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Dust from core-collapse supernovae (CCSNe), specifically Type IIP SNe, has been suggested to be a significant source of the dust observed in high-redshift galaxies. CCSNe eject large amounts of newly formed heavy elements, which can condense into dust grains in the cooling ejecta. However, infrared (IR) observations of typical CCSNe generally measure dust masses that are too small to account for the dust production needed at high redshifts. Type IIn SNe, classified by their dense circumstellar medium (CSM), are also known to exhibit strong IR emission from warm dust, but the dust origin and heating mechanism have generally remained unconstrained because of limited observational capabilities in the mid-IR. Here, we present a JWST/MIRI Medium Resolution Spectrograph (MRS) spectrum of the Type IIn SN 2005ip nearly 17 years post-explosion. The Type IIn SN 2005ip is one of the longest-lasting and most well-studied SNe observed to date. Combined with a Spitzer mid-IR spectrum of SN 2005ip obtained in 2008, this data set provides a rare 15-year baseline, allowing for a unique investigation of the evolution of dust. The JWST spectrum shows a new high-mass dust component ($\gtrsim0.08$ M$_{\odot}$) that is not present in the earlier Spitzer spectrum. Our analysis shows dust likely formed over the past 15 years in the cold, dense shell (CDS), between the forward and reverse shocks. There is also a smaller mass of carbonaceous dust ($\gtrsim0.005$ M$_{\odot}$) in the ejecta. These observations provide new insights into the role of SN dust production, particularly within the CDS, and its potential contribution to the rapid dust enrichment of the early Universe.

Given a supermanifold equipped with an odd distribution of maximal dimension and constant symbol, we construct the formal moduli problem of deformations of the distribution. This moduli problem is described by a local super dg Lie algebra that provides both a resolution of the structure-preserving vector fields on superspace and a derived enhancement of superconformal symmetry. Applying our construction in standard physical examples returns the conformal supergravity multiplet in every known example, in any dimension and with any amount of supersymmetry$\unicode{x2014}$whether or not a superconformal algebra exists. We discuss new examples related to twisted supergravity, higher Virasoro algebras, and exceptional super Lie algebras. The compatibility of our techniques with twisting also leads to a computation of every twist of the stress tensor multiplet of a superconformal theory, including universal operator product expansions. Our approach uses a derived model for the space of functions constant along the distribution, which is applicable even when the distribution is non-involutive; we construct other natural multiplets, such as K\"ahler differentials, that appear naturally through this lens on superspace geometry., Comment: 68 pages, 7 tables. Comments welcome! v2: updated funding information

Current efforts to detect nuclear detonations and correctly categorize explosion sources with ground- and space-collected discriminants presents challenges that remain unaddressed by the Event Categorization Matrix (ECM) model. Smaller events (lower yield explosions) often include only sparse observations among few modalities and can therefore lack a complete set of discriminants. The covariance structures can also vary significantly between such observations of event (source-type) categories. Both obstacles are problematic for ``classic'' ECM. Our work addresses this gap and presents a Bayesian update to the previous ECM model, termed B-ECM, which can be trained on partial observations and does not rely on a pooled covariance structure. We further augment ECM with Bayesian Decision Theory so that false negative or false positive rates of an event categorization can be reduced in an intuitive manner. To demonstrate improved categorization rates with B-ECM, we compare an array of B-ECM and classic ECM models with multiple performance metrics that leverage Monte Carlo experiments. We use both synthetic and real data. Our B-ECM models show consistent gains in overall accuracy and a lower false negative rates relative to the classic ECM model. We propose future avenues to improve B-ECM that expand its decision-making and predictive capability., Comment: Main text 20 pages, 5 figures

Scientists often search for phenomena of interest while exploring new environments. Autonomous vehicles are deployed to explore such areas where human-operated vehicles would be costly or dangerous. Online control of autonomous vehicles for information-gathering is called adaptive sampling and can be framed as a POMDP that uses information gain as its principal objective. While prior work focuses largely on single-agent scenarios, this paper confronts challenges unique to multi-agent adaptive sampling, such as avoiding redundant observations, preventing vehicle collision, and facilitating path planning under limited communication. We start with Multi-Agent Path Finding (MAPF) methods, which address collision avoidance by decomposing the MAPF problem into a series of single-agent path planning problems. We then present information-driven MAPF which addresses multi-agent information gain under limited communication. First, we introduce an admissible heuristic that relaxes mutual information gain to an additive function that can be evaluated as a set of independent single agent path planning problems. Second, we extend our approach to a distributed system that is robust to limited communication. When all agents are in range, the group plans jointly to maximize information. When some agents move out of range, communicating subgroups are formed and the subgroups plan independently. Since redundant observations are less likely when vehicles are far apart, this approach only incurs a small loss in information gain, resulting in an approach that gracefully transitions from full to partial communication. We evaluate our method against other adaptive sampling strategies across various scenarios, including real-world robotic applications. Our method was able to locate up to 200% more unique phenomena in certain scenarios, and each agent located its first unique phenomenon faster by up to 50%., Comment: Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract here is shorter than that in the PDF file

