Search

Exoplanet systems are thought to evolve on secular timescales over billions of years. This evolution is impossible to directly observe on human timescales in most individual systems. While the availability of accurate and precise age inferences for individual exoplanet host stars with ages $\tau$ in the interval $1~\text{Gyr}\lesssim~\tau~\lesssim10~\text{Gyr}$ would constrain this evolution, accurate and precise age inferences are difficult to obtain for isolated field dwarfs like the host stars of most exoplanets. The Galactic velocity dispersion of a thin disk stellar population monotonically grows with time, and the relationship between age and velocity dispersion in a given Galactic location can be calibrated by a stellar population for which accurate and precise age inferences are possible. Using a sample of subgiants with precise age inferences, we calibrate the age--velocity dispersion relation in the Kepler field. Applying this relation to the Kepler field's planet populations, we find that Kepler-discovered systems plausibly in second-order mean-motion resonances have $1~\text{Gyr}\lesssim~\tau~\lesssim2~\text{Gyr}$. The same is true for systems plausibly in first-order mean-motion resonances, but only for systems likely affected by tidal dissipation inside their innermost planets. These observations suggest that many planetary systems diffuse away from initially resonant configurations on secular timescales. Our calibrated relation also indicates that ultra-short-period (USP) planet systems have typical ages in the interval $5~\text{Gyr}\lesssim~\tau~\lesssim6~\text{Gyr}$. We propose that USP planets tidally migrated from initial periods in the range $1~\text{d}\lesssim~P~\lesssim2~\text{d}$ to their observed locations at $P<1~\text{d}$ over billions of years and trillions of cycles of secular eccentricity excitation and inside-planet damping., Comment: 15 pages, 3 figures, 3 tables; Accepted for publication in the Astronomical Journal

Rare-earth ion-doped crystals are of great interest for quantum memories, a central component in future quantum repeaters. To assess the promise of 1$\%$ Tm$^{3+}$-doped yttrium gallium garnet (Tm:YGG), we report measurements of optical coherence and energy-level lifetimes of its $^3$H$_6$ $\leftrightarrow$ $^3$H$_4$ transition at a temperature of around 500 mK and various magnetic fields. Using spectral hole burning, we find hyperfine ground-level (Zeeman level) lifetimes of several minutes at magnetic fields of less than 1000 G. We also measure coherence time exceeding one millisecond using two-pulse photon echoes. Three-pulse photon echo and spectral hole burning measurements reveal that due to spectral diffusion, the effective coherence time reduces to a few $\mu$s over a timescale of around two hundred seconds. Finally, temporal and frequency-multiplexed storage of optical pulses using the atomic frequency comb protocol is demonstrated. Our results suggest Tm:YGG to be promising for multiplexed photonic quantum memory for quantum repeaters.

Operator learning is an emerging area of machine learning which aims to learn mappings between infinite dimensional function spaces. Here we uncover a connection between operator learning architectures and conditioned neural fields from computer vision, providing a unified perspective for examining differences between popular operator learning models. We find that many commonly used operator learning models can be viewed as neural fields with conditioning mechanisms restricted to point-wise and/or global information. Motivated by this, we propose the Continuous Vision Transformer (CViT), a novel neural operator architecture that employs a vision transformer encoder and uses cross-attention to modulate a base field constructed with a trainable grid-based positional encoding of query coordinates. Despite its simplicity, CViT achieves state-of-the-art results across challenging benchmarks in climate modeling and fluid dynamics. Our contributions can be viewed as a first step towards adapting advanced computer vision architectures for building more flexible and accurate machine learning models in physical sciences., Comment: 23 pages, 13 figures

Spin and charge are the two most important degrees of freedom of electrons. Their interplay lies at the heart of numerous strongly correlated phenomena including Hubbard model physics and high temperature superconductivity. Such interplay for bosons, on the other hand, is largely unexplored in condensed matter systems. Here we demonstrate a unique realization of the spin-1/2 Bose-Hubbard model through excitons in a semiconducting moir\'e superlattice. We find evidence of a transient in-plane ferromagnetic (FM-$xy$) order of exciton spin - here valley pseudospin - around exciton filling $\nu_{ex}$ = 1, which transitions into a FM-$z$ order both with increasing exciton filling and a small magnetic field of 10 mT. The phase diagram is different from the fermion case and is qualitatively captured by a simple phenomenological model, highlighting the unique consequence of Bose-Einstein statistics. Our study paves the way for engineering exotic phases of matter from spinor bosons, as well as for unconventional devices in optics and quantum information science., Comment: Supplementary Materials attached

