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Magnetic reconnection is a ubiquitous process in plasma physics, driving rapid and energetic events such as coronal mass ejections. Reconnection between magnetic fields with arbitrary shear can be decomposed into an anti-parallel, reconnecting component, and a non-reconnecting guide-field component which is parallel to the reconnecting electric field. This guide field modifies the structure of the reconnection layer and the reconnection rate. We present results from experiments on the MAIZE pulsed-power generator (500 kA peak current, 200 ns rise-time) which use two exploding wire arrays, tilted in opposite directions, to embed a guide field in the plasma flows with a relative strength $b\equiv B_g/B_{rec}=\text{0, 0.4, or 1}$. The reconnection layers in these experiments have widths which are less than the ion skin depth, $d_i=c/\omega_{pi}$, indicating the importance of the Hall term, which generates a distinctive quadrupolar magnetic field structure along the separatrices of the reconnection layer. Using laser imaging interferometry, we observe quadrupolar structures in the line-integrated electron density, consistent with the interaction of the embedded guide field with the quadrupolar Hall field. Our measurements extend over much larger length scales ($40 d_i$) at higher $\beta$ ($\sim 1$) than previous experiments, providing an insight into the global structure of the reconnection layer., Comment: 12 pages, 9 figures. Submitted to Physics of Plasmas for review

Context. Binary star systems allow us to study the planet formation process under extreme conditions. In the early stages, these systems contain a circumbinary disk and a disk around each star. To model the interactions between these disks in the frame of one of the stars, strong fictitious forces must be included in the simulations. The original Fargo and the Fargo3D codes fail to correctly simulate such systems if the indirect term becomes too strong. Aims. We present a different way to compute the indirect term which, together with a tensor artificial viscosity prescription, allows the Fargo code to simulate the circumbinary disks in a non-inertial frame of reference. In this way, the Fargo code can be used to study interactions between circumstellar and circumbinary disks. Results. We find that updating the indirect term becomes relevant when the indirect term becomes stronger than the direct gravitational forces, which occurs for mass ratios of $q > 5\%$. The default artificial viscosity used in the Fargo code inherently produces artificial pressure in a non-inertial frame of reference even in the absence of shocks. This leads to artificial mass ejection from the Hill sphere, starting at brown dwarf masses ($q > 1\%$). These problems can be mitigated by using a tensor artificial viscosity formulation. For high mass ratios, $q > 1\%$, it is also becomes important to initialize the disk in the center-of-mass frame. We expect our proposed changes to be relevant for other grid-based hydrodynamic codes where strong indirect terms occur, or for codes that use artificial viscosity., Comment: 13 pages, 13 figures, accepted by A&A

This research examines the stability of crossed-field amplifiers (CFAs) and characterizes their different modes of operation: amplification, driven oscillation, and self-excited oscillation. The CFA used in this paper is the Recirculating Planar Crossed-Field Amplifier (RPCFA), which is a high power (MW) pulsed (300 ns) amplifier that operates around 3 GHz. Initially, the RPCFA is shown to be a stable amplifier with moderate gain (5.1 dB), but by either reducing the anode-cathode (AK) gap spacing or increasing the driving current, the amplifier operation transitions from amplification to oscillation. Depending on the operating conditions, these oscillations are either driven by the input RF signal or self-excited. These self-excited oscillations can have a lower synchronization phase velocity than the maximum velocity in the electron beam, implying that slower electrons within the Brillouin hub can interact with electromagnetic modes on the RF circuit. A cold tube analysis of the RPCFA shows that the Q-factor of certain modes on the RF circuit varies significantly when the AK gap geometry of the RPCFA is altered which leads to a discrete shift in operating frequency. The operation of the RPCFA close to Hull cutoff is found to share some key features of magnetically insulated transmission line oscillators (MILO) that could also explain the dramatic frequency shift. Instantaneous phase analysis by Hilbert transforms can be used, in conjunction with the frequency and output power analysis, to determine the onset of the transition from amplification to oscillation, and to characterize the oscillation.