Topological field theories and holomorphic field theories naturally appear in both mathematics and physics. However, there exist intriguing hybrid theories that are topological in some directions and holomorphic in others, such as twists of supersymmetric field theories or Costello's 4-dimensional Chern-Simons theory. In this paper, we rigorously prove the ultraviolet (UV) finiteness for such hybrid theories on flat space, and present two significant vanishing results regarding anomalies., Comment: 51 pages, no figures. An error in the proof has been fixed. Corrected several typos. Comments welcome

Sample Return Capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 24 September 2023 arrival of the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing (DAS), and GPS technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the dataset collected during this campaign will improve entry and propagation models as well as augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources., Comment: 87 pages, 14 figures

We compute the local cohomology of vector fields on a manifold. In the smooth case this recovers the diagonal cohomology studied in work of Losik, Guillemin, Fuks and others. In the holomorphic case this cohomology has recently appeared in work of Hennion and Kapranov in their study of the Lie algebra cohomology of vector fields on a complex manifold. Additionally, we construct explicit representatives for cocycles in Gelfand--Fuks cohomology via descent., Comment: 30 pages, comments are very welcome!

In four-dimensional conformal field theory, the numbers a and c are defined as coefficients of particular terms in the operator product expansion (OPE) of the energy-momentum tensor. With supersymmetry there are relations between these coefficients and mixed R-symmetry and gravitational anomalies. In this paper we prove a relationship between these coefficients and anomalies to holomorphic reparametrization symmetry at the level of the holomorphic twist., Comment: 42 pages, comments welcome!

In this work, we revisit and elaborate on twisted holography for AdS$_3 \times S^3 \times X$ with $X= T^4$, K3, with a particular focus on K3. We describe the twist of supergravity, identify the corresponding (generalization of) BCOV theory, and enumerate twisted supergravity states. We use this knowledge, and the technique of Koszul duality, to obtain the $N \rightarrow \infty$, or planar, limit of the chiral algebra of the dual CFT. The resulting symmetries are strong enough to fix planar 2 and 3-point functions in the twisted theory or, equivalently, in a 1/4-BPS subsector of the original duality. This technique can in principle be used to compute corrections to the chiral algebra perturbatively in $1/N$., Comment: 91 pages, 9 figures (v2: minor corrections and additions)

Recent simulations have shown that asymmetries in the ejecta distribution of supernova remnants (SNRs) may be a reflection of asymmetries left over from the initial supernova explosion. Thus, SNR studies provide a vital means for testing and constraining model predictions in relation to the distribution of heavy elements, which are key to improving our understanding of the explosion mechanisms in Type Ia supernovae. The use of a novel blind source separation method applied to the megasecond X-ray observations of the historic Kepler and Tycho supernova remnants has revealed maps of the ejecta distribution. These maps are endowed with an unprecedented level of detail and clear separations from the continuum emission. Our method also provides a three-dimensional (3D) view of the ejecta by individually disentangling red- and blueshifted spectral components associated with images of the Si, S, Ar, Ca, and Fe emission. This approach provides insights into the morphology of the ejecta distribution in those two remnants. Those mappings have allowed us to thoroughly investigate the asymmetries in the intermediate-mass elements and Fe distribution in two Type Ia supernova remnants. We also compared the results with the core-collapse Cassiopeia A remnant, which we had studied previously. The images obtained confirm, as expected for Type Ia SNRs, that the Fe distribution is mostly closer to the core than that of intermediate-mass elements. They also highlight peculiar features in the ejecta distribution, such as the Fe-rich southeastern knot in Tycho.