Over the years there has been ongoing interest in detecting authorship of a text based on statistical properties of the text, such as by using occurrence rates of noncontextual words. In previous work, these techniques have been used, for example, to determine authorship of all of \emph{The Federalist Papers}. Such methods may be useful in more modern times to detect fake or AI authorship. Progress in statistical natural language parsers introduces the possibility of using grammatical structure to detect authorship. In this paper we explore a new possibility for detecting authorship using grammatical structural information extracted using a statistical natural language parser. This paper provides a proof of concept, testing author classification based on grammatical structure on a set of "proof texts," The Federalist Papers and Sanditon which have been as test cases in previous authorship detection studies. Several features extracted from the statistical natural language parser were explored: all subtrees of some depth from any level; rooted subtrees of some depth, part of speech, and part of speech by level in the parse tree. It was found to be helpful to project the features into a lower dimensional space. Statistical experiments on these documents demonstrate that information from a statistical parser can, in fact, assist in distinguishing authors.

Assuming power travels instantaneously, can be steered by us, and is lost quadratically in each power line, the dynamic optimal power flow problem simplifies to a min-cost dynamic generalized flow with quadratic losses (MCDGFWQL) problem. As this is a special case of the min-cost concave dynamic generalized flow (MCCDGF) problem, we derive both general results for the MCCDGF problem and stronger results for the MCDGFWQL problem. Our main contribution is a fully polynomial-time approximation scheme for a mild restriction of the MCDGFWQL problem. We also implement and benchmark a slight modification of this algorithm, finding it to be efficient in practice, with a slightly superlinear and possibly subquadratic dependence of execution time on the edge count of the input graph. Our secondary contributions are the derivation of a reduction from the MCCDGF problem to a convex program and a corresponding sensitivity analysis of the MCCDGF problem. We also provide a brief comparison of our dynamic optimal power flow simplification and the classic direct current simplification and point out some interesting directions for future research., Comment: 74 pages, Master's thesis

We consider the probability distributions of the subsystem (staggered) magnetization in ordered and disordered models of quantum magnets in D dimensions. We focus on Heisenberg antiferromagnets and long-range transverse-field Ising models as particular examples. By employing a range of self-consistent time-dependent mean-field approximations in conjunction with Holstein-Primakoff, Dyson-Maleev, Schwinger boson and modified spin-wave theory representations we obtain results in thermal equilibrium as well as during non-equilibrium evolution after quantum quenches. To extract probability distributions we derive a simple formula for the characteristic function of generic quadratic observables in any Gaussian theory of bosons.

Before the launch of the Kepler Space Telescope, models of low-mass planet formation predicted that convergent Type I migration would often produce systems of low-mass planets in low-order mean-motion resonances. Instead, Kepler discovered that systems of small planets frequently have period ratios larger than those associated with mean-motion resonances and rarely have period ratios smaller than those associated with mean-motion resonances. Both short-timescale processes related to the formation or early evolution of planetary systems and long-timescale secular processes have been proposed as explanations for these observations. Using a thin disk stellar population's Galactic velocity dispersion as a relative age proxy, we find that Kepler-discovered multiple-planet systems with at least one planet pair near a period ratio suggestive of a second-order mean-motion resonance have a colder Galactic velocity dispersion and are therefore younger than both single-transiting and multiple-planet systems that lack planet pairs consistent with mean-motion resonances. We argue that a non-tidal secular process with a characteristic timescale no less than a few hundred Myr is responsible for moving systems of low-mass planets away from second-order mean-motion resonances. Among systems with at least one planet pair near a period ratio suggestive of a first-order mean-motion resonance, only the population of systems likely affected by tidal dissipation inside their innermost planets has a small Galactic velocity dispersion and is therefore young. We predict that period ratios suggestive of mean-motion resonances are more common in young systems with 10 Myr $\lesssim \tau \lesssim 100$ Myr and become less common as planetary systems age., Comment: 25 pages, 10 figures, and 3 tables in aastex631 format; accepted for publication in AJ