Previous simulations of cataclysmic variables studied either the quiescence, or the outburst state in multiple dimensions or they simulated complete outburst cycles in one dimension using simplified models for the gravitational torques. We self-consistently simulate complete outburst cycles of normal and superoutbursts in cataclysmic variable systems in two dimensions. We study the effect of different $\alpha$ viscosity parameters, mass transfer rates, and binary mass ratios on the disk luminosities, outburst occurrence rates, and superhumps. We simulate non-isothermal, viscous accretion disks in cataclysmic variable systems using a modified version of the FARGO code with an updated equation of state and a cooling function designed to reproduce s-curve behavior. Our simulations can model complete outburst cycles using the thermal tidal instability model. We find higher superhump amplitudes and stronger gravitational torques than previous studies, resulting in better agreement with observations., Comment: Accepted in A&A. 21 pages, 27 figures

Novel reinforcement learning algorithms, or improvements on existing ones, are commonly justified by evaluating their performance on benchmark environments and are compared to an ever-changing set of standard algorithms. However, despite numerous calls for improvements, experimental practices continue to produce misleading or unsupported claims. One reason for the ongoing substandard practices is that conducting rigorous benchmarking experiments requires substantial computational time. This work investigates the sources of increased computation costs in rigorous experiment designs. We show that conducting rigorous performance benchmarks will likely have computational costs that are often prohibitive. As a result, we argue for using an additional experimentation paradigm to overcome the limitations of benchmarking., Comment: 19 pages, 13 figures, The Forty-first International Conference on Machine Learning (ICML 2024)

This paper investigates a new approach to model-based reinforcement learning using background planning: mixing (approximate) dynamic programming updates and model-free updates, similar to the Dyna architecture. Background planning with learned models is often worse than model-free alternatives, such as Double DQN, even though the former uses significantly more memory and computation. The fundamental problem is that learned models can be inaccurate and often generate invalid states, especially when iterated many steps. In this paper, we avoid this limitation by constraining background planning to a set of (abstract) subgoals and learning only local, subgoal-conditioned models. This goal-space planning (GSP) approach is more computationally efficient, naturally incorporates temporal abstraction for faster long-horizon planning and avoids learning the transition dynamics entirely. We show that our GSP algorithm can propagate value from an abstract space in a manner that helps a variety of base learners learn significantly faster in different domains., Comment: Published in the Planning and Reinforcement Learning Workshop at ICAPS 2024. arXiv admin note: text overlap with arXiv:2206.02902

The Brillouin flow is a rectilinear, sheared electron fluid flow in a crossed electric field (E) and magnetic field (B), in the E x B direction with zero flow velocity and zero electric field at the surface with which the flow is in contact. It is broadly considered as the equilibrium electron flow in high power crossed-field devices including the magnetron and magnetically insulated transmission line oscillators. This paper provides an examination of Brillouin flow in two dimensions, in a cylindrical geometry where the anode radius changes abruptly at a single axial location while the cathode surface has a constant radius. Our simulation confirms the proof that there is no equilibrium Brillouin flow solution for such a geometry. It further reveals that this change in the anode radius introduces novel bunching of the electrons within the Brillouin hub. This bunching occurs at low frequencies and is very pronounced if the Brillouin flow is from the small gap region to the large gap region, but is minimal if the Brillouin flow is from the large gap region to the small gap region. New insights are provided into the physical processes that initiate and sustain the bunching processes that are unique for a crossed-field diode, as compared with a non-magnetized diode. We argue that this enhanced bunching, and its concomitant formation of strong vortices, is not restricted to an abrupt change in the anode-cathode gap spacing.

We introduce an ultra-sensitive interferometric protocol that combines weak value amplification (WVA) with traditional interferometry. This WVA+interferometry protocol uses weak value amplification of the relative delay between two paths to enhance the interferometric sensitivity, approaching the quantum limit for classical light. As an example, we demonstrate a proof-of-principle experiment that achieves few-attosecond timing resolution (few-nanometer path length resolution) with a double-slit interferometer using only common optical components. Since our example uses only the spatial shift of double-slit interference fringes, its precision is not limited by the timing resolution of the detectors, but is instead limited solely by the fundamental shot noise associated with classical light. We experimentally demonstrate that the signal-to-noise ratio can be improved by one to three orders of magnitude and approaches the shot-noise limit in the large amplification regime. Previously, quantum-limited WVA delay measurements were thought to require imaginary weak values, which necessitate light with a broad spectral bandwidth and high-resolution spectrometers. In contrast, our protocol highlights the feasibility of using real weak values and narrowband light. Thus, our protocol is a compelling and cost-effective approach to enhance interferometry., Comment: 3 figures