Autonomous mobile agents often operate in hazardous environments, necessitating an awareness of safety. These agents can have non-linear, stochastic dynamics that must be considered during planning to guarantee bounded risk. Most state of the art methods require closed-form dynamics to verify plan correctness and safety however modern robotic systems often have dynamics that are learned from data. Thus, there is a need to perform efficient trajectory planning with guarantees on risk for agents without known dynamics models. We propose a "generate-and-test" approach to risk-bounded planning in which a planner generates a candidate trajectory using an approximate linear dynamics model and a validator assesses the risk of the trajectory, computing additional safety constraints for the planner if the candidate does not satisfy the desired risk bound. To acquire the approximate model, we use a variational autoencoder to learn a latent linear dynamics model and encode the planning problem into the latent space to generate the candidate trajectory. The VAE also serves to sample trajectories around the candidate to use in the validator. We demonstrate that our algorithm, LaPlaSS, is able to generate trajectory plans with bounded risk for a real-world agent with learned dynamics and is an order of magnitude more efficient than the state of the art.

The progenitor of the W49B supernova remnant is still under debate. One of the candidates is a jet-driven core-collapse supernova. In such a highly asymmetric explosion, a strong $\alpha$-rich freezeout is expected in local high entropy regions, which should enrich elements synthesized by the capture of $\alpha$-particles such as $^{44}$Ti and $^{48}$Cr (decaying to $^{44}$Ca and $^{48}$Ti, respectively). In the present work, in order to infer the progenitor of the W49B remnant, we constrain the amount of stable Ti ($^{48}$Ti) synthesized, using the {\it Suzaku} observation. We found no firm evidence for the Ti line and set the upper limit of $M_{\rm Ti}/M_{\rm Fe} < 8.2 \times$ 10$^{-4}$ (99\% limit using Xspec) and $M_{\rm Ti}/M_{\rm Fe} < 1.9 \times$ 10$^{-3}$ (99\% limit using SPEX), and thus excluded almost all hypernova/jet-driven supernova models. Our results, as complemented by some previous studies, suggest that a Type Ia supernova from a near-$M_{\rm Ch}$ (Chandrasekhar mass) white dwarf is the most favorable candidate for the origin of W49B. Future observations with X-ray calorimeter missions, such as XRISM, will give us a stronger constraint on the progenitor., Comment: Submitted to ApJ, 7 pages, 3 figures, 1 table

Since the discovery of synchrotron X-ray emission from the shell of the supernova remnant (SNR) SN 1006, multiple observations from Chandra and XMM-Newton have shown that many young SNRs produce synchrotron emission in X-rays. Among those, a few peculiar SNRs have their X-ray emission largely dominated by synchrotron radiation, showing no or only faint traces of thermal emission. In this paper, we report our mapping of the thermal emission in three emblematic synchrotron-dominated SNRs: G330.2+1.0, 3C58, and RX J1713.7-3946. We used a blind source separation method able to retrieve faint components from X-ray data in the form of Chandra and XMM-Newton observations. The thermal candidates disentangled by the algorithm were then used to select regions of extraction. We then analyzed the extracted spectra to assess their physical nature. We conclude that the components retrieved by the algorithm indeed represent the spatial distribution of the thermal emission in G330.2+1.0 and 3C58, and a likely thermal candidate in RX J1713.7-3946. Our findings confirm and expand on past studies.

The Advanced X-ray Imaging Satellite (AXIS) is a Probe-class concept that will build on the legacy of the Chandra X-ray Observatory by providing low-background, arcsecond-resolution imaging in the 0.3-10 keV band across a 450 arcminute$^2$ field of view, with an order of magnitude improvement in sensitivity. AXIS utilizes breakthroughs in the construction of lightweight segmented X-ray optics using single-crystal silicon, and developments in the fabrication of large-format, small-pixel, high readout rate CCD detectors with good spectral resolution, allowing a robust and cost-effective design. Further, AXIS will be responsive to target-of-opportunity alerts and, with onboard transient detection, will be a powerful facility for studying the time-varying X-ray universe, following on from the legacy of the Neil Gehrels (Swift) X-ray observatory that revolutionized studies of the transient X-ray Universe. In this paper, we present an overview of AXIS, highlighting the prime science objectives driving the AXIS concept and how the observatory design will achieve these objectives., Comment: Published in Proceedings of SPIE Optics & Photonics 2023, San Diego

We propose a method for extracting the Higgs and Coulomb branches of a three-dimensional N = 4 quantum field theory from the algebra of local operators in its holomorphic-topological twist using the formalism of raviolo vertex algebras. Our construction parallels that of the chiral ring and twisted chiral ring of an N = 2 superconformal vertex operator algebra., Comment: 45 pages; feedback welcome

We show that the action of residual supersymmetries in holomorphic-topological twists of $N = 2$ theories in three dimensions naturally extends to the action of certain infinite dimensional Lie superalgebras. We demonstrate this in a range of examples, including $N = 4$ Yang-Mills theories and superconformal Chern-Simons theories, describing how the symmetries are implemented at the level of local operators., Comment: 41 pages, feedback welcome!

