperatures may be approximately optimal for low dimensions and non i.i.d. product target densities, and that constructing an inverse temperature ladder with spacings given by a swap acceptance of 0.234 is a viable strategy. However, we observe the applicability of the 0.234 acceptance rate heuristic diminishes for both RWM and PT algorithms below a certain dimension which differs based on the target density, and that inhomogeneously scaled components in the target density further reduces its applicability in lower dimensions., Comment: Submitted to Communications in Statistics - Simulation and Computation

In this bachelor's thesis, isotope effects for pedestal instabilities have been studied based on an ASDEX Upgrade H-Mode scenario. This was done using the JOREK code for extended MHD simulations, including the ion diamagnetic drift and the establishment of ExB flows. Simulations with single toroidal harmonics were performed for multiple times during the build-up of the pedestal, to assess the evolution of the linear stability of modes occurring near the edge. When changing the average ion masses from 2.0 to 2.5 and 3.0, the variations were small, and MHD's momentum equation was shown to be the major cause for them. As a second step, simulations with multiple toroidal harmonics were performed to simulate an Edge Localized Mode (ELM) crash, again comparing between the average ion masses of 2.0, 2.5, and 3.0. The resulting variations of heat and particle losses were compared to JET results. The experimental differences between ion masses could not be reproduced. Together with the fact that the simulations' pedestal for an average ion mass of 2.5 and 3.0 was not matched to the experiment, this indicates that other effects, such as small-scale turbulences, must be included - for example, by adapting the simulations' transport coefficients - to explain the experimental differences.

We review and provide new proofs of results used to compare the efficiency of estimates generated by reversible MCMC algorithms on a general state space. We provide a full proof of the formula for the asymptotic variance for real-valued functionals on $\phi$-irreducible reversible Markov chains, first introduced by Kipnis and Varadhan. Given two Markov kernels $P$ and $Q$ with stationary measure $\pi$, we say that the Markov kernel $P$ efficiency dominates the Markov kernel $Q$ if the asymptotic variance with respect to $P$ is at most the asymptotic variance with respect to $Q$ for every real-valued functional $f\in L^2(\pi)$. Assuming only a basic background in functional analysis, we prove that for two $\phi$-irreducible reversible Markov kernels $P$ and $Q$, $P$ efficiency dominates $Q$ if and only if the operator $Q-P$, where $P$ is the operator on $L^2(\pi)$ that maps $f\mapsto\int f(y)P(\cdot,dy)$ and similarly for $Q$, is positive on $L^2(\pi)$, i.e. $\langle f,(Q-P)f\rangle\geq0$ for every $f\in L^2(\pi)$. We use this result to show that reversible antithetic kernels are more efficient than i.i.d. sampling, and that efficiency dominance is a partial ordering on $\phi$-irreducible reversible Markov kernels. We also provide a proof based on that of Tierney that Peskun dominance is a sufficient condition for efficiency dominance for reversible kernels. Using these results, we show that Markov kernels formed by randomly selecting other "component" Markov kernels will always efficiency dominate another Markov kernel formed in this way, as long as the component kernels of the former efficiency dominate those of the latter. These results on the efficiency dominance of combining component kernels generalises the results on the efficiency dominance of combined chains introduced by Neal and Rosenthal from finite state spaces to general state spaces., Comment: 27 pages

Waveguide quantum electrodynamics, the study of atomic systems interacting with propagating electromagnetic fields, is a powerful platform for understanding the complex interplay between light and matter. Qubit control is an indispensable tool in this field, and most experiments have so far focused on narrowband electromagnetic waves that interact with qubits at specific frequencies. This interaction, however, changes significantly with fast, broadband pulses, as waveguide properties like dispersion affect the pulse evolution and its impact on the qubit. Here, we use dispersion to achieve spatial addressing of superconducting qubits separated by a sub-wavelength distance within a microwave waveguide. This novel approach relies on a self-focusing effect to create a position-dependent interaction between the pulse and the qubits. This experiment emphasizes the importance of dispersion in the design and analysis of quantum experiments, and offers new avenues for the rapid control of quantum states.