MUGAST is a state-of-the-art silicon array combining trapezoidal and square shaped double-sided silicon strip detectors (DSSD) to four MUST2 telescopes. Coupled to a {\gamma}-ray spectrometer, the excellent angular coverage and compacity of the MUGAST array make it an ideal tool for the study of transfer reactions. It is a first step toward the development of the new generation of silicon arrays using pulse shape analysis (PSA) for particle identification, such as the future GRIT array developed by our collaboration. In recent years, MUGAST has been widely used at GANIL. First with the AGATA {\gamma}-ray spectrometer and the VAMOS large acceptance spectrometer for the study of ISOL beams from the SPIRAL1 facility. It is now coupled with twelve EXOGAM clovers and to a new zero degree detection system at the end of the LISE fragmentation beamline.

Atomic frequency comb (AFC) quantum memory is a favorable protocol in long distance quantum communication. Putting the AFC inside an asymmetric optical cavity enhances the storage efficiency but makes the measurement of the comb properties challenging. We develop a theoretical model for cavity-enhanced AFC quantum memory that includes the effects of dispersion, and show a close alignment of the model with our own experimental results. Providing semi quantitative agreement for estimating the efficiency and a good description of how the efficiency changes as a function of detuning, it also captures certain qualitative features of the experimental reflectivity. For comparison, we show that a theoretical model without dispersion fails dramatically to predict the correct efficiencies. Our model is a step forward to accurately estimating the created comb properties, such as the optical depth inside the cavity, and so being able to make precise predictions of the performance of the prepared cavity-enhanced AFC quantum memory., Comment: 7 figures, 10 pages

The presence of long-lived oscillations in the expectation values of local observables after quantum quenches has recently attracted considerable attention in relation to weak ergodicity breaking. Here we focus on an alternative mechanism that gives rise to such oscillations in a class of systems that support kinematically protected gapped excitations at zero temperature. An open question in this context is whether such oscillations will ultimately decay. We resolve this issue by considering spin models that can be mapped to systems of weakly interacting fermions, which in turn are amenable to an analysis by standard methods based on the BBGKY hierarchy. We find that there is a time scale beyond which the oscillations start to decay, which grows as the strength of the quench is made small., Comment: 14 pages, 13 Figures

Unsupervised learning with functional data is an emerging paradigm of machine learning research with applications to computer vision, climate modeling and physical systems. A natural way of modeling functional data is by learning operators between infinite dimensional spaces, leading to discretization invariant representations that scale independently of the sample grid resolution. Here we present Variational Autoencoding Neural Operators (VANO), a general strategy for making a large class of operator learning architectures act as variational autoencoders. For this purpose, we provide a novel rigorous mathematical formulation of the variational objective in function spaces for training. VANO first maps an input function to a distribution over a latent space using a parametric encoder and then decodes a sample from the latent distribution to reconstruct the input, as in classic variational autoencoders. We test VANO with different model set-ups and architecture choices for a variety of benchmarks. We start from a simple Gaussian random field where we can analytically track what the model learns and progressively transition to more challenging benchmarks including modeling phase separation in Cahn-Hilliard systems and real world satellite data for measuring Earth surface deformation.

Moir\'e potentials in two-dimensional materials have been proven to be of fundamental importance to fully understand the electronic structure of van der Waals heterostructures, from superconductivity to correlated excitonic states. However, understanding how the moir\'e phonons, so-called phasons, affect the properties of the system still remains an uncharted territory. In this work, we demonstrate how phasons are integral to properly describing and understanding low-temperature interlayer exciton diffusion in WS2/WSe2 heterostructure. We perform photoluminescence (PL) spectroscopy to understand how the coupling between the layers, affected by their relative orientation, impacts the excitonic properties of the system. Samples fabricated with stacking angles of 0{\deg} and 60{\deg} are investigated taking into account the stacking angle dependence of the two common moir\'e potential profiles. Additionally, we present spatially and time-resolved exciton diffusion measurements, looking at the photoluminescence emission in a temperature range from 30 K to 250 K. An accurate potential for the two configurations are computed via density functional theory (DFT) calculations. Finally, we perform molecular dynamics simulation in order to visualize the phasons motion, estimating the phason speed at different temperatures, providing novel insights into the mechanics of exciton propagation at low temperatures that cannot be explained within the frame of classical exciton diffusion alone., Comment: A. Rossi, J. Zipfel, and I. Maity contributed equally