We present mid-infrared (mid-IR) imaging of the Type IIL supernova (SN) 1980K with the James Webb Space Telescope (JWST) more than 40 yr post-explosion. SN 1980K, located in the nearby ($D\approx7$ Mpc) "SN factory" galaxy NGC 6946, was serendipitously captured in JWST/MIRI images taken of the field of SN 2004et in the same galaxy. SN 1980K serves as a promising candidate for studying the transitional phase between young SNe and older SN remnants and also provides a great opportunity to investigate its the close environment. SN 1980K can be identified as a clear and bright point source in all eight MIRI filters from F560W up to F2550W. We fit analytical dust models to the mid-IR spectral energy distribution that reveal a large amount ($M_d \approx 0.002 {M}_{\odot}$) of Si-dominated dust at $T_{dust}\approx 150$ K (accompanied by a hotter dust/gas component), and also computed numerical SED dust models. Radiative transfer modeling of a late-time optical spectrum obtained recently with Keck discloses that an even larger ($\sim 0.24-0.58~{M}_{\odot}$) amount of dust is needed in order for selective extinction to explain the asymmetric line profile shapes observed in SN 1980K. As a conclusion, with JWST, we may see i) pre-existing circumstellar dust heated collisionally (or, partly radiatively), analogous to the equatorial ring of SN 1987A, or ii) the mid-IR component of the presumed newly-formed dust, accompanied by much more colder dust present in the ejecta (as suggested by the late-time the optical spectra)., Comment: 14 pages, 9 figures

Continuous-variable quantum key distribution (CV-QKD) using a true local (located at the receiver) oscillator (LO) has been proposed to remove any possibility of side-channel attacks associated with transmission of the LO as well as reduce the cross-pulse contamination. Here we report an implementation of true LO CV-QKD using "off-the-shelf" components and conduct QKD experiments using the fiber optical network at Oak Ridge National Laboratory. A phase reference and quantum signal are time multiplexed and then wavelength division multiplexed with the classical communications which "coexist" with each other on a single optical network fiber. This is the first demonstration of CV-QKD with a receiver-based true LO over a deployed fiber network, a crucial step for its application in real-world situations.

We develop an algebraic structure modeling local operators in a three-dimensional quantum field theory which is partially holomorphic and partially topological. The geometric space organizing our algebraic structure is called the raviolo (or bubble) and replaces the punctured disk underlying vertex algebras; we refer to this structure as a raviolo vertex algebra. The raviolo has appeared in many contexts related to three-dimensional supersymmetric gauge theory, especially in work on the affine Grassmannian. We prove a number of structure theorems for raviolo vertex algebras and provide simple examples that share many similarities with their vertex algebra counterparts., Comment: 78 pages. Comments and feedback are welcomed!

Neutrino interactions with stellar material are widely believed to be fundamental to the explosion of massive stars. However, this important process has remained difficult to confirm observationally. We propose a new method to verify it using X-ray observations of the supernova remnant Cassiopeia A. The elemental composition in its Fe-rich ejecta that could have been produced at the innermost region of the supernova, where neutrinos are expected to interact, allows us to examine the presence of neutrino interactions. Here we demonstrate that the amount of Mn produced without neutrino nucleosynthesis processes (i.e., the $\nu$- and $\nu$p-process) is too small to explain the Mn/Fe mass ratio we measure (0.14--0.67\%). This result supports the operation of significant neutrino interactions in the Cassiopeia A supernova. If the observed Mn/Fe mass ratio purely reflects the production at the innermost region of the supernova, this would be the first robust confirmation of neutrino-matter interactions in an individual supernova. We further show that the Mn/Fe mass ratio has the potential to constrain supernova neutrino parameters (i.e., total neutrino luminosity, neutrino temperature). Future spatially-resolved, high-resolution X-ray spectroscopy will allow us to investigate the details of neutrino-supernova astrophysics through its signatures in elemental composition not only in Cassiopeia A but also in other remnants., Comment: 17 pages, 10 figures. Accepted for publication in ApJ