Context: Planet-disk interactions play a crucial role in the understanding of planet formation and disk evolution. There are multiple numerical tools available to simulate these interactions, including the often-used FARGO code and its variants. Many of the codes were extended over time to include additional physical processes with a focus on their accurate modeling. Aims: We introduce FargoCPT, an updated version of FARGO incorporating other previous enhancements to the code, to provide a simulation environment tailored to study interactions between stars, planets, and disks, ensuring accurate representation of planet systems, hydrodynamics, and dust dynamics with a focus on usability. Methods: The radiation-hydrodynamics part of FargoCPT uses a second-order upwind scheme in 2D polar coordinates supporting multiple equations of state, radiation transport, heating and cooling, and self-gravity. Shocks are considered using artificial viscosity. Integration of the N-body system is achieved by leveraging the REBOUND code. The dust module utilizes massless tracer particles, adapting to drag laws for the Stokes and Epstein regimes. Moreover, FargoCPT provides mechanisms to simulate accretion onto the stars and planets. Results: The code has been tested in practice by its use in various publications. Additionally, it comes with an automated test suite to test the physics modules. Conclusions: FargoCPT offers a unique set of simulation capabilities within the current landscape of publicly available planet-disk interaction simulation tools. Its structured interface and underlying technical updates are intended to assist researchers in the ongoing exploration of planet formation., Comment: 31 pages, 18 figures; accepted for publication in Astronomy and Astrophysics (A&A)

In this paper, we introduce a fresh perspective on the challenges of credit assignment and policy evaluation. First, we delve into the nuances of eligibility traces and explore instances where their updates may result in unexpected credit assignment to preceding states. From this investigation emerges the concept of a novel value function, which we refer to as the \emph{bidirectional value function}. Unlike traditional state value functions, bidirectional value functions account for both future expected returns (rewards anticipated from the current state onward) and past expected returns (cumulative rewards from the episode's start to the present). We derive principled update equations to learn this value function and, through experimentation, demonstrate its efficacy in enhancing the process of policy evaluation. In particular, our results indicate that the proposed learning approach can, in certain challenging contexts, perform policy evaluation more rapidly than TD($\lambda$) -- a method that learns forward value functions, $v^\pi$, \emph{directly}. Overall, our findings present a new perspective on eligibility traces and potential advantages associated with the novel value function it inspires, especially for policy evaluation., Comment: Accepted in The 38th Annual AAAI Conference on Artificial Intelligence

Designing reward functions for efficiently guiding reinforcement learning (RL) agents toward specific behaviors is a complex task. This is challenging since it requires the identification of reward structures that are not sparse and that avoid inadvertently inducing undesirable behaviors. Naively modifying the reward structure to offer denser and more frequent feedback can lead to unintended outcomes and promote behaviors that are not aligned with the designer's intended goal. Although potential-based reward shaping is often suggested as a remedy, we systematically investigate settings where deploying it often significantly impairs performance. To address these issues, we introduce a new framework that uses a bi-level objective to learn \emph{behavior alignment reward functions}. These functions integrate auxiliary rewards reflecting a designer's heuristics and domain knowledge with the environment's primary rewards. Our approach automatically determines the most effective way to blend these types of feedback, thereby enhancing robustness against heuristic reward misspecification. Remarkably, it can also adapt an agent's policy optimization process to mitigate suboptimalities resulting from limitations and biases inherent in the underlying RL algorithms. We evaluate our method's efficacy on a diverse set of tasks, from small-scale experiments to high-dimensional control challenges. We investigate heuristic auxiliary rewards of varying quality -- some of which are beneficial and others detrimental to the learning process. Our results show that our framework offers a robust and principled way to integrate designer-specified heuristics. It not only addresses key shortcomings of existing approaches but also consistently leads to high-performing solutions, even when given misaligned or poorly-specified auxiliary reward functions., Comment: (Spotlight) Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)

We investigate the propagation of acoustic singular surfaces, specifically, linear shock waves and nonlinear acceleration waves, in a class of inhomogeneous gases whose ambient mass density varies exponentially. Employing the mathematical tools of singular surface theory, we first determine the evolution of both the jump amplitudes and the locations/velocities of their associated wave-fronts, along with a variety of related analytical results. We then turn to what have become known as Krylov subspace spectral (KSS) methods to numerically simulate the evolution of the full waveforms under consideration. These are not only performed quite efficiently, since KSS allows the use of `large' CFL numbers, but also quite accurately, in the sense of capturing theoretically-predicted features of the solution profiles more faithfully than other time-stepping methods, since KSS customizes the computation of the components of the solution corresponding to the different frequencies involved. The presentation concludes with a listing of possible, acoustics-related, follow-on studies.