In a recent numerical study by Haldar et al. (Phys. Rev. X 11, 031062) it was shown that signatures of proximate quantum critical points can be observed at early and intermediate times after certain quantum quenches. Said work focused mainly on the case of the axial next-nearest neighbour Ising (ANNNI) model. Here we construct a simple time-dependent mean-field theory that allows us to obtain a quantitatively accurate description of these quenches at short times, which for reasons we explain remains a fair approximation at late times (with some caveats). Our approach provides a simple framework for understanding the reported numerical results as well as fundamental limitations on detecting quantum critical points through quench dynamics. We moreover explain the origin of the peculiar oscillatory behaviour seen in various observables as arising from the formation of a long-lived bound state., Comment: 25 pages, 13 figures

Ulta-wide bandgap semiconductors based on $\beta$-Ga$_2$O$_3$ offer the potential to achieve higher power switching performance, efficiency, and lower manufacturing cost than today's wide bandgap power semiconductors. However, the most critical challenge to the commercialization of Ga$_2$O$_3$ electronics is overheating, which impacts the device's performance and reliability. We fabricated a Ga$_2$O$_3$/4H-SiC composite wafer using a fusion-bonding method. A low temperature ($\le$ 600 $^{\circ}$C) epitaxy and device processing approach based on low-temperature (LT) metalorganic vapor phase epitaxy is developed to grow a Ga$_2$O$_3$ epitaxial channel layer on the composite wafer and subsequently fabricate into Ga$_2$O$_3$ power MOSFETs. This LT approach is essential to preserve the structural integrity of the composite wafer. These LT-grown epitaxial Ga$_2$O$_3$ MOSFETs deliver high thermal performance (56% reduction in channel temperature), high voltage blocking capabilities up to 2.45 kV, and power figures of merit of $\sim$ 300 MW/cm$^2$, which is a record high for any heterogeneously integrated Ga$_2$O$_3$ devices reported to date. This work is the first realization of multi-kilovolt homoepitaxial Ga$_2$O$_3$ power MOSFETs fabricated on a composite substrate with high heat transfer performance which delivers state-of-the-art power density values while running much cooler than those on native substrates. Thermal characterization and modeling results reveal that a Ga$_2$O$_3$/diamond composite wafer with a reduced Ga$_2$O$_3$ thickness ($\sim$ 1 $\mu$m) and thinner bonding interlayer ($<$ 10 nm) can reduce the device thermal impedance to a level lower than today's GaN-on-SiC power switches., Comment: 17 pages, 9 figures

The creation of well understood structures using spectral hole burning is an important task in the use of technologies based on rare earth ion doped crystals. We apply a series of different techniques to model and improve the frequency dependent population change in the atomic level structure of Thulium Yttrium Gallium Garnet (Tm:YGG). In particular we demonstrate that at zero applied magnetic field, numerical solutions to frequency dependent three-level rate equations show good agreement with spectral hole burning results. This allows predicting spectral structures given a specific hole burning sequence, the underpinning spectroscopic material properties, and the relevant laser parameters. This enables us to largely eliminate power dependent hole broadening through the use of adiabatic hole-burning pulses. Though this system of rate equations shows good agreement at zero field, the addition of a magnetic field results in unexpected spectral diffusion proportional to the induced Tm ion magnetic dipole moment and average magnetic field strength, which, through the quadratic Zeeman effect, dominates the optical spectrum over long time scales. Our results allow optimization of the preparation process for spectral structures in a large variety of rare earth ion doped materials for quantum memories and other applications.