When agents collaborate on a task, it is important that they have some shared mental model of the task routines -- the set of feasible plans towards achieving the goals. However, in reality, situations often arise that such a shared mental model cannot be guaranteed, such as in ad-hoc teams where agents may follow different conventions or when contingent constraints arise that only some agents are aware of. Previous work on human-robot teaming has assumed that the team has a set of shared routines, which breaks down in these situations. In this work, we leverage epistemic logic to enable agents to understand the discrepancy in each other's beliefs about feasible plans and dynamically plan their actions to adapt or communicate to resolve the discrepancy. We propose a formalism that extends conditional doxastic logic to describe knowledge bases in order to explicitly represent agents' nested beliefs on the feasible plans and state of execution. We provide an online execution algorithm based on Monte Carlo Tree Search for the agent to plan its action, including communication actions to explain the feasibility of plans, announce intent, and ask questions. Finally, we evaluate the success rate and scalability of the algorithm and show that our agent is better equipped to work in teams without the guarantee of a shared mental model., Comment: 10 pages, Published at ICAPS 2023 (Main Track)

In this work, we demonstrate the application of a first-order Taylor expansion to approximate a generic function $F: R^{n \times m} \to R^{n \times m}$ and utilize it in language modeling. To enhance the basic Taylor expansion, we introduce iteration and piecewise modeling, leading us to name the algorithm the Iterative Piecewise Affine (IPA) approximation. The final algorithm exhibits interesting resemblances to the Transformers decoder architecture. By comparing parameter arrangements in IPA and Transformers, we observe a strikingly similar performance, with IPA outperforming Transformers by 1.5\% in the next token prediction task with cross-entropy loss for smaller sequence lengths.

We discuss the properties of quarter-BPS local operators in four dimensional ${\cal N}=1$ supersymmetric Yang-Mills theory using the formalism of holomorphic twists. We study loop corrections both to the space of local operators and to algebraic operations which endow the twisted theory with an infinite symmetry algebra. We classify all single-trace quarter-BPS operators in the planar approximation for $SU(N)$ gauge theory and propose a holographic dual description for the twisted theory. We classify perturbative quarter-BPS operators in $SU(2)$ and $SU(3)$ gauge theories with sufficiently small quantum numbers and discuss possible non-perturbative corrections to the answer. We set up analogous calculations for some theories with matter., Comment: v1:55+20 pages, 61 footnotes, comments welcome; v2: published version

In this paper, we address the trajectory planning problem in uncertain nonconvex static and dynamic environments that contain obstacles with probabilistic location, size, and geometry. To address this problem, we provide a risk bounded trajectory planning method that looks for continuous-time trajectories with guaranteed bounded risk over the planning time horizon. Risk is defined as the probability of collision with uncertain obstacles. Existing approaches to address risk bounded trajectory planning problems either are limited to Gaussian uncertainties and convex obstacles or rely on sampling-based methods that need uncertainty samples and time discretization. To address the risk bounded trajectory planning problem, we leverage the notion of risk contours to transform the risk bounded planning problem into a deterministic optimization problem. Risk contours are the set of all points in the uncertain environment with guaranteed bounded risk. The obtained deterministic optimization is, in general, nonlinear and nonconvex time-varying optimization. We provide convex methods based on sum-of-squares optimization to efficiently solve the obtained nonconvex time-varying optimization problem and obtain the continuous-time risk bounded trajectories without time discretization. The provided approach deals with arbitrary (and known) probabilistic uncertainties, nonconvex and nonlinear, static and dynamic obstacles, and is suitable for online trajectory planning problems. In addition, we provide convex methods based on sum-of-squares optimization to build the max-sized tube with respect to its parameterization along the trajectory so that any state inside the tube is guaranteed to have bounded risk., Comment: Accepted by IJRR (extension of RSS 2021 paper arXiv:2106.05489 invited to IJRR)

Text embeddings are useful features for several NLP applications, such as sentence similarity, text clustering, and semantic search. In this paper, we present a Low-rank Adaptation with a Contrastive objective on top of 8-bit Siamese-BLOOM, a multilingual large language model optimized to produce semantically meaningful word embeddings. The innovation is threefold. First, we cast BLOOM weights to 8-bit values. Second, we fine-tune BLOOM with a scalable adapter (LoRA) and 8-bit Adam optimizer for sentence similarity classification. Third, we apply a Siamese architecture on BLOOM model with a contrastive objective to ease the multi-lingual labeled data scarcity. The experiment results show the quality of learned embeddings from LACoS-BLOOM is proportional to the number of model parameters and the amount of unlabeled training data. With the parameter efficient fine-tuning design, we are able to run BLOOM 7.1 billion parameters end-to-end on a single GPU machine with 32GB memory. Compared to previous solution Sentence-BERT, we achieve significant improvement on both English and multi-lingual STS tasks.