Coagent networks for reinforcement learning (RL) [Thomas and Barto, 2011] provide a powerful and flexible framework for deriving principled learning rules for arbitrary stochastic neural networks. The coagent framework offers an alternative to backpropagation-based deep learning (BDL) that overcomes some of backpropagation's main limitations. For example, coagent networks can compute different parts of the network \emph{asynchronously} (at different rates or at different times), can incorporate non-differentiable components that cannot be used with backpropagation, and can explore at levels higher than their action spaces (that is, they can be designed as hierarchical networks for exploration and/or temporal abstraction). However, the coagent framework is not just an alternative to BDL; the two approaches can be blended: BDL can be combined with coagent learning rules to create architectures with the advantages of both approaches. This work generalizes the coagent theory and learning rules provided by previous works; this generalization provides more flexibility for network architecture design within the coagent framework. This work also studies one of the chief disadvantages of coagent networks: high variance updates for networks that have many coagents and do not use backpropagation. We show that a coagent algorithm with a policy network that does not use backpropagation can scale to a challenging RL domain with a high-dimensional state and action space (the MuJoCo Ant environment), learning reasonable (although not state-of-the-art) policies. These contributions motivate and provide a more general theoretical foundation for future work that studies coagent networks.

Robust Markov Decision Processes (MDPs) are receiving much attention in learning a robust policy which is less sensitive to environment changes. There are an increasing number of works analyzing sample-efficiency of robust MDPs. However, there are two major barriers to applying robust MDPs in practice. First, most works study robust MDPs in a model-based regime, where the transition probability needs to be estimated and requires a large amount of memories $\mathcal{O}(|\mathcal{S}|^2|\mathcal{A}|)$. Second, prior work typically assumes a strong oracle to obtain the optimal solution as an intermediate step to solve robust MDPs. However, in practice, such an oracle does not exist usually. To remove the oracle, we transform the original robust MDPs into an alternative form, which allows us to use stochastic gradient methods to solve the robust MDPs. Moreover, we prove the alternative form still plays a similar role as the original form. With this new formulation, we devise a sample-efficient algorithm to solve the robust MDPs in a model-free regime, which does not require an oracle and trades off a lower storage requirement $\mathcal{O}(|\mathcal{S}||\mathcal{A}|)$ with being able to generate samples from a generative model or Markovian chain. Finally, we validate our theoretical findings via numerical experiments, showing the efficiency with the alternative form of robust MDPs.

Context: The sizes of dust in the interstellar medium follows a distribution where most of the dust mass is in smaller grains. However, the re-distribution from larger grains towards smaller sizes especially by means of rotational disruption is poorly understood. Aims: We aim to study the dynamics of porous grain aggregates under accelerated ration. Especially, we determine the deformation of the grains and the maximal angular velocity up to the rotational disruption event by caused by centrifugal forces. Methods: We pre-calculate aggregates my means of ballistic aggregation analogous to the interstellar dust as input for subsequent numerical simulations. In detail, we perform three-dimensional N-body simulations mimicking the radiative torque spin-up process up to the point where the grain aggregates become rotationally disrupted. Results: Our simulations results are in agreement with theoretical models predicting a characteristic angular velocity $\omega_{\mathrm{disr}}$ of the order of ${ 10^8 - 10^9\ \mathrm{rad\ s^{-1}} }$, where grains become rotationally disrupted. In contrast to theoretical predictions, we show that for large porous aggregates ($< 300\ \mathrm{nm}$) $\omega_{\mathrm{disr}}$ reaches a lower asymptotic value. Hence, such grains can withstand an accelerated ration more efficiently up to a factor of 10 because the displacement of mass by centrifugal forces and the subsequent mechanical deformation supports the buildup of new connections within the aggregate. Furthermore, we report that the rapid rotation of grains deforms an ensemble with initially 50:50 prolate and oblate shapes, respectively, preferentially into oblate shapes. Finally, we present a best fit formula to predict the average rotational disruption of an ensemble of porous dust aggregates dependent on internal grain structure, total number of monomers, and applied material properties., Comment: 17 pages, 10 figures, 3 tables