Continuous neural representations have recently emerged as a powerful and flexible alternative to classical discretized representations of signals. However, training them to capture fine details in multi-scale signals is difficult and computationally expensive. Here we propose random weight factorization as a simple drop-in replacement for parameterizing and initializing conventional linear layers in coordinate-based multi-layer perceptrons (MLPs) that significantly accelerates and improves their training. We show how this factorization alters the underlying loss landscape and effectively enables each neuron in the network to learn using its own self-adaptive learning rate. This not only helps with mitigating spectral bias, but also allows networks to quickly recover from poor initializations and reach better local minima. We demonstrate how random weight factorization can be leveraged to improve the training of neural representations on a variety of tasks, including image regression, shape representation, computed tomography, inverse rendering, solving partial differential equations, and learning operators between function spaces., Comment: 33 pages, 21 figures, 12 tables

We summarise the recent progress of the Axion Longitudinal Plasma HAloscope (ALPHA) Consortium, a new experimental collaboration to build a plasma haloscope to search for axions and dark photons. The plasma haloscope is a novel method for the detection of the resonant conversion of light dark matter to photons. ALPHA will be sensitive to QCD axions over almost a decade of parameter space, potentially discovering dark matter and resolving the Strong CP problem. Unlike traditional cavity haloscopes, which are generally limited in volume by the Compton wavelength of the dark matter, plasma haloscopes use a wire metamaterial to create a tuneable artificial plasma frequency, decoupling the wavelength of light from the Compton wavelength and allowing for much stronger signals. We develop the theoretical foundations of plasma haloscopes and discuss recent experimental progress. Finally, we outline a baseline design for ALPHA and show that a full-scale experiment could discover QCD axions over almost a decade of parameter space., Comment: Endorsers: Jens Dilling, Michael Febbraro, Stefan Knirck, and Claire Marvinney. 26 pages, 17 figures, version accepted in Physical Review D, typo corrected

A panoply of unconventional electronic states has been observed in moir\'e superlattices. Engineering similar bosonic phases remains, however, largely unexplored. We report the observation of a bosonic correlated insulator in WSe2/WS2 moir\'e superlattices composed of excitons, i.e., tightly bound electron-hole pairs. We develop a pump probe spectroscopy method that we use to observe an exciton incompressible state at exciton filling {\nu}_ex = 1 and charge neutrality, indicating a correlated insulator of excitons. With varying charge density, the bosonic correlated insulator continuously transitions into an electron correlated insulator at charge filling {\nu}_e = 1, suggesting a mixed correlated insulating state between the two limits. Our studies establish semiconducting moir\'e superlattices as an intriguing platform for engineering bosonic phases., Comment: Science (2023)

In our previous publication, we discussed the optical properties of multi-layered nanocomposite samples consisting of 300 pairs of an AlOx layer and a Cu layer produced from sputtering atomic layer augmented deposition (SALAD). These samples displayed unusual spectral reflectance that could not be well described via conventional means and could not be explained as an interpolation of the constituent materials. Computational models were then needed to both describe the results that were obtained and to predict the samples' other material properties. This process was approached by using the transfer-matrix method to describe the spectral reflectance based on the constituent materials, and then the dispersion method was used to find the composite index of refraction for the samples. The models successfully described pure Cu but encountered minor difficulties when it came to AlOx, as such, more research is needed to either properly model non-holomorphic materials like AlOx with the current algorithm or to find a better model that can adequately describe both Cu and AlOx. The dispersion model implemented predicts that the samples, composed of many thin film layers of metal and dielectric, would display semiconductor-like behavior. Therefore, this indicates that SALAD's combination of sputtering and ALD permits the generation of novel metal-dielectric based semiconductors., Comment: 25 pages, 5 figures

Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By directly learning maps (operators) between infinite dimensional function spaces, these models are able to learn discretization invariant representations of target functions. A common approach is to represent such target functions as linear combinations of basis elements learned from data. However, there are simple scenarios where, even though the target functions form a low dimensional submanifold, a very large number of basis elements is needed for an accurate linear representation. Here we present NOMAD, a novel operator learning framework with a nonlinear decoder map capable of learning finite dimensional representations of nonlinear submanifolds in function spaces. We show this method is able to accurately learn low dimensional representations of solution manifolds to partial differential equations while outperforming linear models of larger size. Additionally, we compare to state-of-the-art operator learning methods on a complex fluid dynamics benchmark and achieve competitive performance with a significantly smaller model size and training cost.