In this multi-messenger astronomy era, all the observational probes are improving their sensitivities and overall performance. The Focusing on Relativistic universe and Cosmic Evolution (FORCE) mission, the product of a JAXA/NASA collaboration, will reach a 10 times higher sensitivity in the hard X-ray band ($E >$ 10~keV) in comparison with any previous hard X-ray missions, and provide simultaneous soft X-ray coverage. FORCE aims to be launched in the early 2030s, providing a perfect hard X-ray complement to the ESA flagship mission Athena. FORCE will be the most powerful X-ray probe for discovering obscured/hidden black holes and studying high energy particle acceleration in our Universe and will address how relativistic processes in the universe are realized and how these affect cosmic evolution. FORCE, which will operate over 1--79 keV, is equipped with two identical pairs of supermirrors and wideband X-ray imagers. The mirror and imager are connected by a high mechanical stiffness extensible optical bench with alignment monitor systems with a focal length of 12~m. A light-weight silicon mirror with multi-layer coating realizes a high angular resolution of $<15''$ in half-power diameter in the broad bandpass. The imager is a hybrid of a brand-new SOI-CMOS silicon-pixel detector and a CdTe detector responsible for the softer and harder energy bands, respectively. FORCE will play an essential role in the multi-messenger astronomy in the 2030s with its broadband X-ray sensitivity., Comment: 12 pages, 8 figures. Proceedings of SPIE Astronomical Telescopes and Instrumentation 2022

The nature of Type Ia supernovae remains controversial. The youngest remnants of Ia supernovae hold clues to the explosion and to the immediate surroundings. We present a third epoch of Chandra observations of the $\sim600$-year-old Type Ia remnant 0519-69.0 in the Large Magellanic Cloud, extending the time baseline to 21 years from the initial 2000 observations. We find rapid expansion of X-ray emitting material, with an average velocity of 4760 km s$^{-1}$. At the distance of the LMC this corresponds to an undecelerated age of 750 years, with the true age somewhat smaller. We also find that the bright ring of emission has expanded by 1.3\%, corresponding to a velocity of 1900 km s$^{-1}$ and an undecelerated age of 1600 years. The high velocity of the peripheral X-rays, contrasted with the modest expansion of the main X-ray shell, provides further evidence for a massive shell of circumstellar material., Comment: 8 pages, 4 figures, accepted for publication in ApJ

We consider the motion planning problem for stochastic nonlinear systems in uncertain environments. More precisely, in this problem the robot has stochastic nonlinear dynamics and uncertain initial locations, and the environment contains multiple dynamic uncertain obstacles. Obstacles can be of arbitrary shape, can deform, and can move. All uncertainties do not necessarily have Gaussian distribution. This general setting has been considered and solved in [1]. In addition to the assumptions above, in this paper, we consider long-term tasks, where the planning method in [1] would fail, as the uncertainty of the system states grows too large over a long time horizon. Unlike [1], we present a real-time online motion planning algorithm. We build discrete-time motion primitives and their corresponding continuous-time tubes offline, so that almost all system states of each motion primitive are guaranteed to stay inside the corresponding tube. We convert probabilistic safety constraints into a set of deterministic constraints called risk contours. During online execution, we verify the safety of the tubes against deterministic risk contours using sum-of-squares (SOS) programming. The provided SOS-based method verifies the safety of the tube in the presence of uncertain obstacles without the need for uncertainty samples and time discretization in real-time. By bounding the probability the system states staying inside the tube and bounding the probability of the tube colliding with obstacles, our approach guarantees bounded probability of system states colliding with obstacles. We demonstrate our approach on several long-term robotics tasks., Comment: International Conference on Intelligent Robots and Systems (IROS), 2023

In this paper, we consider the closed-loop control problem of nonlinear robotic systems in the presence of probabilistic uncertainties and disturbances. More precisely, we design a state feedback controller that minimizes deviations of the states of the system from the nominal state trajectories due to uncertainties and disturbances. Existing approaches to address the control problem of probabilistic systems are limited to particular classes of uncertainties and systems such as Gaussian uncertainties and processes and linearized systems. We present an approach that deals with nonlinear dynamics models and arbitrary known probabilistic uncertainties. We formulate the controller design problem as an optimization problem in terms of statistics of the probability distributions including moments and characteristic functions. In particular, in the provided optimization problem, we use moments and characteristic functions to propagate uncertainties throughout the nonlinear motion model of robotic systems. In order to reduce the tracking deviations, we minimize the uncertainty of the probabilistic states around the nominal trajectory by minimizing the trace and the determinant of the covariance matrix of the probabilistic states. To obtain the state feedback gains, we solve deterministic optimization problems in terms of moments, characteristic functions, and state feedback gains using off-the-shelf interior-point optimization solvers. To illustrate the performance of the proposed method, we compare our method with existing probabilistic control methods., Comment: International Conference on Intelligent Robots and Systems (IROS), 2023