Experimental measurements of plasma and neutral profiles across the pedestal are used in conjunction with 2D edge modeling to examine pedestal stiffness in Alcator C-Mod H-mode plasmas. Experiments on Alcator C-Mod observed pedestal degradation and loss in confinement below a critical value of net power crossing the separatrix, $P_\mathrm{net} = P_\mathrm{net}^\mathrm{crit} \approx 2.3$ MW. New analysis of ionization and particle flux profiles reveal saturation of the pedestal electron density, $n_{e}^\mathrm{ped}$ despite continuous increases in ionization throughout the pedestal, inversely related to $P_\mathrm{net}$. A limit to the pedestal $\nabla n_{e}$ emerges as the particle flux, $\Gamma_{D}$ continues to grow, implying increases in the effective particle diffusivity, $D_\mathrm{eff}$. This is well-correlated with the separatrix collisionality, $\nu^{*}_\mathrm{sep}$ and a turbulence control parameter, $\alpha_{t}$, implying a possible transition in type of turbulence. The transition is well correlated with the experimentally observed value of $P_\mathrm{net}^\mathrm{crit}$. SOLPS-ITER modeling is performed for select discharges from the power scan, constrained with experimental electron and neutral densities, measured at the outer midplane. The modeling confirms general growth in $D_\mathrm{eff}$, consistent with experimental findings, and additionally suggests even larger growth in $\chi_{e}$ at the same $P_\mathrm{net}^\mathrm{crit}$.

This article develops general conditions for weak convergence of adaptive Markov chain Monte Carlo processes and is shown to imply a weak law of large numbers for bounded Lipschitz continuous functions. This allows an estimation theory for adaptive Markov chain Monte Carlo where previously developed theory in total variation may fail or be difficult to establish. Extensions of weak convergence to general Wasserstein distances are established along with a weak law of large numbers for possibly unbounded Lipschitz functions. Applications are applied to auto-regressive processes in various settings, unadjusted Langevin processes, and adaptive Metropolis-Hastings., Comment: Fixed a typo in Assumption 4 and added improvements to Section 8

In this paper, we initiate the study of constant dimension subspace codes restricted to Schubert varieties, which we call Schubert subspace codes. These codes have a very natural geometric description, as objects that we call intersecting sets with respect to a fixed subspace. We provide a geometric construction of maximum size constant dimension subspace codes in some Schubert varieties with the largest possible value for the minimum subspace distance. Finally, we generalize the problem to different values of the minimum distance.

The Transiting Exoplanet Survey Satellite (TESS) has discovered hundreds of new worlds, with TESS planet candidates now outnumbering the total number of confirmed planets from $\textit{Kepler}$. Owing to differences in survey design, TESS continues to provide planets that are better suited for subsequent follow-up studies, including mass measurement through radial velocity (RV) observations, compared to Kepler targets. In this work, we present the TESS-Keck Survey's (TKS) Mass Catalog: a uniform analysis of all TKS RV survey data which has resulted in mass constraints for 126 planets and candidate signals. This includes 58 mass measurements that have reached $\geq5\sigma$ precision. We confirm or validate 32 new planets from the TESS mission either by significant mass measurement (15) or statistical validation (17), and we find no evidence of likely false positives among our entire sample. This work also serves as a data release for all previously unpublished TKS survey data, including 9,204 RV measurements and associated activity indicators over our three year survey. We took the opportunity to assess the performance of our survey, and found that we achieved many of our goals including measuring the mass of 38 small ($<4R_{\oplus}$) planets, nearly achieving the TESS mission's basic science requirement. In addition, we evaluated the performance of the Automated Planet Finder (APF) as survey support and observed meaningful constraints on system parameters due to its more uniform phase coverage. Finally, we compared our measured masses to those predicted by commonly used mass-radius relations and investigated evidence of systematic bias., Comment: 51 pages (22 of text), 24 figures

Large Language Models (LLM) have become a popular approach for implementing Retrieval Augmented Generation (RAG) systems, and a significant amount of effort has been spent on building good models and metrics. In spite of increased recognition of the need for rigorous evaluation of RAG systems, few tools exist that go beyond the creation of model output and automatic calculation. We present InspectorRAGet, an introspection platform for RAG evaluation. InspectorRAGet allows the user to analyze aggregate and instance-level performance of RAG systems, using both human and algorithmic metrics as well as annotator quality. InspectorRAGet is suitable for multiple use cases and is available publicly to the community. The demo video is available at https://youtu.be/MJhe8QIXcEc