It has been shown that hot Jupiters systems with massive, hot stellar primaries exhibit a wide range of stellar obliquities. On the other hand, hot Jupiter systems with low-mass, cool primaries often have stellar obliquities close to zero. Efficient tidal interactions between hot Jupiters and the convective envelopes present in lower-mass main sequence stars have been a popular explanation for these observations. If this explanation is accurate, then aligned systems should be older than misaligned systems. Likewise, the convective envelope mass of a hot Jupiter's host star should be an effective predictor of its obliquity. We derive homogeneous stellar parameters -- including convective envelope masses -- for hot Jupiter host stars with high-quality sky-projected obliquity inferences. Using a thin disk stellar population's Galactic velocity dispersion as a relative age proxy, we find that hot Jupiter host stars with larger-than-median obliquities are older than hot Jupiter host stars with smaller-than-median obliquities. The relative age difference between the two populations is larger for hot Jupiter host stars with smaller-than-median fractional convective envelope masses and is significant at the 3.6-$\sigma$ level. We identify stellar mass, not convective envelope mass, as the best predictor of stellar obliquity in hot Jupiter systems. The best explanation for these observations is that many hot Jupiters in misaligned systems arrived in the close proximity of their host stars long after their parent protoplanetary disks dissipated. The dependence of observed age offset on convective envelope mass suggests that tidal realignment contributes to the population of aligned hot Jupiters orbiting stars with convective envelopes., Comment: 35 pages, 9 figures, and 6 tables in aastex631 format; accepted for publication in AJ

We construct supersymmetric $AdS_3$ solutions of $D=11$ supergravity, dual to $d=2$, $\mathcal{N}=(0,2)$ SCFTs, that are associated with M5-branes wrapping two different four-dimensional orbifolds. In one case the orbifold is a spindle fibred over another spindle, while in the other it is a spindle fibred over a Riemann surface with genus $g>1$. We show that the central charges of the $d=2$ SCFTs calculated from the gravity solutions agree with field theory computations using anomaly polynomials. The new $D=11$ solutions are obtained after constructing a new consistent Kaluza-Klein truncation of maximal $D=7$ gauged supergravity reduced on a spindle down to $D=5$ minimal gauged supergravity., Comment: 37 pages. Very minor changes. Published version

The new neutron-deficient isotope $^{249}$No was synthesized for the first time in the fusion-evaporation reaction $^{204}$Pb($^{48}$Ca,3n)$^{249}$No. After separation, using the kinematic separator SHELS, the new isotope was identified with the GABRIELA detection system through genetic correlations with the known daughter and granddaughter nuclei $^{245}$Fm and $^{241}$Cf. The alpha-decay activity of $^{249}$No has an energy of 9129(22)$~$keV and half-life 38.3(2.8) ms. An upper limit of 0.2\% was measured for the fission branch of $^{249}$No. Based on the present data and recent information on the decay properties of $^{253}$Rf and aided by Geant4 simulations, the ground state of $^{249}$No is assigned the 5/2$^+$[622] neutron configuration and a partial decay scheme from $^{253}$Rf to $^{245}$Fm could be established. The production cross-section was found to be $\sigma$(3n)=0.47(4) nb at a mid-target beam energy of 225.4 MeV, which corresponds to the maximum of the calculated excitation function. Correlations of the $^{249}$No alpha activity with subsequent alpha decays of energy 7728(20) keV and half-life $1.2_{-0.4}^{+1.0}$ min provided a firm measurement of the electron-capture or $\beta^{+}$ branch of $^{245}$Fm to $^{245}$Es. The excitation function for the 1n, 2n and 3n evaporation channels was measured. In the case of the 2n-evaporation channel $^{250}$No, a strong variation of the ground state and isomeric state populations as a function of bombarding energy could be evidenced.

We report measurements of the reflection and transmission spectra of 2% doped Thulium Yttrium Gallium Garnet (Tm:YGG) using variable-angle spectroscopic ellipsometry(VASE) over a wavelength range from 210 to 1680 nm (0.73-5.9 eV). The well-known Tm resonances are identified and separated from the aggregate data, allowing us to calculate the previously unknown frequency dependence of the complex refractive index of the host material. This information is important for many applications of YGG in classical and quantum photonics, including constructing optical cavities, laser-based applications, and quantum information devices. A complete database of the obtained parameters is included in the supplementary information.