Some young supernova remnants exhibit thin filaments of X-ray synchrotron radiation coinciding with the forward shock due to accelerated electrons interacting with the local magnetic field. The two main models accounting for the radial brightness evolution of these filaments differ in their prediction of the narrowing (or not) of the filaments with increasing photon energy. In this paper, we report our observation of such a narrowing of the synchrotron filaments in Cassiopeia A at X-ray energies, and how this finding could help in understanding the mechanisms at stake in their formation. We used a new blind source separation method on the 1 Ms Chandra observation of Cassiopeia A, in order to obtain detailed and unpolluted images of the synchrotron emission in three energy bands. We then extracted the profiles of several filaments at the forward shock and the reverse shock to estimate and compare their widths. We find that there is indeed a narrowing with energy of the synchrotron filaments both at the forward and at the reverse shocks in Cassiopeia A. The energy dependency of this narrowing seems stronger at high energy, which is indicative of a damping effect, confirmed by radio observations., Comment: Accepted by A&A

Many practical applications of robotics require systems that can operate safely despite uncertainty. In the context of motion planning, two types of uncertainty are particularly important when planning safe robot trajectories. The first is environmental uncertainty -- uncertainty in the locations of nearby obstacles, stemming from sensor noise or (in the case of obstacles' future locations) prediction error. The second class of uncertainty is uncertainty in the robots own state, typically caused by tracking or estimation error. To achieve high levels of safety, it is necessary for robots to consider both of these sources of uncertainty. In this paper, we propose a risk-bounded trajectory optimization algorithm, known as Sequential Convex Optimization with Risk Optimization (SCORA), to solve chance-constrained motion planning problems despite both environmental uncertainty and tracking error. Through experiments in simulation, we demonstrate that SCORA significantly outperforms state-of-the-art risk-aware motion planners both in planning time and in the safety of the resulting trajectories.

Supernova (SN) explosions have been sought for decades as a possible source of dust in the Universe, providing the seeds of galaxies, stars, and planetary systems. SN 1987A offers one of the most promising examples of significant SN dust formation, but until the James Webb Space Telescope (JWST), instruments have traditionally lacked the sensitivity at both late times (>1 yr post-explosion) and longer wavelengths (i.e., >10 um) to detect analogous dust reservoirs. Here we present JWST/MIRI observations of two historic Type IIP SNe, 2004et and SN 2017eaw, at nearly 18 and 5 yr post-explosion, respectively. We fit the spectral energy distributions as functions of dust mass and temperature, from which we are able to constrain the dust geometry, origin, and heating mechanism. We place a 90% confidence lower limit on the dust masses for SNe 2004et and 2017eaw of >0.014 and >4e-4 M_sun, respectively. More dust may exist at even colder temperatures or may be obscured by high optical depths. We conclude dust formation in the ejecta to be the most plausible and consistent scenario. The observed dust is radiatively heated to ~100-150 K by ongoing shock interaction with the circumstellar medium. Regardless of the best fit or heating mechanism adopted, the inferred dust mass for SN 2004et is the second highest (next to SN 1987A) inferred dust mass in extragalactic SNe thus far, promoting the prospect of SNe as potential significant sources of dust in the Universe., Comment: 12 pages, 7 figures, submitting to MNRAS

Chromosome analysis is essential for diagnosing genetic disorders. For hematologic malignancies, identification of somatic clonal aberrations by karyotype analysis remains the standard of care. However, karyotyping is costly and time-consuming because of the largely manual process and the expertise required in identifying and annotating aberrations. Efforts to automate karyotype analysis to date fell short in aberration detection. Using a training set of ~10k patient specimens and ~50k karyograms from over 5 years from the Fred Hutchinson Cancer Center, we created a labeled set of images representing individual chromosomes. These individual chromosomes were used to train and assess deep learning models for classifying the 24 human chromosomes and identifying chromosomal aberrations. The top-accuracy models utilized the recently introduced Topological Vision Transformers (TopViTs) with 2-level-block-Toeplitz masking, to incorporate structural inductive bias. TopViT outperformed CNN (Inception) models with >99.3% accuracy for chromosome identification, and exhibited accuracies >99% for aberration detection in most aberrations. Notably, we were able to show high-quality performance even in "few shot" learning scenarios. Incorporating the definition of clonality substantially improved both precision and recall (sensitivity). When applied to "zero shot" scenarios, the model captured aberrations without training, with perfect precision at >50% recall. Together these results show that modern deep learning models can approach expert-level performance for chromosome aberration detection. To our knowledge, this is the first study demonstrating the downstream effectiveness of TopViTs. These results open up exciting opportunities for not only expediting patient results but providing a scalable technology for early screening of low-abundance chromosomal lesions.