Accurate knowledge of the spectral features of noise and their influence on open quantum systems is fundamental for quantitative understanding and prediction of the dynamics in a realistic environment. For the weak measurements of two-level systems, the weak value obtained from experiments will inevitably be affected by the noise of the environment. Following our earlier work on the technique of the auto-correlative weak-value amplification (AWVA) approach under a Gaussian noise environment, here we study the effect of non-Gaussian noise on the AWVA technique.In particular, two types of noise with a negative-dB signal-to-noise ratio, frequency-stationary noises and frequency-nonstationary noises are studied. The various frequency-stationary noises, including low-frequency (1/f) noises, medium-frequency noises, and high-frequency noises, are generated in Simulink by translating the Gaussian white noise with different band-pass filters. While impulsive noise is studied as an example of frequency-non stationary noises. Our simulated results demonstrate that 1/f noises and impulsive noises have greater disturbance on the AWVA measurements. In addition, adding one kind of frequency-stationary noise, clamping the detected signals, and dominating the measurement range may {have} the potential to improve the precision of the AWVA technique with both a smaller deviation of the mean value and a smaller error bar in the presence of many hostile non-Gaussian noises., Comment: 22 pages,8 figures

We examine the precision limits of Hong-Ou-Mandel (HOM) timing measurements, as well as precision limits applying to generalized two-photon measurements. As a special case, we consider the use of two-photon measurements using photons with variable bandwidths and frequency correlations. When the photon bandwidths are not equal, maximizing the measurement precision involves a trade-off between high interference visibility and strong frequency anticorrelations, with the optimal precision occuring when the photons share non-maximal frequency anticorrelations. We show that a generalized measurement has precision limits that are qualitatively similar to those of the HOM measurement whenever the generalized measurement is insensitive to the net delay of both photons. By examining the performance of states with more general frequency distributions, our analysis allows for engineering of the joint spectral amplitude for use in realistic situations, in which both photons may not have ideal spectral properties., Comment: 12 pages, 6 figures; resubmission

Assuming Newton's law of cooling, the propagation and structure of isothermal acoustic shocks are studied under four different viscosity laws. Employing both analytical and numerical methods, 1D traveling wave solutions for the velocity and density fields are derived and analyzed. For each viscosity law considered, expressions for both the shock thickness and the asymmetry metric are determined. And, to ensure that isothermal flow is achievable, upper bounds on the associated Mach number values are derived/computed using the isothermal version of the energy equation., Comment: 26 pages, 2 figures, journal article

By choosing more orthogonality between pre-selection and post-selection states, one can significantly improve the sensitivity in the general optical quantum metrology based on the weak-value amplification (WVA) approach. However, increasing the orthogonality decreases the probability of detecting photons and makes the weak measurement difficult, especially when the weak measurement is disturbed by strong noise and the pointer is drowned in noise with a negative-dB signal-to-noise ratio (SNR). In this article, we investigate a modified weak measurement protocol with a temporal pointer, namely, the auto-correlative weak-value amplification (AWVA) approach. Specifically, a small longitudinal time delay (tiny phase shift) $\tau$ of a Gaussian pulse is measured by implementing two simultaneous auto-correlative weak measurements under Gaussian white noise with different SNR. The small quantities $\tau$ are obtained by measuring the auto-correlation coefficient of the pulses instead of fitting the shift of the mean value of the probe in the standard WVA technique. Simulation results show that the AWVA approach outperforms the standard WVA technique in the time domain with smaller statistical errors, remarkably increasing the precision of weak measurement under strong noise background., Comment: 18 pages, 11 figures

Close binaries ($a_{bin} < 20$ au) are known to harbor planets, yet planet formation is unlikely to succeed in such systems. Studying the dynamics of disks in close binaries can help to understand how those planets could have formed. We study the impact that numerical and physical parameters have on the dynamics of disks in close binaries. We use the $\gamma$-Cephei system as an example and focus on disk quantities such as disk eccentricity and the precession rate as indicators for the dynamical state of the disks. We simulate disks in close binaries by performing two-dimensional radiative hydrodynamical simulations using a modified version of the Fargo code. First, we perform a parameter study for different numerical parameters to confirm that our results are robust. In the second part, we study the effects of different masses and different viscosities on the disks' dynamics. Previous studies on radiative disks in close binaries used too low resolutions and too small simulation domains, which impacted the disk's dynamics. We find that radiative disks in close binaries, after an initialization phase, become eccentric with mean eccentricities between 0.06 to 0.27 and display a slow retrograde precession with periods ranging from $4 - 40T_{bin}$ which depends quadratically on the disk's mean aspect ratio. In general, the disks show a coherent, rigid precession which can be broken, however, by changes in the opacity law reducing the overall eccentricity of the disk., Comment: Accepted in A&A; 14 Pages, 23 figures