Motion prediction is crucial in enabling safe motion planning for autonomous vehicles in interactive scenarios. It allows the planner to identify potential conflicts with other traffic agents and generate safe plans. Existing motion predictors often focus on reducing prediction errors, yet it remains an open question on how well they help identify the conflicts for the planner. In this paper, we evaluate state-of-the-art predictors through novel conflict-related metrics, such as the success rate of identifying conflicts. Surprisingly, the predictors suffer from a low success rate and thus lead to a large percentage of collisions when we test the prediction-planning system in an interactive simulator. To fill the gap, we propose a simple but effective alternative that combines a physics-based trajectory generator and a learning-based relation predictor to identify conflicts and infer conflict relations. We demonstrate that our predictor, P4P, achieves superior performance over existing learning-based predictors in realistic interactive driving scenarios from Waymo Open Motion Dataset., Comment: 7 pages, 4 figures, 3 tables

Although only a small fraction of stars end their lives as supernovae, all supernovae leave behind a supernova remnant (SNR), an expanding shock wave that interacts with the surrounding medium, heating the gas and seeding the cosmos with elements forged in the progenitor In this chapter, we introduce the basic properties of galactic and extragalactic SNRs (Section 2). We summarize how SNRs evolve throughout their life cycles over the course of ~10^6 yrs (Section 3). We discuss the various morphological types of SNRs and discuss the emission processes at various wavelengths.(Section 4)., Comment: 13 pages, 8 figures, To appear in "Handbook of X-ray and Gamma-ray Astrophysics" by Springer - Editors in chief: C. Bambi and A. Santangelo

Interactive traffic simulation is crucial to autonomous driving systems by enabling testing for planners in a more scalable and safe way compared to real-world road testing. Existing approaches learn an agent model from large-scale driving data to simulate realistic traffic scenarios, yet it remains an open question to produce consistent and diverse multi-agent interactive behaviors in crowded scenes. In this work, we present InterSim, an interactive traffic simulator for testing autonomous driving planners. Given a test plan trajectory from the ego agent, InterSim reasons about the interaction relations between the agents in the scene and generates realistic trajectories for each environment agent that are consistent with the relations. We train and validate our model on a large-scale interactive driving dataset. Experiment results show that InterSim achieves better simulation realism and reactivity in two simulation tasks compared to a state-of-the-art learning-based traffic simulator., Comment: Accepted at IROS 2022. Author version with 8 pages, 4 figures, and 2 tables. Code and demo available at paper website: https://tsinghua-mars-lab.github.io/InterSim/

We present a conjectural description of the space of local operators on a stack of finitely many fivebranes in $M$ theory at the level of the holomorphic twist. Our approach is through the lens of twisted holography and utilizes a description of the minimal twist of eleven-dimensional supergravity. We find that the spaces of local operators are modules for the exceptional linearly compact super Lie algebra $E(3|6)$. From the conjectural description of local operators we deduce closed formulas for the superconformal index of six-dimensional $\mathcal{N}=(2,0)$ theories of type $A_{N-1}$., Comment: Comments and feedback are welcome!

We present a third epoch of Chandra observations of the Type Ia Large Magellanic Cloud Supernova remnant (SNR) 0509-67.5. With these new observations from 2020, the baseline for proper motion measurements of the expansion has grown to 20 years (from the earliest Chandra observations in 2000). We report here the results of these new expansion measurements. The lack of nearby bright point sources renders absolute image alignment difficult. However, we are able to measure the average expansion of the diameter of the remnant along several projection directions. We find that the remnant is expanding with an average velocity of 6120 (4900 -- 7360) km s$^{-1}$. This high shock velocity is consistent with previous works, and also consistent with the inference that 0509-67.5 is expanding into a very low density surrounding medium. At the distance of the LMC, this velocity corresponds to an undecelerated age of 600 yrs, with the real age somewhat smaller., Comment: 9 pages, 5 figures. Accepted for publication in ApJ