Many real-world sequential decision-making problems involve critical systems with financial risks and human-life risks. While several works in the past have proposed methods that are safe for deployment, they assume that the underlying problem is stationary. However, many real-world problems of interest exhibit non-stationarity, and when stakes are high, the cost associated with a false stationarity assumption may be unacceptable. We take the first steps towards ensuring safety, with high confidence, for smoothly-varying non-stationary decision problems. Our proposed method extends a type of safe algorithm, called a Seldonian algorithm, through a synthesis of model-free reinforcement learning with time-series analysis. Safety is ensured using sequential hypothesis testing of a policy's forecasted performance, and confidence intervals are obtained using wild bootstrap., Comment: Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020)

Performance evaluations are critical for quantifying algorithmic advances in reinforcement learning. Recent reproducibility analyses have shown that reported performance results are often inconsistent and difficult to replicate. In this work, we argue that the inconsistency of performance stems from the use of flawed evaluation metrics. Taking a step towards ensuring that reported results are consistent, we propose a new comprehensive evaluation methodology for reinforcement learning algorithms that produces reliable measurements of performance both on a single environment and when aggregated across environments. We demonstrate this method by evaluating a broad class of reinforcement learning algorithms on standard benchmark tasks., Comment: 30 pages, 9 figures, Thirty-seventh International Conference on Machine Learning (ICML 2020)

The Askaryan Radio Array (ARA) experiment at the South Pole is designed to detect high-energy neutrinos which, via in-ice interactions, produce coherent radiation at frequencies up to 1000 MHz. In Dec. 2018, a custom high-amplitude radio-frequency transmitter was lowered into the 1700 m SPICE ice core to provide test sources for ARA receiver stations sensitive to vertical and horizontal polarizations. For these tests, signal geometries correspond to obliquely propagating radio waves from below. The ARA collaboration has recently measured the polarization-dependent time delay variation, and report more significant time delays for trajectories perpendicular to ice flow. Here we use fabric data from the SPICE ice core to construct a bounding model for the ice birefringence and the polarization time delays across ARA. The data-model comparison is consistent with the vertical girdle fabric at the South Pole having the prevailing horizontal crystallographic axis oriented near-perpendicular to ice flow. This study presents the possibility that ice birefringence can be used to constrain the range to a neutrino interaction, and hence aid in neutrino energy reconstruction, for in-ice experiments such as ARA., Comment: submitted to Ann. Glac

We propose a new objective function for finite-horizon episodic Markov decision processes that better captures Bellman's principle of optimality, and provide an expression for the gradient of the objective., Comment: 1 page, 0 figures

We examine second-sound phenomena in a class of rigid, thermally conducting, solids that are described by a special case of the Maxwell--Catteneo flux law. Employing both analytical and numerical methods, we examine both temperature-rate waves and thermal traveling waves in this class of thermal conductor, which have recently been termed Graffi--Franchi--Straughan type conductors. In the present study, the temperature-dependent nature of the thermal relaxation time, which is the distinguishing feature of this class of conductors, gives rise to a variety of nonlinear effects; in particular, finite-time temperature-rate wave blow-up and temperature traveling waveforms which exhibit a "tongue". The presentation concludes with a discussion of possible follow-on studies., Comment: 24 pages, 5 figures

We report on the first experimental demonstration of enantioselective rotational control of chiral molecules with a laser field. In our experiments, two enantiomers of propylene oxide are brought to accelerated unidirectional rotation by means of an optical centrifuge. Using Coulomb explosion imaging, we show that the centrifuged molecules acquire preferential orientation perpendicular to the plane of rotation, and that the direction of this orientation depends on the relative handedness of the enantiomer and the rotating centrifuge field. The observed effect is in agreement with theoretical predictions and is reproduced in numerical simulations of the centrifuge excitation followed by Coulomb explosion of the centrifuged molecules. The demonstrated technique opens new avenues in optical enantioselective control of chiral molecules with a plethora of potential applications in differentiation, separation and purification of chiral mixtures.

With the rise of neural models across the field of information retrieval, numerous publications have incrementally pushed the envelope of performance for a multitude of IR tasks. However, these networks often sample data in random order, are initialized randomly, and their success is determined by a single evaluation score. These issues are aggravated by neural models achieving incremental improvements from previous neural baselines, leading to multiple near state of the art models that are difficult to reproduce and quickly become deprecated. As neural methods are starting to be incorporated into low resource and noisy collections that further exacerbate this issue, we propose evaluating neural models both over multiple random seeds and a set of hyperparameters within $\epsilon$ distance of the chosen configuration for a given metric., Comment: ACM SIGIR - LND4IR Workshop